The other day at work we encountered a problem. It required us to change the routing systems and processes we use to service our customers.

We repair home medical equipment. We drive out to home care dealers to pick up broken equipment and return repaired equipment.

Because of changes with a partner, we gained a significant increase in the number of stops that we have. But because the data provided to us from that partner was incomplete, we didn’t know if the changes will mean an extra 2-3 customers per week or 20-30 per week. In fact, we really don’t know if it means it will be 100-200 more customers that we have to start visiting.

So, we started to do some evaluation of our current systems around routing vehicles to customers. We started to lay out different scenarios and what that would mean to the current system.

We quickly found that the system we currently have in place is too rigid. It works great with a set number of customers that we see every other week. Throw in the occasional change and we have that covered. But throw in a large number of changes all at once and we have a problem.

It might seem logical then, that we need to add more routes and drivers. The common response to an increase in something is that we need to increase the resources around it.

But there is a problem. The problem is that the business relies on the efficiencies we have built into these routing structures. We have fine-tuned the systems to be as effective and efficient as possible.

Another response could be to say no. We could tell our partner that, sorry, we aren’t doing it. But in this case that option isn’t a good option at all and would do too much harm to the business.

So, we buckled down to think through the issue and come up with ways to handle the changes. Luckily, we all know the systems and processes very well and tend to rely on systems thinking whenever we attack a problem such as this.

Instead of using linear thinking and deciding to just say no or to add more resources, we started to think about the full system. We looked for leverage points, flexible elements and areas we can change.

We ended up addressing the biggest problem that we found - rigidity. We had built an efficient, but rigid, system. The rigidity allows us to profit from the efficiency.

Instead of blowing it all up, we focused on the rigid elements. We started to dissect our system. We found that some of the rigidity could be removed by rearranging the order we did the steps.

Instead of doing lots of work on the front end to build the routes, we would wait until the end of the process. We would provide minimal route guidelines and would allow all sorts of changes to occur before we created the rigid route.

We would start with a very loose structure for the route. It would have a few of our core customers on it. We would determine ahead of time how much flex there was in that route.

This meant we would know ahead of time how many extra stops that route could accommodate. We knew how much extra drive time we had. We knew what the capacity in the vehicle was. We still didn't know what stops would end up on the route but had a framework for each service area.

By doing this, we attacked the rigid elements and worked to find ways to make them adjust. We found ways to create a system that changes based on demands. It kept the efficiency but added flexibility.

Flexible systems can be great if done right. We can allow for all sorts of variables without losing our efficiencies. We can be systematic and malleable.

We already had a flexible system built in that allowed us to add a new stop. But this process was very structured and required a great deal of work each time. So, we used the basic foundation of that system, and changed some elements to make it simpler. The best part was that doing this started to give us scalability, along with flexibility.

If you have a good system or habit in place but see changes coming, don't ignore the benefits of a flexible system. Don't blow it all up to avoid rigidity. Instead learn how to be flexible and systematic.

Doing this is difficult and requires a higher level of thinking. But the results improve over a system that has unseen flaws due to being too concrete. It opens up new ways to solve problems.