We love to dig into our client’s business processes and help them overachieve their stated goals of improved efficiency or compliance. It’s a mentally challenging and stimulating exercise that we really enjoy. However, we have learned that part of the challenge is the fact that there’s a real bias to under-divulge information about what the current process consists of.
This bias is not intentional by any means. It’s a function of unconscious acceptance of exception management as part of the job. Put more simply, most employees just handle the issues that come up when there is an exception, and it doesn’t register as a “step” in the process. However, it is exactly these exceptions that take the most time and therefore cost the most money. Therefore, eliminating the bias to get to the true process is a great place to start.
Start with investigating the exceptions to documented or routine processes. For instance, when employees search for client documents, how often do they need to look in three or four different locations because the client was acquired, or an acronym was used? How often is an approval held up because some data or documentation is non-standard? Get the answers to why these things happen.
When you dig deeper into the exceptions it is likely that there is an underlying problem with the data or supporting documents. Therefore, to get to the best automated process you need to clean up the data and get the supporting documents organized. A project of getting the supporting documentation organized will simultaneously result in cleaning up the data. Good data is of course valuable data.
Now that you have a solid base to work with, implement the new processes to keep the data clean. For instance, once you have your client documents organized and that organization structure matches your ERP or CRM perfectly, design a digital workflow to capture new client data and client changes. Similarly, when you have your vendor documents in order and they match the ERP, implement the vendor onboarding and management workflow to keep it clean.
To recap, dig deep into the full existing process including exceptions. Clean up existing data to remove as many potential exceptions as possible. Then, design the new process to keep it all clean. In the end, the goal of better efficiency will be met, but you will also over-achieve because your data will be better. Address your employees process bias. Get to the bottom of it and you will exceed your goals.