Data Elitism is an Error of Omission

Never heard the term.   But it was always it our goal to include decision makers that used the data and decision process as closely as possible.  If you don't you are inviting failure.    I don't think its the default, its a error of omission.  Good to repeat the idea:  seriously include decision makers, owners,  aka 'stake holders'.

Does Your Company Have a Data-elitism Problem?  in K@W

Digital transformation is a buzz phrase at the forefront of many business plans today. Data, of course, is at the heart of it. But who has access to that critical data for decision-making? If your data is controlled by a coterie of elite specialists, even though not many outside that group may show much interest, your organization is likely to be far less effective, argues Brett Hurt, CEO and co-founder of data.world, in this opinion piece.

Consider the last time your team used data to make a decision. Were stakeholders with relevant knowledge throughout the business involved in the process? Or did they learn about the decision after it was made, without their input? Were the people doing the data analysis also experts in the subject matter? If you’re a high-level decision maker, you’re probably completely removed from how data is collected, organized and analyzed. Any plan, however brilliant seeming, stands on loose pillars if it comes from a team that is long on data talent and short on domain knowledge. This scenario, unfortunately, is the norm in corporate America.

Here’s a second scenario. You uncover a business problem that data can help solve. The employees who deal with the challenge daily, who feel its pain acutely, get immediately looped in on the project and consulted throughout its progress. You make the data available with the context they need to understand it. They ask questions only people like them would think to ask. Your data scientists and analysts probe the data and come back with illuminating answers. Everyone speaks the same language with the help of a shared data dictionary. This inclusive approach to collaboration capitalizes on the amazing array of perspectives, skills and knowledge available at any sizeable company. And deep data collaboration increases the data literacy of your non-quants while improving the business knowledge of your data people. As a result, the next project begins on better footing, and its result is even better than the last.

If the first scenario is more familiar, you have a data elitism problem. Data elitism happens when decision-makers only focus on ways to make advanced users more productive with data. Put another way, data elitism is any practice that makes data less inclusive. It’s usually not intentional — it’s more of a default state.   .... "