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Building Data Trust One Proof of Concept at a Time
- Christian Steinert
- Aug 5
- 3 min read
The cornerstone of articulating data strategy & governance successfully
Pitching the value of analytics and data governance can seem like an endless pit. There are so many angles to take for selling the grander vision of data in an organization.
Here are a few:
Cost savings
Time savings
Risk mitigation
Revenue generation
Uncover market opportunities
Upsell customers with highest LTV
Over the past 2 months, I’ve done extensive self-study on data strategy and how to position data’s value to executives. Being part of a few large data modernizations & transformations in my career…
I’ve learned that starting small is the key to a successful project.
A small project is also referred to as a Proof of Concept (POC).
If you promise the world and boil the ocean for your stakeholders, you’ll end up with dust particles.
Focusing on a small scope of work to start creates specificity. Specificity creates easily digestible and tangible results. These tangible results create interest and curiosity.
“If we take this small win and 10X it, what will the outcomes look like then?”
Painting the Foundation of Trust With Data Governance and a POC
People are complex. In my experience, typically the data product isn’t the problem.
It’s the people consuming the product that create all the issues. Organizational politics will always be there, and I’ve dealt with some pretty entangled situations in my data career.
One that stands out:
Technical enterprise leaders that don’t see the need for a data warehouse.
“Why do we need to spend money on a data warehouse? We can just pull from our raw database to get what we need!”
“We don’t need everyone in the business using the data. Only those that have to have it.”
That’s why it’s so important to have a specific and tangible outcome. And early on, before full stakeholder buy-in is there, a small and specific project gives you the ability to showcase the benefits to the business.
Many of you have heard this narrative before in some form or fashion. I want to take a different, data governance-centric, approach that I’ve pitched to a few clients.
The place I see these POC projects fall short the most are with data governance.
Data governance is often prioritized last because it’s thought of as bureaucratic and a blocker of fast progress. But what is really the key purpose of data warehouse integration?
Established trust to make confident decisions.
Trust is your cornerstone. Without it, your users won’t use the data and products that you’ve spent insane amounts of time building.
Due to the nature of a POC, no data professional can possibly fix data governance issues in a project of that small scope. This makes it an extremely useful angle to pitch opportunity cost from.
Showcasing What Your Proof of Concept Lacks
Sometimes the most powerful motivator for change is showing where they are significantly falling short.
The POC projects that I’ve built for clients delivered on what we said, but still wrestled with inaccurate data (at times) due to non-existent data governance guardrails.
Here’s a classic example: semantic models that include Excel workbooks as tables. These workbooks are dependent upon complex formulas and hours upon hours of refresh maintenance.
Furthermore, many of the fields used to group things like sales by product or sales by location use Excel-based reference tables. If one row changes due to a user updating the Excel spreadsheet, you risk offsetting the entire report and how it’s displaying the sales numbers.
Even in a perfectly delivered POC, these governance-based problems cause issues that impact end users. I’ve never been embarrassed when this happens. Instead, I use these issues as an opportunity to articulate the importance of strong data governance.
Instead of broadly claiming “we need data governance so the data is consistent”, the call-outs from a POC give specific and tangible examples that demonstrate why we need data governance.
Now executives are on the same page!
Leverage Your POC to No End
This is all about using what you have.
When I first started in data strategy, like I referenced at the beginning, the amount of angles to sell data on is too vast. It can feel like drinking out of a firehose while staring into a black hole.
You HAVE to have a specific project and outcome defined. Every win, whether it’s cost/time savings or revenue generation, needs to tie back to this. It makes it very clear to showcase in front of executives looking for undeniable proof, not corporate fluff.
Christian Steinert is the founder of Steinert Analytics, helping healthcare & roofing organizations turn data into actionable insights. Subscribe to Rooftop Insights for weekly perspectives on analytics and business intelligence in these industries.
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