10 steps to success as a data-driven organization

Looking through job titles on LinkedIn, I couldn’t help but notice an unfortunate reality when it comes to data roles in the business world: it’s a mess. Companies are putting a lot of effort into collecting and analyzing data, yet there’s so much ambiguity regarding responsibilities between different departments, that it’s going to have an influence on business insights.

There are a number of reasons for this, from internal politics to a lack of knowledge how an organization should structure itself in terms of data functions.

Over the years, I’ve worked with dozens of companies. I’d like to suggest a few strategies to optimize structure and tackle issues which arise from duplication of roles and functions, and insufficient efforts by various departments, to help your enterprise get back on track and be more data-driven.

Here are 10 strategies to make any company a more successful data-driven decision-based organization.

1. It starts at the top. The CEO must appreciate that data is a basic element in the success of a company, and that the ability to quickly and accurately analyze data for business insights is of critical importance to maintain a competitive edge. Otherwise, there will be problems across every department. It’s as simple as that.

2. The CDO (Chief Data Officer) is the most critical and powerful role in the data organization. The CDO must be a strong C level position who should take part in all of the data-related responsibilities. That doesn’t mean that a specific department can’t analyze on its own; but it does mean that data management and analysis is strategic, and requires an effective leader who reports directly to the CEO.

3. If the customer is fundamental, then the data department must be recognized as a service-oriented department, beyond simply a technical role. The most successful companies I’ve worked with were the ones that saw data analysts as providing the services and mechanisms that enabled BI (Business Intelligence) tools, including data monitoring and analysis tools. “Although digital business thrives on data and its analysis, we still see that data and analytics only play a supportive role when it comes to business initiatives,” says Mike Rollings, research vice president at Gartner. This has to change.”

4. The data department also cannot function as a “dictator.” It’s a common mistake to believe that everything regarding data should stay inside one department. But, it doesn’t work. Not all the data tools in an organization need be managed by the data department, either. That may sound counterintuitive, but if a tool like Google Analytics serves only the marketing department it makes sense that the employees there will purchase, maintain, and use the tool for their own needs, and won’t involve the data department.

5. Data Analyst? Business Intelligence? There’s a lot of confusion in the market regarding job titles and functions. This creates an untenable challenge for HR companies and departments trying to find the right people for essential positions. Are you looking for a BI or a Data Analyst? The first step is to understand the various responsibilities. I see BI as just one part of the equation.