Archive for the ‘Frameworks’ Category

Does the human-centered design industry believe in it’s own process?

Generic diagram found online

Generic diagram found online

Listening to users, and incorporating their feedback is considered the key differentiator for the practice of human-centered design. Yet, one wonders, if the design industry has understood that this philosophy must necessarily include the feedback from their clients as well. That is, while we are all aware of the navel gazing tendencies displayed by design thinkers and writers, we very rarely come across any pragmatic criticism of the industry itself, and it’s approach and processes, by those purchasing their services.

Yesterday, during my reading on ‘Doing Development Differently’,  I came across an incisive critique of what can only be called Big Design, by Geoff Mulgan, the Chief Executive of Nesta – the UK’s innovation foundation. His insights are worth pondering.


Source: Ben Ramalingam

One could almost interpret this as saying that human centered designers are unable to incorporate user feedback.

As Mulgan himself says on page 5:

I’ve several times sat in meetings with designers and design promoters, alongside policymakers, where the same pattern has repeated. The policymakers grudgingly accepted that they might have quite a bit to learn from the designers; but the designers appeared baffled when it was suggested that they might have something to learn from the policymakers, or from the many other organisations and fields with claims to insight into service design: social entrepreneurs, professions, consultancies, IT, policymakers. There are plenty of exceptions to this rule: but overblown claims that design methods are uniquely placed to tackle complex, holistic problems has not always helped to inspire a culture of collaboration and mutual learning.

When an overweening sense of one’s place on the team overrides ‘deep craft’, what are the future implications for the designer’s role in shaping their own environment?

And, what are the ramifications for the entire design industry, when Big Design’s Big PR hampers progress more than it helps?

Time to reach consensus on the #informaleconomy debate

As yesterday’s post showed, the unforeseen outcome of India’s demonetization initiative on the rural cash economy arose due to the lack of disaggregation of all that tends to get lumped together under the umbrella label “informal”. Segmentation would lead to more impactful design of policy and programmes.

WIEGO has an excellent review of the academic debates on the informal economy, covering the competing schools of thought. There is the Shadow Economy with its tax evasion and under reporting vs the livelihoods of the poor struggling to make a living in adverse conditions.


In 2009, Ravi Kanbur, Professor of Economics at Cornell University, posited a conceptual framework for distinguishing between four types of economic responses to regulation, as follows:

A. Stay within the ambit of the regulation and comply.
B. Stay within the ambit of the regulation but not comply.
C. Adjust activity to move out of the ambit of the regulation.
D. Outside the ambit of the regulation in the first place, so no need to adjust.

Under the Kanbur framework, category A is “formal.” The rest of the categories are “informal,” with B being the category that is most clearly “illegal.” (Kanbur 2009). […] Kanbur argues that using a single label “informal” for B, C, and D obscures more than it reveals – as these are distinct categories with specific economic features in relation to the regulation under consideration.

While acknowledging that it is useful to have aggregate broad numbers on the size and general characteristics of the informal economy, Kanbur concludes that disaggregation provides for better policy analysis.

So, why do we continue to wave our hands over the whole thing and conflate the legal with the illegal?

These distinctions are all well and good to debate in the cozy conditions of a seminar room without needing to come to any consensus, but as the human and economic cost of demonetization in rural India becomes clear, particularly the impact on the planting season, it puts a spotlight on the shortcomings of the way the rural and cash economies are currently dealt with. A pragmatic conclusion is urgently required.

My literature review on the past 20 years of research on the informal trade sector in Eastern Africa showed that this lack of distinction between what was shadow (B) and what was merely below the radar of the regulations (C &D per Kanbur’s distinctions above) gave rise to the criminalization of even the smallest livelihood activities of the local tomato seller who might cross a border to get a better price for her wares.

This in turn led to their harassment – particularly financial and sexual – by the authorities as there were no counteractive regulations in place that recognized fulltime crossborder trade as a licit occupation or profession.

What will it take for this to change?

India’s current experiences provide ample evidence of the dangers of leaving this untouched.

Unforeseen outcomes of India’s demonetization shine light on the value of our design philosophy

Informal Economy, Market Analysis and SegmentationLatest news on India’s demonetization informs us how the rural economy is bearing the brunt of this initiative.

The action was intended to target wealthy tax evaders and end India’s “shadow economy”, but it has also exposed the dependency of poor farmers and small businesses on informal credit systems in a country where half the population has no access to formal banking.

The details shed light on the consequences of implementing interventions without a holistic understanding of the landscape of the operating environment. In this case, it is the rural, informal cash intensive economy.

