People, Process, Technology and the Data Loop

Where the model comes from

In the 1960s the organizational psychologist Harold Leavitt described a business as four connected parts: people, tasks, structure and technology. His point was that you can't change one without moving the others. Managers later folded tasks and structure into one word, Process, and People, Process, Technology became a standard way to look at change. Data sits at the core of how I work: let one area slip, and the others start to unravel over time.

People: questions, signs and a case

Ask yourself

1. Who owns each outcome, and do they know it?
2. Are the right people in the right roles, and were they hired for fit or for loyalty?
3. Who on the team has an honest read of what's happening on the ground, and do you hear it?

Signs it lives here

• Good people are hard to find, and harder to keep
• A good person is in the wrong role
• Every change meets resistance
• Decisions wait for one person

Process: questions, signs and a case

Ask yourself

1. Where does work wait, and on whom?
2. Which decisions still need the owner, and which could someone else make with the right guardrail?
3. When something slips, who notices, and how long does it take?

Signs it lives here

• Things slip through the cracks, and the same problems come back
• I can't take a week off without things stalling
• There's more work than one person can finish

From a client engagement

A global company was about to drop its data agency. It looked like a Data problem. Interviews on both sides showed departments that didn't talk to each other and no communication process between the company and its agencies. A shared process, a cross functional team and governance followed, and the agency nearly tripled its revenue in three years. The full case

Technology: questions, signs and a case

Ask yourself

1. Which tools does the team actually use, and which do they work around?
2. Where is someone retyping what one system already knows?
3. What could AI take off someone's plate this week, and who checks its work?

Signs it lives here

• Our tools don't talk to each other
• AI hasn't changed how the work gets done
• Information gets chased, then chased again

From a client engagement

A property management team spent its week chasing paperwork across tools that didn't connect. I built them an onboarding tool in Claude that tracks what's pending and sends the reminders, plus dashboards for the team and for each property owner. Owners renewed, added services, and revenue rose 18% year over year. The full case

Data: questions, signs and a case

Ask yourself

1. Which numbers do you make decisions on, and does the team trust them?
2. How long between something happening and you seeing it?
3. Is the same thing named the same way across teams, tools and clients?

Signs it lives here

• Reports take too long, or nobody trusts them
• Every new project starts the data from scratch
• Two reports, two different answers

From a client engagement

An agency needed six to eight months before a new client saw a report, because nothing was named the same way twice. A data accelerator of ready models mapped to standard fields, built by industry, cut that to weeks and became a differentiator that helped win new business. The full case

FAQ

What is the People, Process, Technology framework?

It's a way of looking at change in a business that traces back to Harold Leavitt, who in the 1960s described a business as four connected parts: people, tasks, structure and technology. Managers later folded tasks and structure into Process. The point is that you can't change one part without moving the others.

Where does Data fit in People, Process and Technology?

Data runs under all three. It shapes how you decide on People, Process and Technology, and keeping track of all three is what keeps those decisions informed. When tracking slips in one area, the numbers wobble, and every decision they feed starts to wobble too.

How do I know which area my problem is in?

Look at the signs: work that waits on one person points to Process, tools that don't talk to each other point to Technology, reports nobody trusts point to Data. Signs aren't always the root cause, which is what Discovery is for.