My most common discussion around super user metrics for the past few years has seemed to revolve around what is the correct level of coverage – aka how many super users are enough? This is an important question, but it doesn’t get to the heart of the key challenges faced when attempting to create and operate a successful super user program. Coverage alone doesn’t address core issues such as program sponsorship, super user selection or program performance. The following are some key metrics that we have gleaned from analyzing the performance of super user programs over the past 2 years. You might say these are numbers to live by.
Not all users are equal. Some spend way more time in an application and consume significantly more functionality. These same users do most of the heavy lifting for your organization. They are called Power Users. You don’t expect all users to be Power Users, roles are different and segregation of duties must be maintained. But what you wouldn’t expect is that Power Users that were once upon a time a powerful asset have become a significant business risk for your organizations. In short, we have expected too much from too few and the cost of this overburden has come home to roost as organizational drag.
Yesterday I was reading a Reuters article describing the 3rd consecutive quarter of declining labor productivity. The article lamented how this is a multi-year trend and a big problem for growth. The article goes on to conclude that this decline has occurred largely because businesses have been reluctant to make capital investments – specifically citing IT. This assertion is just flat out WRONG. It is not only WRONG, it really makes my blood boil.
Most enterprise software buyers are flying blind when it comes to adoption of their enterprise applications. That is a shame as so many technology investment decisions are then made (or not made) based upon politics and squeaky wheels. In the course of discussing how organizations can move to a more data-driven management approach, I am I am often asked, what passes for good user adoption analytics? What data is necessary? Is there a specific dashboard that you recommend?
As the interest in end-user adoption analytics continues to grow, I have repeatedly been asked which data streams should be analyzed to improve user performance. Or put another way, most organizations have so much data today, which data streams are better for improving user efficiency and consumption. Obviously the usage stream of end-users is critical, but most organizations today do not have an accurate and reliable source of this data.
Very few organizations have constant monitoring of their user performance so it is difficult to appreciate the value of collecting a complete usage history over time. To oversimplify, the key benefits of accumulating usage data fall into two buckets.
We have recently returned from our annual trip to SAP Insight’s Super User conference in Texas. In addition to very good BBQ, we had more cause to celebrate as two of our customers, McKesson and City of Edmonton, both won best in class awards for their change management/super user programs. We were lucky enough to capture some of their presentations on video.
Even the best organizations don't always get the new model going for all their processes. In the picture above we have the User Productivity change of processes managed under two different support models at one of our clients. The processes managed under the old model have declined -1.9% over the past 12 months, the processes managed under the new model have improved 2.7%.
After 10+ years of selling their “User Error” approach for SAP education service providers - Knoa still has very few meaningful success stories. This is not for a lack of trying. There have been many attempts to deploy and support user education programs. The real problem is that the Knoa “user error” approach is inherently flawed. While focusing on user errors sounds logical, the errors need to actually impact user productivity and /or business results in a negative manner for subsequent education services to be worthwhile.
We had big hopes going into this year’s Sapphire event for topics focused on the end-user. While the majority of user centric discussions revolved around new usability initiatives driven by SAP, we definitely noticed a rise in the number of companies discussing their user / change programs. We were lucky enough to be interviewed live by Tom Wailgum from ASUG News.
As a semi-retired bean counter I have always liked accounting jokes.
Q: How many accountants does it take to screw in a light bulb?
A: What kind of answer did you have in mind?
When it comes to asking how many Super Users are needed that is no laughing matter for a Super User program lead. As the answer is usually – well it depends.
I have had many thoughtful congratulations over the past week as Neochange steams past the 15 year mark. Thanks to all of you that have made our journey so interesting. As more notes have come in I took the time to reflect on the most obvious question for a 15 year old endeavor - why we are still working on the user adoption challenge after all these years?