(ThyBlackMan.com) Ever heard the phrase, “You can lead a horse to water, but you can’t make it drink?” Well, you can deploy data analytics tools, but you can’t always make people use them. However, organizations can optimize conditions, so employees have everything they need to incorporate data analytics tools into their routine workflows and are incentivized to do so.
Research firm Gartner questioned why business intelligence (BI) and data analytics adoption rates remained so low at around 30 percent of employees in 2017 — noting “pervasive BI remains elusive.” In other words, boosting data analytics adoption rates has been an ongoing challenge for organizations, even as tools keep advancing.
Here are five tips for doing so.
Make It Easy to Dig for Data Insights
The first hurdle your enterprise will need to overcome is ease of use. How simple is it for your average employee to pull data insights or find the answer to a question they have? Hint: The longer, more confusing and more convoluted the process, the more adoption rates are going to suffer.
This is precisely why the latest wave of self-service search analytics has been built on a familiar paradigm — querying data is akin to typing in a question on a search engine, or speaking it aloud to a virtual assistant. People are already familiar with asking questions this way, which smooths out the transition to using search-driven data analytics tools like ThoughtSpot.
Help Employees Uncover Insights Without Needing to Ask
Some data insights are the result of an employee asking a specific question or creating a particular chart using search analytics. But what about the answers to questions nobody’s had a chance to ask yet? Instead of waiting for an analyst to manually uncover these insights, artificial intelligence (AI) analytics platforms empower employees to find hidden insights with a click.
In other words, it’s a lot less daunting to approach data when it’s not contingent on knowing exactly what you want to ask. When insight-detection algorithms can do the heavy lifting, employees are able to focus on the quality and relevancy of the insights uncovered by AI analytics — then offer simple feedback to refine the system for future use.
Part of increasing adoption is facilitating different use cases — helping employees uncover insights, whether they have a question in mind or just want to investigate possibly useful patterns that might be submerged in stored data.
Embed Data Analytics Where People Spend Time
Embedding data analytics where people already spend time, rather than into a new workflow, is a good way to incentivize people to interact with these tools and share their findings with others. Look for solutions that are embeddable into existing portals and applications to maximize convenience in this regard.
Incorporate Data into Company Culture
Your business has BI tools. But does it have a data-driven culture surrounding those tools.
According to TechCrunch, these five building blocks contribute to a data-driven company culture.
- Single, centralized source of truth
- Glossary of data terminology and metrics
- Widespread employee data access
- Data literacy and training
- Data-driven decision making
While your data analytics platform will provide the actual interface between employees and data insights, the surrounding culture will influence how people approach data and how much they factor it into business decisions.
Make Sure Leaders Are Adopting Data Analytics
Employees look to leaders for cues on how to act. This is why executives and team managers are key to driving BI adoption. As CIO writes, “Top-down support from organizational leaders to challenge the status quo, and push for business process transformation, is mandatory for success.”
If employees see leaders integrating analytics into their presentations and decision-making processes, they’re more likely to follow suit. If employees feel leaders are parroting the company line without really embracing analytics, this attitude could seriously sabotage adoption efforts.
The better BI and analytics adoption rate your company experiences, the better its chances of driving desirable business outcomes based on data.
Staff Writer; Calvin Ford