Category Archives: Design

allocation of floor area to function of housing

Minimum Spatial Housing Requirements for Human Flourishing

Karl T. Ulrich

University of Pennsylvania. The Wharton School. Operations, Information, and Decisions Department, Philadelphia, PA 19104, USA

KT Ulrich. Minimum Spatial Housing Requirements for Human Flourishing. Buildings. 2025. Volume 15.
(full text below PDF)

Abstract

This study defines evidence-based minimum internal floor areas required to support long-term residential use across different household types. It addresses the following question: what is the smallest viable floor area that supports sustained occupancy without persistent stress, conflict, or turnover? An integrative review method was employed, drawing from behavioural studies in environmental psychology, international regulatory standards, and real-world market data. The analysis focuses on essential domestic functions including sleep, hygiene, food preparation, storage, social interaction, and work. Quantitative findings from tenancy surveys, post-occupancy research, and market performance data indicate that residential units below 30 square metres for single occupants and 45 square metres for couples are consistently associated with reduced satisfaction and shorter tenancies. Regulatory minimums across diverse jurisdictions tend to converge near these same thresholds. The study proposes technical minimums of 30, 45, and 60 square metres for one-, two-, and three-person households, respectively. These values reflect functional lower bounds rather than ideal or aspirational sizes and are intended to inform performance-based housing standards.

Keywords: minimum home size; affordable housing; floor area; unit size; housing standards; micro housing; nano housing; tiny homes

1. Introduction

In the face of a global affordability crisis, housing systems increasingly rely on compact dwellings to expand supply in urban areas. However, the pursuit of higher densities and lower construction costs often proceeds without robust empirical guidance on how small is too small. While attributes such as energy efficiency, structural integrity, and environmental impact are routinely measured and regulated, internal floor area, the most fundamental spatial parameter of dwelling performance, is inconsistently addressed in most building codes [1,2].

A growing body of research suggests that below certain spatial thresholds, residential dwellings may no longer support the basic conditions for health, autonomy, and psychological well-being. Evidence from environmental psychology, building design, post-occupancy studies, and housing markets points to consistent patterns in how households respond to limited living space. These include rising levels of stress, shorter tenancy durations, reduced satisfaction, and increased rates of residential turnover [3–5].

This paper addresses the following central research question:

What is the minimum internal floor area required for a housing unit to support long-term human flourishing?

To answer this question, the study draws on evidence from multiple domains, including environmental psychology, regulatory frameworks, and market behaviour. Rather than focusing on average or desirable housing sizes, it aims to identify the technical and functional minimum: the smallest internal floor area that allows a household to carry out essential domestic activities over time without persistent stress, conflict, or risk of displacement.

Recent policy developments and market research reinforce the urgency of establishing empirically grounded spatial minimums. The 2025 update to the UK national space standards affirms 37 square metres as the lowest acceptable internal area for a single-person dwelling, reflecting a continued reliance on point-value thresholds in regulatory guidance [6]. Recent analysis of English space standards reveals ongoing tensions between affordability pressures and adequacy requirements in social housing provision [7]. In North America, compact living is increasingly framed as a mainstream strategy for achieving affordability and urban density [8]. Empirical evidence from land-use reforms shows that relaxing regulatory constraints can increase available living space while reducing per-unit cost burdens [9]. These developments underscore the need to define lower spatial bounds using behavioural and functional indicators, not solely historical precedent or policy negotiation.

This study differs from previous work by focusing not on average or desirable unit sizes, but on identifying functional lower bounds for long-term residential use. While many studies explore housing quality, affordability, or density in isolation, few integrate evidence across behavioural psychology, regulatory standards, and market performance to define minimum viable space. This triangulated approach yields floor area thresholds that are both technically grounded and practically relevant. By aligning spatial adequacy with real-world behaviour, the findings offer a performance-based framework that can inform policy, design, and code development in diverse contexts.

1.1. Supporting Questions and Policy Relevance

In identifying these minimum floor area thresholds, the study also explores several supporting questions:

  • What are the spatial requirements for core domestic functions such as sleep, hygiene, food preparation, storage, social interaction, and remote work?
  • How do regulatory standards for minimum dwelling size vary across jurisdictions, and how well do they align with behavioural and psychological evidence?
  • What does market behaviour reveal about the practical limits of compact housing, especially in high-cost urban environments?
  • At what point does spatial inadequacy lead to measurable declines in satisfaction, tenure stability, or mental health?

These questions have direct implications for several pressing housing challenges. Among them are:

  • What is the lowest feasible cost for delivering liveable housing at scale?
  • How much residential floor area is required to support a given urban population within environmental constraints?
  • What unit sizes are most appropriate for modular and prefabricated housing systems?
  • How should housing standards evolve to address the rise in single-person households and the increasing prevalence of remote work?

None of these issues can be addressed meaningfully without a baseline understanding of how much space people need, at a minimum if not an ideal, to sustain daily life in a stable, healthy, and autonomous manner.

1.2. Global Household Size and Composition: A Foundation for Space Standards

Average household size has fallen worldwide for more than four decades. United Nations data show a decline from approximately 4.9 persons per household in 1980 to about 4.0 in 2020, with the median country now near or below four persons [10,11]. The trend is especially pronounced in high-income economies. The OECD reports a current average household size of 2.4 persons, with more than one third of member countries now composed primarily of one- and two-person households [12,13].

Rapidly ageing East Asian societies display the same pattern. Japan’s 2020 census records 2.3 persons per household nationally and 1.9 in the Tokyo metropolitan core [14]. South Korea reports 2.2 persons nationwide and fewer than 2.0 in Seoul [15].

Small households already dominate urban housing demand. Across large European metropolitan areas, single-person dwellings account for 35 to 45 percent of occupied units, while two-person households add another 30 to 35 percent [13]. United Nations Habitat analysis finds a similar structure in rapidly urbanising regions of Latin America and East Asia, although three-person households remain slightly more common there [16]. Table 1 summarises these proportions and links them to their principal drivers: population ageing, delayed marriage, declining fertility, and the rise in solo living among both younger and older adults [17,18].

Table 1 . Three Size Categories of Households.

Household TypeEstimated ShareTrendDemographic BasisDesign Relevance
Single-Person28–35%Strongly
increasing
Ageing, urban migration, autonomyMost common compact unit
Two-Person32–38%IncreasingCouples without children, retireesKey transitional household
Three- to Four-Person30–35%Stable/DecliningNuclear families, emerging middle classCore benchmark for family units

Multigenerational and group households continue to be significant in parts of Africa, South Asia, and the Middle East, yet their spatial requirements differ enough to warrant separate treatment later. For the compact-dwelling typology that follows, the focus remains on one- to four-person nuclear households, which represent the bulk of future housing demand in urbanised regions.

1.3. Methodological Approach

This study uses an integrative review methodology to identify evidence-based minimum internal floor areas suitable for long-term residential use. The aim is to synthesise findings from multiple domains, including environmental psychology, building regulation, and housing market behaviour, to establish the functional lower bounds of spatial adequacy. An integrative review is appropriate in this context because the evidence base includes both peer-reviewed research and grey literature and spans diverse methodological formats [19].

The analysis proceeded in three phases. First, spatial requirements for core domestic functions were identified from studies in environmental psychology, ergonomics, and post-occupancy evaluation. These functions include sleeping, hygiene, food preparation, social interaction, storage, and remote work. Second, national and local building codes were reviewed to assess formal minimum size requirements. Sources included official building standards, planning documents, and housing regulations across multiple jurisdictions. Third, market typologies and occupancy outcomes were examined in cities where compact dwellings are widely built and occupied. Data sources included tenancy duration surveys, resident satisfaction reports, real estate market analyses, and public-sector housing datasets.

Findings from the three domains were organised using a comparative matrix. Where psychological thresholds, regulatory minimums, and observed market behaviour consistently aligned, a floor area threshold was proposed. These proposed values are defined as technical lower bounds for sustained residential use. They are not intended as normative goals or average sizes.

Because the study integrates both academic and non-academic materials, no systematic keyword protocol or database screening process was used. Sources were selected for empirical specificity (such as quantified thresholds for domestic activities), jurisdictional diversity (including regulatory frameworks from multiple continents), and conceptual relevance to spatial sufficiency and long-term residential stability. The review drew from more than 100 documents, including peer-reviewed studies, government standards, industry reports, and post-occupancy surveys. Although no formal date cut-off was imposed the majority of sources were published after 2000, with priority given to post-2010 studies where available. This flexible approach supports evidence-informed design and policy decisions where minimum standards must be reconciled with lived outcomes.

2. Spatial Requirements for Well-Being and Function

A building’s spatial adequacy is a key component of its performance. While regulatory minimums and market behaviour often reflect political compromise or economic constraint, they do not necessarily ensure long-term psychological comfort, physical health, or functional usability. This section synthesises research from environmental psychology, ergonomics, post-occupancy evaluation, and time-use studies to identify the threshold at which housing space continues to support core human activities and enables flourishing. These insights inform our proposed floor area minimums by grounding them in behavioural and functional performance rather than availability, aesthetics, or tradition. A growing body of research has examined the relationship between spatial parameters and occupant well-being at the urban and building scale [20–22]. However, these studies primarily focus on external or neighbourhood-scale spatial qualities, whereas this work addresses the spatial adequacy of the home itself.

2.1. Crowding, Density, and Psychological Stress

Crowding refers to the subjective experience of having insufficient personal space, while density refers to the number of people per unit area. Studies consistently show that it is perceived crowding, not density alone, that predicts negative psychological outcomes [21]. Evans et al. [3] found that residential crowding, often defined as fewer than 15–20 square metres per person or more than one person per room, is associated with chronic stress, cognitive delays in children, and elevated cortisol levels. These psychological impacts can be quantified using established well-being valuation methodologies [23,24], enabling systematic assessment of housing adequacy’s broader social costs. These effects tend to occur once space drops below key thresholds, suggesting the presence of spatial tipping points in psychological resilience.

Research on social housing in Great Britain provides additional evidence of these threshold effects. Hickman [25] demonstrates that inadequate housing conditions significantly impair residents’ ability to maintain social connections and access “third places” for community interaction, with spatial constraints being a key factor in social isolation. Furthermore, longitudinal studies of tenancy sustainment reveal that housing inadequacy, including insufficient space, is strongly associated with tenancy breakdown and residential instability [26]. These findings reinforce the importance of establishing evidence-based spatial minimums that support not only individual well-being but also community cohesion and housing stability.

2.2. Privacy, Control, and Territorial Function

The ability to regulate one’s environment through visual, acoustic, and spatial boundaries is central to housing performance. Ozaki and Lewis [27] identify four domains of privacy: personal, informational, territorial, and acoustic. When these are compromised, occupants report increased psychological distress and decreased satisfaction. Kopec [28] finds that households in compact units often struggle to maintain behavioural autonomy, particularly in relation to partners or children. Our synthesis suggests that below 30 square metres for single adults and 45 square metres for couples, housing units frequently fail to support the full range of privacy functions, even with good design.

2.3. Activity-Based Space Requirements

Post-occupancy evaluations and time-use studies offer detailed insight into the spatial requirements of essential domestic activities. While cultural context and layout quality affect thresholds, certain space needs recur across geographies and dwelling types.

  • Sleeping typically requires 5 to 7 square metres per person, accounting for bed size, circulation, and storage. A single bed with access on one side requires approximately 4.5 square metres, while a double bed needs 6 to 8 square metres for comfort [29,30].
  • Food preparation and dining require a minimum of 4 to 6 square metres per household. Research on kitchen ergonomics shows that functionality depends more on workflow efficiency than household size [31,32]. Kitchens smaller than 3.5 square metres are associated with reduced satisfaction and increased time inefficiency [33].
  • Hygiene facilities require 3 to 4 square metres to comfortably accommodate toilet, basin, and shower fixtures. Although compact bathrooms can function in as little as 2.5 square metres, users consistently prefer bathrooms of at least 3.5 square metres for comfort and accessibility [29].
  • Socialising and relaxation typically require 7 to 12 square metres, depending on household size. Single-person households can function with 6 to 8 square metres for a small seating area and media use, while larger households require more space to accommodate multiple users simultaneously [34,35].
  • Work or study requires 2 to 3 square metres per working occupant. This accommodates a desk, task chair, and minimal storage. Spaces below 2 square metres are associated with reduced productivity and increased fatigue [36–38].
  • Storage needs average 3 to 4 square metres per person, including space for clothing, equipment, seasonal items, and household supplies. When this falls below 2.5 square metres per person, spatial disorder and visual clutter increase significantly [29,39,40].

When units fall below these thresholds, “activity compression” occurs. In these cases, essential tasks begin to overlap or displace one another as follows: sleeping occurs in living spaces, eating happens on beds, or work is done in hallways. Bratt [41] describes how such compression can degrade usability and lead to residential dissatisfaction. Lawrence [42] and Després [43] emphasise that these spatial compromises are not just inconvenient, but symbolically and psychologically disruptive. Over time, the cumulative effect of compressed or improvised functions erodes the domestic environment’s ability to support stability, identity, and autonomy.

2.4. Adaptation and Design Moderators

Residents employ a variety of coping strategies in very small dwellings. Temporal zoning, selective use of common areas, personalisation of limited surfaces, and cognitive reframing can all moderate the feeling of crowding [44]. High ceilings, abundant daylight, generous built-in storage, and carefully framed views increase perceived spaciousness and postpone fatigue. Even so, longitudinal evidence shows that adaptation has clear limits once floor area drops below roughly twenty square metres per person.

Several dense-city studies illustrate those limits. In Hong Kong, sixty per cent of households occupying flats smaller than twenty-five square metres rate their living space as unsatisfactory, and a majority intend to relocate within two years [45,46]. In Tokyo, micro-apartments under twenty square metres support average tenancies of only 1.8 years, whereas similar buildings with twenty-five square metres or more achieve average stays of 3.2 years [47]. Hong Kong turnover is likewise highest in nano-flat households that share less than twenty square metres per person [5]. Mumbai surveys show a parallel pattern, with dissatisfaction and intent to exit rising sharply after twelve to eighteen months in eighteen to twenty-five square metre “nano homes” [48].

Good design can reduce noise, create visual depth, and provide multi-functional furniture that stretches usability for short periods; however, extended residence below the twenty-square-metre threshold consistently produces higher stress, clutter, and social friction. Across cases, ingenuity and supportive management can delay but not eliminate the physiological and psychological burdens imposed by extreme spatial constraint.

2.5. Cultural Modifiers of Spatial Expectation

Cross-cultural research shows that acceptable space standards vary with social norms, and that urban context, including spatial parameters of neighbourhoods and access to green spaces, also significantly affect well-being [22,49]. East Asian residents, for example, often rate smaller units as acceptable due to norms of compact living, floor-sitting, and shared public amenities. Ozaki and Lewis [27] found that Japanese households consider 20% less space acceptable than matched British counterparts. However, Whiteford and Hoff [50] show that all cultures share basic needs for control, quiet, and autonomy, indicating that minimums can vary slightly but not be abandoned altogether.

2.6. Children and Developmental Needs

Children are particularly sensitive to spatial inadequacy. Overcrowded homes (under 8 m2 per child) are linked to lower academic performance, behavioural problems, and impaired sleep [51]. Developmental needs include quiet study space, physical separation for sleep, and play areas. These requirements support higher minimums for family dwellings.

