Part 2: The Ultimate Goal Is Analytic Maturity

Focus on growing your organization’s analytics maturity to begin to see business value, organizational impact and return on investment from your analytic systems. 

In the midst of the challenges that face the technology departments, business users and company leaders, where should an organization start when they try to move towards thriving with data rather than drowning in it?

Focus on maturing your organization’s analytic systems, processes and people to begin to see business value, organizational impact and return on investment.

Successful companies have a mature application and adoption of analytics that allows them to organize their data and then leverage that information to create actionable insights. 

So how do you measure your maturity level? Use a maturity model to evaluate yourself. 

Maturity Models In The Industry

You can find a variety of maturity models online that provide criteria and benchmarks for different levels of analytic maturity. For example, the Gartner model evaluates the implementation and organizational competence of business intelligence solutions within the company.

However, the focus of some of the models revolves more around the tool without taking into account the analytic maturity level of the organization's people and processes. The models don't always evaluate how well the people, processes and tools are woven into the fabric of that company. An organization may be listed as mature on various models because their BI system is implemented and established, yet their people are analyzing and reporting using elementary techniques and siloed data that show limited insights rather than the full picture of business impact. 

This is why we take a different approach to our maturity model. 

Analytics8’s Maturity Model

Analytics8’s maturity model looks at the focus and intention of analytic endeavors and the how well data is collected, organized and shared. 

This model goes beyond implementation success and evaluates if an organization is actually equipped to make data-driven decisions and act on them. The model evaluates the type of integration of analytic people and processes throughout the organization. It also evaluates the level of key performance indicators and the type of analysis used to empower data-driven decisions and actions. 

As a company moves up the maturity model, they are better equipped to mitigate business risk and improve the value of business processes. As they get to higher levels, they’re not just responding to fires – they’re anticipating fires and putting solutions in place before they happen. Some ways a company may move up the model and grow in maturity include:

  • Move away from manual consolidation and integration and towards automated systems.
  • Move away from departmental silos and towards enterprise systems.
  • Move away from ad hoc reporting and towards predictive analyzing.
  • Move away from lagging indicators and towards leading indicators.

See the model

It's important to note that being analytically mature is not a final destination that you arrive at by completing an implementation. 

Growing in analytics maturity is a continual and evolving journey of improving various factors throughout the entire organization, not just within your business intelligence software.

 

Do you know which factors are contributing to your company's overall analytics maturity level?

Continue reading in the series:

Missed the first part of the series? 

Part 1: The Potential, Problem and Pressures With Data

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