6 Steps To Determine Your Data And Analytics Maturity

You've got buy-in from your CEO about how important it is to have a Big Data strategy, your IT department says you've been collecting plenty of data, and perhaps you've even started looking for the people, tools and technologies necessary to analyze it.Now what?

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

Technology is a critical foundation to data collection and analysis. Whether you have just started with Javascript tags on your Web pages or you’ve integrated your back end business data, customer data, on and offline advertising data and more, getting this right is essential. At the higher levels of maturity, the tech is what will enable intelligent reporting, useful visualizations, statistical modeling and even predictive analytics.

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.

1 comment about "6 Steps To Determine Your Data And Analytics Maturity".
Check to receive email when comments are posted.
  1. H M from LexisNexis, September 18, 2013 at 11:18 a.m.

    Nice perspective on Big Data David. With the explosion of big data, companies are faced with data challenges in three different areas. First, you know the type of results you want from your data but it’s computationally difficult to obtain. Second, you know the questions to ask but struggle with the answers and need to do data mining to help find those answers. And third is in the area of data exploration where you need to reveal the unknowns and look through the data for patterns and hidden relationships. The open source HPCC Systems big data processing platform can help companies with these challenges by deriving insights from massive data sets quick and simple. Designed by data scientists, it is a complete integrated solution from data ingestion and data processing to data delivery. Their built-in Machine Learning Library and Matrix processing algorithms can assist with business intelligence and predictive analytics. More at

Next story loading loading..