Data Analytics Maturity Model- Stages

An analytics maturity model is a sequential series of stages that shows the company’s evolution in managing internal and external data and use it for analytics and drive informed and insightful decision making. The model gauges the company’s ability to use their resources optimally and drive the best value of data. 

Of the various data analytics maturity models, Gartner’s maturity model for data and analytics is the most common. Gartner’s model can help in knowing the existent state of the IT infrastructure of the company and create a roadmap for efficient data handling and high analytical maturity of the organization. 

                       Stages of Gartner’s Data Analytics Maturity Model 

  1. Descriptive Analytics– Descriptive Analytics helps in collecting and visualizing the historical data. This data is obtained in various formats and from various sources like spreadsheet, CRM, reporting tools and so on. The tools allow visualization of data along with describing it. This data is parsed to understand the changes that have occurred in businesses. It gives a picture of what has happened in the business and how the performance differed in various comparable periods. Descriptive analytics can variably answer what happened. 
  1. Diagnostic Analytics– Diagnostic Analytics drills down into the why of the business. It includes tools and facilities like data warehouses, data mining techniques, data management platforms and so on. Diagnostic analytics allows visualization and reporting and in-depth analysis of relationships between data variables, identifying patterns in trends and reasoning out why the business trend is of specific manner. This is the stage when organizations start valuing analytics and use technologies for interpretation of data accurately 

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  1. Predictive Analytics- In this, advanced analytical tools are used for forecasting future outcomes. Large volumes of historical and existent data are used for creating data models, simulations for futuristic inference and others. It basically enables knowing what will happen in future. 
  1. Prescriptive Analytics- It is the highest level of analytics that prescribes decisions and the best course of action for business based on predictive models, analyzing huge volumes of historical and current data and data from past actions taken by the organization. 

 

Sales were up this quarter 

Sales were up because niche markets were tapped 

Next quarter the sales will probably go up by 40% 

Best way to ensure 40% growth in sales is by focusing more on customers in niche market as they are to grow at x% 

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