2.7. Remote Work and the New Domestic Function

Post-pandemic housing must now accommodate remote work as a standard rather than exceptional domestic function. The rapid shift to home-based work has fundamentally altered spatial requirements, with implications for minimum housing standards that previously assumed work occurred outside the dwelling unit.

Effective home workspaces require an additional 3–5 m2 per worker beyond traditional residential functions, with minimum dimensions of 1.2 m × 1.5 m[M18] [KU19]  to accommodate desk, chair, and equipment storage [52,53]. This represents a 15–20% increase in space requirements for households with remote workers. Studies of telework environments indicate that workspaces below 2.5 m2 per user result in reduced productivity, increased physical discomfort, and higher rates of work-related stress [54,55].

The quality of home workspace significantly affects both work performance and residential satisfaction. Research during COVID-19 lockdowns found that lack of dedicated workspace in units under 30 m2 was strongly associated with depressive symptoms, anxiety, and decreased job satisfaction [56,57]. Workers in compact housing without defined work zones reported difficulty maintaining work–life boundaries, leading to extended working hours and reduced recovery time [58].

Work zones must be visually and acoustically distinct from other domestic functions to support cognitive performance and psychological boundaries [59,60]. Open-plan arrangements where work occurs in living or sleeping areas show measurably lower task performance and higher stress indicators compared to spatially separated workspaces [61,62]. Even temporary visual barriers or acoustic separation can improve work effectiveness in constrained spaces [63,64].

Ergonomic requirements for sustained computer work, including proper desk height (72–76 cm), chair clearance (minimum 60 cm behind desk), and screen distance (50–70 cm), establish minimum spatial envelopes that cannot be compressed without health consequences [65,66]. Studies of home-based workers show increased musculoskeletal problems when workspace dimensions fall below ergonomic minimums [67,68].

The acoustic environment proves equally critical for remote work functionality. Research indicates that background noise levels above 50 dB significantly reduce cognitive performance and increase fatigue in knowledge work [69,70]. Compact housing often struggles to provide acoustic separation between work and domestic activities, particularly in units below 40 m2 where spatial buffering is limited [71].

Storage requirements for work equipment add approximately 0.5–1 m2 per remote worker, including space for technology, documents, and professional materials that cannot be integrated with household storage [52,72]. Inadequate work storage leads to spatial spillover that compromises both work efficiency and domestic function.

These findings suggest that housing units intended to accommodate remote work require baseline increases of 20–25% over pre-pandemic spatial standards. For single-person units, this elevates functional minimums from approximately 25 m2 to 30 m2, while couple units require approximately 45 m2 to maintain both residential quality and work functionality. Units that cannot accommodate these expanded requirements may function for short-term residence but prove inadequate for sustained occupancy in an economy increasingly dependent on home-based work.

The thresholds identified in behavioural and post-occupancy research provide a functional basis for determining spatial adequacy. These findings set reference points for evaluating whether existing regulations reflect the space required to support long-term residential well-being. The next section surveys regulatory standards to assess how policy frameworks correspond to the evidence on domestic activity needs and psychological thresholds.

3. Global Regulatory Standards and Spatial Minimums

While spatial adequacy is grounded in functional and behavioural needs, housing regulations set the operational boundaries for what can be legally built. This section reviews regulatory minimum dwelling sizes across diverse jurisdictions to assess the extent to which existing standards align with or diverge from empirically defined spatial thresholds.

3.1. Regulatory Diversity and Spatial Baselines

Minimum dwelling-size rules differ sharply from one world region to the next. A west-to-east review, following the ordering in Table 2, highlights both the variety of legal instruments and the narrow band into which many numeric thresholds ultimately converge. Recent analyses underscore the need for clearer alignment between minimum standards and lived spatial needs, especially in the context of regulatory reforms in East Asia [73].

North America begins with a code baseline rather than a whole-unit floor. All fifty US states adopt the International Building or Residential Code, whose only size mandate is a habitable room of at least 11 m2; every dwelling must contain at least one such room [74]. Canada’s Ontario Building Code raises that figure to 13.5 m2 for a living room, while most bedrooms must be at least 7 m2 [75]. Large Canadian cities then overlay per-person limits: Toronto requires a minimum of 9 m2 of usable floor area for each adult occupant, enforceable through its property-standards by-law [76]. In short, North American regulation relies on room-by-room rules or occupancy caps rather than a fixed flat-size plateau.

Latin America and the Caribbean show a split between market housing and social-housing programmes. Mexico City’s 2018 construction code sets a statutory lower bound of 25 m2 net floor area for any new apartment, giving the region’s most compact private-sector limit [77]. Brazil and Chile impose larger figures but only where federal or national subsidies are involved: Brazil’s relaunched Minha Casa Minha Vida requires 41.5 m2 for an apartment and 40 m2 for a single-family house [78], while Chile’s DS-49 programme mandates 40 m2 for subsidised dwellings [79]. Outside those programmes, private developments can be smaller.

Europe embeds minimums directly in national legislation but uses two distinct logics. England fixes a studio plateau of 37 m2 gross internal area through the Nationally Described Space Standard [80]. Sweden’s building code recognises 35 m2 as the lower limit for a self-contained unit because many accessibility concessions apply only when the dwelling is larger [81]. Germany, France, and the Netherlands regulate crowding instead: Germany’s Länder bar lettings that fall below about 9 m2 per adult [82], France requires 14 m2 per person for the first four occupants [83], and the Dutch Bouwbesluit demands at least one living area of 18 m2 in every dwelling [84]. Despite different metrics, these rules cluster between 35 m2 for a single occupant and 14–18 m2 per person in multi-person units.

Africa combines per-room codes with programme minima. Kenya’s draft National Building Code sets 7 m2 usable floor area for every habitable room, creating a practical lower bound for one-room units if the draft is adopted [85]. Lagos State’s planning standards require 10.8 m2 for each habitable room, slightly higher than Kenya’s figure [86]. South Africa’s subsidy programme for Reconstruction and Development Programme housing mandates 40 m2 gross floor area for a detached house, but that rule applies only to publicly funded units [87].

South Asia shows a single national guideline. India’s Affordable Housing in Partnership scheme fixes 25 m2 carpet area as the minimum self-contained dwelling that can receive central subsidy; states vary in their own policies, with some (for example Maharashtra) raising the floor to about 27 m2 [88].

East and Southeast Asia illustrate every tool in the regulatory toolbox. Japan’s Building Standards Act sets no flat-size floor but insists every habitable room be at least 7 m2 internal area [89]; one-room apartments therefore start at that point but market practice in Tokyo rarely goes below 15 m2 [90]. Hong Kong imposes a 26 m2 saleable-area minimum on all new private projects through land-lease conditions, while its public-rental sector follows a 7 m2 per-person allocation rule [91]. Singapore limits private and public studios outside the central area to 35 m2 gross floor area [92]. Mainland China’s national design code fixes 22 m2 usable floor area for a self-contained dwelling, though some provinces accept smaller single-occupant units [93]. Together these standards span a range from per-room minima (Japan) to whole-unit floors that rise from 22 m2 in China, through 26 m2 in Hong Kong, to 35 m2 in Singapore.

Table 2. Standards for minimum housing size by region.

RegionJurisdictionMin. Size (m2)
(Dominant
Household)
Metric †Enforcement ‡SectorSources
North AmericaUnited States (IBC/IRC model code)11 m2
(one-room dwelling)
IFASPrivate[74]
 Canada—Ontario Building Code13.5 m2
(living room)
IFASPrivate[75]
 Toronto (Property Standards)≥9 m2/personIFAAPrivate/Public[76]
Latin America and CaribbeanMexico—Mexico City Construction Code25 m2
(dwelling)
IFASPrivate[77]
 Brazil—Minha Casa Minha Vida (programme)41.5 m2 (apartment);
40 m2 (house)
IFAAPublic programme[78]
 Chile—DS49 Social Housing (programme)40 m2 (dwelling)IFAAPublic programme[79]
EuropeUnited Kingdom37 m2
(1 person, 1-storey)
GIASPrivate[80]
 Sweden35 m2 (1 person)GIASPrivate[81]
 Germany≥9 m2/personIFASPrivate[82,94]
 Netherlands18 m2
(living-space benchmark)
IFASPrivate[2,4,95]
 France14 m2/person
(≤4 persons)
IFASPrivate[83]
AfricaKenya—National Building Code 2024 (draft)7 m2/habitable roomIFAS
(draft)
Private[85]
 Nigeria—Lagos State10.8 m2/habitable roomIFASPrivate[86]
 South Africa—RDP Housing Norm40 m2
(subsidised house)
GFASPublic programme[87]
South AsiaIndia—Affordable-Housing Guidelines25 m2 (dwelling)CAAPublic–private[88]
East and Southeast AsiaTokyo (Japan)7 m2/habitable roomIFASPrivate[89]
 Hong Kong26 m2 (flat)SALPrivate[91,96
 Singapore35 m2 (studio)GFASPrivate[92]
 Mainland China22 m2 (dwelling)IFASPrivate[93]
OceaniaAustralia—New South Wales35 m2 (studio)IFASPrivate[97]
 New Zealand—Auckland Unitary Plan35 m2
(self-contained unit)
GFAZPrivate[98]

Metric codes—IFA = internal floor area; SA = saleable area; GIA = gross internal area; CA = carpet area; GFA = gross floor. ‡ Enforcement codes—S = statutory building/planning rule; L = mandatory land-lease/development agreement; A = administrative guideline or allocation rule; Z = zoning overlay.

Oceania closes the sweep with parallel state and city-level rules. New South Wales requires 35 m2 internal floor area for a studio and larger plateaus for bigger flats, a template most Australian jurisdictions now follow [97]. New Zealand’s Auckland Unitary Plan adopts the same numeric threshold, 35 m2 gross floor area, for any self-contained dwelling in the city’s medium-density zones [98].

Despite wide variation in enforcement tools, including statutes, land-lease clauses, programme rules, and zoning overlays, the numeric floors for long-term single occupancy cluster between 22 m2 and 37 m2, with many jurisdictions converging on the 30–35 m2 band. Where standards are expressed per person, figures fall between 7 m2 and 14 m2, again bracketing the 10 m2 mark. These convergences support the minimum thresholds advanced later in this paper while also revealing the political and economic pathways by which different societies pursue spatial adequacy.

3.2. Historical Patterns and Regulatory Evolution

Minimum space rules first appeared in nineteenth-century public health reforms that targeted overcrowded tenements in rapidly industrialising cities. Early by-laws in London, such as the 1890 Housing of the Working Classes Act, and New York’s 1901 Tenement House Act emphasised daylight, ventilation, and a minimum cubic volume of air per person [99,100]. After the Second World War, the welfare-state consensus encouraged many countries to adopt far more generous space norms. In England, the Parker Morris standards required about eighty-eight square metres for a four-person dwelling along with detailed room and storage requirements [101]. Sweden’s Million Programme of 1965–1974 pursued a comparable goal, producing large, well-equipped flats that averaged more than thirty square metres per person [102].

Fiscal restraint and deregulation in the late 1970s and early 1980s reversed this expansion. The Parker Morris requirements, mandatory for public housing since 1967, were formally withdrawn in 1980 as part of wider expenditure cuts [103]. Similar retrenchment occurred in Australia, Canada, and parts of continental Europe, leading to divergent national standards and shrinking average unit sizes during the 1980s and 1990s.

Since the early 2000s governments have renewed interest in minimum spatial benchmarks, driven by housing affordability crises, demographic change, and growing evidence that extreme compactness harms well-being. England adopted the Nationally Described Space Standard in 2015, restoring a minimum of thirty-seven square metres for a one-person one-storey dwelling [80]. Mexico City introduced a twenty-five square metre minimum in 2018 [77], and Hong Kong recently decided that new private flats under public land lease must not be smaller than twenty-six square metres [91]. The post-war expansion, subsequent rollback, and recent re-regulation illustrate how space standards respond to shifting social priorities as much as to technical or market constraints.

4. Revealed Preferences in Space-Constrained Markets

While regulatory standards establish what may be built and behavioural studies indicate what ought to be optimal, the lived experience of residents in compact dwellings shows the practical limits of spatial sufficiency. Observed occupancy behaviour—including tenancy duration, mobility patterns, satisfaction levels, and housing-application choices—supplies a form of revealed preference that complements normative frameworks. In the highest-cost urban markets, where land is scarce and demand intense, dwellings are routinely produced and occupied close to the lower spatial thresholds. These situations show not only what households tolerate but also when they decide to leave, adapt, or forgo particular housing options entirely.

In Hong Kong, flats smaller than forty square metres represented about one fifth of all private sales between 2019 and 2021 [104]. Micro-units of fifteen to twenty square metres are now a recognised market segment for single professionals and investors. Multiple studies document low satisfaction in such dwellings: a survey of subdivided-unit tenants found pervasive stress, health complaints, and strong intentions to relocate [46], while another study reported that sixty percent of residents in units below twenty-five square metres described themselves as “unsatisfied” or “very unsatisfied” with living space [45] (Lau & Wei, 2018). Dissatisfaction intensifies when more than one person shares these micro-flats [105].

Tokyo displays a similar pattern in its “one-room mansions,” typically fifteen to twenty-five square metres and roughly a third of the central-city rental stock. Although prized for location and efficiency, these units are mostly occupied by students and early-career professionals. Data show that apartments below twenty square metres support average tenancies of just 1.8 years, whereas those above twenty-five square metres average 3.2 years [106].

In New York City, the adAPT NYC pilot introduced twenty-four to thirty square metre studios featuring integrated storage and convertible furniture. Initial surveys recorded positive evaluations, yet a follow-up by the city’s housing department found that nearly half of occupants sought larger homes within eighteen months, especially after remote work became common [107]. London’s new co-living schemes, offering private rooms of twenty-four to thirty square metres with shared amenities, function mainly as stop-gap housing for mobile professionals, with average stays of eight to fourteen months [108].

Singapore presents a mixed public–private picture. Government-built studio flats of thirty-five square metres maintain overall satisfaction above ninety percent, although the most frequently cited reason for intending to move is the desire for more personal space [109]. In the private sector, so-called “shoebox” apartments of thirty-five to forty-five square metres attract single residents, yet market surveys indicate that more than one third of prospective buyers see lack of space as the main push factor [110].

Emerging-market cities employ compact housing as an affordability strategy. In Mumbai, “nano homes” of eighteen to twenty-five square metres target lower-middle-income singles; sixty-five percent of single buyers in a 2020 study accepted such units, but only thirty-one percent of couples found them viable [111]. São Paulo offers ten to fifteen square metre micro-apartments for mobile professionals, with average occupancy of eleven months [112]. South-African surveys show that single or childless adults will accept twenty-five to thirty square metres if build quality is high, whereas households with children express dissatisfaction below fifty square metres [113].

Across these cities, one pattern recurs. Single-person households are more tolerant of spatial constraints than couples or families, but only up to roughly thirty square metres. Tenancy duration rises by about one year for each additional ten square metres between fifteen and forty square metres [5,106]. Units smaller than twenty-five square metres exhibit sharply higher turnover, especially when occupied by more than one person.

Cultural differences shape how space is perceived, yet they do not erase the underlying tolerance thresholds. Japanese households may consider about twenty percent less space acceptable than British counterparts [27], and residents in Seoul or Hong Kong may normalise tighter dwellings. Nonetheless, units below twenty square metres consistently trigger stress, intent to relocate, and functional strain when more than one person is present [49,50].

