As the saying goes, “The fastest way from point A to point B is a straight line.” Now, math and physics experts might debate you on this, but the point is that there’s something to be said for directness when it comes to getting from where you currently are to where you want to be.
In today’s data-driven workplace, point A represents current performance. Point B represents optimal performance according to goals—higher revenue, lower operational expenses, etc. And data is the most direct path between them.
But it’s entirely possible for a company to have tons of data on hand and still struggle to achieve performance goals. Why? Because their data strategy fails to clear a path from A to B; employees struggle to get the data insights they need to make smart decisions, fast. It’s like throwing in a few detours and loop-the-loops into the path. Suddenly getting from A to B takes longer and involves a lot more hassle.
The value of data depends on an organization’s ability to turn it into actionable insights. This is why having data elites acting as gatekeepers is a problem. Keep reading to learn more about why companies are taking great strides to democratize their data.
Downsides of Data Elitism
Data elitism means gatekeepers stand between users and data. So, the average end user must go through an IT or data team to get reports and insights. Under this model, non-technical employees have little understanding or direct access to data tools—they must rely on specialists to query stored data, pull insights, compile reports and create charts.
The primary downside of this model is that it simply takes longer to get data insights into the hands of the people who will be factoring them into real decisions. Requesting a report and waiting for it to land on your desk or in your inbox can take days, weeks or months. But business tends to move much faster than that, meaning key opportunities slip through the cracks.
Another issue with using a gatekeeper model for data is that it often produces static reports. So, if the recipient of the report has follow-up questions, they have to repeat the entire process over again. It’s not necessarily easy to drill down into data to keep asking questions, which, again, means some opportunities go untapped.
Making Data More Accessible to All
Data democratization means giving data access to employees at every level. As one Forbes contributor notes, “It empowers individuals at all levels of ownership and responsibility to use the data in their decision making.”
Under this model, a marketer would no longer have to wait for a data scientist to crunch the numbers for them. Access to a front-end interface would allow them to ask questions directly and straightforwardly. Self-service data analytics tools like ThoughtSpot’s allow users to query data and create automatic data visualizations based on their findings in seconds—all without requiring a background in data science or IT.
Long story short: Freeing up employees form the need to work through data elites empowers them to pull their own insights on demand. It also allows users to dive deeper into data, asking as many follow-up questions as they need to understand a situation fully and make a subsequent decision.
Data democratization allows employees to proceed from point A to point B with no hurdles in between. And the bigger-picture benefit here is that the users of self-service analytics systems are able to make decisions beneficial for business. If your company still operates with data as the domain of elite, specialized employees, you’re missing out on opportunities to capitalize on your stored data.
Comment this news or article