Posts Tagged ‘informal economy’

The dangerous assumption that there’s no competition from the informal sector

In addition, the informal economy of open street markets still dominates 90% of retail in large countries like Nigeria and Kenya, meaning it’s a near safe bet there’s plenty of room to grow. ~ Quartz Africa, Jan 2017

Failure is a risk, and an inescapable function of the amount of resources invested, not just money. Time, effort, and managerial ambitions are also losses that destroy value for companies. Danger, then, lies in leaping to assumptions that turn out to be wrong. This is one of them.

First, a bit of history. Just over a decade ago, the Indian market was opening up to world’s investment flows in the retail sector, and estimates of the potential were as rosy and glowing as Africa’s today. From The Economist in April 2006:

Most Indian shops belong to what is known, quite accurately, as the “unorganised” sector—small, family-owned shops surviving on unpaid labour and, often, free land for a small stall. “Organised” retailing accounts for only 2-3% of the total, and of that, 96% is in the ten biggest cities, and 86% in the biggest six. However, organised retailing is growing at 18-20% a year and inspiring a rush of property development. Shopping malls are springing up in every big town: some 450 are at various stages of development.

By 2015, it was clear that these ambitious potentials were never going to materialize, though many malls did spring up in cities across the country. Last year, I covered this topic looking back at the growth projections and the subsequent real numbers achieved from the perspective of the resilience shown by the informal retail sector. I noted, in August 2016:

Yet if you look at the data from 2015, you’ll see that the forecasts were far too ambitious – formal retail has only reached 8% penetration in the past 10 years. Nowhere close to the 25% expected by 2010. Mind you, these were all the management consultancy reports bandying the numbers around.

I bring this up because I’m seeing the same kinds of projections happening right now for the African consumer market by the very same firms.

Second, this time it’s not just a management consultancy report with all the research and analysis efforts they pour into making their case. It’s not been distilled into one single yet dangerous sentence:

meaning it’s a near safe bet there’s plenty of room

Yeebo_Market_08

“Plenty of room” (Photo Credit: Yepeka Yeebo in Accra, Ghana)

There’s an inherent assumption within the assumption that the myriads of little stands, market ladies and their longstanding relationships with customers and suppliers, and the entire ecosystem which exists, such as in the photograph above, can simply be bulldozed over with a granite and marble mall development covered in shiny unreflective glass.
It didn’t happen in India, and it’s not happening in Africa. From Ghana, this news article on mall development says:

Ghana’s economic woes have translated into a variety of challenges for formal retailers who are competing for sales alongside the dominant and deep-rooted informal shopping sector. According to a recent report by African commercial property services group Broll overall sales in most modern shopping malls are well below historic averages, despite garnering sufficient foot traffic.

cth8lgkwcaauetyFurther, and more dangerously, this blithe assumption of a cakewalk where an informal sector so tangibly exists, overlooks the innate ingenuity of those who seek a dignified life even while hustling for a living. And that there’s no competition or customer service.

Snapshot of the Dynamics of the Urban Informal Retail Trade in Nairobi, Kenya

Informal Economy Dynamics - Updated

Made by Latiff Cherono – click for larger image

Latiff Cherono quickly made up this diagram during a brainstorming session with Francis Hook and myself on the ways and means to further disaggregate the general category of “Informal wholesale and retail trade” that the Kenya National Statistics Board uses to lump together the second largest sector providing employment in Kenya after agriculture.

jobs2 In urban conditions, vending and hawking of this sort is the largest source of income for the formally unemployed.

As you can see in the map visualizing Latiff’s analysis of a well known location for street vendors and hawkers to operate breaks down traffic flows not only by speed but also takes in account both static and dynamic forms of informal trade.

It may look chaotic but there are principles underlying the decisions made by both pavement vendors and mobile vendors (streethawkers in traffic) for their location of choice. These relate to the speed of passersby and potential customers – both wheeled and heeled, as Francis is wont to say – and closer analysis will most likely provide evidence of attempt to drive more footfalls to the shopfront, so to speak.

An example is the way pavement vendors locate themselves on either side of the busy bus stops, while mobile vendors who vend their way through traffic focus on the bottlenecks created by the roundabout and the traffic police.

We’re still in early days yet but time and money seem to be two of the factors that describe the attributes to segment and categorize the informal retail sector in urban Africa.

Signs of Interdependency between the Formal and the Informal Economy

bridging economiesThere is a lot to be unpacked here – I made a mindmap of the urban African entrepreneur who is the backbone of the visible emergence of a consumer class. I’m drawing from my experience of the Kenyan context. I started this in response to Michael Kimani’s Storify recently on the mythical “middle class” and the African consumer market.

We know that this demographic, regardless of the efforts to label it “middle class”, is quite unlike the traditional bourgeoisie that built the developed world a century ago. We can call them the informal bourgeoisie – solid members of society who nonetheless break stereotypes of the white collar, university educated, salaryman.

More often than not, they are entrepreneurs and businesswomen, traders and makers, and workshop owners, who bootstrap their lines of business through the traditional means available amongst what is still called the informal economy. If they’re lucky they might have finished high school, or even graduated from university, but a degree is not a prerequisite as it might be in a private sector job.

In this post, I’m only going to write about something that struck me last night when I was staring at the mindmap. The line that links business to entrepreneur can also be considered a bridge between the informal economy and it’s business practices, and the upcoming formal markets of urban population centers.

The successful workshop owner or regional trader rapidly acquires the signals of his or her business success in the form of consumer goods and increased expenditure on staples and necessities, including upgrades to choice of schools and church. I believe that formal financial services and products such as bank accounts, credit cards, and various apps on a smartphone are part and parcel of this.