Market data reinforce these behavioural findings. Rents per square metre rise steeply once units exceed twenty-five square metres in markets such as Hong Kong and Tokyo [5,90]. Application patterns also reveal preferences: in Singapore, studio flats of thirty-five square metres attract longer waiting times than forty-five square metre one-bedrooms despite higher total prices [109]. New York micro-units draw forty percent fewer lottery applications per available unit than conventional one-bedrooms [114].

Together, these cases underline the convergence of behavioural, economic, and cultural indicators. For single occupants, around thirty square metres is broadly viable. For two-person households, the floor rises to about forty-five square metres. Below these thresholds, dissatisfaction, early turnover, and lower application demand signal that a critical spatial limit has been breached. Compact units smaller than thirty square metres can serve short-term or transitional roles, but long-term stable occupancy, particularly for more than one person, consistently favours larger space.

5. Empirical Benchmarks from Constrained Housing Environments

The case studies in Section 4 reveal consistent thresholds at which spatial constraint begins to undermine occupancy duration, satisfaction, and housing stability. This section synthesises those patterns into an empirical typology. Drawing on formal and informal housing models, it identifies the floor area per person typically associated with sustained residence. Relationships are organised along two axes: internal space per occupant and typical length of stay. Together they outline a spatial envelope inside which compact housing continues to function without elevated turnover, dissatisfaction, or forced mobility.

Figure 1 plots each housing type by modal floor area per person and expected occupancy duration. Icons indicate typical household size and whether private kitchen and bathroom facilities are present. The horizontal axis measures duration in days (capped at three years) and the vertical axis shows floor area per person (capped at forty square metres to keep the focus on constrained dwellings). A dashed line marks a notional lower bound for long-term viability, derived from tenancy and satisfaction data.

Graph illustrating typical floor area per occupant (in square meters) versus typical duration of living period (in days) across various housing types. The graph highlights critical thresholds for long-term viability in compact housing contexts, with annotations indicating various types of accommodations.

Figure 1. Typical floor area per occupant and typical duration of residence across a range of constrained housing types. Points are annotated with the number of typical occupants and indicate whether private bathrooms and kitchens are included. The dashed line represents an approximate lower bound for residential use. Approximate modal values shown. (Graphic by author.).

At the lower end of the envelope sit dwelling types intended for very short stays or institutional use. Cruise cabins, emergency shelters, and São Paulo’s ten to fifteen square metre mini apartments fall here; these private, self-contained units support average stays shorter than one year [112]. Military barracks and student dormitories also appear in this zone. In the United States, unaccompanied military housing offers roughly thirteen to seventeen square metres per person in shared rooms, while standard dormitories provide about nine to eleven square metres per person, with longer stays enabled by institutional context and communal support systems.

A second cluster contains micro-units and efficiency apartments that offer more autonomy but remain tightly constrained. Tokyo’s one-room mansions and Hong Kong’s nano flats provide roughly fifteen to twenty-five square metres per person. Although popular with single professionals and students, tenancy data show average stays under three years and high turnover when more than one person shares these units [5,106]. New York’s adAPT pilot studios, twenty-four to thirty square metres, achieved moderate early satisfaction but saw notable attrition after eighteen months, particularly among residents working from home [107]. London co-living schemes display similar patterns, with average stays of eight to fourteen months [108].

The upper band of the envelope includes units that support longer residence and higher satisfaction. Mumbai’s eighteen to twenty-five square metre nano homes work for singles but show marked dissatisfaction among couples [111]. Government-built studio flats of thirty-five square metres in Singapore report satisfaction above ninety per cent, yet the main reason households give for planning to move is the wish for more personal space [109]. National market polling shows that thirty-six per cent of prospective buyers of private shoebox apartments cite lack of space as their chief concern, versus seventeen per cent among those considering units larger than forty-five square metres [110]. In Hong Kong, surveys find that sixty per cent of residents in units below twenty-five square metres rate their living space as unsatisfactory and that stress rises sharply when more than one person shares such flats [45,46,105].

A non-linear relationship emerges between space and duration. Dwellings smaller than fifteen square metres per person serve mainly short-term or institutional purposes. Between fifteen and twenty-five square metres, transitional use becomes feasible for single adults, but turnover remains high. From twenty-five to thirty-five square metres per person, long-term residence becomes more common, especially in self-contained units with daylight and acoustic buffering. Spatial efficiency offers some advantage for couples who can share kitchens and bathrooms, yet satisfaction improves markedly only when unit size nears forty-five square metres [105,109]. Tenancy duration rises by roughly one year for every additional ten square metres between fifteen and forty square metres [5,106].

Across locations and cultures, two functional lower bounds recur. Single adults can usually sustain long-term residence once a dwelling reaches about thirty square metres. Two-person households require roughly forty-five square metres to maintain privacy, reduce spatial stress, and limit turnover. Units below these limits repeatedly exhibit dissatisfaction, early mobility, and weak demand.

These empirical patterns reinforce earlier behavioural and regulatory thresholds. Units smaller than thirty square metres for single occupants and forty-five square metres for couples align with research showing that crowding below fifteen to twenty square metres per person elevates stress and social conflict [3,38]. While some households accept tighter quarters for cost, location, or life-stage reasons, the convergence of tenancy data, satisfaction surveys, and market behaviour around these thresholds supports their use as performance benchmarks. Compact dwellings smaller than those limits may meet short-term needs but seldom function as stable, long-term homes.

6. Synthesis of Evidence for Minimum Viable Floor Areas

The evidence presented across behavioural research, regulatory practice, and real-world market behaviour converges on a narrow and consistent range of floor areas required to support sustained residential use. Each of these domains identifies spatial thresholds below which occupancy becomes difficult to maintain, domestic activities begin to conflict, or turnover increases. When viewed together, these sources provide a triangulated basis for defining the lower bounds of functional housing.

Table 3 summarises this convergence. The first column lists internal floor area minimums found in regulatory frameworks across jurisdictions. The second column captures the size ranges of dwellings in widespread use within space-constrained housing markets, even when these units are considered suboptimal. The third column identifies the observed thresholds for sustained occupancy, based on tenancy duration, satisfaction, and post-occupancy outcomes. The final column presents a proposed technical minimum for each household type, grounded in the alignment of behavioural evidence, policy standards, and built examples.

Table 3. Summary of recommended minimum viable internal floor area.

Household TypeRegulatory RangeMinimums in Space-Constrained MarketsObserved Thresholds
for Sustained Occupancy
Proposed
Minimum
Single Person12–40 m215–25 m225–30 m230 m2
Couple30–55 m235–45 m240–45 m245 m2
Family
(3–4 people)
40–90 m245–75 m255–75 m260 m2

For single-person households, long-term viability consistently begins between 25 and 30 square metres. Units smaller than this are frequently tolerated, but studies report elevated stress, social withdrawal, or desire to exit within one to two years. Couples require 40 to 45 square metres to preserve privacy, functional differentiation, and behavioural autonomy. For three- to four-person households, the spatial demands of sleeping, socialising, working, and circulation require a minimum of 55 to 75 square metres depending on household composition and activities.

The proposed technical minimums are set at 30, 45, and 60 square metres for one-, two-, and three- to four-person households, respectively. These values represent the smallest viable floor areas capable of supporting long-term occupancy under compact housing conditions. They are not aspirational design targets or quality-of-life ideals. Rather, they define the floor below which spatial sufficiency begins to break down, even in well-designed, well-located dwellings. At these sizes, households can sleep, cook, bathe, work, and relax without constant compromise or persistent conflict. Below these thresholds, housing may still function temporarily, but is unlikely to support autonomy, stability, or psychological well-being over time.

While the difference between a three- and four-person household is meaningful, the 60 square metre value is proposed as a rounded baseline for both. A household of three may find this space sufficient; four people may require closer to 65 or 70 square metres. However, the use of round values in 15 square metre increments—30, 45, and 60—serves two practical purposes. It supports modular construction and housing aggregation, and it provides clarity and memorability for implementation in policy, planning, and code enforcement.

These thresholds offer a defensible reference point for performance-based housing standards. They reflect a lower bound on viability rather than a cap on quality or aspiration. While adaptation and local variation will always apply, this framework allows for compact housing solutions that preserve essential functions without compromising long-term habitability.

Example Floor Plans

Poor design can render even a large home unliveable. The challenge of maximising the liveability of a given floor area remains for talented designers and the marketplace. While this study does not prescribe specific design solutions, it is useful to demonstrate that the proposed minimum floor areas can accommodate full domestic function. Figure 2 presents one example of how units at 30, 45, and 60 square metres can be laid out to support daily life, based on a common and efficient multi-family configuration. The plans assume a double-loaded central corridor, with units arranged on a 4 m structural grid. Each dwelling has one exterior wall for daylight and ventilation. This configuration is compact, repeatable, and adaptable across many housing typologies.

Floor plans showing the layout of residential units of 30 m², 45 m², and 60 m², illustrating spatial dimensions for living, kitchen, and bathroom areas.

Figure 2. Feasible floor plans for one-person, two-person, and three- to four-person minimum floor area units. (Note that for the 60 sqm unit shown here, a second exit door, fire sprinklers, and/or mechanical ventilation would likely be required for code compliance in most jurisdictions.).

The 60 square metre unit essentially doubles the core layout of the 30 square metre unit, while the 45 square metre version adds a “half module” to provide a second sleeping area or more generous shared space. All three units use the same bathroom configuration, with the 60 square metre plan including two bathrooms. Each plan includes a dedicated space for a stacked clothes washer and dryer, and all units provide sufficient room for sleeping, eating, working, and relaxation. In the smallest unit, additional flexibility may be achieved through use of a lofted bed above a desk or integrated storage elements. The dimensions are comparable to those of an economy hotel room, a typology that has long demonstrated the spatial efficiency achievable within a minimal footprint.

These plans are not intended as optimal layouts, but rather as proof that the minimum floor areas proposed in this study can support essential domestic functions with clarity and coherence. Other configurations may yield better outcomes depending on site constraints, user needs, and architectural strategy. The key point is that at these floor areas, it is possible to provide private, enclosed spaces for sleeping and hygiene, areas for cooking and eating, and sufficient volume for work and relaxation.

7. Concluding Remarks

This study has identified lower bounds for internal floor area that appear necessary to support sustained residential use across three common household types. For single-person households, 30 square metres enables full domestic function with minimal spatial stress. For couples, 45 square metres allows for behavioural autonomy and reduced conflict. For families of three to four people, 60 square metres supports differentiated sleep, hygiene, and work zones while maintaining circulation and privacy. These values are not optimal targets, but rather performance-based thresholds derived from the convergence of behavioural research, policy standards, and market outcomes.

The goal of this work is not to dictate housing typologies or enforce rigid formulas. Instead, it is to clarify the spatial boundaries within which compact dwellings can function reliably over time. Below these thresholds, evidence from diverse settings points to higher turnover, reduced satisfaction, and compromised domestic activities. The thresholds represent a floor that supports liveable outcomes under spatial constraint, not a ceiling on aspiration or quality.

Clarifying this floor opens the door to more precise answers to larger systemic questions. What is the lowest feasible cost for delivering liveable housing at scale? How much residential floor area is required to support a given urban population within environmental constraints? What unit sizes are most compatible with modular or prefabricated construction? How can compact homes accommodate the needs of ageing populations, single-person households, or remote workers without compromising well-being? These questions cannot be addressed meaningfully without a clear understanding of how much space is minimally required to support daily life.

The thresholds proposed here do not resolve these challenges, but they provide a starting point. They define a stable platform on which designers, developers, and policymakers can build compact housing that is not just efficient, but functional and enduring. Future research should explore how these benchmarks intersect with environmental performance, construction systems, and regional context.

The risk of ignoring these limits is not just technical, but human. Compact housing that falls below the point of viability may be cheaper or more abundant in the short term, but it is less likely to support autonomy, stability, or well-being in the long run. In that sense, understanding spatial adequacy is not a matter of regulation alone. It is also a matter of practical foresight for cities, for builders, and for the people who will live in these spaces.

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Commercializing a Physical Product as a Solo Inventor

About once a week, a student, alumnus, or member of the general public reaches out and says something like, “I have an idea for a new physical product. I just need to find a manufacturer. Can you help me?”

First, let me be clear and succinct about a few points. First, an idea is rarely worth much unless combined with the will, effort, and tenacity to develop that idea into a product that is available to customers and that meets their needs. Second, if all you have is an idea, then you do not just need to find a manufacturer. You need to apply your will, effort, and tenacity to the process of transforming your idea into a specification of the solution that will both delight your customers and that unambiguously communicates the details of the solution to a manufacturer. That transformation is not easy. Thankfully, there are many concepts, tools, and methods that can help you achieve your goals and to avoid wasting time and money.

In this guide, I provide an overview of what you will likely need to do and I provide links to other more detailed resources relevant to your pursuit.

May I suggest that before you proceed any further, you view these videos I made describing my attempts to create a new physical product (the Belle-V Ice Cream Scoop) and to take it to market as a solo inventor. (Note that I did not remain solo for long, and had a lot of help from talented partners in the middle phases.)

Belle-V Ice Cream Scoop – Part A
Belle-V Ice Cream Scoop – Part B

OK, now you get the idea and hopefully understand that the process is not trivial, even for a seemingly simple product like an ice cream scoop. Next, let me provide more detail on the key steps:

  1. Develop a solution concept using the triple-diamond model.
  2. Create a prototype that really does the job.
  3. Design the to-be-manufactured version of the product.
  4. Make and sell 1000 (or maybe 100 if possible).
  5. Refine your go-to-market system.

I’ll also include some content related to these important financial and competitive concerns:

  • Can I actually make money from this entrepreneurial opportunity?
  • What about patents?

By the way, if teaching yourself this material is daunting to you, please consider enrolling in my on-line course Design: Creation of Artifacts in Society (via Coursera) from which some of this content is derived. Last I checked, a version of this course was available for free. (Of course, if you are a Penn student, you could also take my course OIDD 6540 Product Design.)

Develop the Solution Concept Using the Triple-Diamond Model

The Triple-Diamond Model

Diamond 1 – Jobs Analysis

Diamond 2 – Understanding User Needs

Diamond 3 – Developing a Solution Concept

Create a Prototype that Really Does the Job

Here are the videos from my Coursera Design Course on Prototyping.

Design the Product

Once you have a prototype that works very well for you, and perhaps for a few potential customers, you can actually design the product. Huh? What do I mean by design the product? I already have a working prototype. Sure, but that working prototype is not typically implemented in an economical and reliable way, and you have not fully specified the artifact in a way that a factory could produce it.

It’s possible that you can take your prototype to a factory that produces similar goods and that their employees can create the production documentation (e.g., computer models and drawings) required to actually make the components of your product. However, more typically, you need to do this specification yourself. Furthermore, the detailed specification of the product comprises your own intellectual property, and so you may wish to control it fairly closely. In that case, you will need to find someone who can create the documentation (e.g., drawings and models) that represent the production-intent version of your product.

There are lots of different types of skills that may be required for this task. I’m not able to detail them all here. A good next step may be to consult with some independent contractors via platforms such as Upwork to understand better your options.

