I’m a big fan of kaizen events.
My background is in lean engineering, and if there’s one thing that makes a lean engineer salivate, it’s continuous improvement. Over the past few years, I’ve both conducted kaizen events as a process engineer and helped customers with kaizens as the head of continuous improvement with Drishti. All in the name of making process improvements that can drive change on the factory floor.
But not all kaizen events are created equal. That’s why I’ve taken a few minutes to guide you on how to make your next kaizen event more productive and impactful while taking less of your team’s time to complete. Sounds like a dream, I know — but here are three relatively easy ways to make that dream a reality:
No. 1: Increase your available data. And greatly reduce the number of staff you use to collect that data.
Probably sounds conflicting, right? But hear me out. Right now, when you’re ready to commence a kaizen event, you’re unleashing your industrial engineers to spend the weeks leading up to the event on the line, diligently observing every action and recording how long each step takes. We did a study with Kearney a while back that indicated an industrial engineer spends nearly a third of his or her time doing time and motion studies and that’s during normal, non-kaizen moments. Imagine how much more time is spent on dedicated observations prior to a kaizen event.
Instead, consider a solution like Drishti. We install cameras on every station and line that will be evaluated during a kaizen event. These cameras seamlessly collect timing data on every single step performed on that station. More data, less staff — the perfect equation!
No. 2: Hone the accuracy of the data you collect.
While we’re talking about data collection, let’s think about the accuracy of the data that normally gets collected prior to a kaizen event. The operators know that you’re about to make recommendations on how to optimize the line. So while your engineers are gathering data, chances are one of two things is happening: The operators are performing better than ever to avoid criticism and being called out for improvements, or they’re performing worse than ever because they don’t want you to implement unrealistic process improvement changes or recommend staff reductions.
When you have a camera on every station continuously collecting data for weeks or months prior to a kaizen event, you know the data is accurate. Because even if there is a handful of cycles where operators over- or underperform, statistically speaking those outliers don’t skew the data when there are thousands of samples.
No. 3: Make an honest evaluation of whether the improvements you implement are working.
Drishti can shorten the duration of a kaizen event from a few weeks to a few days. Even so, a kaizen event is a substantial use of resources: You have lots of engineers in a room evaluating data, and then a significant commitment to process change after the event ends. That’s why there’s often an optimistic post-evaluation of a kaizen event’s impact that distorts the reality.
But with Drishti, there’s no room for overly optimistic viewpoints or biases: The data doesn’t lie. So you’ll either see significant improvements — which is the likeliest scenario, given the accuracy and volume of data you have going into the kaizen — or you’ll have a clearer focus on what else needs to be addressed to solve process issues. And with the data to backup your conclusions, it’ll be easier to get other stakeholders on board with your recommendations.
In the spirit of continuous improvement, Drishti has significantly up-leveled the kaizen experience by providing the data you need to make your event more impactful. I’d love to show you in person what Drishti can do for your next kaizen — let’s talk continuous improvement with AI-powered production from Drishti.
Dalia Peña is the head of customer experience at Drishti. Dalia brings extensive experience and a keen understanding of lean manufacturing principles to Drishti. She has been able to infuse that background into the company, particularly to members of Drishti who bring less manufacturing expertise to the table. In doing so, Dalia has ensured that Drishti’s AI-powered computer vision technology stays hyper-focused on meeting the needs of discrete manufacturers across North America. Dalia was one of Drishti’s first employees, and at the time, one of the only employees with actual assembly line experience.