Taking Your Field Service to the Next Level

Published at: 01/10/2017
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Service is all about the balance between customer satisfaction and efficiency.

If you don’t have enough people to provide the appropriate service levels, you won’t meet your commitments. But if you have too many people, it will be hard to keep everyone busy. If your workers aren’t busy, they’re not utilized. Then, you’re not operating at an optimal efficiency point.

Resource planning is a process that takes place at different points in time. The different decisions that you make along the planning spectrum help optimize the management of mobile resources.

It’s easier to change day-to-day decisions about who’s doing what and when. It’s more difficult to change long-term decisions because the number of people doing the work can’t change immediately. If you decide that you need more or less people, it will take time to execute on that decision.

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The planning spectrum always starts with long-term decisions. Typically, long-term decisions are about:

  • how many technicians you need
  • where these technicians are located
  • what skills these technicians have
  • what hours these technicians are available


Supply and Demand

In the planning spectrum, you must create an alignment between supply and demand – “the supply” is the mobile resources and “the demand” is the work that these resources are about to perform.

One of the challenges in long-term planning is that not everything is “known” at the time you need to make decisions. Let’s say it takes 3 months to bring workers up to speed, including recruitment and training. In most cases, when you need to make long-term decisions, you won’t know the demand for 3 months in the future. So planning will require some predictions about expected demand. The expected demand is based on historical data (e.g., the demand at this time last year) and on smart predictions about what will happen 3 months in the future. You’re trying to find a balance between these predictions and how many people you’ll need.

Another challenge is you’re not just deciding on the number of people you need. But how many people you need with the granularity of the scheduling problems that you’re trying to solve. On average, you may have “enough people” in your organization. But if some people work in Zone A, but can’t work in Zone B because it’s too far away, then you don’t have enough people. You need to ensure you have enough people to work in Zone A and Zone B. If your staff has different skills, then you must make predictions about specific work types, and align these work types with the people who have the right skills. Then, with any scheduling problems that you have to solve, you’ll know that supply and demand are aligned.

Once you’ve determined how many people you need, you’ll need to review the demand that you already know about. Keep in mind that demand still has the element of long-term decisions. The most common long-term decisions are maintenance activities that occur over long periods of time. These projects could be:

  • replacing certain assets in a facility or replacing millions of meters
  • performing maintenance work on thousands of cell towers
  • conducting a calibration process for thousands of assets

While these projects are “demand” that you already know about, you’re not deciding today who’s going to do what and when for these projects from now until the end of the year. Things could change over time, so it doesn’t make sense to decide right now. You’ll need visibility into a project in order to divide the work in a reasonable way along the project’s timeline.


The Optimal Plan

To make sure you’re not scheduling everything today and you’re not waiting until the last month of the year to meet your commitments, you need the ability to show progress along the timeline – often called “backlog management”. This visibility ensures you’re on top of meeting long-term commitments over long periods of times by having the right number of people in the right place. Then, on the day of service, you must make decisions about who is doing what and when. Most often, with these decisions, you must answer the question: What is an optimal plan for the business?

Different businesses have different business objectives. Your business might be accustomed to providing a high level of service and you might be expected to demonstrate efficiencies. You’ll need to find the balance between these objectives. But in many cases, these objectives conflict with each other.

An optimal plan includes decisions about:

  • your business priorities
  • your business objectives
  • your priorities within these business objectives

You need sophisticated tools to take the stream of work orders and the list of resources to create a plan aligned with your prioritized business objectives. Many times, in dealing with mobile workforce management problems, the focus is “creating optimal routes”. Most tools try to minimize the time that workers spend on the road, but that’s just part of the issue.

Some organizations want a plan that minimizes the risk to miss appointments. With this objective, if you have a time window of 10am-noon, you want to avoid scheduling service for 11:50am, because the risk of missing the time window is much higher.

If you want to optimize driving routes, you’ll need to compromise something else. But achieving this balance of business objectives is what takes your service organization to the next level. You must be able to say, “It’s important that we don’t miss appointments, so we’re willing to compromise some level of travel time in order to avoid missed appointments.”


Exceptions Happen

The last element of the planning spectrum is the field service environment itself. Exceptions can occur simply because of traffic, or because it’s hard to make 100% accurate assumptions about every work type that must be performed in the field.

You can try to make assumptions about certain work types. But even installing the same type of equipment might take one hour in one case and two hours in another because of something unexpected. There are a lot of assumptions that go into a plan, including travel times and work times. But these assumptions won’t be 100% accurate on the day of service because exceptions happen.

If an exception occurs, you want to handle the impact as soon as possible, in order to minimize the effect of missing appointments and not meeting your commitments. You need a set of tools to optimally manage exceptions with visibility into the plan, including the progress in executing the plan, and making assumptions about what’s likely to go wrong.

Let’s say according to the plan, a technician should have left for the next site 15 minutes ago. A sophisticated system would sense something is about to happen that’s not according to plan. At that point, you can start making decisions about whether to re-plan or re-schedule the next job. You might need to re-schedule the entire afternoon, in order to ensure you can meet every commitment.

An early identification of these types of situations is key. Once these situations are identified, you must make the right decisions. Some situations can be resolved automatically; other situations may require human intervention. There are tools to present these situations in a way that helps decision makers resolve these problems more easily.

For example, the system receives an indication that a technician must leave early due to illness. This type of re-scheduling requires human intervention, so it makes sense to present this issue to the planner including all the employees with similar skills that are nearby and sorted by “less busy”. In this way, the decision about who can pick up the work is easier.

Planning is an activity that takes place at different points in time. To make the right decisions for these different scenarios, you need the right tools that can:

  • break down and spread long-term commitments in a reasonable way along the timeline
  • utilize sophisticated algorithms, matching many work orders with many resources to meet often multiple and conflicting business objectives
  • help you manage exceptions by analyzing many signals to identify potential exceptions and automate or semi-automate the response to those exceptions

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