Make and Sell 1000 (or even 100)

In all but the most time-critical competitive environments, at some point sooner rather than later you should just start making and selling your product. Ideally you would find a way to make and sell just a few — say 100 units. This will teach you so much more than doing further research and development. These first 100 units will not be very good, but hopefully they will be good enough that a few brave customers will buy them and give you feedback. The challenge is figuring out how to make just a few units that are both good enough that someone other than a family member could figure out how to use them and tolerate the inevitable warts on the product and that can be produced at reasonable cost. You shouldn’t expect to make any money on these units, but hopefully you won’t lose ridiculous sums either. In some cases you may need to find the resources to make 1000 units — when, for example, the production economics are such that it is just not possible to reasonably produce 100 pieces. Lots more to say about this, but hopefully this quick advice gets you started.

Find a Manufacturer

Here is a video on my own experiences finding a manufacturer in China. You may find it helpful.

Patents

A patent can be a useful element of a plan for developing and commercializing a product. However, it is not really a central element of that activity. Patenting an invention can wait until many of the technical and market risks have been addressed.

A patent by itself rarely has any commercial value. (An idea by itself has even less value.) To extract value from a product opportunity, an inventor must typically complete a product design, resolving the difficult trade-offs associated with addressing customer needs while minimizing production costs. Once this hard work is completed, a product design may have substantial value.

In most cases, pursuing a patent is not worth the effort except as part of a larger effort to take a product concept through to a substantial development milestone such as a working prototype. If the design is proven through prototyping and testing, a patent can be an important mechanism for increasing the value of this intellectual property.

Licensing a patent to a manufacturer as an individual inventor is very difficult. If you are serious about your product opportunity, be prepared to pursue commercialization of your product on your own or in partnership with a smaller company. Once you have demonstrated a market for the product, licensing to a larger entity becomes much more likely.

File a provisional patent application. For very little money, an individual using the guidelines in this chapter can file a provisional application. This action provides patent protection for a year, while you evaluate whether your idea is worth pursuing.

Here are a couple of videos with examples and details. (The textbook chapter I refer to in the first video is from Ulrich, Eppinger, and Yang — Product Design and Development.

Can You Make Money?

In the short run, do you have gross margin and can you acquire customers efficiently? Here are a couple of resources that may be helpful in answering these questions.

Go to Market Systems

In the long run, do you possess the alpha assets to sustain competitive advantage? Read this to learn more about alpha assets and the five flywheels.

Competition and Product Strategy

You may believe that you have identified a unique opportunity to create value with your new business. You’re probably mistaken about the unique part. Others have likely tried to do this job before, and some scrappy entrepreneurs just getting started elsewhere in the world probably share your hopes and dreams. Even if your insight is unique, it can’t remain a secret for long. If you are able to grow your business and achieve profitability, you will effectively be publishing the location of a gold mine to the public. Competition is a central, unavoidable characteristic of entrepreneurship. But, competition is not necessarily a bad thing, particularly at the dawn of a new market. Competitors can teach you a lot about what works and what doesn’t, spur you to innovate and move quickly, and share the burden of educating potential customers about an emerging market.

Many aspects of competition are unpredictable and so entrepreneurs should probably not spend inordinate time obsessing over rivals. Still, some attention to competition can result in smarter strategic choices in product positioning and in refining the definition of the beachhead market. Furthermore, potential investors will want to see that you have identified and analyzed the competition and have made sensible decisions about how to direct your efforts given the competitive landscape. As a way to organize this chapter and to avoid unnecessary theory, let me start with an identification of the key questions most entrepreneurs need to answer and the associated decisions they need to make. Then, I’ll illustrate several key concepts, analyses, and ways of presenting information that are most useful in addressing these questions and decisions.

What Questions are You Really Trying to Answer?

Three questions relevant over three different time horizons are usually most pressing.

First, is there really a gap in the market? This is the immediate question relevant to the decision to pursue an opportunity. Entrepreneurial opportunity is born out of disequilibrium, and for start-ups that disequilibrium is usually either (a) some technological change that has given rise to a new solution to an existing job to be done, or (b) some new job to be done that has emerged because of changes in attitudes, preferences, demographics, regulation, or other external forces. A closely related question is how big is the gap in the marketplace in terms of TAM and SAM.

Second, given that an opportunity exists, how should the specific attributes of your solution be positioned relative to the alternatives available to your potential customers? Positioning concerns both the decisions you make about the substantial features of your solution, as well as what you emphasize in your marketing efforts. This question is answered as you develop your solution, refine its characteristics, and craft a message for communicating your value proposition.

Third, how likely is your new organization to be able to sustain competitive advantage in the long term? In most cases a start-up’s most valuable assets relative to larger rivals are speed and agility. But, if you are successful, you will likely become bigger and a bit more sluggish. Existing and new companies will come for your customers. How can you thrive when that happens?

In order to answer these three questions, you’ll first form a hypothesis about the job to be done, the beachhead market, and your solution concept. If you are following the process in this handbook, this hypothesis is developed with the triple-diamond model. In any case, to consider the issues in this chapter you should have at least a preliminary decision in these three areas. In many cases, these preliminary decisions are the key elements of the description of the entrepreneurial opportunity.

With a hypothesis about the opportunity in hand, here’s a process to assess the competition, position your solution, and articulate how you will sustain competitive advantage:

  1. Identify the direct, indirect, and potential competitors and research their solutions and marketing strategy.
  2. Refine and articulate your value proposition by Iteratively refining your product positioning and by mapping your solution relative to those of direct competitors on the dimensions of product performance that most influence the value you offer to your potential customer.
  3. Develop your advantage thesis by articulating your alpha assets, the moats and barriers that you possess or hope to develop over time.

Identify Direct, Indirect, and Potential Competitors

In broad terms, competition is comprised of the organizations that deliver a solution that customers can select to do the job you have identified as the primary focus of your business. These rivals can be categorized as direct competition, indirect competition, and potential competition.

Direct competition refers to organizations that deliver essentially similar solutions to the same customer segment you are targeting and more or less addressing the same customer needs — the Coke and Pepsi of the soft drink market, UPS and FedEx for ground parcel delivery, Nike and Adidas in athletic shoes. Direct competitors are usually the most obvious and visible sources of competition.

Indirect competition refers to organizations that offer a substantially different solution to your segment for addressing the same or closely related customer needs. For example, Peet’s Coffee and Red Bull are indirect competitors for morning stimulants.

Potential competition refers to organizations that do not currently offer solutions to the focal customer segment, but who have the capability and incentive to do so in the future. For example, Amazon and Google are potential competitors in many markets where they do not currently operate, such as healthcare or education. Potential competitors are dormant, but may substantially pollute the attractiveness and sustainability of an opportunity given the possibility they may enter the market later.

Once you’ve identified the direct, indirect, and potential competitors, spend some time learning what you can about them. Devote the most time to direct competitors, but also investigate the indirect competitors; it’s possible they are more aligned with your beachhead market than you think. Your time is probably not best spent going deep on all the companies that could potentially be competitors — too much uncertainty clouds their role in your future. For the most relevant competitors, read white papers and articles; listen to podcasts; watch video interviews; try out their products; talk to their customers. These competitors, as a result of their marketing efforts, have effectively all run experiments out in full view of the public. You should take advantage of whatever information you can glean from what is working for them, what has not worked for them, and what weaknesses are revealed about them by their current efforts.

Refine and Articulate the Value Proposition

When you developed your solution concept, you probably used a concept selection matrix to compare alternatives. (See the chapter on Concept Development.) The criteria you used for comparison included the key customer needs for the beachhead market. Now pull out that list of needs again and revise and extend it until you have 6 – 10 key customer needs that will mostly determine the value that your solution can deliver to your customer.

Needs are usually expressed in the language of the customer, not as technical specifications. At this point you may wish to elaborate the metrics that most closely match each customer need. For instance, if the customer need for an electric vehicle is “has sufficient range for my daily needs” then some metrics might be “range at 50 kph average speed” and “range at 100 kph average speed” which would capture both city and highway driving.

Once you’ve compiled a list of needs, organize them in a table, along with the key performance specifications. Then, fill in the values for your solution and those of your direct — and possibly indirect — competitors. For example, Mokwheel is a relatively recent start-up company entering the electric bike market with the Mokwheel Basalt model.

Mokwheel bike solution concept. Source: Mokwheel

Here is a table showing the comparison of the Mokwheel Basalt relative to some of its competitors.

Customer NeedMetricMokwheelRad Power RadRover 6 PlusJuiced Bikes CC XNiner RIP E9 3-StarLectric XP 3.0Ride1UP 700 SeriesAventon Level.2
RangeMiles per charge on test course60453030253040
AffordabilityPrice (USD)$1,999$1,999$2,499$6,295$999$1,495$1,800
WeightKilograms35.934.325.023.528.624.528.1
Ride comfortSuspension typeFront fork suspension w/ lockout. Fat tires.Front fork suspension and rear coil-over suspension w/ lockoutFront fork suspension w/ lockout Full suspension w/ RockShox ZEB Select forkRigid frame/fork w/ fat tires for cushioningFront fork suspension w/ lockoutFront fork suspension
Payload capacityRack weight limit (Kg)8245N/AN/AN/AN/A55

The hypothesis for Mokwheel is that an affordable, rugged electric bicycle with very long range and huge cargo capacity will be well received in the beachhead market, even if the weight of the vehicle is relatively high.

Product Positioning on Key Dimensions

Competitive positioning is often boiled down to just two dimensions to allow visualization with a scatter plot. For this example, let’s assume that the two attributes of electric bikes that seem to best describe differences in products and in preferences in the market are weight and range.

Given two dimensions, we can then draw a map of the landscape of possible solutions. You could very reasonably object to this oversimplification. You’re right. In virtually any market, we oversimplify by representing the competitive landscape in two dimensions. Still, it’s done all the time, and has an obvious benefit for visualization. Recall that you have already captured the other dimensions that matter in the value proposition table from the previous section. You can experiment with which two dimensions are both important to customers and reflect meaningful differences among competitors.

Note that you can sometimes sneak in a third dimension, say price, by labeling the data markers in the scatter plot, as I’ve done with price below.

In using scatter plots for communicating product positioning, a distinction between two types of attributes is important. Weight and range are largely more-is-better or less-is-better attributes. Everyone can agree that — at least for reasonably foreseeable solutions — more range and less weight are desirable. All else equal, customers would prefer a product located in the upper left corner — low weight and high range. However, cost and technical feasibility likely make that position overly optimistic. In contrast, imagine you are designing a chocolate bar and that the two attributes of greatest importance to customers are (1) intensity of chocolate flavor and (2) crunchiness. For the chocolate bar domain, each customer likely has an ideal point — a combination of intensity of chocolate flavor and of crunchiness that they prefer. The producer can position the solution pretty much anywhere, as most positions are technically feasible at similar cost. Reinforced by these examples, we can probably all agree on some basic principles:

  • All else equal, a product should be positioned where there is demand.
  • All else equal, products should be positioned where there is little competitive intensity.
    • For more/less-is-better attributes, cost and technical feasibility constrain the position of your solution, and you likely will face trade-offs among competing attributes.

By the way, many of you have heard about or read the book Blue Ocean Strategy – that’s all the book really says. Put your product where there is demand and where there’s limited competition. Much of the field of quantitative market research is devoted to increasingly precise methods for measuring preferences and optimizing product positions in a competitive landscape. There’s nothing wrong with that logic or that approach. However, I want to warn you about two ways this approach to product positioning could lead you astray.

First, not every location in this space is feasible. Imagine, we were applying the same process, but for cameras, and our axes were image quality and size. There would be a big open area – a so-called “blue ocean” in the region of very high quality images and tiny size. Yet, the optics of photography introduce a fundamental tradeoff between size and quality, for a given imaging technology. This suggests that product strategy and product positioning in technology-intensive industries are cross-functional challenges, and that engineering breakthroughs are what allow for differentiation. For instance, the advent of computational photography, the use of image processing of several images in order to create one excellent composite image, which underlies much of the power of photography on today’s mobile devices, allows some loosening of the connection between camera size and image quality. In the electric bike market, advances in battery chemistry, motor efficiency, aerodynamics, and tire performance may allow for competitive positioning that beats the basic trade-offs reflected by existing competitors and solutions.

My second concern is probably more substantial. If you find yourself drawing two dimensional maps of your product landscape and debating the fine points of position, or if you find yourself building elaborate mathematical models to estimate market share in a crowded market for products in which a few attributes dominate consumer preference, you are probably not in a dynamic industry with abundant entrepreneurial opportunities. Rather, you are in a stagnant industry in which tuning is done by product marketing managers, and often based on mathematical models and consumer data. The goal is a few additional points of market share. If this is your situation, my advice is to find a way to make this industry less stable, to shake it up, and introduce some new dimensions of competition.

In fairness to the authors of Blue Ocean Strategy, shaking up the industry is more the essence of their message. Avoid head to head competition tuning product parameters within a highly evolved product landscape. Instead, look for a way to introduce new attributes to the competitive landscape. For example, in the chocolate bar space, consider the FlavaNaturals bar, which is made with cocoa that is super concentrated in flavonoids, which have been shown clinically to increase memory. Or consider the KIND bar, which cleverly blurs the boundary between candy and health food. It tempts the consumer with chocolatey flavor while presenting an image of wholesome goodness with the obvious use of nuts and seeds. Those are both competitors that have shaken up the more traditional dimensions of competition in the candy bar market.

Develop an Advantage Thesis

I’ve written a lot about competitive advantage elsewhere. (See Alpha assets and the Five Flywheels.) But, in sum, advantage always arises from controlling or possessing some resource that significantly enhances your performance in doing a job and that your rivals can’t easily get. I call those resources your alpha assets.

A unique solution is usually the start-up’s initial alpha asset. In a few rare instances, the solution will remain hard to imitate for a long time. For instance, in the pharmaceutical industry a new molecular entity can be patented, and what is patented is what eventually receives government approval. Thus, rivals can not offer the approved compound without infringing the patent. Given the typical time requirements for commercialization, such patent protection may offer 10 or even 15 years of exclusivity. But, outside of the biopharmaceutical industry, patents rarely provide strong barriers to imitation for very long (Ulrich, Eppinger, and Yang 2019). Your unique solution combined with your speed and agility probably give you a few years of advantage, at which point you had best have developed other sources of advantage. The most likely are brand and the scale economies enabled by a large established customer base.

Why Can’t Google Do this?

One of the most common questions that entrepreneurs face from investors is “Why can’t Google (or Apple, Meta, Amazon, et al.) do this?” This question reflects the concern that Google, or any other large and powerful company, could enter your market and offer a similar or better solution than yours, using their vast resources, capabilities, and customer base. The “Google question” is common enough to consider specifically. The answer varies depending on your industry, market, and product category. For example, consider how the answer may differ for two start-ups, one pursuing on-line dating and one pursuing cloud-based video services. Although these examples are specific to the competitive threat by Google, they are illustrative of how an entrepreneur might think about competitive threats from any large, powerful incumbent.

Google could enter the online dating market and offer a similar or better solution than a start-up, but it is unlikely that they will do so for several reasons. First, online dating is not aligned with Google’s mission, which is to organize the world’s information and make it universally accessible and useful. Second, the online dating market is fraught with privacy concerns. Google may face legal and ethical issues if it enters the online dating market and uses customer data for matching purposes. Third, online dating is a highly competitive and dynamic industry. Google may not exhibit sufficient agility to keep up with changing customer preferences and needs, as well as the emerging technologies and features in the online dating space. Putting these reasons together, one could argue that Google is not a serious potential competitor in the online dating market. In sum, Google could do it, but Google won’t do it.

