Part one of this series focused on creating a business culture. That is, “Why are you in business, and what do you provide for your customers? ” It’s an essential part of business success because it places everyone on your team responsible for the outcome. If they know why you’re in business, they can better match their work with your business. And as we learned, it’s more than a list of tasks; the why must be included in what they do.
Part two covered ways to remain more focused on the outcome you’re after and revealed time wasters we’re all faced with. We all have the same amount of time each day. The useful time is merely the byproduct of what we have available (24 hours) minus distractions that have no positive effect on the outcomes we’re after. This is a particular challenge in these days of social media and phone notifications that we have trouble ignoring (or maybe we don’t know how to turn them off).
Now we’re ready to roll up our sleeves and put some new tools to work. There’s a math function called the Standard Deviation that I’ve found to be one of the best tools for analyzing data and refining an outcome. I learned this function in 2007 and use it in many aspects of my personal and business life.
Simply put, it recognizes that any time you examine a collection of data, most of it centers around an average. For example, if a particular transmission takes around four hours to rebuild, you’d expect to find rebuild times like 3:52, 4:20, 3:45, 4:10, etc. (hr:min). If a builder only spent two hours and twenty minutes, you’d wonder what they left out or if any bolts were loose. On the other hand, if someone spent seven hours rebuilding this unit, you’d wonder what they were doing with their time. With this idea in mind you can see how you can apply it to just about any process you have. It’s great for setting goals, too. In fact, I used it for the June 2023 Gears article, “Business By The Numbers,” to establish throughput goals based on survey results from actual shops.
With this in mind, let’s start by defining a project. A project is a sequence of tasks that must be completed to attain a specific outcome. Notice the key terms here, tasks, and outcome. Generally, we know the tasks involved in a project. But too often, we don’t have a defined outcome that turns those tasks into a project.
So, let’s look at some outcomes you may want to control. A list of outcomes for a shop might be:
- Rebuild Times: Perhaps you have a quality or output problem you want to control. Rushing through a rebuild can result in defects and CBs, and spending too much time creates a backlog of cars and customer dissatisfaction. Somewhere in the middle is the target.
- R& R Times: We can use the same thinking we used for rebuilding here. It’s a balance between defects and customer service. In addition, if you focus on this area, you may discover an increased output and better customer service by keeping your rack times more consistent. Again, go to the June 2023 article for more on this.
- Delivery Time: The amount of time a customer’s car sits in the lot. A customer drops their car off at 8:15 Monday morning. From past surveys, we know that customers expect to be without their car for about three days if they need a transmission rebuild. What happens to customer satisfaction if it takes two weeks? You can bet they’ll have words to share with their friends, warning them to stay away from your shop if they need transmission services. And something else to consider here: this time lag could have nothing to do with your staff. Perhaps the backlog is due to your parts supplier. It might be worth paying more for a provider that offers better delivery times.
- Repair Order Amounts: I’m not much a fan of having a target RO amount, but using the Standard Deviation, like we’ll see in a moment, along with the average RO figure you’re accustomed to, can offer insight into other areas of your business. If you already collect RO amounts, looking more deeply into it is a snap. In addition, however, if you have more than one sales agent, this is a terrific way to track and compare their performance. You can combine their sales figures and establish sales goals.
- Customer/Car Count: This is one of those metrics for which we always want more. We want everyone who needs their car fixed to come into our shop. But do we really? Like any other workflow area, you can reach a point where you exceed the sweet spot. The sweat spot is when you’ve got plenty of work, it’s going out the door, you get paid, and your customer is happy. Once you exceed that, the cars start piling up, customers get delayed, nobody is happy, and the word gets out. You may even lose key employees over it.
These are just examples, but if it’s something you can measure, you can run it through this system. Now, let’s take a look at data. For our purpose, data is a measure of time (minutes, hours, or days), quantity, Dollars, or even an arbitrary score you’ve created to compare performance output. If you can add, subtract, multiply, or divide the data, you can use it for careful examination. The second thing to consider is that data always has an upper and lower constraint. We’re fully aware of the lower constraint: we don’t have enough customers, and production and money are good examples. But we rarely consider the upper constraints. You don’t often hear people complain that they have too much work or money, but an upper limit exists, even if we don’t always recognize it.
