Analytics Maturity.  A common buzzword (or shall I say, buzz phrase) I am certain most individuals in the technology world have heard at one point or another. As in many phrases, acronyms, or buzzwords, we often wonder, what does this actually mean?   What is the Analytics Maturity Model? The term “Analytics Maturity” is one of the buzzwords that actually provides a great deal of value because it’s meaning can translate to every single organization.

Analytics Maturity is a model for assessing an organizations ability to effectively practice data exploration and decision-making using levels or stages. The Analytics Maturity model can be easily broken down into 5 simple segments by using this common graph chart, or “Analytics Maturity Curve”.

Analytics Maturity

Here is a breakdown of each level:

Descriptive – What Happened?

The beginning. Congratulations on starting your journey! The Descriptive Analytics phase asks the question “What Happened”, by performing operational reporting (which is often done manually and heavily Excel driven), data exploration, and benchmarking.  Most organizations are at this stage of development, or reactive within the analytics maturity model.  It is largely centered around reporting to lay the groundwork and develop a single source of truth.

Diagnostic – Why Did it Happen?

Very similar to the Descriptive Analytics but adding in a desire to answer the questions, “why did it happen, why is it happening”. It is taking data exploration a step further to analyze historical and past data to produce insights about the present. For example, some of the insights that organizations rely on are market segmentation, using social media to understand customer satisfaction issues, IT backlogs, etc.

Predictive – What Will Happen?

Predictive Analytics answers the question of, “What will happen?” by utilizing statistical analysis, predictive models, forecasting and scenario planning.   These analytics tools provide a better understanding of future scenarios and the implications to your business.

Prescriptive – What Should We Do About It?

We’ve already answered the what, why and what will happen. So now the next important question is, “What should we do about it?” Prescriptive Analytics takes Descriptive and Predictive a step further by improving the accuracy of our predictions and continually processing and automating new data, in turn fully optimizing decision making.

Cognitive – What Don’t I Know?

Cognitive Analytics is the highest level of automation. Involves machine learning and natural language processing.  It answers the question, “What insights don’t I know about yet?” Even though this is the top tier of analytics maturity, the practice of Cognitive Analytics can be used in the prior levels.  Jean Francois Puget says it best in an IBM blog post in which he states, “Cognitive computing is not another level of analytics, it rather extends the analytics journey to areas that were unreachable with more classical analytics techniques like business intelligence, statistics, and operations research.”


Here is the bottom line: with the overwhelming amount of data available today, organizations need analytics more than ever. Given these points, the Analytics Maturity Model is the easiest, most comprehensive way to track and determine the development of analytics within your organization. If you’re just starting out in the Descriptive phase, do not feel discouraged. In fact, give yourself a pat on the back! You’re practicing strategic, forward-thinking and doing your company an invaluable favor.  The insights and new information you’ll discover along the way, whether at the level of  Descriptive or Cognitive, will catapult your business in ways you hadn’t thought possible.