Google could also enter the market for cloud-based video services and offer a similar or better solution than the start-up. They might credibly do so for several reasons. First, cloud services is their core business and competency. Google already offers a range of cloud services products such as Google Cloud Platform, Google Workspace, Google Cloud Storage, etc. It has the incentive and interest to enter a niche or specialized segment of the market in order to stimulate demand for Google’s core services. Second, cloud services is a technologically complex industry. Google has the resources and capabilities to enter the cloud services market and offer a high-quality and reliable solution that meets the needs and expectations of customers. Third, cloud services is large and growing industry. Google not only could do it, but Google likely will do it, and has the opportunity and potential to enter the cloud services market and capture a significant share of customers and revenue. If you are in the directly path of a company like Google in its core business, then you will likely need to make an argument about the importance of speed and agility, and some important alpha asset — such as network effects — that can be developed in the two or three years it will take Google to recognize and respond to the opportunity. You may of course also argue that Google would more likely acquire your start-up than build its business from scratch. Such arguments are weak, in my opinion, unless you can make a credible argument for why your start-up will have significant alpha assets within a few years, and in that case, whether or not Google would acquire the company, you have built something of substantial value.

Wrap-Up and Common Pitfalls

Your business plan or “pitch deck,” whether for investors or just for your own planning, should have a section on competition. Everyone expects that, and for good reason. You’ll usually have a table showing how your solution stacks up against the rival solutions on a handful of key customer needs. You’ll likely show your product position relative to direct competitors on a two-dimensional plot. You’ll devote some space to an articulation of your planned sources of long-term competitive advantage.

Do those things and at the same time avoid these rookie mistakes:

  • Do not claim that you have no competitors or that you are better than all of them. Every job to be done has been around in some form for a very long time in society. Your potential customers were getting that job done somehow before you had your bright idea. The pre-existing solutions are competitors.
  • Do not be dismissive of competitors. If there is an existing company doing the job you are setting out to do, then that company is more accomplished than you are at the time of your analysis. Show some respect and learn from that company’s experience.
  • Do not argue that you are the first mover, and that this is a source of competitive advantage. There are rarely first-mover advantages, except sometimes when the market exhibits very, very strong network effects. Consider that Google was not even one of the first ten companies to enter the internet search business.
  • Do not cite patents or “patent protection” as a significant source of competitive advantage. Unless you are a bio-pharmaceutical company, patents are at best a low picket fence around your solution. They are not typically a significant barrier to entry.

Notes

Karl T. Ulrich, Steven D. Eppinger, and Maria C. Yang. 2019. Product Design and Development. Chapter “Patents and Intellectual Property.” McGraw-Hill. New York.

Karl T. Ulrich. Alpha Assets and the Five Flywheels. Working Paper. The Wharton School. 2018.

Kim, W. C., and R. A. Mauborgne. 2005. Blue Ocean Strategy: How to Create Uncontested Market Space and Make the Competition Irrelevant. Boston: Harvard Business School Press.

Understanding Customer Needs (Diamond 2)

Let’s say I want to create a better eat-at-home meal solution for work-from-home professionals. That’s not really a strikingly novel problem. Indeed, food and beverage services are some of the oldest businesses in existence. I will face fierce competition to do the job. Why will customers choose my solution and not those of my competitors? 

Maybe because I do a better job of advertising, or because my product is more available, or because it’s priced lower. Those things are important for sure. But, much more significant, customers will choose my product if it better meets their needs.

The second diamond in the triple-diamond design process begins with a job to be done, understands the customer needs, and identifies one or more insights. There are two key goals of the second diamond. The first is to comprehensively catalog your customers’ needs. The second is to identify one or two latent needs – needs that are important but not yet addressed in the marketplace. We call these latent needs insights and they are useful in pulling a compelling solution concept when we get to the third diamond.

What are Customer Needs?

We aren’t here only talking about fundamental human needs in the sense of food, shelter, and belonging. Rather, for any given job to be done, customers typically care about 30 to 50 distinct attributes of a potential solution that if provided will result in greater satisfaction. We call these attributes needs, and they tend to vary a lot across individuals. For example, consider these two products. First, the Wendy’s Pretzel Bacon Pub Triple Cheeseburger. Second, the Soylent liquid meal. Both are solutions to the job “How might we provide lunch to hungry workers?” But, clearly the burger is better at meeting the primal craving for fat and salt, and the Soylent is better at meeting the need for high efficiency.

Wendy’s Pretzel Bacon Pub Triple Cheeseburger (Source: Wendy’s)
Soylent read-to-drink meal (Source: Soylent)

You have a focal customer, or type of customer, sometimes called your beachhead market, and represented by your customer persona. Once you have specified the target segments, a goal of the second diamond is to create a comprehensive list of user needs. There are entire textbooks that teach the methods for understanding user needs. In fact, I am a co-author of one of them (Ulrich et al. 2020). Here is an example of a comprehensive list of customer needs for a music player.

Example comprehensive list of customer needs for a music player.

How to Identify Customer Needs

In sum, you create this list by doing a set of open-ended interviews with individual potential customers. You interpret what you hear and see in terms of the individual underlying needs. 

You do your best to express these needs independently of solution concepts. So, instead of stating that the music player has a touch screen enabling a finger to rearrange the order of a playlist, you state that the music player allows the user to predetermine a sequence of songs, a statement independent of any particular solution concept. 

Once you have a comprehensive set of unique needs, you arrange them into clusters. For example, the primary need “The music player lets me control the music” is supported by a cluster of secondary needs that are more specific and detailed like “The music player lets me easily find and play music I have enjoyed previously” and “The music player lets me reduce frequency of play of a song.”

The full needs list is important for the ultimate product design. After all, you don’t want to miss anything important. You may also at some point use more formal quantitative customer research tools in order to understand which needs are most important across different market segments and the relative importance of say price and convenience for a particular segment. But, in the triple diamond model of design, our goal is the development of a compelling solution concept, and for that purpose, we are doing an initial exploration of customer needs in order to understand the important unmet needs among our potential customers – what we call an insight.

What is an Insight?

A woman named Emily Harper recently posted a video on the social media site TikTok showing how she prepares ground beef for use in recipes. With the comment that all this fat is disgusting, she is shown first cooking the meat and then washing it thoroughly with hot water using a wire strainer. The video went viral with seemingly half the world aghast that she had removed all the flavor from her food, and the other half thrilled at this revelation of a new technique for healthy living.

Your job as a zero-to-one product leader is not to pass judgment on crazy customer behavior. Rather, you benefit from acting like an anthropologist and asking yourself what deep insight does this behavior reveal about the nature of your potential customers.

In thinking about the opportunity for 99 Bowls, a service providing immediately available yummy food for work-from-home professionals, I hope to observe Emily with a curious and open mind.

The insight I derive from watching Emily going to extreme lengths to adhere to strict dietary constraints is that some individuals feel a compelling need to tightly control the macro nutrient profile of the food they eat.

Among designers, the term insight refers to a user need that is:

  1. authentic
  2. non-obvious, and
  3. significant.

Authentic means that the insight is based on an actual observation of users in the target market.

Non-obvious is self explanatory.

Significant means that if your solution addresses the need it would result in a meaningful enhancement in the value perceived by the customer.

In the second diamond of the triple-diamond model the designer achieves two goals: first, comprehensively identify the customer needs in the target segment and second, flag a small subset of those needs that comprise insights. 

Four Categories of Needs

The result of a set of customer needs interviews is a comprehensive list of customer needs, usually 30-50 distinct items. These needs can be sorted into four categories, illustrated by a framework from the Japanese total quality movement of the 1980s and 1990s called a Kano Diagram.

Four categories of needs as represented by a Kano Diagram. (Adapted from original by KTU.)

The horizontal axis is the extent to which the need is satisfied by the solution. The vertical axis is the resulting change in customer satisfaction, or perceived value of the solution.

The “don’t care” needs are needs that are irrelevant to the customer. Address them or not –  the customer’s satisfaction does not change. For example, for me, whether or not the food you deliver to me is gluten free, I don’t notice or care.

The “linear” needs are those for which the customer’s satisfaction is essentially directly proportional to the extent to which your solution addresses the need. For example, affordability is often a linear need. When the food is a little more expensive, I’m a little less satisfied.

The “must haves” are needs that if fully addressed do not result in dramatic improvements in satisfaction, but if not addressed at all, result in extreme dissatisfaction. For example, if a food container is microwavable, I don’t particularly notice. However, if the container immediately melts or sparks in the microwave, I’ll be very dissatisfied.

The “latent” needs are needs that if unaddressed are not missed, but if addressed result in surprise and delight. For example, if my food service allows me to precisely specify the macronutrients of my lunch, say 20% carbohydrates, 40% fat, and 40% protein, I’m thrilled.

While there have been some attempts to use the Kano framework quantitatively based on survey methods, it’s mostly conceptual. It gives you a way to think about customer needs and to direct your investment. Ignore the don’t cares. Deliver the must-haves. Invest at competitive parity in the linear needs. But, then, seek out the latent needs like hidden gems. The latent needs are by definition non-obvious. To the extent that they derive from your observation of users, they are authentic. Those that are significant – a big deal for customers if addressed – are insights. These insights will be used in the third diamond to pull compelling solution concepts.

How to do Customer Interviews

OK, but how do I actually get the information to identify the customer needs. Put simply, you get out of the office and interact with customers.

More specifically, you conduct at least 10 one-on-one interviews for each distinct market segment. For new zero-to-one products you’ll probably just have one beachhead market. Perhaps surprisingly, you need just 10 interviews to identify 90 percent of the customer needs that would eventually be revealed by interviewing hundreds of customers.

I recommend you do these interviews as follows:

  • Identify about 10 potential customers for each segment. These customers need not be typical. In fact, they could be extreme in some ways. After all, our ultimate goal is to find unmet needs, and sometimes the extreme users are better at revealing those needs. For example, if our segment is work-from-home professionals, we might interview some professionals who work from highly remote locations, say a cabin in the mountains. Or, we might interview workers who are extremely passionate about food, so called foodies, say those who are food writers. Or possibly those with extreme food regimens, say adherents of ketogenic diets.
  • Conduct the interviews either alone or with one other person. You can get by doing them alone, but you’ll find it easier to keep track of what you learn if you have a partner. The other advantage of doing interviews in pairs is that you can engage a lot of people in the process. For example, bringing members of your technical team on interviews is a very powerful way of developing empathy for the customer.
  • You can use an audio recording device, but honestly I rarely do. I think notes are pretty much just as effective. I think recordings are a bit obtrusive and they are rarely actually transcribed and used. Having said that, I do take a lot of photos and even some short video clips, as the visuals are very helpful in reporting on the interviews and in remembering specifics.
  • Do the interviews in the customer’s use environment if possible. If interviewing office workers about lunch, do the interview around lunch time at their offices. The reason for this approach is that you are going to observe as much as you are going to listen. You will develop an entirely different and better understanding of your customer if you observe them in their own world.
  • Plan on about an hour of unstructured conversation. I know this is a bit daunting for many people, but I’m pretty sure you can do it. I have four questions that I use to get the conversation started, but rarely need them. You simply start with an open-ended question related to the job to be done. For instance, “what’s your plan for lunch today?” Once you’ve asked a question, listen carefully to the response and look for an open door. For example, your customer might say, “well, I usually skip lunch.” That’s a huge open door. You know what to do – step through the door by asking, “really? Why’s that?” I guarantee a big fat customer need is about to be delivered to you with that question. The response might be “i’m trying to lose a few pounds” or “I don’t have time” or “I’m planning to eat a big dinner later” or “I forgot to bring my food” – whatever the customer says, you’ll learn a lot. If you walk through a bunch of doors and find yourself way off topic, bring the conversation back to the job to be done with one of your prepared questions. The prepared questions I like are “How do you currently do the job” which you’ll ask more naturally like “what do you do most days for lunch?” or “What issues do you consider when choosing what to do for lunch” or “what most annoys you about lunchtime?” or “what would be your perfect lunch experience?” Any of these questions will result in more open doors – then you step through them.
  • Whenever possible, ask the customer to show you as opposed to tell you about the question. For example, if the customer responds “I bring my lunch” ask to see the lunch itself. You’re going to learn a lot by observing them. For example, you might learn about office food storage, or dietary preferences, or portion sizes, all revealing of needs in a more direct and truthful way than would be an oral response to a question.
  • After your interview, sit with your partner and debrief. Revisit the conversation and identify as many needs as you can, even if obvious or obscure. This process results in a long list — usually 30-50 distinct needs. I say usually, but for some complex products there could be many more. I once worked on a project to design a better blood pressure monitor, and we identified about 400 distinct customer needs.
  • Finally, work to identify those needs that could be considered insights.

What About Large-Scale and Quantitative Market Research Techniques?

The triple diamond model of design is highly effective in understanding latent customer needs and in developing novel solution concepts in response to those needs. However, it has no mathematical underpinnings. There is no notion of statistical significance or estimation of the magnitude of a consumer response to a given feature. Many of you probably have backgrounds in engineering, economics, or mathematics and may be uncomfortable relying on such a qualitative process to create new products.

Of course your discomfort is justified. After all, in business we do really need to answer questions like how big is the addressable market? What should our price point and product specifications be? How will our new product fare in a competitive landscape?

These and other important questions are best answered with quantitative market research tools. 

But be careful – the triple-diamond model is intended to engage you in a rich and multi-sensory way with the customer. You won’t achieve that goal with a web-based survey. Avoid the impulse to employ quantitative market research techniques until after you have used the customer-centered, qualitative approach captured by the triple diamond model.

Notes

Ulrich, Eppinger, and Yang. 2020. Product Design and Development. McGraw-Hill.

List of highest-calorie fast-food burgers available in the United States. https://www.eatthis.com/fast-food-burgers-highest-calories/

Wikipedia description of Kano Model. https://en.wikipedia.org/wiki/Kano_model

Concept Development (Diamond 3)

The triple diamond model is a user-centered approach to design and concept development. The first two diamonds really focus on better defining the “what” – who is our customer, what is the job to be done, and what needs are potentially most relevant to them. In this chapter, we turn to the “how”? Given an understanding of the customer and the job to be done, how can we create a great solution? For this, we use the third diamond, another cycle of divergent and convergent thinking.

I want to underscore that the tools and approaches in this chapter have two contexts for application. First, these tools are used to create a great solution concept in the context of zero-to-one product development – say the original concept for the Strava fitness app. Second, these tools can be used in the daily work of individuals and teams for any kind of design challenge, say improving the social networking features within the Strava app, or even for internal innovation problems like how we might increase retention of customers on the Strava platform.

What makes for a great concept?

The goal of the triple diamond model is to deliver a great solution concept. But, what makes for a great concept?

A concept is a preliminary description of how you plan to do the job for the customer.

For physical goods, it’s usually a sketch of the physical embodiment of the solution. For example, here are 10 concepts that were generated by two of the students in my product design class at the University of Pennsylvania to do the job of carrying an ID card, a key, and perhaps a mobile device unobtrusively underneath clothing. They called the resulting product the underwallet. They did a particularly nice job of illustrating these concepts by hand.

For services, the concept is often illustrated with a visual storyboard, or possibly simply with a paragraph of text.

