The Data Dictionary: Your First Step to Becoming Data-Driven
My wife and I have a common language. We both know that when we say “bedtime” for the kids what that means. It’s the exhausting process that includes the 4 Bs: Baskets (they have baskets that they carry upstairs each night to keep the downstairs clean), Baths, Brushing teeth, and Books. It starts at 7pm and takes about 45 minutes.
Our babysitters have different, looser definitions. To them bedtime means getting the kids in bed by 8 or 8:30 with no tears.
Our kids have yet another definition. They believe that bedtime is more of a suggestion and that simply being in their bedrooms is enough:
Without a shared understanding of what “bedtime” truly is, there’s confusion, unmet expectations, and arguing.
The business world is no different.
If Sales has one definition of a lead and Marketing another, then there’s bound to be disagreement. Chances are members of your own team already have radically different interpretations of your commonly used metrics.
I was talking to a sales professional the other day who said that at his previous job, the company’s account executives couldn’t agree on when an opportunity should be moved from one stage to another. This is more much commonplace than it should be.
Without straightforward, clear cut definitions of key metrics, there will be plenty of miscommunication, confusion, and bad decision-making.
Enter the Data Dictionary
Communication is the cornerstone of effective collaboration. If you are seeking to drive high performance through data, then everyone on the the team must know and understand the key metrics. It’s important that everyone on the sales team (and in the organization) agrees on the definition of a SQL (Sales Qualified Lead), when the stage of the funnel is complete, and how you calculate win rate.
In Winning with Data Tomasz Tunguz writes all about how to best operationalize your data. The first step is the creation of a data dictionary.
A data dictionary is a collection of the your most important company metrics clearly defined and accessible to all. This living collection of canonical definitions becomes the common language that aligns everyone in the organization.
Why is it important? Tunguz writes of the benefits of a data lexicon, “This Rosetta Stone enables productive and incisive conversations about data across teams, bolstering or refuting arguments and accelerating decisions.”
You can track hundreds of metrics, but if there is no agreement and understanding of what those metrics actually mean and if those metrics are not actionable, then what’s the point?
Ambiguity is the enemy.
If you’re looking to truly operationalize your data, channel your inner Merriam-Webster and start with a company data dictionary.