How will I know my customers and clients are being looked after while I'm away?

Hey there,

I apologise for leaving you hanging last time.

I got you measuring how long it takes for you to give a customer what they want, and then left you to it.

Well, this time I'm going to give you a simple tool you can use to look at the data you recorded and decide what to do with it. It's an extension of the spreadsheet I shared last time, set up so that all you have to do is enter your data.

That tool is a graph, specifically, a moving range chart. It looks at a set of data points statistically, rather than as values in themselves. It also looks at them with time as a key element.

So today I'm going to talk you through using a moving range chart to measure your business performance:

What a moving range chart shows
Patterns of variation to look out for
What to do with the information

I've created a new template for you to use, called (imaginatively) EXTENDED KEEP PACKAGE PROMISE TIMINGS PROP (TEMPLATE).

I made it in Excel because that's easier than Google Sheets, so do make sure you download a copy before you play with it.

Then, if you've already collected the data I suggested last time, copy it into your own version of this new spreadsheet. If you haven't, have a go at the end of this newsletter.

In all my examples today, I'm using made-up data, just to show you how it all works.

Here goes.

This is my data for 'how long it took us to give the customer everything they wanted':

And here's the graph that goes with it:

What the moving range graph shows

The x-axis shows 'how long it took us to give them everything they wanted' in days.

The y-axis shows the 20 clients we looked at.

The red line across the middle shows the average duration. The upper and lower control limits show 3 standard deviations either side of that average.

Presenting the data this way allows you to visualise the variation that exists in your system, without getting bogged down in individual numbers. It's the shape that matters. And you need at least 20 data points to get a shape that will make sense.

In this case, every data point falls between the upper and lower control limits. This means that all the variation is coming from the business system.

This is good news, it means that the sources of variation are under the control of the business owner.

This is also good news from the perspective of taking a break, because as long as everything is between the upper and lower limits, the Boss can relax while they're away. The system is working as usual.

In this example, there's quite a gap between the upper and lower control limits. This shows that the variation between clients can be quite large. This isn't necessarily a problem, but in general the narrower the gap, the better - because when the customer gets what they want quicker, it costs the business less to do it.

What a moving range graph doesn't show

A moving range graph doesn't tell you the cause of any variation. You have to go and look at your system to find that out.

For example, here, it might be that everything the business does is totally bespoke to each client - every solution starts from scratch and is built to order. So the variation is entirely due to the fact that clients want something different.

Or it might be that some of the work that goes on in this business is not really serving the client, and actually gets in the way of giving them what they want as quickly as possible.

It's impossible to tell until you go and look. But the second is more likely.

Patterns of variation to look out for

Now that I've introduced you to the idea of a moving range graph, let's look at some common shapes that will tell you something's not quite right.

Something extraordinary happens.

If one or more data points fall outside the upper or lower control limits, the chart is telling you that something extraordinary has happened. It's also telling you that the cause for this variation, comes from outside your system. You can see that because the data point is more than 3 standard deviations away from your average.

For example:

In this case, it took 31 days for a particular client to get everything they wanted. As you can see that is extraordinary compared to every other data point.

You won't know what caused this until you go and look, but what you do know is that it isn't due to the normal workings of your business. The fact that the data point is above your upper control limit tells you that.

It could be that something happened at a supplier's business. They had a fire and had to close for a month. Or a key member of their team (the only one who could deal with you), had to take a month off. Or maybe there was a national emergency that meant everyone was closed for a month.

If the reason is a one-off, it may be reasonable to simply ignore it.

Or you might decide to find a way to make sure it can't happen again, e.g. by adding a back-up supplier. What you do about it is up to you.

Trends

A run of numbers, all above average, all below average, or simply all heading in the same direction, tells you that a trend is forming.

For example:

For clients 5 through to 11, the time it took to deliver everything they wanted was below average.

You won't know what caused this until you go and look, but what you do know is that a) it hasn't sent the business system out of control, and b) it isn't due to the normal workings of your business. You would expect the data points to be random.

Here's another example, this time measuring bookings per week:

After 50 weeks of normal variation, bookings start to fall gradually over the next 7 weeks. This is an indication that something is going on. If this range chart represents a venue - say a given branch or franchise outlet - it's telling you that something is going on to interfere with normal workings, but not what that something is.

It could be that at week 51 the local authority introduced paid parking where before it had been free. It could be that there are roadworks outside the venue, that make it hard for people to drop in. It could be that whoever is running the venue is going through something bad, and getting worse.

As always you won't know until you take a look, but a run of 7 numbers going down means you should take a look before the situation becomes irrecoverable.

And if the numbers were all going up instead, you'd still want to take a look. Perhaps there's something happening at or around this venue you could take advantage of elsewhere.

Maybe an ice-cream parlour opened up next door, incentivising more people to join the dance class, knowing they can treat themselves afterwards. You might decide to make a nearby ice-cream parlour a criteria for choosing your next venues.