For software, the concept is usually illustrated with the screens that comprise the user interface on a mobile device or desktop computer.

Not all concepts are equally good. Here are the four characteristics that I believe make for a great concept.

1. Addresses Needs

The first and most important characteristics of a great concept is that it addresses the needs of the customer.

Here’s an example. I love Google Docs. The concept is a word processing tool that runs in the web browser with no downloads or installation required. The file is stored in the cloud and is backed up automatically with a history of prior versions. The file can be accessed from any device, including my mobile phone, or from multiple devices simultaneously. Search works great, allowing me to find a document with just a few keystrokes. The software is clean, simple, and fast. I can share a file with anyone or everyone with a couple of clicks. I can export the document as a PDF file if necessary. Other than one tiny complaint about how bullets are formatted, this product is perfect for my needs.

2. Cost Efficient

The second characteristic of a great concept is that it is cost efficient. Here is an example of a cost-efficient packaging concept. Many of you probably know about GLIDE dental floss. It was pioneered by the company WL Gore. It’s made from Teflon or polytetrafluoroethylene. The compound is very slippery and so glide is particularly valuable to customers whose teeth are tight up against each other. Thus, the name Glide.

Glide itself is an interesting product, but it’s the package that I want to talk about for a minute. The Glide floss package is a single injection molded part designed with a living hinge that allows it to both fold into the deployed configuration, include an integral cap, and to be configured in a way that it can be molded as a single piece, and in a way that the part can easily come out of the mold.

My guess is that the manufacturing cost of this package is a few cents. Although the smooth pebble-like form is unobjectionable, the glide concept really shines not because of its beauty or function, but because of its extreme cost efficiency.

3. Wow Factor

The third characteristic of a great concept is what I call the wow factor. Here’s an example. I have an app on my mobile device called “Picture This.” I was riding my mountain bike this past summer and sat down for a rest. I smelled an interesting minty fragrance, which seemed to be coming from foliage near my feet. I snapped a photo using PictureThis and within seconds the app told me I was looking at Mountain Monardella, also known as mountain coyote mint. Who knew? Picture This has a bunch of nice features including the ability to keep a database of plants previously identified. But, the wow evoked when some image processing algorithm identifies a plant from a snapshot is magic.

The wow factor is valuable for at least two reasons. First in a commercial context, if you have some wow, then you typically also can achieve some intellectual property protection, usually in the form of a patent. This can provide a modest and temporary barrier to competitors replicating your design.

The second reason, and perhaps the more important reason, is that if you’ve got some wow in your concept, then you have something to talk about in the market, and you can get a user excited about the product. In a commercial setting it allows for your product to distinguish itself from the competing alternatives.

4. Aesthetics and Elegance

The fourth and final characteristic of a great concept is aesthetics and elegance. That is, as designers we should strive to create things that are beautiful. I can wax on about the beauty of purely functional objects, but automobiles are perhaps more interesting examples because they embody a complex bundle of function, identity, and meaning. When Volkswagen announced its all electric microbus, it revealed a concept to which a lot of attention had been paid to aesthetics, including a careful and tasteful reflection of the heritage of the original VW van.

Source: https://fortune.com/2022/01/06/volkswagen-to-finally-reveal-the-id-buzz-ev-spiritual-successor-to-the-iconic-vw-bus/

OK so those are objectives. We want to create something that meets user needs, can be produced at low cost, has some wow, and is beautiful.

Concepts for Digital Goods

The four elements that make for a great concept are particularly important for physical goods and for services. In both physical goods and services, cost is critically important. However, for digital goods, cost is usually less important.

Furthermore digital goods can often be thought of more as bundles of features than as a single distinctive solution concept. These features can be added and subtracted incrementally over time as the product evolves.

Perhaps in part for these reasons, the development of a great concept tends to receive less attention for digital goods than it does for physical goods or services. Zero-to-one product managers sometimes feel that a software solution concept follows directly from the job to be done and the customer needs, and even if it doesn’t, the solution can be refined over time.

I think this view is a mistake. Digital goods offer almost unlimited flexibility in solution approach, so if anything, a thorough exploration of the solution landscape is even more important in digital goods than it is in physical goods.

Let me give you a few examples of distinctive concepts in digital goods.

Twitter – what’s the concept? A social network organized around the idea of followers in which an individual creates a virtual bulletin board, usually viewable by the public, in which messages of 144 characters or less are posted chronologically. Messages are pushed to followers and appear on a scrollable feed. (Of course many features have been added over the years, including direct messaging, the ability to respond to tweets, the ability to like tweets and so forth, but the original and still essential concept is quite distinct.)

Slack – what’s the concept? SMS/Txt for work, organized around topical channels. The big idea is to consolidate information and discussions into threads by topic to avoid the chaos of email. Again, many additional features have been added over time, including document sharing, emoji responses, push notifications and so forth. But, the big idea remains asynchronous communication for work organized by topic.

Tinder – what’s the concept? A mobile-only dating app focused on photos, in which individuals express interest in a potential partner by swiping an image to the right, and rejecting a potential partner by swiping an image to the left. When and if two parties swipe right on each other, the app declares a match and allows the two parties to start a conversation via text message.

Strava – a GPS-enabled fitness app, originally focused on running, in which an individual’s route and running time are automatically recorded, and then shared with a network of other runners. The route is automatically divided into segments and a leaderboard is established for the fastest times along those segments.

Because these concepts have been so successful, we take them for granted, even assuming that there could only be one way to do things. But, that perception reflects a hindsight bias.

There are a huge number of possible solution concepts for virtually any problem domain. For example, consider the simple task of listening to pre-recorded music using a digital device. What are the different ways that might be done?

One early solution, Apple iTunes, had these key elements. The iTunes store in which you could buy individual songs, originally for USD 1 each. Then, local storage of those songs in a master library on a physical device. Then, the creation of playlists from the master library. That was it.

A very different, and quite revolutionary concept arrived with the service Pandora. With Pandora, a user simply typed a single song or artist into a web-based application and Pandora created a virtual radio station based on other songs that shared the same “music genome” – Pandora’s name for the distinctive musical elements of a song. No need to create playlists. Pandora does it for you, and you can have as many stations as you want for  free, if you are willing to listen to some audio advertisements, or if not, for a single monthly subscription fee.

Then, Spotify came along with an all-you-can-eat subscription service in which you could create playlists from extensive available catalogs, but without actually having to own and keep track of the digital content itself.

Today, YouTube Music is a significant player in the music space. The insight addressed by YouTube is that in many settings people really want the option of viewing video of the artists from live performances or highly produced visuals.

I know some of you are thinking that these different ways of listening to music are now blended together on many platforms. For example, Spotify allows for downloading of files for off-line listening and allows for the use of Pandora-like stations. By the way, I recommend the “dinner chill” station for nice music for dinner parties.

This convergence is a reflection of the massive amount of experimentation and innovation that competitors have engaged in over about two decades at the beginning of this century. At some point preferences of customers became clear, market segments came into focus, and the solution concepts matured and became fairly stable. This is the normal pattern of evolution in an industry.

The maturation of the approach an industry takes to doing a job is another reason concept development may not be emphasized as much as it should be for digital goods. So often the product manager joins the team long after the original solution concept was established. Anyone joining Strava today as a product manager would not likely be doing a zero-to-one design for a new app, but rather would be improving and tuning an existing app. Still, even in this context, the skill of concept development is important. Even if you are working on some small feature within a larger established product context, you should strive for a solution concept that meets needs, is cost efficient, has some wow, and is beautiful.

Concept Development – Basic Approach

The essence of the third diamond in the triple diamond model is another cycle of divergent and convergent thinking. 

Concept generation and selection is essentially a mini tournament of ideas. We’re going to generate a lot of alternatives; a dozen or maybe even a hundred different solution concepts. We’re then going to select from among those in order to find an exceptional concept.  For most people this does not come naturally. The good news is that as with most challenges in life, a little bit of process and practice goes a long way.

Before we get into the mechanics of how to actually do this, I want to emphasize three points.

First, I want to emphasize that concept generation is really hard. It takes much more effort than most people appreciate. I do not want to sugar coat this reality. Here’s an example to illustrate what I mean.

Some of you might have noticed a little stick figure in some of my illustrations. The stick figure is one element of one graphic in a few sessions of one of my courses. There are hundreds of such elements.

“Stick Figure” in lower left

But that little stick figure concept is the result of deliberate exploration. I went back through my files and I found this sheet showing more than 100 different alternatives for what that stick figure might look like. I eventually found one that I thought worked quite well. Some of you are rolling your eyes and thinking how can it possibly be worth investing that kind of effort in a stick figure. You could be right.

But, the point I want to make here is that the tiniest design challenge when done well still requires tremendous effort. This is hard work. You need to be prepared to do the hard work to get great outcomes.

As a slight aside, let me make a comment about life and professional success more generally. You should embrace things that are hard, especially when by hard, I really mean just putting in the effort. If you can internalize the idea that great concepts are mostly the result of hard work, while others believe a spark of creative genius is required, then you have a superpower. You can be confident that if you do the work using a solid process, you are going to get better results than everyone else, and all you have to do is show up and do the work.

The second point I want to make about exploration is that we need to be open to ideas that come from anywhere and everywhere. Sometimes it’s even dumb luck that leads to a great design concept.

Here’s an example. I’m the inventor of a product called the Nexride bicycle seat. Let me tell you where the concept came from. A few  years ago I was working on creating a better bicycle seat. As part of the process I was testing out several of the existing non-traditional products. I was out riding one of the saddles that’s essentially a bench-shaped form mounted perpendicular to the direction of travel.

So, I’m out riding about 30 kilometers from home when the clamp that attaches the seat post to the frame breaks. This meant not only that the seat fell down so that it was right up against the frame, but also that it was free to pivot side to side. I considered walking home, but then decided I should try to ride the bike anyway, as that approach would still be faster than walking. To my dismay I discovered that the pivoting action allowed by the lack of a rigid clamp made the saddle much more comfortable. It allowed the bench to get out of the way as my leg extended on the down stroke.

I immediately went home and created a prototype of a pivoting bike seat, and I eventually ended up inventing a new saddle, the Nexride bicycle seat.

I say “invent” but really that concept came from a dumb accident – a broken bolt out on a bike ride. I’m not complaining. In fact,  I’m emphasizing that you need to be open to the possibility of ideas from any source including random occurrences.

Lastly I want to point out that even though we have a process, and I am going to teach you some methods for doing exploration, please understand that concept generation tends to be highly iterative. It’s quite likely that as you generate ideas, the definition of your job to be done will come into better focus. It’s also quite possible that as you proceed to refine a particular concept and build and test prototypes, you’ll have additional ideas for new concepts. That’s normal. Don’t be alarmed. That iteration is fundamental to the way design happens in practice. 

A few years ago I founded a company called Terrapass. We provided a service to offset the environmental footprint of driving a car. Given the complexity of understanding what and how we actually mitigated environmental damage, we settled on a solution concept that was very simple. For one fixed fee, USD 79 per year, we would provide enough carbon dioxide credits to offset the emissions of your car. See, it’s really, really hard to explain the product clearly. Still, what we discovered was that our customer was really interested in the details, and had a deep appetite for understanding  the nuance of the environmental impact of driving. We found that we had to modify our concept, and actually increase complexity by adding a highly customizable emissions calculator to our website. This solution allowed the customer to precisely specify the make and model of their car, the amount of driving they did, and their driving habits. Iteration on the solution concept is usually required in order to achieve great outcomes. 

Ideation process

I’ve mostly talked about the third diamond in generalities. Let’s dive into the details, starting with the divergent part. How can you reliably generate a lot of solution concepts?

The human mind is pretty good at thinking of solution concepts, especially after considering carefully the job to be done and engaging with the customer. So, before getting too fancy, just write down or sketch out any ideas you have from the top of your mind. In my experience, you already have at least three or four ideas. 

Now comes the part that really differentiates expert creators from novices. Just put those ideas aside. They may eventually prove to be the best solution to the job at hand. But, experts know that those ideas are not going away. You’ve already captured them. So, just let them go for now. Move on and see if you can generate another half dozen or more alternatives.

You can use some simple techniques to stimulate your thinking. Here are five that I like.

First, pull from insights. You’ve already invested heavily in the second diamond, understanding the customer, and that effort should have produced a couple of insights. Insights are customer needs that are authentic, non-obvious, and significant. I guarantee you that if you identify an insight, a solution concept will just fall out of your mind.

Let’s try it. My hoped-for new venture 99 Bowls makes and ships frozen prepared lunch foods like soups, chowder, and chili to professionals working from home. In my customer research, I identified the insight that many people strive to tightly control the macro nutrient profile of their food. For example, some want higher fat and lower carbohydrates, and others low fat and high protein. Can you think of any solution concepts for 99 Bowls that would be responsive to that insight? 

Of course you can. Here are a few. How about starting with standard recipes, say for chili (a mexican-inspired spicy soup), but whose ingredients can be adjusted in a custom production process to deliver a pre-specified macro nutrient profile? Want higher fat and lower protein? Increase the amount of cheddar cheese and reduce the amount of ground turkey. Want higher carbohydrates? Substitute corn kernels for the cheddar. Another would be to have a vast assortment of soups, but then to automatically filter the options to those that satisfy the customer’s desired nutrient profile. A third option would be a sort of bento box that assembles different food items – say sliced turkey, pita chips, hummus, and cheese – into a lunch portfolio that satisfies the overall target nutrient profile.

In fact, the whole purpose for finding those insights in the first place is to use them to pull distinctive solution concepts. This technique is the most powerful item in your concept generation tool kit.

A second approach is to apply the decomposition principle, focusing on just one element of the job to be done. You can decompose by customer needs, which is essentially what we do when focusing on an insight, or you can decompose by sequence of user actions or according to different sub-functions within a larger solution. For example, for 99 Bowls we might decompose the overall service into selection, ordering, delivery, and consumption. Now, focus on just one of those functions and consider all the different ways you might do it. For instance, consider delivery. 99Bowls could ship a carton of 12 individual servings that are frozen and placed in insulated packaging. Or, the customer could pick up a month’s supply at a regional refrigerated drop-off point. Or, a single serving could be delivered ready to eat at a pre-specified time each day. Or, the company could locate a compact freezer in apartment complexes and neighborhoods acting as a sort of vending machine for meals that have been pre-purchased. We could follow the same process for the other sub-functions, say selection. Once the decomposed problem has been tackled, pieces that work together can be assembled into complete solution concepts.

In a third approach, consider how an organization with a distinctive approach to product would solve the problem. For example, how would the Japanese household products company Muji implement 99 Bowls? I’m envisioning very tidy and beautiful containers, likely rectangular in shape that stack into a modular storage and shipping solution. The containers are either reusable or returnable. How would Nike do it? Maybe with selections endorsed by famous athletes – say the Michael Jordan meal plan. How would Netflix do it? They would make meal suggestions based on my eating history. You get the idea – take the best elements of the distinctive approaches of other companies and see how they might apply to your challenge.

Fourth, consider analogous problem domains. 99 Bowls is trying to solve the problem of what’s for lunch while working from home. What’s an analogous problem? Maybe the problem of what to watch at home in the evening. How do I solve that problem? I have different channels and platforms like YouTube, Disney, HBO, and Hulu. Maybe I can have different lunch channels, with varied offerings.

