“A goal is a dream with a deadline,” said American author Napoleon Hill. I heard executives in the financial services industry share many dreams and wishes that would make analytics successful in their organization last week during a Power Session at the SAS Financial Services Executive Summit. As explained in a recent post, these sessions provide a format for participants to gather into groups and discuss real business problems and share experiences with their peers.
To kick off the fun, the executives were asked to write down their top three wishes individually. Then they moved into groups divided by business area (marketing, CIO, finance) to come up with the top three wishes among the group. After that, everyone moved from their respective business units to another white board where they found peers who had moved from other business units. Now the group comprised of a figurative C-suite of an organization and needed to identify the top two wishes for improving outcomes from analytics across the enterprise. Lots of creative concepts came out of this activity, and many of them overlapped with each other. Here were the main categories of wishes:
Acquire, retain and develop analytical talent – Educate existing and develop new talent. Create a “culture of learning.” There are different kinds of talent to consider: analytics (skill), business (SME) and discipline. You need cross-functional talent where analytics representatives have roles in areas outside of analytics groups.
Support for analytical culture – Infiltrate the company with analytics. You need both evangelists (from the ground up) and senior-level executive sponsorship (top down) to make it work.
Data management strategy, also heard this called and “agile delivery model” – This comprises complete data and clean data access, budget flexibility and relevancy (what is really needed?), technology and business partnerships, and accurate and timely data.
Also data must have integrity, be supported by sound operational platforms and data architecture/infrastructure that supports the dynamic needs of analytics. One example a participant gave was when the analytics group “black-marked” a piece of a project that came from IT. The IT group was resistance to look into because it implied that they did something wrong on their end. Sound familiar?
A SAS participant echoed the analytics/IT gridlock saying that she is in meetings all the time with analytics and IT and the lack of care for what the other department is interested in is very apparent. IT doesn’t understand the analytics lifecycle at all. And this constant disagreement is the single biggest inhibitor to successful analytics projects.
Center of Excellence – Stands as the mecca for guiding principles of analytics, data governance (including getting the roles and responsibilities right) and quality. To do this well, the organization needs to have “a culture where data is viewed as an asset.”
The summary of wishes and lengthy discussion at the end of the session were full of varying views on what is actually happening at participants’ organizations. For example, they talked about how one can get into a political untenable situation if the analytics recommendation contrasts with what the CEO and his/her friends want to do. The CEO will move forward his/her way and it’s quite discouraging when the outcome isn’t as positive as it would have been with the data-driven decision. Has this happened to you?
Using your data – ALL of it – also came up. “How do you find a needle in a haystack if you don’t have the haystack? Just a piece of the data won’t cut it,” one executive said. “Authorization is at the pump and fraud detection needs to be in real-time, with all the data we can get our hands on,” he continued.
The group talked about the importance for business decision makers to have analytics acumen. “They need to really get it, and it’s so much better if they’ve actually done analytics,” said a participant.
Another executive said that he rotates senior business people around to different departments for them to see analytics at work. In one case, a product manager performed a project with analytics and another did the same project without analytics. Of course the one who used analytics was more successful. The result? The senior business person had the opportunity to see firsthand the benefits of analytics, and the product manager who didn’t use analytics was enlightened.
The same executive shared how he trains on analytics. A dedicated trainer takes a cart around the building to hand out analytics materials and holds classes to give everyone a feel for the fact-based approach. After familiarizing themselves with analytics, business groups ask themselves, “Now how can I implement changes?” … and there you have your analytics support.
Find out more ways executives have developed an effective culture and infrastructure by reading the white paper, Making Business Analytics Work. And let’s keep this session going online. Share your business analytics wishes with this community by commenting below.