Are You Catching the Data Wave or Floundering in the Deep?

Are You Catching the Data Wave or Floundering in the Deep?Analytics isn’t about tracking everything. It’s about selecting what should influence behaviour. In 2026, with better tools than ever, the question is simple, are you surfing the data wave, or struggling to stay afloat?

Why this matters: we measure too much, and decide too little

To continue the series on data-driven storytelling, I want to build on something we touched on recently: good analytics is about measuring the right things and answering the right question. That sounds obvious. It isn’t. Because most organisations still behave as though the goal is to measure everything.

But good analytics doesn’t track everything that can be measured. It identifies which signals matter, which patterns are meaningful, and which changes require attention. It selects what should influence behaviour.

Data is like oil (and that’s the point)

I’ve always liked the analogy that compares data to oil. In its raw form, oil is messy, sticky, unpleasant, and largely useless. You don’t pour crude oil into your car and expect it to run. You refine it. You process it. You extract value from it.

Data is the same. Raw data, straight from operational systems, is chaotic. It’s incomplete, duplicated, and inconsistent. It contains signal and noise tangled together. It only becomes valuable when it’s refined, cleaned, structured, modelled, and interpreted. And here’s the part of the analogy that people don’t mention enough: if you spill oil where you shouldn’t, you’re in serious trouble.

Data is the same. Poor governance. Misuse. Exposure. Misinterpretation. All of it creates risk. So yes, data is valuable. But only when 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 replied that  Ralph Kimball had said something similar  around the turn of the century ~2003 ish:

We are swimming in data. We just can’t get to it.

At the time in the early 21st century, that was largely true. Data lived in silos. Access was limited. Querying was slow. Integration was painful.

Fast forward to 2026, and the tools have evolved dramatically: cloud platforms, modern warehouses, Fabric, Power BI, semantic models, and self-service analytics.

In many organisations now, access isn’t the primary constraint. Although governance processes and politics can still play a part. You can get to the data. The more interesting question is: Can you do something meaningful with it?

The surfing analogy: same wave, different outcomes

The Kimball comment made me think of another water analogy. If we were “swimming in data” twenty years ago, today we’re facing waves. Some organisations are surfing them. Others are floundering in the deep. When you watch a skilled surfer, it looks effortless. They don’t try to ride every wave. They don’t panic when the water moves. They read the conditions, position themselves, and commit at the right moment. They ride the wave to the shore.

Now watch someone inexperienced: they wait too long, go too early, try to stand without balance, or get knocked down and spend the next few minutes recovering. The wave is the same. The outcome isn’t.

The data wave isn’t slowing down

The wave isn’t going away. If anything, it’s accelerating:

• More telemetry
• More AI outputs
• More behavioural tracking
• More integration between systems

The difference between companies isn’t who has the most data anymore. It’s who can ride it.

What “surfing” looks like in analytics

Organisations that surf the data wave have usually learned to:

• Define the decision before diving into the dataset
• Identify the 3–5 signals that truly matter
• Build reports that reduce noise instead of adding to it
• Move from “interesting” to “actionable”

What “floundering” looks like

Others respond to uncertainty by adding more dashboards, metrics, and pages, hoping that clarity will emerge from volume. It rarely does.

Measuring what influences behaviour

One of the most important lines in this entire series is this:

It is not about tracking everything that can be measured. It is about selecting what should influence behaviour.

Because people do what you measure them by.

If you measure twenty things, none of them feel urgent. If you measure the right three things, behaviour changes.

That’s the difference between swimming and surfing.

Swimming keeps you afloat and moving slowly. Surfing takes you somewhere on the wave quite quickly.

Are you catching the wave?

So here are the key questions.

• Are you surfing the data wave, or floundering in the deep?
• Do your reports clarify what matters, or do they mirror the chaos of the underlying systems?
• Does your analytics function refine raw data into decision-ready insight, or does it simply make more of it visible?

Because the tools are no longer the excuse. Access is no longer the excuse. The wave is here.

Next step

If this resonates, it’s exactly the shift we focus on inside the Data Accelerator: moving from drowning in data to riding it with intent, by starting with the decision, refining the signal, and designing reports that create clarity.