Fifth, set a numerical goal. I generally like to use a goal of 10 distinct solution concepts. Over thirty years of teaching product development, I’ve found that the number 10 is challenging, but achievable. If you have identified 10 distinct ways to do a job, you have probably done a decent job of covering the landscape.

All else equal, the easiest way to find a better idea is to generate more ideas. And, the easiest way to generate more ideas is to engage more people. Engage your team. Engage your engineers. Engage your customers. Ask anyone who will listen if they have suggestions or ideas about how to do the job.

One technique I like when working with a team, is to prepare in advance a list of what I call Emergency Stimuli. These are prompts that might dislodge new ideas. Here’s an example of some stimuli for the 99 Bowls challenge.

  • What food trends are taking hold in restaurants located around busy office complexes? Might some of those trends be applied in a home delivery service?
  • As increasing numbers of professionals work from home, what are the most common complaints about the experience? Might 99 Bowls address some of those pain points?
  • What innovations in food science are emerging, but perhaps not yet widely available? Might some of those innovations be incorporated into the 99 Bowls solution.

In my experience, almost any prompt will work to get team members unstuck. Just think of a handful of questions that can nudge people to think differently, and then use those questions when and if the ideation process gets stalled or people complain they are out of ideas.

The divergent portion of the third diamond is all about generating a lot of alternatives. There’s no shortcut, other than perhaps the trick of involving a lot of people, which certainly makes the task easier. Apply the process, do the work, engage a team, and you’ll end up with a rich set of solution concepts.

Harnessing the Power of Individuals and Groups

Some projects are completed by individuals working alone, but more typically you will find yourself in a team. How can you most effectively harness the power of individuals and groups to generate concepts?

The most common organizational practice is to call a meeting and to conduct a brainstorming session. You’ve all done this. You get a group of people around the table. Maybe you have a flip chart and an easel or a whiteboard, and someone facilitates the meeting.

I exaggerate only slightly in saying that this is probably the single worst thing you can do in order to effectively deploy your team.

Let me make an analogy. Imagine that you and your team are on a small plane that crashes on a remote island. Everyone survives but your first task at hand is to find food, water, and shelter – this is the metaphorical equivalent of looking for a great solution concept.

Now imagine two strategies. In the first, the team huddles together in a rugby scrum and you wander around as a group looking at the ground together. That’s the equivalent in organizational life to calling a meeting.

In a second scenario, everyone on the team heads off in different directions, with the mandate to come back and report on what they found after 30 minutes. Then, after sharing information you all go look more carefully in the most promising areas.

Hopefully your intuition is that the second approach will more reliably find the best food, water, and shelter. This same strategy of employing independent parallel exploration is also the best way to engage a group in concept development.

You don’t have to take my word for it. My colleagues Christian Terwiesch, Karan Girotra, and I have tested this idea experimentally. We compared two different approaches to ideation. In what we call the group approach, four people work together for 30 minutes. In a second technique, we call the hybrid approach, those same four people work for 10 minutes alone as individuals independently and in parallel and then those four people work together for 20 minutes exploring the ideas that they generated alone as individuals.

We did this study with 44 individuals divided into 11 groups of 4 and we had them work on exploring for alternatives for two different product design problems.

We found that with the hybrid approach the same 4 individuals could generate about 2 – 1/2 times more ideas if they took the hybrid approach than if they worked together as a group.

Not only that but the ideas they generated were actually better in quality as well. 

We have unambiguous evidence that a hybrid process is better than a group process and that you need to have an individual phase for at least some of your exploration effort. 

It’s very helpful to provide a numerical target for that individual phase. I usually use a goal of 10 ideas per individual.

Lastly, some people find out that it’s very hard in some organizations to actually get people to do their homework –  that is to actually do the assigned work of generating 10 ideas working individually. 

If that’s the case for you, then I recommended you go ahead and call a meeting, which is effective in getting people to allocate some time.  But then after you’ve called the meeting and after you’ve got people together, you ask them to work alone for the first 10 minutes, after which you can proceed to work together as a group.

Just to be sure I’m clear, I want to reiterate that I’m not opposed to working in teams. Rather, you should cherish the value of the team resource and work to deploy it most effectively, by having your team members spend some time working individually and alone before you bring together team members into a group process.

Selection Methods and the Concept Selection Matrix

The third diamond in the triple-diamond model includes a convergence from many solution alternatives to a single plan for going forward. We clearly shouldn’t pick from our alternatives at random. How do we converge?

In most cases, the convergence comprises two steps. First, the team, without the benefit of any external testing, narrows a set of 10 or more solution alternatives to a few, say 2 or 3. Second, some kind of testing with potential customers is used to converge on the best single solution. Here I focus on the first step – screening and selecting internally.

The technique used most widely in practice is multi-attribute utility analysis — which is an overly fancy name for a criteria matrix. Even if you don’t know the technical name, you’ve probably used one of these tables before. In this example I use a google sheet to quickly create the matrix, but any table will do, even a marker on a whiteboard.

Just as an arbitrary convention, I like to use the columns for the different solution alternatives and the rows for the criteria.

A desirable characteristic of a structured selection method is that you can remember, codify, and communicate the logic behind a decision long after it has been made. The selection matrix is self documenting. So, if you do use a whiteboard, remember to snap a photo for archival purposes.

For physical goods, I find it is sometimes nice to draw a little sketch next to the textual description of the concept at the head of each column. You can also use a separate document with illustrations to document in more detail each of the concepts captured by the matrix.

The rows of the matrix are the selection criteria. I like the criteria to be the key customer needs. In this example I’ve shown three needs – quick and easy to use, removes all the ice cream from the container, and forms a nice ball. Almost always there are three additional criteria that apply, and they are cost or some measure of the economic efficiency of delivering the solution, wow, that is how fundamentally interesting and novel is the solution, and elegance and beauty. These criteria map directly to the universally desirable attributes of a solution concept.

Now you just consider the relative performance of each concept relative to the criteria. The convention that I like to use for representing relative performance is a three level scale using a plus, a zero, and a minus.

Note that even though I use the term cost here, I adopt the convention that plus is always better, and minus is always worse, so a plus indicates lower cost.

Once you’ve evaluated all of the concepts relative to all of the other criteria, you can then summarize the net score by adding up plusses and subtracting minuses for each concept.

One positive outcome of the selection process is that it helps the team to realize when elements of one concept might be combined with another, or when concepts are actually quite similar to each other. For instance, as a result of this process, I discovered that concept E was conceptually very similar to concept G, a concept that I ended up pursuing further.

In this example, two concepts really stood out as superior, and so I focused on those two for further development. I often see three concepts that emerge as most promising. Rarely does a team have more than three really compelling concepts based on this internal selection process.

Now those of you who are more right brained have an objection. You argue that we can’t really reduce everything in life to a quantitative evaluation. Instead you need to make a more holistic judgment of the qualities of the concepts.

I hear you on this point, and I think it’s good discipline to see if you can get the concept selection matrix to be consistent with your intuition. That suggests that you’ve been able to capture what’s really behind your intuition, and that will benefit you when you go to communicate your rationale to other people, maybe to the more left brain of the stakeholders on the project.

[As a complete aside, I know remembering what those terms left brain and right brain mean is really hard – they are terrible labels. Here’s the mnemonic device I use. Remember that LEFT is LOGICAL…]

Those of you who are more left brained have your own objection. You argue that not all criteria are equally important and that it’s hard to reflect accurately the relative quality of concepts using just three levels. 

Of course both of these concerns are valid. For this quick selection method to be effective, the criteria need to be roughly equal in importance, and in some cases, a crude three-level quality rating will mask some huge differences in relative quality of concepts. You can of course easily modify the criteria matrix to increase the number of quality levels, say using a  1 to 5 scale, and you can weight the relative importance of the criteria using a percentage weighting scheme or a point system. However, in my experience, if the goal is merely to narrow a set of alternatives to about three, then the simple criteria matrix will work quite well.

Concept Testing 

In the third diamond, we are sort of flying blind. It’s been a while since we engaged with our potential customers. For this reason, we need to do some concept testing.

Let me illustrate why this is so important using a simple example. Imagine you are designing a new hot sauce.  (Have you noticed by the way that I use a lot of food examples? That’s because I love food.)

You can think of any individual as having an ideal point, which is their true preference, say on two dimensions of saltiness and spiciness. When you interview them and observe them, they tell you how much salt and heat they like – maybe they tell you they like it really hot and not very salty. Of course, you as the designer don’t hear them perfectly well, and they are not perfectly accurate in describing what they like. There’s inevitably some imprecision.

Then, you go to the lab and create a product based on what you understand, and there is a further translation error in that execution. By the time, you’ve gone through three phases of interpretation, what you have cooked up and what the customer wants are likely not perfectly aligned. Correcting any such mismatch is not hard. You give them a prototype of your hot sauce and ask them what they think. Yikes, they say, that’s too hot and tastes sort of bland. Hopefully you land pretty close though, and can incrementally refine your solution to hit the target.

Of course, I bet very few of you are designing hot sauce, but the same logic applies to creating a service experience or a piece of software. What the customer tells you, how you understand it, and the fidelity of your engineering process will inevitably result in a mismatch between what the customer actually wants and what you have actually built. Concept testing lets us estimate whether or not you have a good match before you actually develop the product.

There are three common types of concept tests. The first is informal qualitative feedback based on a quite schematic description of the solution concept. For example, this is the very first prototype of the Apple iPod. It was made by Tony Fadell from cardboard covered with a laser printed graphic. I bet it didn’t take more than an hour to build.

Source: Tony Fadell. Build.

You can’t have too much feedback on prototypes. Even showing potential users hand-drawn screens on paper – sometimes called “paper prototypes” – is super helpful in clarifying where the solution concept misses the mark.

In a second type of concept test, you set up a forced choice among a small set of concept alternatives, usually three.

For example, here is a forced choice concept test for three ice cream scoop concepts. The 3 options typically result from an internal concept selection process using a criteria matrix in which 10 original concepts are narrowed to 2 or 3.

You can use this kind of forced choice in lots of different design settings, not necessarily just for overall product concepts. Here’s another example of a forced-choice survey I used in testing three possible names for the environmental services company I co-founded. The name Terrapass was the clear winner and we went with that option.

In a third type of concept test, you ask potential consumers to indicate their purchase intent. Purchase intent is almost always measured using a five-box scale, from definitely would not purchase to definitely would purchase.

Here’s one of the ice cream scoop concepts as it would be used in a purchase-intent survey.

Purchase intent surveys are notoriously imprecise in predicting demand, but they are the best single predictor of consumer acceptance of a new product at the concept phase of development. I believe they are best used for relative comparison of several concepts. In my own research, I have found that you can test up to 50 concepts with a single respondent without too much fatigue, and that you only need a sample of about 15 representative consumers to get a reliable estimate of how potential customers will react to your product.

Of course the way you represent solution concepts to your audience influences their response. For example here’s the same purchase intent survey with the concept illustrated with a photo-realistic rendering. In this case the vibrance of the color is much more evident than with a black-and-white line drawing.

You will probably not have the details of your concept fully worked out when you engage in concept testing, so you will have to just do your best in representing the solution. In my opinion, consistency in the fidelity of the concept descriptions across different concepts is more important than the absolute level of quality of the representation of your concepts.

More Iterative Refinement

If you are very lucky, you will find that the concept you select (1) meets the customer needs, (2) is cost efficient, (3) evokes the “wow” response, and (4) exhibits beauty and elegance. More likely, significant iterative refinement remains as you put prototypes in front of potential customers and refine your solution. That’s normal. Hopefully, however, the results of a deliberate concept development process get you close to the target and a process of incremental improvement will allow you to hit the bullseye.

Notes

Karl T. Ulrich, Steven D. Eppinger, and Maria C. Yang. 2020. Product Design and Development. McGraw-Hill. New York.

Laura Kornish and Karl T. Ulrich. 2014. The Importance of the Raw Idea in Innovation: Testing the Sow’s Ear Hypothesis. J. Marketing Research.

Karan Girotra, Christian Terwiesch, and Karl T. Ulrich. 2010. Idea Generation and the Quality of the Best Idea. Management Science. Vol. 56, No. 4, pp. 591–605.

Tony Fadell. 2022. Build: An Unorthodox Guide to Making Things Worth Making. Harper Business.

The Triple-Diamond Model of Design

I’ve been a product designer my entire adult life. Here is one of the products I created, the Belle-V ice cream scoop. In full disclosure, I had a lot of help from a talented team. When people see the product they impute genius to the designer – wow, that’s amazing. How did you come up with that?

I’m using an example of a physical good for specificity, but I’ve experienced the same kind of reaction to digital products and services.

The reality is that I learned an effective process when I was in my 20s and I’ve applied that process repeatedly, sometimes weekly or even daily for 40 years. When you only observe the outcome, the results seem magical. But, the truth is that a fairly straightforward sequence of process steps can reliably lead you to a great result.

Design is just another word for the pull approach to innovation. All design processes are a sequence of steps that begin with some articulation of the “what” and result in some description of the “how” – the process moves from what to how.

Commercial phase-gate product development processes are just an elaboration of that basic idea, with lots of detail. My textbook on product design and development (Ulrich et al. 2020) is a comprehensive description of that detail. Most of you working in larger organizations probably use some sort of phase-gate process that is specific to your industry.

But, here I’m going to abstract a bit, and focus on the elemental design process – what is design at its very core. While design is the core problem solving approach within the product development process, design can be applied beyond product development. It’s almost a building block of being human – of dealing with life.

My goal is to describe the design process in a way that it can be used in myriad situations, from the creation of a new product from scratch, to the improvement of an existing product, and even for solving internal innovation challenges such as finding new ways to reduce waiting times in emergency departments.

To reiterate, the standard phase-gate product development process is a fully elaborated methodology that typically includes the roles of different functions within the organization. It emphasizes not only what to do in each phase, but the notion of a gate that must be cleared in order to proceed to the next phase. I am now going to boil that basic process down to its essence to give you a tool I call the triple-diamond model that can be used not just in zero-to-one product development, but also in almost any other problem solving situation.

To give credit where credit is due, the triple-diamond model is my extension and elaboration of the Double Diamond Model articulated by the UK-based Design Council, a non-profit organization with the mission of improving design practices.

The three diamonds correspond to three steps. 

  1. Clarify the job to be done in a jobs analysis
  2. Understand the needs of the customer or user. 
  3. Create a great solution concept.

In practice, a fourth phase is usually important – implementing that concept in a way that the organization can actually deliver the solution. This involves writing the code, designing the parts, and planning for production.

The three diamonds each represent a cycle of divergent and convergent thinking. For each diamond, the designer explores alternatives, and then focuses.

The first diamond answers the question, “What is the job to be done?” It starts with a target customer and the gap or pain point as you have first sensed it, and it results in a carefully considered reframing of the design problem in terms of a job to be done. In fact, one of the critical elements of an effective design process is not even really problem solving so much as problem definition.

The second diamond begins with a job to be done and develops a comprehensive understanding of the customer needs, which are those aspects of a solution that could result in satisfaction and even delight if satisfied. The convergent portion of the second diamond identifies one or a few insights, which are essentially important customer needs that were previously not known.

The third diamond uses those customer insights to pull many possible solution concepts and then selects one or a few for further refinement and testing.

