For many field service operations, there’s often a dilemma involving scheduling and capacity management. To understand the dilemma, it might be helpful to revisit an old joke you may have heard long ago:
A drunk is pacing back and forth searching for something underneath a street light late at night. A policeman out walking his beat stops, thinking he might be able to help.
“What are you looking for?” asks the officer.
“My keys,” says the drunk. “I dropped them across the street."
“Across the street? Then why are you looking for them over here?”
“Because there’s no streetlight on the other side.”
Yes, the drunk is engaging in a pointless exercise. But it’s an exercise that somehow seems more likely to pay off than searching in the dark (even if that would actually be more worthwhile).
So how does this relate to capacity management and scheduling? When trying to optimize field service performance, people often focus on scheduling because they have the right tools for that task. But if you don’t actually have the resources to deliver against the schedule you’ve developed, it’s likely to lead to frustration – like looking for your missing keys in the one place that you know they definitely aren’t.
In fact, IDC has estimated that glitches caused by errors and surprises in the planning process wind up costing businesses between 20% and 30% of their revenue potential.
The key to solving this dilemma – and capturing that elusive missing potential revenue – is to complement a robust scheduling capability with robust capacity management. The ideal – if elusive – solution to capacity management would address four related, but distinct, challenges:
- Capacity forecasting
- Capacity planning
- Capacity utilization
- Capacity automation
Here’s an overview of each of these capabilities, with an eye toward how a field service management solution should address them.
Most field service operations would love to have a crystal ball that provides educated guesses about what’s likely to happen in the future, whether you’re looking at scheduling maintenance, customer premise equipment installation, or other tasks. And of course, what you really want something more reliable than just educated guesses.
Capacity forecasting uses configurable AI to make sophisticated and accurate projections based on a number of factors, including industry- and use-case specific models combined with as much data as you can throw at it. This makes it easy to:
- Predict demand based on historical data
- Calculate the workforce requirements you’ll need to meet projected demand
- Run what-if scenarios to explore a variety of possible business decisions
For example, a fiber-to-the-premises provider could determine if they have the ability to support the surge in demand expected to be generated by running a marketing campaign in a specific geographic area.
With a reliable forecast in hand, you can focus on what will often be your next step: translating the impact of your capacity forecasts (and other information about upcoming demand) into detailed plans for your workforce and other resources. This will streamline your processes for:
- Mapping out detailed capacity allocation plans for your workforce
- Accurately projecting shift schedules and overtime budgeting
- Creating a real-time dashboard to track capacity and demand metrics
The next piece in the capacity puzzle is to assess and analyze your real-time capacity in real time so that you can continuously adjust how you’re distributing your workforce to match demand in response to requirements that are constantly in flux. For example, suppose you’d planned to have 15 technicians available in a particular area on a particular day, based on your forecasts. But on that day, 1 tech is having car trouble and another has called in sick. The challenge is too quickly reallocate capacity that’s already getting consumed in real time.
With tools for analyzing capacity utilization, you’ll be able to:
- Make capacity decisions based on the best available and most current data
- Re-allocate capacity variables (such as workforce hours) to meet demand
- Ensure that end-customer appointment-booking rules reflect true capacity and availability
- Easily adjust your scheduling with either points or hours
The key to effective capacity management is to apply automation across all of these areas: forecasting, planning, and utilization. Automation triggers different benefits when applied to each area inside a field service management (FSM) solution, including:
- Forecasting: By automating the forecasting process, the FSM can automatically flag and address the impact of relevant information such as weather and traffic conditions or other variables that can impact the forecast
- Planning: With a forecast that reflects a variety of variables more accurately, you’ll be better able to optimize your planning process
- Utilization: Whenever unexpected circumstances crop up that can affect your consumption of resources, you can expect real-time recommendations on the best actions to take that reflect the most current information available
Equipped with comprehensive information, projections, and real-time dashboards to monitor capacity, the final logical step is to implement automation capabilities to generate recommendations and alerts based on any current conditions that require actions or decisions, such as if capacity becomes maxed out. You can expect to use leverage capacity automation to:
- Streamline the reallocation process
- Automatically generate new capacity plans that reflect any changes
- Flagging any out-of-line conditions that require immediate attention
With the right capacity management tool, you can enhance your scheduling and other processes by ensuring that your decisions are based on the most reliable information available, with that’s historical data or reliable projections. And by consolidating all of the information related to – or derived from – real-time capacity data, you can streamline your ability to make informed decisions.
What would this kind of capacity management solution actually look like? Watch this space!