70% of digital transformation projects fail. $2.3 trillion wasted globally every year. And most of that money went to people who left before the consequences showed up. I’ve sat on both sides of the table. The consultant side. The operator side. They’re not the same. Consultants see businesses from the outside. Operators see them from the inside. That difference changes everything—what you recommend, what you build, and whether it actually works when everyone goes home.
TL;DR: Consultants optimise for recommendations. Operators optimise for Monday morning. The difference: operators know the 11pm fixes, the workarounds nobody documented, and why “best practice” isn’t. If you want systems that survive contact with reality, work with someone who’s been inside.
The Consulting Blind Spot
Here’s the pattern I’ve seen dozens of times: Consultant comes in. Spends 6 weeks. Interviews stakeholders. Produces a 50-page deck. Recommends “digital transformation” or “system modernisation” or whatever the current buzzword is. Then they leave. And nothing changes.
Why? Because they never had to live with the consequences.
They didn’t see the sales rep who still uses the spreadsheet because the CRM takes 47 clicks to do what Excel does in 3. They didn’t know about the workaround that Jess in operations invented because the “approved” process doesn’t handle returns properly. They didn’t understand why the team ignores the dashboard—because by the time it updates, the information is already stale.
Consultants see the org chart. Operators see the shadow org chart—the one that actually runs the business. Sound familiar?
What Operators Actually Know
I’ve been the operator. Years of it. Here’s what that teaches you:
| What Consultants Do | What Operators Know |
|---|---|
| Optimise for the recommendation | Optimise for Monday morning |
| Eliminate workarounds | Know which ones are load-bearing |
| Import “best practice” | Ask if it fits this context |
| Plan for the happy path | Plan for 4pm Friday when it breaks |
| Leave after the deck | Stay for the 11pm fix |
1. Plans don’t survive Monday morning. Every plan looks good in the Friday afternoon meeting. Then Monday happens. The edge case nobody considered. The integration that times out. The team member who’s on leave. Operators know the difference between a plan that sounds good and one that works. We’ve learned it the hard way—at 11pm, fixing something that wasn’t supposed to break.
2. The workarounds ARE the process. In every business, there’s the documented process and the real process. The real one has sticky notes, tribal knowledge, and “just ask Sarah” steps that never made it into the workflow diagram. Consultants try to eliminate workarounds. Operators know some of them are load-bearing. Remove the wrong one and everything collapses.
3. Best practice isn’t always best. “Best practice” means “what worked for someone else, somewhere else, at some other time.” It doesn’t mean it works for you. Your constraints are different. Your team is different. Your customers are different. I’ve seen “best practice” implementations fail spectacularly because nobody asked whether the practice actually fit the context.
4. Speed to value beats perfection. Operators know what consultants don’t: a 70% solution shipped today beats a 100% solution planned for next year. Because next year, the requirements will have changed. The team will have changed. The market will have changed. Get something working. Iterate. That’s how real businesses actually operate.
Why This Matters for Technology Projects
Technology projects fail at an alarming rate. McKinsey puts it at 70%. Bain’s 2024 study says 88%. The Standish Group found only 35% of projects finish successfully. The usual explanations: scope creep, budget overruns, technical complexity.
I’d add another one: the people designing the solution never had to operate one.
They’ve never been woken up at 2am because the integration failed. Never had to explain to a customer why their order vanished. Never had to make a system work with a team that doesn’t want to change. That experience changes how you build things.
When I design a system now, I’m not thinking about the happy path. I’m thinking about what happens when the API is down, the data is messy, the user does something unexpected, the person who understands the system leaves, or it’s 4pm Friday and something breaks. These aren’t edge cases. They’re Tuesday.
Have you ever worked with someone who understood that?
First Thing Tomorrow
Stop hiring for advice. Start hiring for consequences.
1. Ask about failures. Consultants talk about successes. Operators talk about what broke and what they learned. If someone can’t tell you about a system that failed and why, they’ve never been close enough to the work.
2. Ask about workarounds. “How do you handle processes that exist outside the official system?” If they say “we document and formalise everything,” they don’t understand how businesses actually work.
3. Ask about maintenance. Who monitors it? Who fixes it at 11pm? Who owns it when the project team moves on? If they can’t answer, they’re not thinking past go-live.
4. Ask for operator references. Not client logos. People who worked alongside them. The ones who saw what happened after the deck was delivered.
If the answers sound like a sales pitch, keep looking.
The Bottom Line
Advice is cheap. Execution is expensive. The gap between a good recommendation and a working system is enormous. It’s filled with edge cases, workarounds, politics, and 11pm fixes. I’ve been on the inside. I know what survives Monday morning.
Advice is cheap. Execution is expensive. That’s the difference.
Need operator-level delivery, not consultant-level advice? That’s what I do. Senior execution. Systems that work. Start a conversation.
Sources
- McKinsey: Common Pitfalls in Transformations — 70% failure rate
- Digital Transformation Failure Rate 2025 — $2.3 trillion wasted annually
- Standish Group CHAOS Report — Only 35% project success
- Harvard Business Review: The Trouble with Consultants
- Consultancy.org: External vs Internal Consultants
- BCG: Why Digital Transformations Fail