Comprehensive Analytic Maturity Assessment

Pam Roman

Companies that know how to leverage their analytic and IT resources gain a business analytic-enabled competitive advantage (Porter, 1980; Sambamurthy, 2000), which is the basis of our research. For the purpose of this guide, the term analytics represents a comprehensive view that encompasses the 5 analytic areas listed below and related topics.

The challenge, when creating an analytic-enabled business strategy, is to identify which activities to focus on. To that end, our research identifies factors of analytic-centric initiatives that significantly contribute to the overall maturity and success of a program (Gonzales, 2012). Building on this research, coupled with extensive practical application of maturity assessments for leading companies our Comprehensive Analytic Maturity Assessment (CAMA) creates an index that measures the analytic-enabled competitive maturity of an organization.

The Value of a Repeatable Analytic Maturity Assessment

While it’s important that companies invest in an unbiased measurement of their analytic maturity, it is only a fraction of the value. One key success factor is the ability to periodically conduct the same assessment to measure and monitor the progress of your analytic program(s). If you can demonstrate significant maturity increases, the results will support your argument for additional budget and resources.

Conducting the same assessment periodically means that you must retain the instruments used and methodology applied. Some assessment services will simply not comply.

Dr. Michael Gonzales, Chief Data Scientist with Prolifics, doesn’t recommend that you invest in any assessment that contains black-box processes. “Frankly, if you do not have an assessment that provides visibility to all aspects of how the maturity level is derived, then it’s not worth the price,” Gonzales explains. “Real value from these initiatives is derived when you can internalize the assessment instruments and processes to enable your organization to periodically conduct the assessment.”

The following video describes 4 of the instruments this author recommends.

Five Analytic Areas for CAMA

  • Data Science (DS) – an inter-disciplinary field to unify statistics, machine learning, deep learning, big data, and data analysis.
  • Machine Learning (ML) – the application of computer algorithms that improve automatically through experience. A sub-set of Artificial Intelligence.
  • Business Intelligence (BI) – techniques and technologies used for data analysis of business information including the provision of historical and current views of operations.
  • Big Data – a field focused on the analysis of data sets too large or complex to be dealt with by traditional data processing.
  • Spatial Analysis – the application of statistical analysis and related techniques to data with a geographical dimension.

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