I should update my older thread on this topic. Talent was always going to be the battleground, and I said this a couple of years ago. You have to build a pipeline that adapts to your needs, rather than fighting in the same market as the rest of the world and complaining when people make optimal choices.
Doing it this way is costly and brutal. Citibank, Nigerian Breweries, and Shell discovered this talent quality problem as far back as the 90s and decided to build a process to take “average people” and turn them world-class.
This process in Nigeria and Africa has focused mainly on coding with Andela and others when coding skills were in high demand globally, but AI changed everything. Demand is still there but it shifted gears.
Coding skills are NOT everything a startup needs. In Nigeria, we lack experienced operators in many areas because there aren't many places for them to learn. One of the things people fail to realize about Japa is that it provides learning and advancement opportunities. You need to create learning opportunities for people as an investment.
This has always been my problem with the so-called “tech investment” in Africa. People are funding the output of a broken pipeline rather than investing in fixing it. They invested in companies skimming from the top rather than building from the bottom up. Google and others did a lot better from the bottom in Africa.
We need company academies again and partnership with educational institutions. I was able to do my undergrad project research because of a lab in UNIBEN partly funded by Shell. This current model we have is unsustainable.
I will write more. This is just a rant.
Retweet until the right people see it.
What will it cost to build DATA CENTERS in Nigeria and setup the SOLAR FARM equivalent to sustain it.
Tag all the tech guys who are familiar with things like this.
Tag engineers who understand this thing
Tag the billionaires who have the funds
Tag the financial people that understand the maths
The policy makers who can push this till it works.
We are wasting time ooo.
We have a decision to make.
We have a short window to regain back our stand in the world oo.
Data is supposed to sharpen decisions, not blur them. The paradox is this: You become a better, more confident product manager the moment you stop trying to prove yourself right every time with data and start trying to learn what is true with just enough data.
One pattern I keep seeing across product teams, especially in early-stage startups, is that the moment they discover dashboards, they stop making decisions. Not because the data is bad, but because there is suddenly too much of it.
4. Decide before the data feels perfect. The team that waits for perfect certainty never ships. The team that acts on directional accuracy wins.
If your team can not decide after reviewing hundreds of data points, it is not a data problem, it is a clarity problem.
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Honesty to yourself: “I did what I could, with what I had, I’m still learning and I’m still growing.”
Sometimes, what you know and what you have could be at different frequencies; that's okay, too. What matters is that you did your utmost best.
It is easy for others to look at your life in hindsight and say, “You should have done this,” or “Why didn’t you just do that?” But they don’t see your choices; the pressure, the timing, the fear, the half-truths life hands you when you are trying to make sense of chaos.
Not everyone will understand the parts of your journey you can’t explain; the quiet compromises, the private breakdowns, the “maybe later” dreams, the limited options. You don’t owe the world those footnotes. But you owe yourself honesty.