…the breakdown in the informal credit sector points to a government that has failed to grasp how the cash economy impacts ordinary Indians.

“It is this lack of understanding and not appreciating the importance of the cash economy in India on the part of the government that has landed the country in such an unwarranted situation today,” said Sunil Kumar Sinha, an economist and director of public finance at India Ratings.

This lack of understanding the dynamics of the cash economy (I don’t mind calling it the prepaid economy, in this context) and it’s role in the rural Indian value web has led to unforeseen challenges at a time when farmers are planting seeds for the next harvest, hampering the flow of farm inputs as traditional lines of credit face the obstacle of an artificial shortage of liquidity.

I want to use this clear example of systems design failure to explain my philosophy and approach to our work in the informal economies of the developing world. I’ve written often enough about what we do, now I have an opportunity to explain why we do it, and why it’s important.

Read On…

Analysis of the mobile phone’s impact on cash flows and transactions in the informal sector

As we saw, Mrs Chimphamba needs to juggle time and money as part of her household financial management in order to ensure that expenses can be met by income. We also saw that the mobile phone was made viable and feasible by the availability of the prepaid business model that gave her full control over timing and the amount required to maintain it — how much airtime to purchase? when? how often? — all of these decisions were in her hands, within the limits of the operator’s business model. Now, we’ll take a closer look at the impact of the mobile on her domestic economy.

Readily available real time communication has helped Mrs C by speeding up the time taken for a decision on a purchase or a sale. That is, the transaction cycle has been shortened. As the speed of information exchange increases, it increases the speed of transactions — it shortens the duration of time taken to execute them from inception to completion. This, in turn, implies that more transactions can now take place in the same amount of time thereby increasing the frequency and the periodicity. When mobile money is present, one can see that as both quantity and frequency of transactions speed up, so does the cash flow. We’ll come back to this factor.

To explain using a real life example, Mrs Chimphamba does not need to sit at her homestead wondering if today someone will pass by to purchase a bottle of wine. Similarly, Mrs C’s customers do not need to go out of their way to pass by her homestead to see if the wine is distilled and ready for sale, or whether it will still take another day or two for the next batch to be ready. Further, the uncertainty of whether they’ll have cash on hand on that future day, or if they’ll return as promised are all elements that real time communication have minimized.

Now, Mrs C is able to let her regular customers know that she’s making a new batch for sale and do they want to reserve a bottle for purchase? It allows her customers to put aside cash for this purchase. She is even able to accept and execute larger orders for some future date, and even accept some cash advances if her operating environment includes the presence of a mobile money transfer system such as those more prevalent in East Africa. This in turn changes her purchasing patterns and decision making as the pattern of cash flows — timing and amount — changes. She isn’t making do anymore on an unknown and predictable sale based on sitting and waiting for someone to show up to buy her wine.

Real time communication has improved the decision making cycle for both buyer and seller in a transaction as it counteracts uncertainty and information asymmetry even while speeding up the time take for a decision.

As the quantity and frequency of transactions increase— first, in cash conducted face to face, and then later, remotely by mobile money, regardless of the size of each transaction — the change in cash flow patterns begins to smooth out the volatility (the uncertainty factor has changed completely) between incoming and outgoing, as well as the decisionmaking involved. That is, the gap between income and expense starts becoming less in terms of both timing and amount — there is the possibility of a steady stream in the pipeline. Calculus offers hints of how the curve can begin to smoothen out as frequency and periodicity of transactions begins to accelerate.

Size of transactions thus begin to matter less in that the incoming amount now does not need to be so large as to cover expenses for an unknown duration of time before the next incoming payment; nor do expenses have to be tightly controlled constantly due to the uncertainty of the duration of time before the next payment, and the types of expenses incurred during this unknown period of time.

So the boost in decision making — how long it takes to complete a transaction, how often can transactions be completed — enabled by the real time communication facilitated by the mobile phone; plus the attendant immediacy of receiving payment via the same platform is the root of the improvement in the hyperlocal economy and consumption patterns among the informal sector actors. This is why large established traders (with sufficient financial cushion) were heard to observe that both purchasing power and consumption patterns had changed in their market town (Busia, Kenya Jan 2016) in the past 10 years since first the mobile phone, and later, mPesa, were introduced into their operating environment.

Uncertainty and information asymmetry that have long characterized the fragile and volatile nature of the informal sector operating in inadequately provided environments with unreliable systems and scarce data. In the next chapter we’ll step back and take a broader look at communication, connectivity, and commerce in the informal economy starting with the description of the operating environment’s characteristics regardless of continent.

