7 figure projects that crash and burn

I've seen several $10-30 million data projects crash and burn.

And numerous other small projects that had embarrassingly low success rates.

Here are 3 key themes that caused issues in each of these failed projects

1 - Outcomes

There were deliverables, technical specs, architecture designs, and plenty of requirements. But those aren't outcomes - those are activities.

Be very wary of a consulting firm that sells you on the activities they will perform, or the deliverables they will produce at the end.

2 - Incentives

When there's no agreement on an end outcome, incentives run wild. Scope creep, change requests, delayed timelines. When people have different desired outcomes, they are incentivized to push for their own agenda.

Chaos ensues.

3 - Expectations

You will see this when you reach the end of a project phase or a sprint and the project hits a standstill. The stakeholders look at your deliverable disappointed or confused. The executive sponsor reallocates the budget and cancels the next two phases of the project.

Their expectations weren’t met. "If you don't tell someone what to expect, how will they know when they've won?" Disappointment in data projects is primarily related to poor expectation setting or poor expectation management.

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If you are facing an upcoming data project - with hundreds of thousands or millions of dollars on the line - you are well served to evaluate these three areas. Hit reply if you are looking for remedies and experience solving these challenges. You aren’t alone.

Which of these issues most resonates with your experience as a data leader?

I made this for you,

Sawyer