As much as leaders within enterprises today repeatedly profess their aim to become data-driven — especially because their competitors are certainly working toward the same goal — many find their organizations are falling short. It turns out making the shift to pervasive data-driven decision making is easier said than done.
It helps to think of the march toward becoming a data-driven organization as a series of interlocking steps, rather than an initiative to be rolled out all at once. It’s an endeavor that requires strategy, buy-in from the right stakeholders, persistence, tools and culture.
Here are four steps organizations can take to become increasingly data-driven over time.
Evangelize Data from the Top
Even the best-intentioned data efforts will flounder if company culture does not support them. One aspect of forging this important cultural shift is evangelizing data from the top. Creating a C-suite role like Chief Data Officer (CDO) is a smart move — as ZDNet reports, 44 percent of orgs with a full-time or acting CDO have a “clear and pervasive” digital strategy, compared to just 21 percent of orgs without this role.
At the very least, all executives and managers need to be using data, talking about it openly and tying it to business goals. Employees tend to respond based on the attitudes surrounding data they notice from leaders. Making sure the championing of data starts high and trickles down is crucial. Take every opportunity to praise data and show exactly how leaders are using it to make their own decisions.
Prioritize Data Accessibility & Ease of Use
Data accessibility and user-friendliness can make or break the endeavor to become a data leader. An employee who can conduct their own ad hoc analysis is one equipped to ask questions, drill down into data insights and incorporate their findings into routine decisions.
The latest wave of analytics platforms facilitates self-service search and AI analytics to connect even non-technical users directly to key insights in seconds. Compare this to the challenges associated with legacy systems — namely heavily siloed data gatekept by data administrators — and you can see why data accessibility is key to bringing data to the forefront of strategy.
Foster a Communal Language & Version of Truth
It’s going to be difficult, if not impossible, to get employees to embrace data if it feels like every team and department is on a different page.
As Harvard Business Review notes, different “data tribes” can spring up, each with their own trusted sources and metrics. Allowing multiple versions of the truth to coexist breeds distrust and confusion, which is where a business intelligence architecture supporting source transparency and a single version of the truth is imperative.
Thus, standardizing data usage and language is a key to opening lines of communication and inspiring collaboration among its users.
Address Gaps in Data Literacy & Competency
Research firm Gartner predicted 80 percent of companies would be purposefully developing competency in regards to data literacy by 2020. In particular, this step includes identifying and addressing skills gaps.
Data literacy training helps non-technical business users get comfortable with the analytics tools at their disposal, take full advantage of their features, confidently analyze data and speak a companywide “language of data.”
Instead of treating training like a one-size-fits-all, one-time event, consider the benefits of ongoing training tailored to job roles. This will help users retain what they’ve learned and forge their own job-specific connection to data, rather than writing it off as something that barely concerns them — or disengaging as a result of feeling overwhelmed.
If becoming data driven is a staircase, then the steps to reach the top cover accessibility, culture, competency and trustworthiness — among others.