What do a doctor suggesting a patient diet, an IT person asking a fellow worker to start using a new application, a mom asking a child to eat something or an analytics expert asking a business person to trust statistical insights all have in common? They are trying to get other people to do things.
But as the old saying goes, too often, this suggestion comes across as “do as I say, not as I do.” We’ve heard other variations on this theme, such as “doctor, heal thyself” or my favorite, “eat your own cooking”.
When I was a CIO, I used to tease some of the staff by pointing out they were all too willing to tell everyone else that they should use some new technology to do their jobs, but when it came to new technology in the IT world, the IT staff was the most resistant to change.
Among the most important changes that need to happen in many organizations today are those based on new insights about the business from analytics. But in big organizations, it is difficult to know how well those necessary changes are being adopted.
Analytics can help with this problem too. Analytics tools can help to figure out what message about a change is getting across and how well is the change being adopted? In which offices, regions, kinds of people?
Yet, it is rare for analytics folks to use their tools to help guide their own success in getting analytics to be adopted. Here, though, are two examples, the first about individuals and the second about organizations as a whole.
Individual Willingness To Change
A couple of years ago, the Netherlands branch of Deloitte created a Change Adoption Profiler (CAP) model of their clients’ employees based on the willingness to adopt changes. As they describe it:
“Imagine being able to predict who will adopt change, and how they will adopt it before the change has even occurred. At Deloitte, we have developed a data driven decision making method called the Change Adoption Profiler – it provides insights into your company’s attitude toward change and allows you to address it head on.
“The CAP uses a diagnostic survey based on personal characteristic and change attitudes. Unlike traditional questionnaires CAP combines this with behavioral data to understand the profiles that exist within the organization. The CAP provides reliable, fact-based analytics – provides client insights that support smart decision making, reveals risks and signals how to approach change at an early stage.”
There is a nice little video that summarizes its work at https://www.youtube.com/watch?v=l12MQFCLoOs
Sadly, so far as I can tell from the public web, no other office of Deloitte is using this model in its work.
Organizational Analysis
Network analysis, especially social network analysis, is not a new focus of those in analytics. But, again, they don’t normally use network analysis to understand how well changes are being spread through an organization or business ecosystem.
One of the exceptions is the Danish change management consulting firm, Innovisor. They put particular emphasis on understanding the real organization – how and why people interact with each other – instead of relying solely or mostly on the official organization chart.
This little video explains their perspective – https://www.youtube.com/watch?v=ncXcvuSwXFM
In his blog post, Henry Ward, CEO of eShares, writes at some length about his company’s use of this network analysis to determine who were the real influencers in the organization. They ended up identifying 9 employees, not necessarily executives, who influenced 70% of all employees directly and 100% through a second connection. A detailed presentation can be found at https://esharesinc.box.com/shared/static/8rrdq4diy3kkbsyxq730ry8sdhfnep60.pdf
Given the value of these kinds of examples, the problem of not eating your own lunch is especially interesting in the analytics field. Perhaps it is new enough that many of its advocates still have the zeal of being part of an early, growing religion and can’t see why others might resist their insights. But they would be convincing if they could show how, with analytics, they did their own jobs better – the job of getting their organizations to achieve the potential of their insights.