While everyone wants to harness the power of data in their organizations, it can be very difficult to tell where to begin or what to do next. Every organization is at a different level of data and analytics maturity. Assessing where you are and what your next steps should be will help you leverage your organization's data for the smartest possible decision-making.
Let's start with a simple definition of data and analytics maturity. Basically, "maturity" describes how deeply and effectively your organization uses tools, people, processes and strategy to manage and analyze data for the purpose of informing business decisions.
So how do I know how "mature" my organization is? The best way to find out is by evaluating your own organization against the following facets of digital analytics maturity.
In an organization that is just starting out, you'll find that data projects are often run ad-hoc or in silos within a particular department or team. The most mature organizations will have well-defined (and well-communicated) roles and responsibilities, holding teams and people accountable across the full spectrum of activities required to collect, analyze, and use data to measure and act on business goals.
How clearly defined are your business objectives and the data points that will help you measure success or failure? Organizations on the lower end of the spectrum will sift through reports from time to time, trying to find something of value, while mature organizations define very clear business goals that are measured by structured Key Performance Indicators (KPIs).
How broadly are you using data and analytics throughout your organization? Are you providing monthly, high-level graphs to your CEO? Are you focusing on a specific single channel such as a Web site or mobile? Or have you reached the point where you’re looking at your whole digital ecosystem and leveraging analytics as an organizational source of competitive advantage?
Team and expertise
No matter how much you have spent on your tools, people need to use them. Teams in mature organizations include the technical implementation resources, experienced analysts and data architects, plus the business users who are empowered and experienced in data-driven decision-making methodologies.
Improvement process methodology
Here we’re referring to structured procedures for defining and solving problems. Many organizations rely on individuals to do this in their own ways and in a vacuum, while others have matured to include formal frameworks such as Agile or (Lean) Six Sigma across their teams and departments. Enabling team members to learn and use these frameworks ensures that continuous improvements are being made throughout the organization.
Tools, technology and data integration
Understanding where you stand with regard to these elements provides a starting point toward setting realistic goals that correspond to your current capabilities, as well as setting out a plan to reach ever-greater levels of maturity.
You will achieve success by ensuring that all of these aspects of data maturity are balanced. For example, many organizations find themselves heavily invested in tools, but have no resources to use them. Just imagine buying a Ferrari when no one in your household has a driver’s license! You’d be better off investing in a driver’s education course and an entry-level car than sitting in the driveway playing with the radio.
Once you have brought the facets of maturity into balance, the objective becomes growing your maturity evenly across each facet by planning and investing intelligently over time.
No matter where you fall on the range of data maturity, there's always room for slow and steady progress -- just be patient. It doesn't happen overnight, but you'll surely find that this framework is a powerful tool for getting you there.