3 Things Employees Need to Make Data-Driven Decisions

Skill Development

Many companies roll out a new business intelligence strategy with high hopes, only to experience underwhelming employee adoption rates and a low return on investment. This situation understandably leaves leaders scratching their heads wondering, “What happened?”

To put it simply: Becoming a data-driven organization requires more than simply deploying new business intelligence (BI) software or ordering employees to turn to data more often in their daily decision making.

Here are three things employees need to make data-driven decisions to fuel positive business outcomes.

Data-Driven Company Culture

Employee decisions don’t exist in a vacuum. Rather, employees’ attitudes about data and their willingness to embrace it into their workflows are very much shaped by the overall company culture.

Here are a few key cultural factors capable of affecting how employees treat data:

  • How leaders use data, talk about data and encourage others to do so
  • The expectations surrounding data usage
  • The degree to which employee decisions are taken seriously, implemented and rewarded

It’s counterintuitive to expect employees to embrace data and incorporate it into regular decision making if leaders seem to be making little effort to do so publicly. Similarly, if an employee sees a colleague stick their neck out to make a suggestion based on data and it’s received lukewarmly or ignored by the rest of the team, they may feel deterred from doing so in the future — and justifiably so. As CIO writes, “Data without decisions is like burying your money in the ground.”

Data-driven culture starts with setting clear expectations, leading by example from the top down and demonstrating to employees their data efforts tangibly affect decision-making and performance.

Accessible Business Intelligence Tools

Employees will also need access to user friendly business intelligence tools to optimize decision-making. Today platforms like ThoughtSpot offer search-driven data analytics tools — allowing employees to ask specific questions and explore queries— plus artificial intelligence-driven analytics to automatically uncover hidden insights lurking within data.

This multi-pronged approach gives employees ad hoc answers to all the questions they have in seconds without requiring them to wait for a report. It also helps alert users to patterns and anomalies that could otherwise hide within billions of rows of data forever, just waiting for someone to notice it.

Modern BI tools offer a few key advantages over their legacy counterparts, including the ability to embed BI throughout existing applications and workflows. Todays’ tools also emphasize user friendliness for non-technical users, which means everyone can access insights without needing in-depth training or constant oversight from IT professionals.

Data Literacy Training

BI tools themselves may be accessible to all, but employees can still benefit from having deeper context for data insights they find. This means companies should invest in data literacy training to provide the foundation for interpreting and analyzing data.

Here’s an example of data literacy in action from Transforming Data with Intelligence: Airbnb found it was not feasible to have a data scientist always present to inform every decision, especially with more than 20 international offices. So, the company launched Data University to provide education to engineers, product managers, designers and everyone else — including how to analyze and visualize data, then incorporate findings into decision making. The result? Employees learned how to handle ad hoc data requests without turning to data specialists, and engagement on its data platform doubled within a year.

Employees need data literacy training, the right BI tools and a data-driven culture to fully incorporate data insights into decision making.