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What is the business intelligence & analytics maturity model?

By Carol Jenner, Business Intelligence & Analytics Architect at Arbela Technologies

In the mid-2000's Wayne Erickson with The Data Warehouse Institute introduced the first maturity model to show how company's use their data as they mature, and where they get stuck. 

These models look at both the technology and the culture of the company. The lower a company is on the Complexity Scale means that they are not getting the most value from their data. There's proof that the higher you are or the further along you are in the BI Journey, the cost to handle your data and keep it relevant becomes lower.

Learn more about BI in this case study: How to Adopt an Agile Business Intelligence Strategy



Below is the Arbela Maturity Model:

BI and Analytics Overview Complexity

Arbela's Maturity Model is similar to the maturity model that Mr. Erickson introduced, with some notable exceptions. Technology has changed, so we updated the model based on our extensive experience working with customers. With Arbela Data Insights (ADI), we can get customers to Forecasting relatively quickly.

However, there's more than applying newer technology and pre-build solutions; there's also cultural and organizational issues that need assessment. We look at the following categories: Organization, Infrastructure, Data Management, Analytics, and Governance. Each of these categories has a set of criteria that we ensure Customers meet to make a successful transition. In upcoming webinars, we will discuss what that the criteria is and how to determine your company's level. The ultimate goal for a BI solution is for decision makers to trust the data and make accurate decisions.

Below is a high-level overview of what an Arbela Assessment looks like:

BI & Analytics Assessment

After a careful assessment, what happens next?

First, we Define and then Create, below are the steps for each phase:

Define and Create Business Intelligence Model

We all have questions, business or personal, and there's data all around us that can help answer them. The problem is we don’t always know what data to use, where to find it, and if it’s good data, so you are sure you can trust it's right.  Most organizations and people do not even use data, they use their “gut” and feel they are right, but statistically, they tend to be more wrong than they realize. 

In the Define phase, we look at the people, process, and technology. We look at Organization, Infrastructure, Data Management, Analytics, and Governance.  Those five categories are used during an assessment to determine a company's level of maturity, each with a set of criteria. For more information, tune into the Arbela webinar series or contact us.  

Technology is easy to solve, but culture is not.  Another issue is that, often, data does not come from one source but multiple sources.  In the define phase, we look at how the organization of data and suggest improvements that allow super-users greater access.  The goal of any architecture is to be flexible and scalable so that it can meet the business needs efficiently. Finally, often overlooked is Data Governance and Change Management processes. During an assessment, we spend a good deal of time looking at existing Governance and Change Management and assist in making improvements so instead of seeing Governance and Change Management as a negative, but a positive.