Manual process tracking can be biased and outdated. Build a digital twin of your processes to see real work. Analyze data to optimize people, process, and technology.
On Tuesday, June 7th, 2022 Skan sponsored a fireside chat on “Building Continuous Improvement into Digital Tools,” in partnership with the SSON Digital Summit 2022. The panel featured:
Below are Skan’s top four insights from the fireside chat on “Building Continuous Improvement into Digital Tools.”
A poll of the attendees revealed that the majority of organizations believe that coordinating people, process and technology collectively is the biggest obstacle to creating a culture of continuous improvement. No one dimension is more important than the other. Process operators must be properly trained and enabled with the necessary tools to do their work. Processes must be streamlined to deliver customer value efficiently. The use of non-core applications must be thoughtfully examined for automation opportunities.
From a second poll, we learned that 20% of attendees are not using any digital tools at all. One of the biggest challenges with manual observations to create process maps is bias. Cognitive bias is a failure to process information logically. For example, Anchoring bias is the tendency to make judgments by reference to a benchmark. A process operator knows that the standard process is the benchmark, and will consequently describe their work based on that benchmark while ignoring all the activities they perform that are outside of that standard process. The result is an incomplete process view of the real work taking place.
Continuous improvement requires a reliable, high-fidelity view of the real work taking place across an end-end process. Digital tools greatly enable this. In particular, process intelligence solutions provide real-time visibility into both the committed state of core applications as well as the activities that occur in between these committed states such as emails, cutting and pasting into notepad, work in spreadsheets or searching on the web. Once a reliable, real-time, high-fidelity view of end-end processes is established, then this ‘digital twin’ can be used to identify and prioritize improvement opportunities, implement and measure improvements going forward.
Analytics on top of a reliable, high fidelity digital foundation can help organizations drive improvements across people, process and technology. For instance, analytic insights help monitor worker productivity: compare top performers with bottom performers to kick off training to narrow the gap and improve productivity. Analytics help monitor process efficiencies: compare process variants with significantly different cycle times to identify standardization and automation opportunities. Analytics help monitor technology usage: analyze non-core application usage to identify automation opportunities to reduce the amount of time in non-core applications. By coordinating improvements across people, process and technology organizations can build and sustain a culture of continuous improvement.