Building An Analytic Enterprise: Three Things

Everyone it seems wants to be an analytic enterprise. But what does it mean to be an analytic enterprise? Well:

• An analytic enterprise applies analytics deeply and broadly.
• It uses analytics to solve its most critical run-the-business problems.
• It uses increasingly advanced and analytics to maximize its ability to get value from its data.
• And it uses analytics everywhere – from customer treatment to operations, from marketing to administration, and from people management to asset management.
• An analytic enterprise informs its strategy with analytics, empowers its people with analytics, and drives its systems with analytics.

In particular, it drives decision-making with analytics, not just reporting or monitoring.

Some years ago we did some research on the landscape of analytics capabilities. We found that enterprises adopt analytic capabilities in a variety of sequences and ultimately need a mix of them. While there seem to be as many reasons for adopting analytic capabilities as there are organizations adopting analytics, the reality is that three key business needs are driving analytic adoption – reporting, monitoring and deciding.

Most organizations need to report on some aspect of their operations, present some data in a report to some internal or external body. Most organizations want to monitor their behavior or performance, generally identifying and tracking some metrics or key performance indicators (KPIs). And organizations increasingly see value in making data-driven or analytic decisions. This need can be explicit, identified at the very beginning as the rationale for an analytic capability. It can also be implicit, as organizations that think they need reporting or monitoring realize that it is acting on the reports and monitoring dashboards that is critical to success. It is this use of analytics - driving decision-making with analytics - that makes an enterprise an analytic enterprise.

Working with companies that are investing in becoming analytic enterprises, we have determined that there are three critical success factors. Whether you are focused on business analytics, data mining, predictive analytics, machine learning, artificial intelligence, or all of the above, these factors will be critical:

Analytic Enterprises Put Business Decisions First

The first critical success factor for analytic enterprises is keeping the focus on business results by beginning (and ending) with business decisions, not analytic technology.  Many analytic projects are technology-led. Some start by focusing on the algorithms or tools a team is familiar with. Others start with the data the team happens to have available, because data access is siloed and difficult. Success projects focus on the decision-making to be improved.

Analytic Enterprises Predict, Prescribe, and Decide

The second critical success factor for becoming an analytic enterprise is moving beyond reporting and analysis of the past to prediction and action by using more advanced analytics to predict, prescribe, and decide. Descriptive and diagnostic analytics might be valuable, but the critical need of an analytic enterprise is for predictive and prescriptive analytics.

Analytic Enterprises Learn, Adapt and Improve

The third critical success factor for becoming an analytic enterprise is recognizing that applying analytics is not a one-time exercise, and focusing on how to use analytics to learn, adapt, and continuously improve. "Big wins" and immediate changes to strategic direction are less likely to create an analytic enterprise than a focus on continuous improvement.

I hope you enjoyed these three videos. And if you do, check out our white paper on building an Analytic Enterprise: decisionmanagementsolutions.com/analytic-enterprise/

And, as always, drop me a line if you would like to chat about how to make your enterprise an analytic enterprise!