Why this matters: we measure too much, and decide too little
To continue the series of data-driven stories, I want to expand on something we discussed recently: good analytics is about measuring the right things and answering the right questions. Sounds clear. No. Because most organizations still behave as if the goal is to measure everything.
But good analytics doesn’t track everything that can be measured. This identifies which signals are important, which patterns are meaningful, and which changes require attention. It chooses what should influence behavior.
Data is like oil (and that’s the point)
I’ve always liked the analogy of comparing data to oil. In its raw form, oil is messy, sticky, unpleasant, and mostly useless. You don’t pour crude oil into your car and expect it to run. You perfect it. You process it. You extract value from it.
The data is the same. The raw data, straight from operational systems, is very messy. It is incomplete, duplicated, and inconsistent. It contains interrelated signals and noise. It only becomes valuable when it is refined, cleaned, structured, modeled, and interpreted. And here’s the part of the analogy that few people mention: if you spill oil where it shouldn’t, you’re in serious trouble.
The data is the same. Bad governance. Abuse. Exposure. Misinterpretation. All of this poses risks. So yes, data is valuable. But only if handled properly.
From “swimming in data” to “drowning in it”
I recently wrote on LinkedIn while promoting “Analytics Decision Support: Why Reporting Alone Isn’t Enough” that we’re not short of data, we’re drowning in it. Someone responded that Ralph Kimball had said something similar around the turn of the century ~2003:
We are swimming in data. We couldn’t achieve it.
At the start of the 21st century, that was largely true. Data is stored in silos. Limited access. Demand is slow. Integration is painful.
By 2026, the tools have evolved dramatically: cloud platforms, modern warehouses, Fabric, Power BI, semantic models, and self-service analytics.
In many organizations today, access is not the main obstacle. Although government and political processes can still play a role. You can get the data. The more interesting question is: Can you do anything meaningful with it?
Surfing analogy: same wave, different results
Kimball’s comment made me think of another water analogy. If we were “swimming in data” twenty years ago, today we are riding a wave. Some organizations are exploring it. Others sunk into the depths. When you watch a skilled surfer, it looks easy. They don’t try to ride every wave. They don’t panic when the water moves. They read the conditions, position themselves, and commit to the right moment. They ride the waves to the shore.
Now consider someone inexperienced: they wait too long, leave too early, try to stand without balance, or fall and spend the next few minutes recovering. The waves are the same. The result is no.
The tide of data is not slowing down
The wave won’t go away. In fact, the acceleration:
- More telemetry
- More AI output
- More behavior tracking
- More integration between systems
The difference between companies is no longer about who has the most data. Who can ride it.
What “surfing” looks like in analytics
Organizations riding the data wave have typically learned to:
- Make a decision before diving into the data set
- Identify 3–5 signals that really matter
- Create reports that reduce noise, not add to it
- Moving from “interesting” to “actionable”
What “floundering” looks like
Others are responding to the uncertainty by adding more dashboards, metrics, and pages, in hopes of clarity from the volume. Rarely happening.
Measure what influences behavior
One of the most important lines in this entire series is this:
It’s not about tracking everything that can be measured. It’s about choosing what should influence behavior.
Because people do what you measure.
If you measure twenty things, none of them will feel urgent. If you measure three things correctly, behavior will change.
That’s the difference between swimming and surfing.
Swimming keeps you afloat and moving slowly. Surfing gets you somewhere on the waves pretty quickly.
Did you catch a wave?
So, here’s the key question.
- Are you surfing a data wave, or sinking in the depths?
- Does your report clarify what’s important, or does it reflect the chaos of the underlying system?
- Does your analytics function distill raw data into decision-ready insights, or just make it more visible?
Because tools are no longer an excuse. Access is no longer an excuse. The wave is here.
The next step
If this is true, then that’s the shift we’re focused on within the Data Accelerator: moving from drowning in data to harnessing it with intention, by starting with decision making, refining signals, and designing reports that create clarity.
PakarPBN
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