Capacity planning is often seen as simply a way to understand and prepare for growth. While it is important when you’re planning an expansion, getting into the practice of analyzing and optimizing your field service team’s capacity can have major benefits for your customers, workers, and the company as a whole.
Author Nick Saraev
Photo: Freepik
Raouf Chaouch from Leica Microsystems explained how his team models their field service capacity to make the best decisions for growth and beyond at Field Service Po50 this year. He shared the ways that this focus helps improve every aspect of the business model, and how any team can start taking practical steps toward optimization.
What Contributes to Effective Field Service
There is a lot that goes into a high-performing service mission, including
- Competitive advantage – Customers shouldn’t only want to work with you because you have the best products, but also because you have the best service
- Best Place to Work – Your biggest assets are your field service engineers. You need to ensure they are secure and excited about their jobs
- Profit and Loss – Because you get resources to invest from your profit margin, having a higher profit means you can invest in better people and processes
When planning how to expand your business, you’ll want to find solutions that include all of these factors.
In order to have the most effective field service possible, you need a lot of things to be going right.
Firstly, you need the right field service agent. This requires your team to have the perfect mix of technical and soft skills so that they can provide the best customer service while getting the job done right the first time.
However, even the best agent in the world can’t help someone if they don’t have the right time. Your entire system needs to work together to boost your team’s reactivity and get them working on problems as quickly as possible.
One of the most overlooked parts of this equation is getting people to the right place. Travel time can put a huge damper on your efforts and make it virtually impossible to fix problems quickly. You need to ensure that your team is located close enough to your clients to arrive in a timely manner.
There are 2080 working hours in a year, but when you account for holidays, productivity, and time off, the majority of your team members will have around 1320 hours a year that they are firing on all cylinders.
When you’re in the field service industry, this productive time is split between labor and travel. A smart company will know that labor is the most important to focus on because it is the customer-facing time that provides value to the people you’re working with.
In order to give your customers the most value possible, and get the greatest return for your team’s time, you need to cut down travel time.
Region DACH: A Study In Efficiency
Many companies within the DACH region deal with a huge workload and slow reactivity. We’ll zoom in on a particular hypothetical team dealing with the stress of this challenging market. Let’s say that there was a request put in for an FSE headcount.
The team could start by looking at the data for how many hours of productive work they required for the last couple of years, and use that data to make an educated guess about their needs coming up. For example, if they had 84700 hours required in 2021 and 85100 hours in 2022, it would make sense to project 85500 hours for 2023.
When you divide this number by the roughly 1320 productive hours each service team member will be able to provide in a year, you land on a need for 64.8 FTE, or 65 workers.
This team can then cross-reference their required amount of workers with the number of actual employees they have in the field, let’s say 60. To fulfill the required amount of work, they would need to have 86% productivity, which is a huge ask and risks burnout and sloppy work.
In order to be successful long term, this company would need to hire at least five more people. This is a clear and straightforward example of the power of data-driven decision-making.
One of the biggest mistakes that companies make when figuring out their capacity is going off of assumptions. You don’t want to make decisions based on what customers say they want or what you think they need. Instead, look at historical data and find what is actually needed consistently.
Some customers will call you twice a month, some you’ll hardly ever hear from. You need to direct your resources toward the pain spots. Again, we can see data-driven decision-making at work.
Find out which clients are asking the most of you, and see how much time you spend at each location. This information can then be cross-referenced with where your workers are located. If you want to add those extra five workers from our earlier example, you’ll want to ensure they are being added to a spot that needs the help.
You can also use this data to optimize your current workforce. If you notice that there is a high concentration of workers in an area that doesn’t get many calls, or that some of your workers are putting in more travel time than actual service time, you know changes need to be made.
Remember, you want the right technician in the right place at the right time. A great way to clock issues here is to look at your travel/labor ratio. If your team is traveling more than they work, no amount of added people or happy customers will solve your issues.
Modeling and Planning for Optimal Field Service Capacity
So how can you start to solve issues with your capacity? The first step is to imagine your ideal world.
Take a look at how your required time is spread out around the map. If you were to start from scratch and hire all new people, where would you want them to be based? Seeing the differences between your ideal map and your current concentration of workers will help guide you in future hiring because you know where there are holes in your perfect network of technicians.
This focus on travel time can open up the possibility that more field service engineers aren’t always what’s needed. Hiring a dispatcher who helps organize your current fleet and cut down on travel time can do far more for your operation and become effective far faster.
When you are looking to hire more people then, there should be several steps in place and questions that need answering. Consider
- How many hours are workers spending at customer sites?
- Are you expecting higher than 80% efficiency?
- What is your travel-to-work ratio?
- Would another FSE solve the problem, or would a dispatch worker?
- Where is the best location for a new FSE to balance the map?
- Could we instead cross-train an existing FSE?
The main goal is to understand all the factors that can lead to your workforce being over-extended, and ensure that the choices you make are going to make the biggest difference.
In Conclusion
Capacity modeling and planning is an invaluable example of data-driven decision-making at work. When utilized fully, it can improve customer service, worker productivity, and the company’s bottom line.
Thinking about capacity modeling as a tool for expansion and nothing else leaves a lot of its power on the table. With a little bit of foresight, you can use this data to find any areas for improvement.
Whether you’re optimizing day-to-day operations or looking to expand, taking the time to look at the data and get serious about deployment can give you the boost your team needs to find success.