This is part of a newly launched Medium where I will write in detail on economic behaviour and its drivers in the informal economy. Much of it draws upon the original research in the field from 2008-2009 which was shared on the prepaid economy blog. I found that time had passed and increased my understanding and I wanted to explore those discoveries in writing. Much of this is the foundation for recent works on ‘Mama Biashara‘.

Systems design and the Monster who squats between the formal and the informal


This framing of the real challenge to development and poverty alleviation comes from Ken Wong writing on his experience in Malawi:

We can only win the war on poverty and hunger in Malawi by targeting the real enemy – and that enemy is the system of how the world tries to help. Specifically:

The system that demands foreign aid be funneled through the government or large NGOs

The system that creates a hierarchy of aid and government workers whose job security and quality of life depends not on their wanting what is good on the ground, but pleasing whoever is above them in rank

The system that discriminates against on-the-ground, local initiatives because of a lack academic credentials, English-speaking skills, and the ability to complete unwieldy applications and fulfill misguided metric targets

If we are to win the war against poverty, we need to face the truth and admit that the system has not only not worked in Malawi, it has made the situation worse.

The system itself is the barrier to progress. The System Monster, as I dubbed it, is quite a nice fellow really, rather well meaning and all that, but he doesn’t see how he’s just stuck there inbetween, unable to adapt to the context on the ground.

Here’s is a 5 minute video where I introduce the concept, from the BankInter Foundation’s Future Trends Forum on Inequality and Technology held in Madrid in early June 2016.

Poverty is Dynamic and Flexible, Just like the Informal Economy: Evidence from India

…the concept of poverty today is fundamentally different from that of poverty three decades ago, and that safety nets need to be tailored to meet the needs of a society in transition.~ The Hindu, 2 Aug 2016

When quantitative data provided by the India Human Development Survey (the first large panel survey in India) provokes the academics involved to question their fundamental assumptions and premise of what poverty is, and what it might mean, its a noteworthy moment.

The survey, conducted by the University of Maryland and the National Council of Applied Economic Research (NCAER) for the same households at two points in time, viz. 2004-05 and 2011-12. Their analysis has led them to say:

Once we recognise that poverty is dynamic in nature, and that as per our conventional definition of poverty, poor households may move out of poverty and the non-poor may become poor over a period of time, we are forced to question the veracity of our fundamental assumptions about poverty. Perhaps poverty occurs not simply due to the accident of birth or as defined in terms of where and in which family people are born, but also due to the accident of life caused by the occurrence of disease, disability and unemployment. Achieving this recognition entails a complete transformation in our mindset.

I will leave them to their explorations from the perspectives of their disciplines, and explore the broader implications of their findings.

A few years ago, as part of my discoveries from more qualitative user research in the field on the informal sector’s financial context and operating environment, I had had my insight on the dynamic nature of poverty as it was conventionally defined.

It was when attempting to clearly distinguish between patterns of cash flow in the formal vs the informal economy, using the concept of the degree of control granted to the end user over the variables of time (duration, frequency, periodicity) and money (amount, cash or kind), that it struck me what kind of difference does control over timing mean for money.

That is, there is a complex value processing underneath each of the decisions on allocating available cash money, particularly in rural areas where cashless transactions can tend to be more common.

When one can control the timing of one’s payments – such as the advance purchase of airtime minutes to use a mobile phone – one’s income could be called dynamic. Within any particular set of calender based time eg a week or a month or a quarter; a vast majority of the lower income bracket cannot predict their total cash income nor feel confident enough to claim it. It can be affected by seasonality prevalent in their region, or it can be purely random volatility, one’s workshop burns down in an accidental fire.

Static income is that which is stuck, such as a fixed salary paid every calender period, regular in frequency, amount and periodicity.

As cash flows tend to be volatile, fluctuating with seasonal influences, chance, and the vagaries of daily life, those whose incomes are not as predictable as a periodic paycheck, are more often than not unable to clearly state (or even know) their monthly or weekly income.

That is, even as data gurus in development banks seek to segment people into neatly defined ranges such as $2 to $4 a day or whatever, it is neither a given that people will remain within this range over the course of the natural year, nor can it be a reliable and consistent indicator of their income level – Below Poverty Line (BPL) is the concept used in The Hindu’s article above.

Therefore, if the survey studied households in an agricultural region during its fallow season the first time, and then went back to study the same households during the post harvest season the second time, that simple little factor of calender time alone can create a difference of as much as 100% to the incomes being claimed during that period. If the study does not follow up the income question to ask if there was seasonality in their cash flows over the course of the natural year and if this question was being asked during the high season or the low season.

When I did the original fieldwork for the prepaid economy project on an IDRC grant, looking at the rural household financial management behaviour in rural India, Philippines, and Malawi, I found that depending on the local region’s primary cash crop harvest patterns over the natural year (say monsoon to monsoon, or Christmas to Christmas) the entire local economy felt the impact of the difference in cash flowing through their ecosystem during the high and the low season. Or, the wet and the dry season.

It was not the naming of the seasons that is important. It is the ability of the people to forecast known fluctuations in their income streams based on patterns recognized from experience and local wisdom. Within the context of an environment of uncertainty and volatility, it offered them some anchors for planning and financial management.

Given that the vast majority of the poor in the developing world, like in India and across Africa, are dependent on irregular, often unpredictable cash flows from a variety of sources, in an environment of higher risk and uncertainty, their incomes can confidently assumed to be dynamic, rather than a static salary.

And the dynamic nature of the informal sector precludes conventional classifications and categorizations of poverty, especially by any stated amount of money mapped against a particular duration of calender time. Time and money are themselves the uncertain elements requiring flexibility built into the systems if they are to work properly in this operating environment.

Thus, I can confidently state that what the Indian data is finally providing the evidence for are the findings from my qualitative research among the same segments of the population, using design ethnography methods. That is, we now have the quantitative data to support the insights derived from the qualitative research.

Full Stop.

Part 2: Enabling development’s paradigm shift from ‘best practice’ to ‘best fit’

Workshop I_end user in sight during evaluation

Programming in International Development jumps directly into the Design phase of the projects. This is the root of the challenge they face now as they seek to change the paradigm away from ‘best practice’ to putting the end users at the center of their strategies, with ‘best fit’. I identified this problem in the Autumn of 2012 whilst delving into the internal project development processes with civil servants at the Netherlands Ministries of Foreign Affairs and Economy during a customized internal workshop.

It should be mentioned at this point that while Robert Chambers has extensively promoted the participatory approach, there were issues in the process that were explored during our work, and can be covered in a separate article. Participatory design is not synonymous with user centered design, and neither approach includes a robust methodology for assessing the landscape of the operating environment in conjuction with solution development for ‘best fit’, particularly in the developing world context.

Before we can jump into the design of a project or programme – whether with or without the participation of the end users/beneficiaries, we need a structured approach to grasping the context of the challenge. Without a map of the landscape of the ‘wicked problem’, one cannot navigate the complexity (1). This so called landscape map of the ecosystem in which the development project will be introduced, should not only include understanding the people and their operating environment, but identify and frame the touchpoints for the design of ‘best fit’ interventions.

That is, there’s a need for framing the problem in a manner such that the outcome narrows down the solution space i.e. delineating the boundaries for ‘best fit’ prior to the inception of the design process. In the field of design, these boundary conditions can be known as design criteria and constraints, along with filters for assessing optimal solutions at the conceptual stage from the plurality available.


These first three steps in the process BEFORE jumping into design are collectively known as Design Planning, and their outcome minimizes the wasteful experimentation of ‘suits to try’ for ‘best fit’ as the design phase begins with the ‘measurements’ necessary for a ‘bespoke suit’ tailored to fit, to stretch the analogy. Bespoke tailors do not expect their carefully measured suit to fit their client on the first try, and usually one returns two or three times for the final fitting. Similarly, customized programming may require tweaks and can be considered a working prototype (a pilot program, for instance, prior to scaling) where the kinks are worked out together with the participants.

This will require work upfront at the start of the multi-year programmes. There are no silver bullets to addressing complexity.


(1) Part 1: An Interdisciplinary Approach to “Best Fit” for International Development: Process and Tools

The 5C’s of Cashless

The Reserve Bank of India has unveiled their Vision 2018, an ambitious plan to shove the juggernaut into a cashless future. Here are their pithy yet to the point 5C’s, which focus the framework on a set of objectives.

  • Coverage – by enabling wider access to a variety of electronic payment services
  • Convenience – by enhancing user experience through ease of use and of products and processes
  • Confidence – by promoting integrity of systems, security of operations and customer protection
  • Convergence – by ensuring interoperability across service providers
  • Cost – by making services cost effective for users as well as service providers

The full Vision 2018 report can be found here. Smells like Rajan’s legacy as he wanders back to academia in the Fall. I’m very impressed by the framework’s conciseness, and the fact it embeds periodic customer feedback surveys (continuous user research) as part of the design.

Platforms that aggregate small businesses can integrate the informal with the formal economy

Continuing my thoughts on Nilekani’s vision introduced in the previous post, I want to use this post to focus on the key element of what captured my imagination from his article “The New Road to Nirvana“:

So manufacturing is squeezed on one side by Chinese overcapacity and on the other side by extreme automation. So the service sector is where the action is.

The era of large companies as we knew them is also over. It will be a world of platforms that aggregate small companies.

Amazon and Flipkart will aggregate goods made by lakhs of vendors and provide a platform to sell them. Similarly, Ola or Uber will aggregate millions of drivers who will work on the platform, Practo will aggregate doctors and patients and so on. Aggregation by platforms is the way that jobs creation will happen.

This platform aggregation will also lead to formalisation of the economy. India’s economy is largely informal. But once, say, a taxi driver becomes part of Ola, then in fact he becomes part of the formal economy.

He is able to use data, get a loan, buy a car, start paying taxes. So the formalisation of a few hundred millions of Indians will spur growth and that is where our focus should be.

My larger point is that it is now all about domestic not export, services not manufacturing and platform aggregation not big companies.

I will be writing further on this concept and exploring its implications for the African context, particularly East Africa.


A Framework for New Market Entry Strategy

There are two parts to this article: The first is a revision of the lenses through which we assess the landscape within which your new market strategy will be expected to operate; and the second covers your implicit assumptions at inception, as well as gaps in your  mental model.

1. The lenses for innovation need a universe to ground them.

The development of the first generation prototype lenses for identifying the sweet spot of innovation in the operating environment prevalent south of the Sahara desert on the African continent are described here. The evolutionary path from the original lenses (shown below) is described.

ideo modelPeople, Pesa, Place were used to replace the words Users, Marketplace, Technical as a means to provide cues for contextual exploration. However, in practice, this revised Venn Diagram (shown below) was still missing a means to distinguish the very different landscape of an emerging market. That is, it overlooked the need to consider the whole as an ecosystem in its own right.

The formal definition of a Venn Diagram, taken from the Oxford Dictionary is as follows:

A diagram representing mathematical or logical sets pictorially as circles or closed curves within an enclosing rectangle (the universal set), common elements of the sets being represented by intersections of the circles.

Without the universal set being represented in these diagrams, it was difficult to create a cue for identifying and describing the often inaccurate yet implicit assumptions made at the very beginning of a new market strategy formulation. And, this gap often revealed itself in form of cognitive dissonance between the observed marketplace and customers, and the tactics intended to support the strategy.

Here is a revised version of this Venn Diagram, enclosed in the rectangle.

VennInformalBy changing the description of the universal set, as shown below, one is then able to evaluate the entire ecosystem holistically.

VennMCCThere is a chasm that divides the value propositions of the producers (sellers, marketers, MNCs) from mainstream consumer culture and the mindset and worldview of the buyers (erstwhile bottom of the pyramid, or emerging consumers from cash intensive, informal economies), and this chasm is where new market strategies tend to falter, and fail. This is particularly noticeable in the African consumer market, especially when considering the mass majority.

2. Questioning the assumptions underlying your value proposition

By adding the missing universal set to the Venn Diagram, one is then forced to acknowledge the systemic differences between one’s own consumer culture, and the vastly different one in this new market. It may indeed be informal and rural, as shown in the sample above, or, it may be the urban consumer markets in the sprawling cities south of the Sahara. Even then, a significant proportion of the economy falls outside of the formal structured environment prevalent in most of the sophisticated consumer markets of the global economy.

And what tends to happen is that elements or concepts from the formal economic ecosystem are introduced or implemented isolated from the supporting information systems and infrastructure. One or two elements from one ecosystem will not thrive in an entirely different ecosystem if there is not fit or context for them to succeed. A clear example is what happens when financial services and tools are introduced under the guise of inclusion.

By going back to the foundation of one’s assumptions, one can identify where the gaps might lie in the value propositions that make so much sense in one’s own context when considering them for consumer segments who might never have been exposed to the same marketing messages, or conditioned to expect “New” to mean “Improved”.

This exercise also provides a cue to consider the systemic differences between the two operating environments, and to assess whether the value proposition or the solution can be introduced as is without the need for an entire support network surrounding it.



Note: I have used the African context as the working example, but the basic framework is flexible to use for any set of disparate operating environments.