From Data to Information

12 Mar, 2025

Why leaders need systematic decision processes

Dashboards are everywhere—ERP extracts, CRM reports, customer click-streams—yet basic questions still stall. Eliyahu Goldratt spotted this decades ago: data only becomes information once it passes through a decision process.

Data + Process = Information

Data ≠ information

Information is an answer to a question.

A data warehouse may hold every transaction, but unless there’s a clear way of asking “which product to back next?” it’s just accumulation. Leaders often solve the wrong problem: they collect more data when what they need is a better decision rule.

Rituals aren’t processes

Many management routines look systematic but aren’t.

A finance meeting that reviews sales variance and then asks “thoughts?” looks structured, but still runs on memory and bias.
An S&OP review that says if demand gap >3%, trigger a capacity review is a process: inputs, thresholds and responses are explicit.

Systematic doesn’t mean rigid—rules can flex—but the logic is visible and auditable.

Gut needs structure

Experience matters, but only when embedded in a flow others can follow. Otherwise decisions default to hierarchy and charisma.

Example: SG&A rises 4%. CFO orders cuts. In reality, marketing prepaid a campaign. A systematic check—timing effect or structural change?—would have caught it.

The missing skill

Few leaders are taught to design decisions. MBAs cover finance and strategy, but not decision engineering. Yet it’s core leadership work:

Define the decisions that matter.
Specify inputs.
Lay out the logic.
Assign ownership and cadence.

Think of it as a factory: data in, decisions out—predictably.

Start small

Don’t redesign the whole company. Begin in your lane:

Sales – run win/loss reviews and refresh decks monthly.
HR – build a hiring tree and track retention by role.
Ops – run a daily buffer check to set priorities.

Small rules build confidence in the method.

Conflict as progress

When the basis of a decision isn’t clear, disagreement feels personal. People end up defending their judgment rather than debating the issue.

Make the logic explicit, and conflict shifts from personalities to principles.

A: “We chose X because throughput per £ was higher.”
B: “Fair, but those numbers are outdated. Let’s refresh.”

Now the argument is about the data or the rule, not about who has authority. Disagreement becomes a way to improve the decision rather than a contest of opinion.

Local vs global

Goldratt’s warning still holds: local optima ≠ global optimum.

Sales may chase high-margin orders while the plant is blocked elsewhere. Mature leaders hold two truths: the process gave the right local answer, but enterprise needs override it—and the override should feed back so local rules evolve.

From data to decisions

Data abundance can paralyse as easily as empower. Leaders who build open, testable decision processes:

cut noise and bias,
enable constructive debate,
align local choices with global priorities.

In an age of AI hype, the bottleneck isn’t data volume. It’s decision design. Build it, show it, test it—and the signal becomes clear.

In most boardrooms, the dashboards impress but the conversation always collapses into the same question: what do we do next?

That’s the moment when data either becomes information or remains decoration. The difference is rarely technology—it’s whether the decision process has been designed at all.

#numbers