Avoiding Dash-Boredom 1:

Starting Point

"The Pivot", Blog of Pivot Point Analytics. By Thad Wengert

When you hear “Monthly business review” do you think

  1. “Exciting! I can’t wait for a chance to invigorate my team and plan to surpass competitors.”

  2. “Hours-long meeting and a deck full of numbers in 8-point font. The only vigorous part is debating which conflicting numbers are correct. I better be sure my phone is charged so I can at least answer emails.”

Many businesses find that people don’t rely on the dashboards and reports which ARE available. They’re laborious. They “just report yesterday’s news.” They flag problems but don’t help diagnose and solve problems.

That is dash-boredom.

“We lack a data-driven culture!” is a common explanation. That’s a bogey. In our experience, people WANT to deliver better results and they’d LOVE to have data to help them. Culture quickly follows the capability to use data.

The recipe to get your team using data for daily decisions within a few months has 4 ingredients. Read on for a taste test, with examples drawn from a telecomm, e-comm, and B2C manufacturer we’ve worked with.

  1. Single version of truth. Land data into a single data store , with a clear, simple glossary of terms.

  2. Dashboards people love. Involve the users of reports in their design.

  3. Metrics that motivate. Define metrics in a way to motivate change, not just to report the news.

  4. A vital strategic challenge.


A bunch of systems and applications make a business run. Each has its own reports, dashboards, and exports. That means

  • there are many definitions … of a customer, a sale, even simply of “month”,

  • and it’s laborious to get a full view of what’s going on through the “snowstorm” of data.

You need a single version of truth.

Data initiatives succeed (or fail) by getting decision makers to agree upon and use a new source of numbers that are the single version of truth. When they don’t, “lack of a data culture” is a bogey often blamed when people don’t use new dashboards and reports. We don’t believe in that bogey.

Rather, to get your team to agree upon and use a new version of truth, these 4 elements must be in the project.

  1. “Thin slices” Tackle a single subject area at a time. Take it all the way from sources to user-facing dashboards and reports. Your team will gain confidence fast when they get data tools early and steadily.

  2. “Glossary” There must be a glossary of definitions of metrics. Documentation is often left as an afterthought of a project; it slows down the “real work.” But just as Chefs insist on “mise en place” neatness, they get it by structuring the kitchen so everything has a convenient place. We use tools for building data pipelines which make it easy - almost unavoidable - to document data definitions as we go. “dbt” is our favorite.

  3. “Agreement” Everyone has to accept definitions of metrics. Yet for example, Marketing and Finance define a “sale” differently, and for good reason. The goal is not unanimity, rather confidence and avoiding time wasted on arguments. Differences are one of two types:

    1. Consistent over time. If the gap between Marketing and Finance is +/-2% from month to month, a leader needs to simply declare one as the winner. AND that difference needs to be documented in footnotes on reports and in the glossary. That instills enough confidence, versus round-and-round arguments about trivial differences.

    2. Inconsistent differences. In our example, Finance may have good reasons to delay recognizing revenue, so the two series of numbers don’t run parallel. The solution is to choose which one will be the company KPI, to make both available only where absolutely needed, and to insist on proper naming on every report and every discussion: “finance sales” vs. “marketing sales”.

  4. “Priority” Choose the first subject areas for a team who will use data intensely and daily. That might not be the group who is the loudest and most demanding! This guarantees a team of people excited by the new data tools.

Putting these elements in your data initiative will get you to a single version of truth that your team accepts. Time lost in debating differences turns into time for discussing action plans.