In effect, the entrepreneur is the link between the informal economy which provides employment and income to the vast majority, and the burgeoning formal sector in consumer facing services and products.

The formal economy is more likely to be dependent upon the health of the informal sectors than the reverse.

This interdependency, and relationship, is important. I will be coming back to this diagram again to unpack more of what I’m seeing here. For now, it’s enough to have figured out that initiatives meant to eradicate the “pesky” informal trade might have greater implications than initially assumed.

Top 3 Assumptions About the African Consumer Market

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Treichville Market, Abidjan, Cote D’Ivoire (Photo Credit: Niti Bhan)

Claims have been made about the Great African Market Opportunity – in retail, in real estate, in banking, and packaged consumer goods – that drive investment decisions and marketing strategies. Yet, reality has been less opportunistic than imagined – Nestle’s struggles in Kenya back in 2015 are one such example.

Here are the top 3 assumptions, if left unpacked or unquestioned, that can make or break a new market entry strategy in the African Consumer Market. For most of the continent, it’s safe to say that the majority of the mass market are primarily employed in the informal economy.

1. Price is the problem
Affordability is not a matter of price but access to payment means or method. Upfront lumpsum cash transactions will narrow potential customer base down, depending on the season, or the income source.

What this means is that there are whole categories of products that would have had a larger audience but do not due to barriers set up by their own transaction model.

Accessibility and Affordability are thus not a function of the Price itself but the lack of flexibility in the business model. Flexibility drives consumer segmentation in the African Consumer Market, as product purchase decisions get made based on cash in hand and cash flow patterns.

2. Consumer Segmentation Metrics are the Same
The factors that influence the segments of the population who have the potential to be consumers are the following:
– Urban or Rural
– Sources of Income

Factors that do not influence “poverty” (ref: textbook market segmentation)
– Education
– Location
– Employer

Example: Schoolteachers are considered part of the rural elite in Kenya, accruing community status and respect. Yet, they may be on a fixed salary within a lower pay grade, albeit teaching with a Master’s degree, with less purchasing power than a school dropout with a successful trading business.

Assumption: Demographic attributes traditionally used such as Education level or stability of Employer correlate to consumer purchasing power or disposable income.

3. Brand Loyalty is absolute and unconditional
Consumer insight reports on the African market opportunity tend to highlight the high degree of brand loyalty prevalent among customers, and leave it at that. Recommendations then emphasize first mover advantage or capturing customer loyalty, with the assumption that once locked in, this will create a committed customer for life. Why brands matter so much is rarely, if ever, asked.

The assumption is that this brand loyalty implies pricing blind consumption and status seeking behaviours. While this may certainly occur at the upper end of the income spectrum, these drivers are not likely to be as common for decision making among the mass majority audience. Demand drivers for brand loyalty more commonly noted are:

– the need to minimize risk (of loss)
– maximizing the return on the investment (in the purchase) including status signalling and reputation factors, which have a role in accrual of social capital leveraged for business activities in the informal sector.

Trade-offs are constantly being made in purchasing decisions, influenced by a variety of factors. Yes, compromises may be made on groceries in order to pay for a branded product, but simplistic interpretations of this behaviour lead to egregious errors in the design of customer experiences.

Implicit Assumptions commonly held about Informal Markets

Mozambique

Woman owned and managed informal retail in Mozambique via Twitter

  1. “Informal Economy” always means illegal, shadowy, gray.
  2. High volume of low value cash transactions imply poverty, ignorance, lack of sophisticated money management.
  3. Operating with a lack of infrastructure and institutions implies ignorance, lack of ambitions and aspirations, and motivation.
  4. Lack of cash implies lack of purchasing power – particularly in rural settings.
  5. Lack of formal retail markets and packaged consumer goods implies lack of knowledge, information, and choices.
  6. Lack of competition, due to all of the above.
  7. Entering markets where informal retail dominates will be a cakewalk.

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.

From WIEGO:

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.

An economy of trust

_92445052_02Cash on credit is the caption given to this cartoon by the BBC. Neighbourhood groceries are offering their regular customers cash advances in addition to bread and milk.

While the media is filled with a plethora of stories of heartbreak, my own suspicion is that we’ll discover the resilience of the cash intensive informal sector lies in the relationships between people, once the hubbub has died down.

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‘.

How to Spot Signals of Local Purchasing Patterns in the Market

np-md-mohamed-kanuThis photograph is taken from a regular news item from a Liberian newspaper announcing the opening of a new petrol station in the town of Ganta. What caught my attention is the size of the LPG cylinders being promoted. On the left is the 6kg and on the right is an even smaller size that I’ve yet to see elsewhere – the 6kg one has been spotted in the lower income side of Jakarta, and in the markets of Abidjan, and Nairobi.

What it tells me is that purchasing power in the local market is not only a little less than a major capital city, this is probably a tier 2 city, but also that its a cash intensive market where incomes are more likely to be the volatile cash flows from commercial activities in the informal sector.

The lumpsums available for LPG aren’t going to be as large as to afford the standard 13kg size, but it doesn’t preclude people from purchasing these smaller sizes more frequently. That is, we cannot assume total consumption volumes to be less than larger cities where larger sizes are more popular. On the other hand, the micro size on the right seems to hint at the possibility of LPG being more popular than traditional fuels such as kerosene, charcoal, or firewood.

These small sizes also signal a fragmented, informal market where small pack sizes and sachets are popular.

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.