Let me show you how the three diamonds played out for the Belle-V scoop. I started with a vague sense that ice cream was really hard to scoop. In diamond 1, I focused on the at-home consumer of ice cream and came up with the job to be done “How might we better dispense bulk ice cream into individual portions?” In the second diamond, I observed people scooping ice cream and noticed that the wrist angle was quite awkward, even painful for some people. That insight allowed me to pull several different solution concepts, including the one that eventually was embodied in the product, a more or less conventional scoop, but with the scoop angled relative to the handle.

Of course, really, it’s diamonds all the way down. The triple diamond model focuses on the concept development process, but when the team proceeds to build the product based around a concept, it will almost certainly use additional cycles of divergent and convergent techniques in order to solve downstream problems, say for establishing a product architecture, or implementing specific components of the solution. For example, even after we had converged on the solution concept of an angled scoop, we did a huge amount of exploration to find the final form of the object. Another diamond focused on the detailed design of the shape of the scoop and handle. And for that matter, there was another diamond when we considered the surface finish of the scoop – divergent exploration of alternatives and then convergence on tri-valent chrome plating.

Some of you are thinking that this model seems pretty tidy for a very simple piece of hardware like an ice cream scoop, but may not apply to more complex goods and services, say to enterprise software or to a hotel experience. I have a couple of reactions to those reasonable thoughts. 

First, as an aside, there’s a reason they call it HARD-ware – it’s hard. Even a simple object like an ice cream scoop presents a lot of complexity and challenges when it comes to actually getting it to the marketplace. 

But, more substantively, for new, zero-to-one systems, software, or services, you must still devise an overarching solution concept. For example, consider LinkedIn – the top-level solution is essentially a user-created resume-like profile with the ability to establish a connection between two individuals, and then the ability to search 1st, 2nd, and 3rd order connections in the resulting professional network. Such an overarching concept could be developed with the triple diamond model. 

For established systems, the triple diamond will be unlikely to be applied to the entire product or suite of products, but rather more likely to a feature within that more complex product. For example, once LinkedIn had become a successful product, the triple diamond model could still be applied, but to a new feature, say the creation of the follower feature, which allows individuals to follow another person and get updates that person publishes, but without requiring the individual to become a bi-lateral connection.

Problem Solving, Design, and Design Thinking

I happened to be on a holiday ski trip when I was writing this chapter. (I know, that doesn’t sound like that much of a holiday.) I kept thinking to myself, skiing is fun, but it’s a huge annoyance to actually get on the slopes. For most novice skiers, you have to procure skis, boots, poles, helmet, goggles, and warm clothing. Then, you have to put all that stuff on. Then, while fully dressed in really warm gear you have to walk awkwardly from transportation to a ski lift, sometimes navigating a flight of stairs. Then, you put on the skis. By then you are sweating and your goggles are fogged up. Next you wait in a line. Then you get on a windy and cold ski lift and become quite chilled. When you finally get to the top of the mountain, you stare at a map trying to figure out the best route down. Finally, you get to slide on the snow, which is actually quite fun. I’m an incurable innovator and so I found myself posing the question, “How might we improve the experience of getting skiers onto the slopes?”

If I were a trendy corporate consultant, I would call this a “design thinking” problem. But, I’m actually a bit of a crusty old designer. I’ve taught design for more than 30 years. So, I have to ask “what exactly is design thinking” and how is it any different from plain old design?

Well, first let’s first go back to the definition of innovation and design.

I define innovation as a new match between a solution and a need. Innovation can result from a push – starting with the solution and looking for a need. For example, what might we use the blockchain for? Or, it could start with the need and pull the solution, like I framed the skiing challenge. “How might we improve the skier experience?” Design is innovation anytime you are pulling a solution from a need.

So considering our definition, the short answer to what is design thinking is that it is design. Really. You apply the same process to creating a better ski experience as you do to creating a better ice cream scoop, or a better fitness app. In fact, the word design thinking annoys a lot of designers, because they are usually less interested in thinking about problems than in actually solving them. 

Once I cool off a bit about the weird term “design thinking,” I realize there may be a gem of an idea in there, and that a bit of nuance may in fact be warranted.

A useful definition of design thinking might be that it is design of things we don’t normally think of as designed.

For example, here are some problems for which the design process could be used, resulting in solutions that would not normally be thought of as designed artifacts.

  • How might we improve the patient experience in the emergency department at our hospital?
  • How might we improve the convenience of using a bicycle for transportation?
  • How might we create a delightful food delivery service?

A lot of people talk about needing to apply more design thinking in business. I find myself wondering if the desire for design thinking is really just a reaction to the use of too many spreadsheets and PowerPoint presentations, disconnected from customers and from exploration of solution concepts. This reaction reflects a desire for a different and better culture of innovation.

I do think that good designers exhibit a few desirable elements of culture. Interestingly, most of these elements don’t need to really be confined to design. Here are five:

  1. Designers exhibit a bias for action.
  2. Designers tend to be optimists, exhibiting a culture of yes.
  3. Designers tend to use exploratory prototypes early in the problem solving process.
  4. Designers tend to be skilled at visual expression.
  5. Designers tend to use empathic methods for understanding customers.

Despite my enthusiasm for all things design, I won’t argue it is universally the best approach to problem solving. For example, it would be a mistake to abandon elements of Six Sigma, Total Quality Management, the Toyota Production System, and data-based approaches. It would also be a bad idea to use a design process to find the volume of a geometric shape, a task better suited to an algorithm.

But, for a huge set of challenging problems, design is a great approach. It is fundamentally divergent and open-ended in its perspective on addressing user needs, and that’s useful whether you are designing a bridge, enterprise software, or an insurance claims process.

Notes

Karl T. Ulrich, Steven E. Eppinger, and Maria C. Yang. 2020. Product Design and Development. McGraw-Hill. New York.

Double Diamond Model. UK Design Council.
https://www.designcouncil.org.uk/our-work/skills-learning/tools-frameworks/framework-for-innovation-design-councils-evolved-double-diamond/

Customer Persona and the Job to be Done (Diamond 1)

I enjoy cooking. I’m not one for recipes, and I especially like making savory stews and soups from seasonal vegetables, and with interesting spices, especially cumin. I usually make a big pot and after enjoying a nice dinner, I’ll stow away a few leftovers in serving-size containers in my freezer. Few moments give me greater happiness than when I remember I have something yummy in my freezer ready to heat up for lunch. 

A while back I had an idea. Why don’t I create a service, which I’ll call 99 Bowls, which periodically sends me a carton of 12 containers of interesting soup? That way I always have something yummy to eat when I’m on my own at home for a meal.

I’m a serial entrepreneur, and this is how a new venture often starts for me. I’ve got some itch myself and I conceive of a company to scratch that itch. Let’s call this the raw opportunity.

A jobs analysis is a good first step in exploring an opportunity. It results in a clear and deliberate articulation of the job to be done for a focal customer (Christensen et al. 2016). The jobs analysis also comprises the first diamond in the triple-diamond model of design and design-thinking.

Let’s first talk about that focal customer. Before you even consider how to solve a problem, you really need to think about “for whom”? Returning to the 99 Bowls example, the product I would create for delivering pre-made meals to a school cafeteria would be dramatically different from the one I would create for a professional office worker or for a graduate student.

Two concepts are useful in identifying the focal customer. First, for zero-to-one products, you should identify the beachhead market. By this I mean the very first group of customers you will target. The best beachhead markets are those with the biggest need, the most acute pain point, and those that you can most easily reach. These markets are usually not the biggest markets. (See this chapter on defining markets for more.) The biggest markets usually have to wait until you have some experience and have started to spin up the flywheel of greater cost efficiency in your business. For 99 Bowls, a beachhead market could be relatively affluent professionals working from home at least two days per week.

The second useful concept is the persona. A persona is a description of a hypothetical customer that is highly representative of your target market. This is useful in making the challenge real to your team and to other stakeholders. A persona is usually constructed with specific attributes like age, gender, professional role, and even personality characteristics. 

Let me tell you about the persona for 99 Bowls. Her name is Grace. She works as a product manager at Facebook. She’s 36 years old and lives alone with her cat Milo. She’s super fitness-conscious religiously going to a yoga class near her house in San Francisco every day. She works at home most days, although occasionally takes the Facebook shuttle to the main office about an hour away in Menlo Park. Grace is Korean-American and finds most prepared food too bland. She’s a foodie and likes a lot of heat and flavor. Makes it real, doesn’t it?

Persona Grace via Midjourney

Your target segment will probably change, and after launching your solution you will almost certainly discover that there are other customer segments that your solution can address. You’ll also inevitably want to expand into adjacent segments. But, you have to start somewhere and specificity helps guide the creation of a solution.

I do a weekly podcast with entrepreneurs and my informal tally of past guests suggests that for about half of them the genesis of their business was a need that they themselves experienced. This raises the question of whether or not it is good practice to use yourself as a target customer.

Here are a few thoughts. First, you will find yourself in many professional situations in which you are not the target customer. If you are creating heavy equipment for the mining industry, you probably are not also a mine owner or equipment operator.

Second, when you are representative of your target market, I believe you are highly likely to create a product that satisfies at least one customer. You. That’s actually no easy feat. It’s a real luxury in entrepreneurship to have an immediate intuition about whether a solution is near the mark or not.

Still, designing for yourself does not guarantee a big market. You represent one data point and in most cases you aspire to serve thousands or even millions of customers. Disciplined and experienced entrepreneurs are able to leverage their own deep intuition about the job to be done while understanding that they need to be able to assume the perspective of the broader market for long-term product success.

Jobs Analysis and the Abstraction Ladder

In one of the most highly cited articles ever in Harvard Business Review, Theodore Levitt wrote “customers don’t want a ¼ inch drill, they want a ¼ inch hole.” Levitt’s insight was that when customers consider your product, they have a job to be done. They don’t typically want your product per se, they want the results of a job it can do for them.

But think about this example a bit more. I don’t know many customers who really want a ¼ inch hole either. They want to fasten a bookshelf to the wall. And do they really want to fasten a bookshelf to the wall, or do they want to store their books?

Every gap, as you first sense it, exists within an interconnected network of alternative problem statements, some more abstract and some more specific.

Here’s a technique called the abstraction ladder for elaborating the alternative ways you could state the design problem. You use the abstraction ladder for divergent thinking, to consider alternative ways you could frame the job to be done.

First, state the problem at the top of mind using the phrase “How might we…” For example, recall the 99 Bowls opportunity, which I could state as “How might we periodically deliver containers of prepared soup to work-from-home professionals?” You might write this on a self-stick note and place it on a wall or your desk.

As an aside, we use the phrase “How might we…” really just to put ourselves in a divergent frame of mind, considering many possibilities, some of which may not even be feasible.

Now, ask yourself what desirable outcome would be achieved if you solved the problem as stated. Or, in other words, why is that problem worth solving? 

For example, we hope to deliver prepared soup so our customer always has something readily available to eat for lunch. Now, use that desirable outcome as the foundation of a second, more abstract, problem statement — “How might we provide a work-from-home professional with something to eat for lunch that is always readily available?” As these motives for doing the job come to mind, just write them down on separate notes and stick them higher up on your work surface.

You see what we’ve just done? We’ve moved up a rung on the abstraction ladder to state our problem a bit more generally. Now why is this a good thing?

Put simply, abstraction opens up additional solution concepts. For example, we’ve now opened up the possibility of a pre-scheduled daily lunch box drop-off, or of a meal kit that allows quick preparation of a fresh meal, or of a club in which a group of five people take turns making lunch for each other once a week. By broadening the definition of the problem, we have opened up the possibility of many more alternative solutions.

But why stop there? What is the benefit of providing readily available lunch? Well, perhaps a key motive is to increase available work time during the day? So, we could rephrase the job to be done as “How might we increase available work time during the day?” That would open up even more solution directions, maybe a virtual personal assistant to help with mundane tasks, professional or otherwise.

Of course, even this statement can be broadened. How might we be more productive? How might we better provide for ourselves and our families? As we ask why we would want to do a job, we broaden the problem definition until eventually we end up with jobs to be done like how might we improve well being in society?

Note that these increasingly general statements are not always strictly arranged on rungs of a linear abstraction ladder.  There are typically many motives for any particular job to be done. Maybe a more significant motive for our target customer is to be able to control diet, or to introduce meal variety, or to enjoy more delicious food. Any given statement of the job to be done is located in a network of alternative problem statements, some more general, and some more specific.

So far in this example, we’ve always moved from more specific to more abstract, the why direction on the abstraction ladder. But, you can also step down a rung or two on the abstraction ladder by asking how — or what approach might we take to do the job. For instance, for the job to be done allow work-from-home professionals to enjoy more delicious food, we could take the approach of providing them with freshly cooked meals. That’s a more specific statement of the job to be done: How might we provide work-from-home professionals with freshly cooked meals?

When is the job to be done too abstract?

Stating the job to be done more abstractly, and thereby opening up additional solution concepts seems like a great thing. But, at what point is the job to be done too broad, too abstract? If you state the job to be done as “How might we improve well being in society?” then a solution might be to provide free neck massages in waiting lines at the airport. Although I might use that service as a customer, somehow that solution would not motivate me to quit my job and start a company. You, specifically, as an entrepreneur have a vision, and if the job to be done doesn’t align with your vision, you’re veering off track.

When you set out to create or improve something, it’s motivated by a gap you have sensed. You own that gap. If you embark on a process to create something that improves the well being of individuals in society, and it does so, but it does not achieve your goals, then you have defined the job to be done too broadly.

Step-by-step process for using the abstraction ladder

  1. State the problem top of mind using “How might we…” For example, how might we periodically deliver a supply of prepared soup to work-from-home professionals?
  2. Now, ask yourself what desirable outcome would be achieved if you solved that problem, and use that desirable outcome as the foundation of a second, more abstract, problem statement — “How might a work-from-home professional always have something available to eat for lunch?”
  3. Now, repeat step 2… For example, “how might we increase the available work time for work-from-home professionals?” Repeat again and again until the problem statement is something like “How might we increase well-being among members of the community?” the most abstract possible motive for solving the problem. In this step, you might use self-stick notes placed on a wall with each note capturing a different job to be done. Place the notes in a hierarchy or network with more abstract statements higher on the wall. Remember that there may be several motives for doing a job — so your abstraction ladder may branch out as you consider alternative how-might-we statements.
  4. Don’t be too hung up on the details of the process. Your goal is to explicitly articulate and consider several alternative problem statements, some more abstract and some more specific. If an alternative job to be done comes to mind, just write it down and put it on your work surface.
  5. After all that divergent thinking, it’s time to converge. Deliberately choose the most abstract statement of the problem that if addressed would still satisfy your personal vision and goals as an entrepreneur. That statement is the job to be done.

I’ve described this process as a single effort that is one and done. In reality as you proceed in developing the opportunity you may find that you benefit from further broadening or focusing of the job to be done to better align with your mandate and vision as you better understand it.

Notes

Christensen, Clayton M., Taddy Hall, Karen Dillon, and David S. Duncan. “Know your customers’ jobs to be done.” Harvard business review 94, no. 9 (2016): 54-62.

Levitt, Theodore. “Marketing myopia.” Harvard business review. 82, no. 7/8 (2004): 138-149.

Drawing for Product Design

I made three relatively short videos to teach my undergraduate students at Penn to draw. There are many types of drawing; the focus of these videos is quick visualization tools for communicating the form of physical objects.

Video 1 – Basics

Video 2 – three simple types of drawings

Video 3 – two-point perspective