I. We Say We’re Data-Driven — But Are We Really?
Across
ministries, donor programs, NGOs, and finance offices, there’s a growing
belief: that data should shape decisions. That evidence should guide strategy.
That we are, or should be, data-driven.
But
quietly — almost universally — we’re ignoring the most reliable data we already
have.
Every
year, hundreds of pages of public reports are published in Kenya — packed with
everything from housing data to water access, clean energy use, employment
trends, budget absorption, and more. They are detailed. They are national. They
are free.
But
they are also long, dense, and hard to act on.
Few
people actually read them. Even fewer extract value from them. And yet, these
same reports are where the real contradictions hide — the tension between what’s
promised and what’s actually happening.
In
other words: the most useful data often dies in unread documents.
My
entry point was simple. Like many data professionals, I started with individual
tables and small datasets — analyzing price trends, population shifts, and
service delivery gaps using Kenya National Bureau of Statistics (KNBS) data.
The
insights were useful — but always isolated.
They
lacked something bigger: the context only full reports provide. I
started reading them — one by one. Reports on housing, construction, the
environment, economic performance. Some were over 200 pages. Others had
appendices longer than the main text.
But
the more I read, the clearer the pattern became:
- Critical data
points were buried in plain sight
- Most findings
lacked direct connection to the people responsible for change
- Reports rarely
translated into planning, funding, or operational decisions
It
wasn’t a content problem. It was a translation problem.
Most
people treat government reports as a formality. Something to quote in a slide
deck or cite in a budget memo.
But
what I found was deeper:
- Contradictions
between budget and outcome
- Hidden service
gaps across counties
- Sector trends
that reveal implementation failures
- National targets
left unmet — but never unpacked
These
aren’t abstract stories. They’re triggers for strategic action.
Inside
these documents are moments where strategy breaks, delivery misses, or
investments fail to land. And in most organizations, these moments never get
seen — not because the reports are secret, but because no one has time to
dig for them.
IV. The Stakeholder’s Reality
Most
decision-makers aren’t trying to avoid data. They’re trying to survive noise—where
time is wasted trying to make sense of useless data.
You
don’t have time to process a 300-page report — not with deadlines, meetings,
politics, and internal reports piling up.
But if you work in housing, water, finance, or infrastructure — these reports
are quietly shaping the policies, regulations, and budgets you’re operating
under.
The real gap is not data access — it’s usable data intelligence.
That’s
what most teams are missing. Not insight itself, but:
- A way to
separate signal (useful information) from noise (useless data).
- A format that
respects time and job pressure.
- A layer that
translates government-wide trends into role-specific clarity.
To
solve this, I built a quiet system: The
Data Brief Engine.
Its
job is simple:
- Read the big
reports so you don’t have to
- Extract
contradiction, intelligence, and insights that matters
- Match it to a
specific stakeholder’s role
- Write it as a
1-page brief you can act on
Each
brief is:
- Based entirely
on official public data or your own data and reports.
- Tailored to a
real institution, department, or team
- Structured for
operational use — not academic analysis
- Free from fluff,
dashboards, or endless KPIs
📂 View the current
portfolio here → https://drive.google.com/drive/folders/14yYbHbPmnNQvDk_dV0o-gWn8OJE1-EX0
📨 Request a tailored
brief → https://docs.google.com/forms/d/e/1FAIpQLScSTYoxntlNijjUPsezBjai-xwiVFYwXLEn4Ieyja7gNaHfCQ/viewform?usp=sharing&ouid=103489511953917394452
These
are not summaries. They’re stakeholder intelligence sheets — meant to inform
real decisions, not just reports.
VI. Where It Complements Traditional Data Work
This
system doesn’t replace small data analysis. It complements it.
- Small data
answers sharp questions about a local issue
- Report-based
analysis answers system questions about national policy or sector
trends
Together,
they give you a complete picture — from ground-level insights to
national level decision intelligence.
We
live in an age of automation and AI — where everyone wants to build the next
dashboard, model, or data pipeline.
But
most of what makes an organization smarter isn’t more data — it’s better
framing of the data we already have.
Reports
like the Kenya Housing Survey or the Economic Survey aren’t obsolete. They’re
just unread. If we want data to actually improve outcomes — not just decorate strategies
— we need systems that turn information into usable signals (strategies,
plans, actions).
That’s
what this work is about.
This
isn’t a pitch. It’s a call to return to the data that matters.
If
you’re a stakeholder — in housing, planning, infrastructure, development,
finance — the reports already contain the context you need. You just may not
have time to find it.
The
Data Brief Engine is a small system, still evolving. But the signal is already
there. It’s hidden in the reports everyone ignores.
Let’s
make them useful again.
JP Mwangi MKH, Independent Data Analyst