Decoding the Service Chain: What is Service Chain Optimization?
Every customer-centric business is ultimately measured by how it performs on the day of service delivery. But the day of service is just the last link in the chain of decisions made weeks, months, or even years in advance. And sometimes your best-laid plans don’t play out as expected. Disruptions in the schedule are bound to happen the day of—customers cancel, jobs take longer than anticipated to complete, traffic conditions vary, and technicians call out sick.
So how can you possibly ensure your techs are at the right places at the right time, while increasing productivity, delivering positive customer experiences, and keeping costs down—even when managing the unexpected?
For one, you must consider the entire service chain, or everything that occurs before, during, and after the day of service. Let’s dive deeper into what this means.
Service Chain Optimization
The modern-day customer has more power than ever before. With companies like Amazon and Uber setting the bar for customer experience, customers today demand and expect reliable, flexible, and almost flawless service. And that’s not impossible to deliver.
In 1996, ClickSoftware coined the term “Service Chain Optimization” (SCO) to define a decision making process for ensuring an efficient day of service. It considers the full life-cycle of service delivery, from the early stages of forecasting and planning, to scheduling and dispatching, to execution and analysis. And it’s meant to help you find the optimal balance between business goals and customer expectations.
It’s important to understand that all the steps in SCO are interrelated, and that missing steps mean service delivery could suffer. Let’s say a dispatcher jumps right into assigning work without considering how many resources are needed to meet demand or their available capacity. They might have too many technicians on a given shift, which is expensive and creates excessive idle time. Or they could have too few techs available for work, which would mean slower response times and frustrated customers. Likewise, without proper planning, a tech might find that he or she is without the right parts to complete a job—again, leaving the customer upset.
It’s not hard to understand why it’s important to consider all links in the service chain. Let’s break it down into the three major stages:
The Months, Weeks, Days Before: Planning
Ultimately the goal of SCO is to ensure your technicians are at the right place at the right time, fully prepared to meet customer demand. But as the service day is full of unpredictability and variation, success is derived from what happens in this planning stage.
Planning involves predicting the expected demand on a particular day or week, based on past performance and many other factors. And it’s where you determine the optimal amount of resources you’ll need to complete every service call, without over or underestimating. Historical data (or anything gathered from the analysis stage) can help you make the right decisions.
The Day of: Execution
The day of service is where everything happens—from scheduling and dispatch, to fixing the customer’s problem and following up with a survey. Though a schedule may have been created days or weeks in advance, not everything will go according to plan. There will likely be customer cancellations, traffic delays, or emergency jobs, which will require real-time management.
As noted, the success of this day depends on the planning ahead. You may not know exactly what’s going to happen on the day of service, but you better be prepared for anything that comes at you. This stage relies heavily on maximizing your time and responding effectively to changes. So it helps to have the flexibility to reshuffle the schedule as new jobs appear.
The Day After: Analysis
We all know that service doesn’t end with execution. In the final stage of the service chain, field service providers must look back on how the day went and whether goals were met. And if they weren’t, what is it that kept them from achieving their goals? How did customers feel about the job done?
Because you can’t improve what you don’t measure, track your performance and use customer feedback to continually improve quality. You can also monitor the performance of regions, districts, and individual technician behavior to target areas of improvement. Although it’s called the service chain, it might be more accurate to think of it as a continuous cycle, where you feed the results of your analysis back to the forecasting and planning for subsequent visits.
Use artificial intelligence to your advantage
You might be wondering how a mere human can possibly optimize every step in the chain, make accurate predictions, and quickly reshuffle the schedule when something comes up. Fortunately, with the power of artificial intelligence (AI) and machine learning, you can automatically optimize schedules and make accurate predictions in seconds.
Here’s an example: with a mobile workforce, it’s important to reduce idle time and keep technicians moving so they can complete more jobs and make as many customers happy as possible. AI-driven technology can take into account both historical and real-time traffic data to quickly choose the best travel routes to customer sites. By avoiding traffic, techs can complete the job faster and move on to the next.
Or consider when there are schedule disruptions. Instead of leaving white space when a customer cancels, the AI-driven technology can account for technician locations and automatically dispatch them to another nearby job. Likewise, to make room for emergency jobs, the system can take SLA requirements into consideration and reshuffle low priority tasks to make room.
The achievement of Service Chain Optimization is a journey, but with the right technology, proper planning, and analysis, it’s possible to deliver near flawless service to your customers. Over the next few weeks we’ll continue to discuss the service chain, delving further into the components and how to achieve optimization.
In the meantime, you can learn more about field service optimization and best practices by subscribing to Field Service Matters.
Categories:Artificial Intelligence, Field Service Management, Scheduling & Dispatch Management, Workforce Management Trends