What is optimization?
M&W defines it as:
Field of applied mathematics whose principles and methods are used to solve quantitative problems in disciplines including physics, biology, engineering, and economics. Questions of maximizing or minimizing functions arising in the various disciplines can be solved using the same mathematical tools.
In a typical optimization problem, the goal is to find the values of controllable factors determining the behaviour of a system (e.g., a physical production process, an investment scheme) that maximize productivity or minimize waste.
In other words, field service optimisation is the attempt to archive the best performance from your system given the conditions you have with the control over the variables.
For field force systems , the variables are the resources (the capacity and availability of your field technicians), the customers (the service calls) and often, the geography (depending on the type of service, for remote service for example when no site visit is required this of course is meaningless)
The optimal results again depend on your business and market but in a very loose way, your revenue and expenses, Trying to get maximum revenue with minimal cost to you.
Why do you need it?
Operating a service organization on this level of optimization is a constant battle between planning and real time events that are injected into your plan.
The task of optimizing the schedule and managing your field service is a task assigned to your back office service delivery teams including schedulers and dispatchers. Many do it without thinking and know the schedule inside out and how to overcome issues by keeping expenses under control. However, no human can manage with all the variations that exist in a system. This will simply be an impossible task for any human to do in a reasonable time.
Although computers are getting faster and better, the task of optimizing a complete schedule is still not widely available. What we are talking here is more of a local optimization, areas of improvement that are overall improvement but not a global optimum. Putting it in different words, automated schedule optimization is not achievable but any good optimization system can and will achieve far better results (and faster) than any human can.
SO what is field force optimization?
Optimizing a schedule as we have seen is a complex problem involving a lot of data. Many variables and strict time constraints make it imperative that you react quickly to changes that happen in real time.
Field force schedule optimization is therefore the process of locally optimizing (or improving) a small region of the global schedule (such as a small group of resources or a geographically isolated area) by searching for small improvements that will lead to overall efficiency.
Does your system allow you to optimize in real time?
If it does, how well can it do it? Competing with your best scheduling team (human), can it reduce your operational costs and deliver more out for your existing field force resources?
Many claim to be able to do so but only a few actually do.