The evolution of technology and all things digital has dropped more information than ever about human needs, preferences, and day-to-day behaviors right into the laps of today’s businesses. That data creates a great opportunity to meet people’s needs and position companies for long-term success with data-driven decision-making.

But that’s much easier said than done. 

For most organizations, capturing, organizing, synthesizing, accessing, understanding, and acting on the enormous amount of information available is not second nature. To seize on this critical opportunity, companies will require a shift in culture – and, unfortunately, many learn this the hard way.  

Only after they have invested millions of dollars in technology and recruitment of top data talent, most companies find their teams are not equipped to maintain data quality or use that data to generate the all-important insights hidden within it. And they are certainly not well-equipped to understand those insights and rally their teams to act swiftly enough to take meaningful action.

A Data-Driven Decision-Making Culture Shift 

To build a data-driven decision-making culture, organizations can benefit from some solid up-front actions: 

1. Create a data strategy with a clear vision and measurable objectives. Why are you investing in building data capabilities for your organization and what products, governance, and processes are you investing in? What’s the intended outcome for the customer/consumer? For the team/employees? The business/shareholder? Be confident about how you’ll measure adoption and what your baseline is at the start. 

• Establish user-friendly governance and processes. What guidelines will you put into place regarding data and how to use it? Who will be responsible for collecting it, maintaining it, organizing it, synthesizing it, accessing it, understanding it? Clarify the role of your global/enterprise teams vs. your local teams. Clarify the role of the commercial, marketing, or data/insights teams vs. the role of your technology teams. So often data ends up being an “IT problem” just because IT teams lead the charge to implement data products. But data/insights teams and other parts of the organization must be jointly accountable for the maintenance and use of data in the organization. 

• Immerse your teams in use cases for the new data and technology products. Only after you’ve grounded them in the clear vision and process changes (steps 1 and 2, above) is it time to show how the technology and data systems fit into their lives. Begin with strong use cases and a “day in the life” tech view for each user group. Build your training/roll-out around that. 

• Build a talent/learning plan around data. Start by identifying the key skills and capabilities your teams will need before they begin using and acting on data. Create a talent strategy to hire for and/or develop those skills. Invest in “retooling” the teams’ data skill sets to adapt to this shift – from recruiting to learning to mentoring to managing. 

• Make it simple, human. Share stories that inspire your teams with the possibilities for their customers, stakeholders, and themselves. Use crisp and compelling communications about what the future will look like. Use plain language that syncs with your business/industry lexicon – and don’t get caught up in geek-speak. 

If you focus on these steps, you will achieve the return on your investment faster and have a true impact on your business. Skipping the hard work of changing your culture to complement the transformational phenomenon that data has created is, truly, at your own peril.