When I teach lean concepts, it’s easy to talk about the concepts of timing the process steps. Most people nod their heads and say, yes, they get it. The idea is easy – each step has a start and a stop.
But when I work with teams, it doesn’t seem to be so easy to work though the data identification step. Here are some things that have been identified as process steps, but there’s no time collection:
- Patient arrival in physician office
- Time patient gets to exam room
- Time doctor gets to exam room
- Time patient leaves office
- Patient arrival for procedure
- Patient ready for procedure
- Patient departs after procedure
It’s important to note that everyone is DOING everything very well, we just don’t have time data for the steps.
When you want to look at your process from a lean perspective, it’s difficult to analyze the process if you don’t know how long each step takes. Naturally, I often get push-back from the team: Patients don’t like to sign in, it takes too much time to track patient movement, we don’t have people who can run around with clipboards writing times down, etc.
At this point, I bring out my example from one of the departments I have worked with. They had all the same objections, but they really wanted to understand the flow of patients in their department. So, they created a flow sheet that included each high-level step, that would travel with the chart (which travelled with the patient) in which each “stop” would include a simple initial and time noted. They created an operational definition of WHO would note the time for each step, and added that onto the worksheet.
Then they took it up one level – if there was a delay, and the cause was known, they asked if they could include that on the worksheet. They agreed to use the worksheet for tracking for one week, and then we would analyze the results.
Lo and behold, not only was the timing extremely interesting, but the delay reasons were fascinating. The delays were not where we thought they would be. And, we found that the primary obstacle was different than all of the team’s guesses, prior to data collection. The department was able to move forward with proposed changes, and they use the worksheet once a month as an audit.
Would it be great to have an automated time-tracker, like a computer system and radio-frequency tracking? Sure it would. Did the department want to wait for a systems review, IT request, and approval process to get going on their improvement? No they didn’t.
I applaud departments like that one who want to understand the current state before plunging into “quick fixes.” In this case, the improvements were more effective, and more sustainable, because they didn’t let the short-term pain of focused data collection become a barrier to moving forward.
I wonder if anyone else has interesting stories to tell about challenges in the data collection phase?