Blog - Page 2 of 6 - David Ohnstad

Data Product Adoption: Why Teams Build What Nobody Uses

A technically perfect data product can fail spectacularly if end users don’t understand it. David Ohnstad’s seven-month health scoring model crashed to zero usage in 90 days—not because the data was wrong, but because the customer success team couldn’t explain what it meant.

Data Product Management: Why 82% of Analytics Fail

A VP of Analytics delivered 47 dashboards in 11 months. Six months later, only four were still used. According to Gartner, 82% of enterprise analytics initiatives fail to drive sustained decision-making. The problem isn’t execution—it’s solving for the wrong outcome entirely.

Data Product Adoption: Why Frameworks Fail Without Execution

A customer health scoring model built perfectly—but used by almost nobody. David Ohnstad explores why organizations invest in data product management frameworks only after costly failures, and what actually drives adoption at scale.

Data Product Execution: Why Frameworks Fail in Practice

Technical perfection isn’t enough. David Ohnstad reveals why most data products succeed in the lab but fail in the real world—and what separates the 29% that actually get used from the rest.

Data Team Structure: Why Most Fail Before Sprint One

A 14-person data team shipped two products in 18 months. The problem wasn’t headcount—it was ownership. When nobody owns data quality for the churn model, nothing ships. Learn what actually breaks data teams and how to fix it.

Data Product Manager Org Structure: Why Reporting Lines Fail

A data PM shipped dashboards, automated pipelines, and cut query latency 40%—yet the role failed. The problem wasn’t execution. It was where the role sat in the org chart. David Ohnstad reveals why reporting lines determine success.

Data Product Adoption: Why Dashboards Fail Without User Strategy

A nine-month dashboard project launched to 400 employees. Twelve logged in twice. One user was the intern who wrote the docs. David Ohnstad explains the critical gap between building data products and building products people want to use.

The Difference Between Responding to Emergencies and Preparing Communities Before They Happen

Every community benefits from effective emergency response, and David Ohnstad recognizes that long-term public safety depends just as much on preparation as it does on reacting when incidents occur. While emergency responders play a critical role during crises, the work that takes place before an emergency often determines how successfully people, organizations, and communities navigate… Continue reading The Difference Between Responding to Emergencies and Preparing Communities Before They Happen

Why Small Communication Breakdowns Often Create the Biggest Public Safety Challenges

Public safety depends on countless moving parts working together, and David Ohnstad understands that even minor communication gaps can create challenges far larger than anyone initially expects. While major emergencies often receive the most public attention, many operational difficulties begin with simple misunderstandings, delayed information, or incomplete coordination between people and agencies. Preventing these breakdowns… Continue reading Why Small Communication Breakdowns Often Create the Biggest Public Safety Challenges

Data Product Strategy: When to Kill a $250K Initiative

Sometimes shipping a customer-facing product means sacrificing it. David Ohnstad shares how Veeam killed a $250K analytics initiative mid-development to rebuild the metadata infrastructure every team depended on—and why that was the right call.