As companies increasingly invest in business intelligence and analytical tools, organisations are increasingly unable to derive critical benefits from them. In most cases, this results because of the inflection shift caused by the new oil, Data. Data has transformed how businesses look at their processes and operations. It has changed perspectives and introduced new sources of revenues, insights and competencies. With AI being on the rise, companies are digitally transforming their organisations at a scale never seen before.

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However in case of any change management, the most critical area to be handled are the people. In an effort to digitally transform, companies invest and develop new technologies that give them advanced analytics and intelligence. However, systems are only as good as their input. What good are insights if the people feeding in the data are not data driven or literate?

Organisations are struggling to create a data driven culture. Often this is because creating a data driven culture is left to the technology teams. CEOs still do not see the power of AI or data as a strategic competency or choose to let their CDOs run it. However, technology teams are limited in their insight as they often chase the trees while missing out on the forest. To create a data driven culture, employees must be re-educated as data literates. Data literacy is the single biggest problem that companies face in their digital transformations. So how can companies create or incept a data literate culture? We broadly list down seven steps to do so:

• Establish baseline adoption using current data: The first step to solving a problem is knowing where you stand. Before improving data literacy, we need to understand what the current adoption of technology is. Start by benchmarking and collecting usage metrics of your mission critical technology tools (Analytics, CRM, etc). This will help in creating a baseline that can be used as a referral point to measure change.
• Identify the bottom 10%: Through usage data, start identifying & segmenting the bottom 10% of your users. The groups with the lowest engagement are the ones that require the highest focus in improving data literacy. Groups with low analytics adoption will have the highest growth opportunity
• Assess data literacy: Start by conducting a survey or assessment of the bottom 10%. Understand their needs and requirements with relation to data. By mapping their needs, you would be in a better position to mould your data strategy and be more inclusive. Gartner, Qlik and many other data literacy firms provide services and resources to measure and gauge your firm’s data literacy.
• Identify your champions: Data champions are your biggest resource. They act as internal evangelists for various digital deployments and technologies. Identify the power users and skilled departments that can communicate meaning, purpose and value between your analytics and business teams. They will be paramount in helping you spread and execute data literacy campaigns.
• Create educational resources: Interview your data champions and record best practices, use cases and other tips & tricks. This will help in creating educational resources for your employees, especially the 10%.
• Launch an internal educational campaign: Using these resources, drive an educational campaign that seeks to impart the best practices and use cases from your data champions to the masses.
• Rinse & Repeat: Finally, measure the success of your campaigns through usage metrics and then continue to repeat steps 1–6 as you improve data literacy. Conduct another skills assessment to gauge improvements.

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This framework will help companies build a data driven culture that can further improve data literacy and provide maximum ROI on your existing BI/AI tools. As we move to a world driven by artificial intelligence and technology, a company without a data centric approach would be like walking blindly in the park expecting to find gold!