International Institute for Analytics

Inquiry:

We’re working on our career development and career paths for our data science and analytics team. We have forty people, and we’re growing. Our concerns include low attrition and the fact that not everyone wants to be a manager.

Inquiry:

We’re implementing a data governance program to support our larger analytics capabilities. What are some of the first steps to start building a data governance strategy? What “gotchas” should we keep an eye out for along the way?

When it comes to cutting-edge analytics initiatives, you’re probably more inclined to think of companies like Amazon and Netflix, which have become synonymous with the savvy use of analytics to gauge customer affinity and deliver recommendations. But pharma companies are—or could be—well equipped to leverage data and analytics to deliver an even better informed and better targeted customer experience.

Inquiry:

We have a mature analytics organization with over a thousand models in production. At this point we know we need a more rigorous governance model than we currently have. Can we speak with someone who can help us think this through?

Inquiry:

We have a hub-and-spoke analytics model with analysts in different divisions. My team is tasked with increasing the maturity/value of the analytics being used across the Enterprise. How can we market ourselves so the analysts across the enterprise understand the full breadth of what our team can do?

This five-part research brief is designed to assist analytics leaders in taking stock of their analytics measurement programs, recognizing and filling any significant gaps, and raising their ability to communicate with the business and its leadership about analytics. This brief provides background and summarizes results and recommendations across the four measurement categories. A separate brief on each category details its findings. In this research, we surveyed 19 enterprises and asked, in each of the four categories, what metrics they use, what they’re good at and what they struggle with, and whether their measures incorporate five common methods or inputs: trends over time, internal customer views, external customer views, external benchmarks, and lessons learned.

Inquiry:

We are interested in discussing what specific use cases and responsibilities should be assigned to central analytics function and what use cases are better allocated to decentralized business units.

Another consideration would include analytic employee engagement – variety of work, career pathing, shared expertise, training/development, retention, and connection of decentralized resources. 

Inquiry:

We are becoming more data-centric at an organizational level, but do not have a governance process in place. In our highly regulated industry, how might we approach this? What should we be thinking about?

Inquiry:

Now that we have our EDW technology in place, my group’s challenge is developing analytics talent across the enterprise. How can we do this in a way that gets us to where we need to be without increasing resistance from the business?

One of the continual challenges for analytics leaders is measuring the work of their analytics groups and communicating the results to business leaders. Sound measurement and transparency form the foundation for strong working relationships, adequate funding of analytics, and trust in the analytics organization. In this phone briefing, IIA Lead Faculty Member, Bob Morison shares highlights of recent research and discuss best practices in the four key domains of analytics measurement: Intent, Performance, Results, and Health.