Let’s get started. Figure One shows a histogram of data collection. Don’t get caught up in the details; just follow along. And know that I’ll have an accompanying video of this with the online version in Gears Overdrive. Notice two things in the illustration. Most of the data lies around the average, at the number three in the legend. This is true with everything you’ll track. Then, you have less data near the lower constraints (1 and 2 in the legend) and upper constraints (4 and 5 in the legend). This is the nature of all data. The difference is how much of your data is near the average and how much lies closer to the outer constraints. This is where the Standard Deviation (StDev) comes in. StDev measures how much of the data is closer or further from the average. If more of it is near the average, we call it “in control.” If too much lies away from the average, it’s “out of control,” maybe even random because it’s so bad.
The second thing to notice is the percentage figures near the top of the chart. These percentage figures represent one StDev and never change. We want to focus on the 34.1% before and after the average. Combined, it equals 68.2% (roughly 2/3s). This is to say that ALL the data collected is 68.2% of all the data collected. I promise that’ll make more sense as we go.
Now, look at the chart in Figure Two. It’s a collection of data in an Excel chart. If you’re mildly familiar with Excel, this looks typical. We have two collections of data with 10 samples of each. They reside in cells C2 through C11 (C2:C11) and E2 through E11 (E2:E11). You can use as much data as you wish as long as you recognize the cell positions, but we’re keeping it at ten for our examples.
Notice the four output labels we use to examine the data now. They are Average, StDev, High, and Low. The legend on the left shows the Excel command for each function. For the average of the first collection of data, click on cell C13, then type the following: =Average(c2:c11), and hit “enter.” In our example, it returns 6.6. Now get the StDev of the collection. In cell C13 type =StDev(c2:c11), then hit “enter.” In our example, it returns 2.008401. You can round it if you wish, but let’s continue.
Now, the “High” limit is simply the sum of the average and StDev, which is 8.6 (rounded). The “Low” value is the difference between the average and StDev, which is 4.6 (rounded). Voilà! You have just created a meaningful goal based on your existing data. For example, if these were rebuilding times on a specific unit, it would say that 68.4%, or about 2/3s of all your rebuilding times, fall within 8.6 and 4.6 hours. That’s a wide gap and one that’s out of control. There’s a four-hour gap between a fast and slow rebuild time. But it gives you a starting point. Now you have a standard that says, if someone rebuilds this unit in less than 4.6 hours, they’ve probably shortcut some steps, and it’s more likely to fail. It also states that a rebuild time of over 8.6 hours is unacceptable. It could suggest that the rebuilder is too slow, or they’re being interrupted throughout the build process. Either way, it gives you a goal and allows you to attend to the units that are out of spec (time-wise). It might evoke additional training or other measures to address these time-related problems.
So now you’ve addressed these concerns, instituted the necessary training, or identified conditions that caused these out-of-time problems and continued your time tracking.
Return to Figure Two and notice the second data collection (column E). These are the rebuild times after establishing the new goals and instituting policies to minimize fast or slow rebuild times. Look at what happens using the same Excel functions (but column E rather than C in the commands). Now, you’re looking at rebuild times that are more in control. Sure, there are still a few that are out of spec, but now you have a fast time of 5.5 hours and a slow time of 7.3. Rather than four hours between the two times, you have about an hour and 45 minutes between the two. This process is in control. The result is greater output and fewer defects.
Using rebuild times is a practical example of creating meaningful goals with actual data. The results become more meaningful and accurate when you use more data, rather than just ten in our example, but this gives you an idea of how it works. If you have shop software that records data, try exporting it to Excel and working through it. You’ll be surprised that you can create meaningful goals for practically everything you do.
This is just the beginning of your path to controlling processes for better results. Once you’re comfortable with the Standard Deviation, you’ll wonder how you ever got along without it. I sure did.
Remember to check out the Gears Overdrive video. I’ll share some Excel tips that’ll help you hone your skills and make this exercise a snap.
