This eighth post in our series on effective change management is about the importance of the data on existing performance.
Existing performance data is often missing altogether
My experience is that most organizations have little or no data relating to the performance of vital processes. It’s like driving a car without a speedometer, or an oil pressure gauge. Rather, they tend to “know,” by gut feel, that the process isn’t performing as it should. That, alone, often prompts them to seek help in making improvements.
What kinds of data are we talking about?
The type of data I’m talking about depends on the type of process. However, the following are some generic performance data elements that have proven helpful in a wide variety of processes we have worked with, from admitting patients in a clinic to receiving bulk freight in a shipping facility:
- Cycle Time: The average elapsed time from beginning to end of a process.
- Range of Cycle Time: The shortest and longest cycle times and the percentage of cycles with shortest and longest times.
- Throughput: The number of units flowing through the process for a given time period (a week, a month, a year, for example). In the examples listed above, “units” could be people moving through the clinic or number of packages received for shipment.
- Errors: The percentage of units that require rework. Again referring to the examples I listed above, errors could include appointment scheduling glitches, lost shipping documents, and so forth.
- Number of FTE’s: The number of full-time equivalent employees involved in production of existing throughput (calculated by summing the percentages of all persons involved in tasks laid out in the process flow).
Why bother to measure the process if you intend to abandon or re-engineer It?
Here’s the answer: Because it’s vital.
First, don’t forget that you’re bucking the odds. Don’t lose sight of the fact that two-thirds of major change efforts fail. So, if having valid existing performance data improves your odds, wouldn’t it be worth having? Well, it does (improve your odds) and it is (worth it). Here’s why:
Existing performance data helps you sell the need for change
We’ve talked about this a good deal, but the simple fact remains: You can’t execute change without the active support of those doing the work. Existing process performance data can help make the case, especially if it can be compared with benchmark data from competitors or best practices analysis.
Further, designing and implementing innovative new designs will require investment. Baseline data, when compared with the new standards defined for the innovative process, will enable you to calculate the return on investment, which will be vital in securing management or governance support for the cost involved.
Existing performance data focuses the design process
An early step in designing the new process is defining the target standard(s) for performance of the new design. Those targets focus the design team on defining breakthroughs that will meet the new standards. That focus reduces the risk of the design team getting sidetracked by enhancements that don’t significantly impact performance.
Existing performance data helps you test the new design
Implementation of the new design will involve early releases or changes that move you toward the new design, but don’t involve a significant investment of time and money. These early releases are vital for two reasons:
- They provide momentum for change
- They verify the workability of the new design.
Collecting real-time data on the new process and comparing it with baseline data as you implement the new releases is a key to achieving that momentum and verifying the soundness of the design.
And, speaking of momentum…
Keep this in mind: Somewhere between 10 and 30 percent of your workforce will actively resist the change. Their instinctive response will be: “It won’t work.” The longer that group hangs on to such a view, the more likely it is that you will encounter performance problems with the new process. This group’s lack of support will lead to poor execution, preventable errors, longer cycle time. They don’t learn the new process. Why? Because they’re convinced it won’t last. However, early releases and data on the efficacy of the new process will sell them on the need to embrace the new way, and not count on going back to the old.
Existing performance data helps create a culture of management by the numbers
An old adage in organizational development is that what you measure takes center stage or defines what matters. Improving your performance metrics begins with good baseline performance data. Seeing the “needle move” or watching the performance improve, gives tangible wins to those who have designed and implemented the change. It also moves management away from reliance on false data or rumor when defining problems and solutions. This is vital to overall performance improvement.
Want to be sure you’re ready? Send us an e-mail
If you would like to verify that you have adequate performance data and the right data to undertake performance improvement, give us a call for a free consultation. To set up such a call, simply drop us an e-mail.
Being certain that you are ready to start and that you have initial conditions for success can save considerable time and money. Further, every failed change effort makes it that much more difficult to complete a successful change in the future.
The rest of the story
To read the rest of the posts in this series on change click on any of the links below: