The rains have arrived — just like the weatherman said.
My parents, seasoned Kenyan farmers, had prepared the farm. Yet, despite accurate forecasts from the Kenya Meteorological Department, things didn’t go as planned.
The fertilizer delivery was delayed. Some seeds failed to germinate. The rain was too much, not just enough. You’d think, with good data, the outcome would be good. But the field had other plans.
And it’s not just on the farm.
📉 Data ≠ Outcome
We often assume that once we have the right information, everything else will follow. But that’s not how life works.
A 2023 Gartner study revealed that more than half of digital initiatives failed to meet their expected outcomes — even when based on reliable data.
So what gives?
It turns out: Data gives clarity. But clarity is only one part of the equation.
🌍 Living Systems Are Tricky
The world doesn’t operate like a spreadsheet. It moves like a living system — shaped by feedback loops, delays, human behavior, and unpredictable events. This includes:
- Weather & climate (see: global warming disrupting rainfall)
- Markets & organizations
- Teams, users, and decision-makers
Even when your input is right, the system can respond unpredictably.
🧠 This is Why This Blog Exists...
In these situations, I don’t just look for answers. I reach for tools — the kind you can use in the moment, when the clean dashboard doesn’t match what’s happening on the ground.
This blog is built on that idea. It’s not theory. It’s practice — for people who build, lead, think, and execute under pressure.
Let me show you how I work through this — and how you can too.
🛠️ Decision Techniques When the Forecast Is Right — But the Outcome Isn’t
These tools come from strategy, systems thinking, behavioral science, and field experience. They’re what I turn to when clarity is high, but control is low.
1. Scenario Planning
Scenario planning is the art of asking: “What if things don’t go as planned?” You draw out three simple stories — best case, expected, and worst case. This method comes from military and strategic planning, and it's what I use when planning projects, product rollouts, or even family budgets.
For example: What if the rains come late? What if input prices suddenly spike?
You don't predict the future — you prepare for versions of it.
2. Lag vs. Lead Indicators
Lag indicators show you what’s already happened. Lead indicators point to what’s coming next.
Farmers often track rainfall (lag), but the smart move is watching things like soil temperature or planting windows (lead). In business, profit is a lag metric — by the time you see it, the opportunity’s passed. But churn rate or customer signups? That’s the early signal.
Knowing the difference helps you act early — before you’re locked into outcomes you can’t change.
I use this split in every project I run. It’s what keeps me proactive, not reactive.
3. Feedback Loops
Feedback loops are signals that tell you how your system is behaving in real time.
A weather alert mid-season. A client cancelling a contract early. A change in soil moisture. When you build in ways to listen and adjust, you reduce the risk of being blindsided.
Most success doesn’t come from one perfect plan — it comes from making 10 fast adjustments.
I track feedback in my notes, meetings, and even conversations.
4. Decision Journals
A decision journal is a simple tool: Write down your reasoning before you act. What do you expect? What could go wrong? Why are you choosing this?
Later, you revisit it to learn what worked — and what didn’t. It trains your pattern recognition and keeps you honest.
I’ve avoided repeating expensive mistakes just by looking back at old decision notes.
5. Stakeholder Mapping
Sometimes, it’s not the rain or the data that causes failure — it’s people.
Maybe the input supplier delayed delivery. Maybe your team wasn’t aligned. Mapping stakeholders helps you see who matters most, who can block you, and where influence lies.
In both farming and tech, success often depends on who gets the message — and who doesn’t.
🙋♂️ The Techniques I Use (And Why)
I don’t just write about tools — I use them. Every major decision I make sits inside a mix of mental models, questions, and backup plans. I’m obsessive about notes, scenario sketches, and knowing my lead indicators early.
What I’ve learned is: Tools aren’t guarantees. But they help you ask better questions, and that gives you an edge.
Some of my other reflections dive deeper into these ideas:
- Why Do Organizations Use Data?
- Building Complex Machine Learning Models
- What Makes a Career in Data Science Work?
🧭 Final Word: Clarity is NOT Control
Whether you're managing a farm or launching a digital product, the takeaway is the same: data can guide, but it can’t guarantee. The real edge comes from thinking in systems — spotting leverage points, sensing patterns early, and staying humble in the face of change.
The forecast might be right — but the outcome depends on how you play the game when the skies shift.
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