As I get acclimatised to what working weeks look like in Kenya this is my first attempt at a “thought piece” within the confines of a job.
It’s about the internal dissonance I felt at the lack of rain in the country right now, and veers off towards using “data for good”.
“Not a cloud in the sky!”
The kernel came when chatting to my friend over Whatsapp. We were comparing what was outside our windows at the time: a bleak mid-winter in Europe and scorching rays in East Africa.
From my lofty vantage point I claimed how lucky I was to be in a clear sky environment – able to walk around in shorts without obvious risk of being caught in the rain.
For some reason the comment stuck with me, and when I was walking to the shops later it turned over in my head a few times and attached itself with flickers of things I’d noticed in the past few weeks.
There was a brief sinking period of post-message remorse as I paired my comfort of low precipitation with the newspaper headlines, small talk at food stalls and radio presenters in Kenya all essentially lamenting: “when will this rain come?”.
I won’t spend too much on the consequences of prolonged water absence, but needless to say it’s tough for those whose livelihood depends most directly on it.
In my lifestyle of getting water from a tap and food from a shop, I’m quite far removed from the direct effects of water shortage. If the shop on the corner doesn’t have tomatoes (which it doesn’t right now) then I just usually find one close by that does.
Speaking to a friend who works for a sanitation organisation at the Kakuma refugee camp in the north of the country, it’s one of the first things he mentioned when I asked how things are.
Being without water in this terrain of tough agriculture is much more severe than my scenario of essentially just needing it to stay hydrated, and then use electricity and WiFi to generate a living for myself.
Using new information creatively
In general I’m much more interested in finding solutions than dwelling on problems.
The area that I find particularly interesting around seemingly unassailable problems like drought is that it is possible to make inroads in the present state.
The “best case” solution is of course a planet that predictably splashes out water in all the important places, but if all resource is expended organising conferences to nod heads and agree that this is the case then it may detract from doing something in the here and now.
An imperfect solution is better than none
The global trend I’m seeing is that data on people, things and the planet is becoming ever more abundant as a result of improving technological capacities. Finding, and then harnessing all of these numbers to apply them to tangible problems such as ensuring a level of welfare for people affected by drought is, to me at least, a pretty engaging challenge.
A model for insurance
I’ve been surprised at the amount of interest I’ve taken in insurance since moving to East Africa.
The basic premise of insurance is that individuals are willing to forgo small amounts of money (premiums) in exchange for a large sum being paid to them should something bad happen.
The organisation dealing with the money (the insurer) collects the premiums and then pays people a large amount if the bad thing happens. If not, they don’t need to pay anything back.
As the payout is typically much larger than the amount collected, the insurer will quickly go out of business if they can’t hold onto some of the premiums without doing some payouts. They therefore try to collect lots of premiums from different sources as a buffer with which to make the large payments from.
We’ll leave it at that, but suffice to stay, if all parties play it right, the insurer can make a profitable business and individuals can feel protected against bad situations happening.
In a competitive landscape of international insurance there is an attempt to find a profitable business in new markets, such as East Africa.
One of the best examples I’ve seen of combining the concepts of more data in the world and imperfect solutions to big problems happening now is with finding a way to pay individuals in the event of a drought, such as is happening in Kenya right now.
This TED talk video explains it in in full:
The premise here is that satellite images (i.e. better technology) can be used to quickly determine whether a payout is required in the event of a drought (i.e. bad thing happening) and that mobile money (i.e. better technology) can make the cost of implementation much lower than previously.
Without the better technology element, the costs of going around surveying landscapes and sending someone to give cash would have been so high that it would only make economical sense if the premiums collected were big. Big premiums, of course, not being affordable for low-income individuals living in rural Kenya.
Whilst we started the post with a classic “first world problem” (the rain might get my shoes wet!) it ended up being a tangent into the growing trend of more information becoming readily available in the world, and creative ways to put it to use.
It’s something I’ve been experiencing too. In my role so far at Pezesha, I’ve been able to feel the effects of how data is making it plausible to sustainably open up credit lines to individuals where it otherwise wouldn’t have been economically viable. All because electronic devices are storing information that was never previously accessible.
In either case, the downpours in Nairobi have continued to be few and far between. Hopefully my feet will be getting wet in the foreseeable future.
Thanks for reading.
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