I'm sure that if Benjy's - the long-defunct sandwich bar chain - had used graphs like this for all its branches it would have spotted that something extraordinarily positive was going on at the Cannon St. branch, found out what it was and rolled it out to all their other branches. https://disciplinemakesdaringpossible.com/2019/04/measuring-what-matters/ They obviously didn't.

The main point here is not to be too premature. A short run in one direction is part of normal variation. A run of 7 isn't normal and signals that you need to take a look.

See-saw

Here's another graph for 'how long it took us to give them everything they asked for' for our 20 clients:

All the data points are well within the normal range, but for some reason they see-saw around the average.

Of course you won't know until you go and take a look, but this might indicate that there are 2 different processes going on, or that two different groups are working in different ways.

For example, it could be that the bottom data points are for a product you always have in stock, while the top ones are a product you always have to order in. As I mentioned last week, these are effectively different packages, because they need different processes to handle them. Give each process their own graph and the see-saw would disappear.

Or it might be that these represent different teams working the same process but on different shifts, and something interferes with the people working one shift, so things take longer.

You only know by finding out.

Cycles

Finally, have a look at this graph:

There's definitely a pattern here, that repeats over a 7-day period. A cycle.

I can explain.

Every Monday, I go to a Pilates class. Afterwards, as a treat, I allow myself a bacon roll.

I'm pretty good at sticking to my healthy eating plan the rest of the week, until Thursday, when I crack and have a biscuit.

Then, on Friday, I have a different Pilates class, followed by toast and Marmite.

Then it's the weekend, so I allow myself some potatoes or white rice, or chips, and before you know it I'm back to Monday.

This is a silly example, but if you see a cyclical pattern in your data, it could mean differences between shifts, or between batches or suppliers or teams. It could just mean that Mondays are extra busy. You'll only know what it is by taking a look at what is really going on.

What to do with the information

The most important thing to remember is that a graph is a prompt for action, not a result in itself.

If you don't like what you see, go and look at how the system is actually working. Ask the people doing the job. Sit with them and see what actually happens. Together with your team, get to the bottom of what's causing the level of variation, so you can all identify ways to reduce it.

Dig down into lower-level processes.

You can apply this measurement technique to any process or sub-process.

For example, you could measure part of your Share Promise process, such as how long it takes for a prospect to go from from enquiry to sign-up.

Then dig down further to look at how long it takes to go from enquiry to quote, and how long from quote to sign up.

You'll soon spot exactly where you can improve performance.

It doesn't always have to be time that you measure.

You could measure how many quotes are made in a week/month. How many calls are taken per day. The percentage of issues resolved in a given day.

Whatever you measure, take at least 20 measurements to get enough data to work with. Remember, the aim is to look at the shape you get.

Act on it.

If the graph shows your system is stable, but with wide variation, the aim is to reduce the level of variation in the system.

If the graph shows your system isn't stable, or is heading towards instability - i.e. it matches one of the patterns of variation given above, the job is to get the system back to a stable condition.

Whichever is the case, look at what's really happening, make an informed adjustment with the help of your team, keep measuring, then watch what happens to the graph.

So, have a go.

Start measuring for one of your Packages. See what shapes you get. Then get together with your team to identify what's going on and what you can do about it. Make your changes, and see what happens to your graph.

Here's the link to the extended tool again.

If you want to discuss a graph you've produced, book a free 20 minute chat. Or simply get in touch to arrange one.

And that’s it.

Here’s what you learned today:

Looking at data over time shows you the variation inherent in your system. It's variation that matters. The more variation there is, the more scope you have to improve how you Keep the Promises you make to customers - to delight them more, at lower cost to your business.
You can have a stable system with wide variation. On the one hand, that stability means you don't need to worry that your customers won't be looked after while you're away. On the other, that wide variation tells you there'll be plenty of room to improve when you get back. Because the variation is coming from the way the system is designed. And consciously created or not, that design is down to you.
If your data points fall within the normal range, your system is currently in control. But this kind of graph can give you advance warning of where it may go out of control - by showing you trends, see-sawing and cycles. They don't inevitably mean that, but they do tell you that it's worth taking a look at what is really happening.

Remember, the graph is a prompt for action, not a result. If you don't like what you see, go and look at how the system is actually working, make an informed adjustment, then watch what happens to the graph.

Remember too, the measure that really matters is how long it takes for the customer to get everything they asked for. From the customer's perspective. The faster you can do this, the less it costs you to do.

Do think carefully about that 'everything', though. It might include activities that inherently take time. And as long as the customer is willing to pay for that, you're fine. What you're really trying to do is strip out of your system, anything that doesn't directly contribute to giving the customer what they want. These moving range graphs are a simple, easy to use way of seeing where you can do that.

And once you're comfortable using them, you'll find you have a really easy way to know that your clients are being properly looked after at all times.

Thanks for reading!

The Disappearing Boss

Continuous Improvement* for customer‑focused small‑business owners - turn your successful company into a self‑managing system for making and keeping promises to customers—no silos, no supervisors—where your people can run light-definition, flexible, end‑to‑end processes with real‑time feedback to keep customer value flowing, and you can take breaks without breaking the business.

*The way Ohno‑san really meant it.