The true data problem is finding the answer to the question, “What does this data do?”
Imagine. A salesman knocks on your door with a product that looks like something you could use, but you don’t know what for.
As you begin to ask this salesman questions, you discover (to your amusement or annoyance depending on you) that this salesman knows a lot about the technical specifications of the product. Things like weight, obscure materials used to create the product, and even the PANTONE color ID of the product. But the sales rep cannot tell you what the product does.
How long would that conversation continue? Probably not for much longer. Except you are a collector with a tic for useful–looking but useless shiny things.
Whenever you think of the second–largest continent in the world, imagine dozens of vendors who know very little about the products they are selling. Next, picture a farming fair where everyone had only one trophy fruit and not much else to say about their farming operation to the large off-taker, processing companies and organic consumers prancing around the fair.
Africa’s national, sub-national and intra-continental markets are like these sellers for the most part. The result is often a spectacular type of market failure where both buyer and seller do not know enough about the product or service to make as near accurate and rational judgements as possible. It’s not quite information asymmetry, but it is very close.
In my opinion, this is a Monet-esque illustration of the state of the knowledge component of African markets. The sellers—you, me and everyone else (African or not) who are trying to sell the African opportunity story— know the broad specs of this opportunity, but they are still a bit fuzzy on how the opportunity works out in real life.
Unfortunately, the effect of this fuzziness weighs heavily on Africa’s emerging digital layer businesses that have to tackle this knowledge fuzziness every step of the way. Informal ventures can get by with anecdotes and large FMCGs have established relationships with distribution networks that offset some of the information gaps. But for upstarts, mature digital ventures and investors that are caught between informality, “smallness” and inefficient government, these types of questions are important ones.
The data problem (I cringe at using that phrase) is a platform problem
It’s easy to try to ask and try to find answers to questions like:
How many tons of grain and other food cross the Kenya–Uganda–Rwanda border every month? How many plastic shoes and sandals are shipped from Aba in southeastern Nigeria to Cameroon every week?How many boda bodas are involved in Nairobi’s food value chain?Why boda bodas and not PSVs? And where does this “why” apply?Surveys and other types of data collection methods can help you answer this question. However, surveys do not tell you much about how your accumulated knowledge becomes a useful service, much less a product.
You can repeat this effect in many contexts and face the same problem. In other words, the valid strategy of choosing to collect data first and deciding what to do with it later is utility-deficient. And usually, it all ends in reports.
Creating sustained knowledge ecosystems means building platforms, not reports. The simplest definition of a platform is that it is an enabler. An operating space or system on which activities are executed. A knowledge platform then would not be a report-termination activity but an action or decision-enabling activity.
This is partly what separates the Bloomberg Terminal, for example, from a Master’s thesis. In other words, the aggregated knowledge is supposed to culminate in a decision or an action. Ideally, it narrows the information gap between both sides of a decision, but more importantly, it serves as a platform i.e an enabler.
A few months ago, Olayinka David-West, a professor and Associate Dean at the Lagos Business School (LBS) pointed out the need for incentives to align for information products to have a shot at even being created. If finding shared incentives is the thread on which all types of platforms run, then collecting and arranging knowledge for platform products is a bet that incentives will align at some point.
Like many people, I used to think the problem was only collecting knowledge. Now, I know that it is only a component problem. And certainly not the biggest.
Think back to your mental snapshot of the farmers’ market where only one trophy fruit was displayed per farmer stand without any additional information or context. Displaying the world’s biggest tomato at the fair might win you the prize, but if that is your only produce, I’m not sure it is enough to win a supply contract from Heinz. If your farm can supply my entire ketchup factory, I want to know that and perhaps more importantly, I want you to know more about making good tomato crops at scale than I do. I want you to have that information asymmetry edge.
Because this is what the ketchup factory demands, it is precisely the sort of information that farmers will come to the fair with—and some sample golden tomatoes.
This is also where a bigger problem lies. Not in collecting data but in knowing what product the data is useful for.
After more than 18 months of thinking, talking and reading all the complaints about “Africa’s data problem,” I am learning that what we have been focusing on looks like the leeward side because we have not prioritised (either as government or the private sector) the services or products that data enables.
Knowing things can create an asymmetric gain, which is true. For our purposes, however, the primary yield of knowledge is in decisions. The faster this happens, the better and more mature a market becomes. And ironically, the result of a thriving knowledge ecosystem is a reduction in asymmetric advantages from simply knowing.
The efforts required to maintain those selling-buying information advantages are then abstracted away in middle-layer platforms like a Bloomberg Terminal, and everyone can get back to focusing on growing better crops or making better things instead of concealing knowledge. That is not to say it completely eliminates knowledge gaps between transacting parties. It just makes it easier to trust.
And “cheap” trust facilitates more business than anything else in the world.
Maybe we like the current environment and are comfortable with the report-writing and survey service industry it has created. But that is short-term and hardly scalable. We can be better salesmen—and buyers—if we can create and sustain data networks designed to enable products and service delivery.
We’ve seen that they can work in the few places where we have created product/service-oriented data platforms. I’m thinking of the Bank Verification Number (BVN) program in Nigeria and the opening of Nigeria’s Inter-Bank Settlement Scheme to fintechs.
So I ask you: Can platforms be built in a similar mould across multiple sectors, industries and borders?
Abraham Augustine writes on Money, Myths & Digital Africa here.
