That day I ordered takeout, waited half an hour, and suddenly thought, isn't this a DMAIC?
To be honest, having stayed in the Fab for a long time, my mind is always on those P_L_C, C_I_M systems, and the endless machines that are always running. That lunchtime I was starving, and on a whim, I ordered a bento box from downstairs at the company. What happened then? The APP showed "Order processing," and it was stuck for half an hour. As I was scrolling on my phone, a thought suddenly flashed through my mind: Isn't this the "excessive waiting time" that our semiconductor fabs dread the most? And this can also be handled with DMAIC! Don't believe it? Listen to me.
Where's the Problem? The Service Industry Also Has Bottlenecks
To put it bluntly, you and I have both encountered such annoying situations: orders sent out, then disappear without a trace. In the factory, we call it "low machine utilization" or "excessive batch waiting time." In the service industry, it's "customer impatience." "Excessive order processing time" sounds abstract, but if you break it down, you'll find it's very similar to our factory's processes. From you placing an order, to kitchen preparation, cooking, packaging, and serving, each step can get stuck. Suppose we want to reduce the average order processing time from 25 minutes to 15 minutes; those 10 minutes in between are where we need to find opportunities.
How to Actually Do It? A Walkthrough of DMAIC
Frankly speaking, DMAIC isn't some black technology; it's just a systematic problem-solving method.
- Define (Define the Problem): We need to clearly know what the current status of "order processing time" is. Suppose we measured 1000 orders and found the average processing time is 25 minutes, with a standard deviation of 8 minutes. In other words, sometimes you get it in 15 minutes, sometimes after 40 minutes it's still nowhere to be seen. Our set goal is an average of 15 minutes, with a maximum not exceeding 20 minutes. This defines our goal.
- Measure (Measure the Current State): This step is the most important. You can't just say "it seems slow" based on feeling. We need data. You can pull out order data using Excel and record the time points for each stage: from "order received" to "preparation started," "cooking completed," "packaging completed," to "dispatch." Suppose we found that the average time for the "cooking" stage is 10 minutes, but the standard deviation is 5 minutes, while "packaging" is only 2 minutes, but sometimes spikes to 8 minutes. At this point, we have discovered potential bottlenecks.
- Analyze (Analyze the Causes): With data, we need to analyze "why it's slow." Suppose we found that cooking time for weekend lunchtime orders is extended because there's only one head chef. Or, the packaging area is often delayed because meal boxes cannot be found. This is about finding the root cause. We can use fishbone diagrams and the 5 Whys method to trace it back. To be honest, often the problem isn't "people being lazy," but rather "poor process design" or "uneven resource allocation."
- Improve (Improve Solutions): Once the cause is found, we find ways to improve. If the head chef is the bottleneck, should we consider adding a sous chef? Or, simplify the menu, reducing the proportion of complex dishes? If packaging is the problem, can we categorize and arrange meal boxes, and set a reorder point below safety stock? In the factory, if we see a machine with low OEE, we'll revise SOPs, replace parts, or add manpower. The service industry is the same.
- Control (Control Effectiveness): Improvement isn't a one-time fix. You need to establish a mechanism to sustain the results. For example, you can track the Cpk of order processing time daily, issuing an alert if it drops below 1.08. Or, review weekly for any new bottlenecks. In other words, it's about "standardizing" good practices and continuously monitoring them.
The Most Common Pitfalls: Numerical Fallacy and Process Inertia
The biggest pitfall I've fallen into is being too fixated on "numbers" at first. We often throw out a bunch of data but rush to conclusions without proper analysis. The result is that the improvement solutions don't even hit the pain point. Another one is "process inertia." Many service businesses, especially old establishments, will say, "we've always done it this way," but times are changing, customer demands are changing, and if you don't change, you'll be eliminated. Just like in our factory, if you use an old recipe, the quality will never improve.
One Thing You Can Do Today
Pick one service step that you feel is the slowest, and start recording it.