This is the last installment of a five-part series on service chain optimization. For more context, you can read the previous posts by visiting the links below:
- Part 1: Forecasting and Planning
- Part 2: Shift Planning and Management
- Part 3: Scheduling and Dispatching
- Part 4: Mobile Field Execution
In the final post of Dissecting the Service Chain, we’ll be focusing on what happens after all the action of planning and execution—performance measurement—the key to ensuring continuous improvement.
Before we dive in, here’s a quick recap (if you’re caught up, feel free to skip to the next section). Service chain optimization is the decision-making process for ensuring service excellence. The service chain encompasses everything that happens before, during, and after the day of service.
So far we’ve discussed:
- How to forecast the demand for service and ensure there’s enough resource capacity (people, skills, parts) to meet that demand
- The importance of effectively planning and managing field service shifts
- Methods for optimizing and automating scheduling, dispatching, and routing
- The importance of mobile workforce management technology to ensure operational visibility, real-time communication, and customer satisfaction
Why Are Field Service Analytics & Reporting Important?
After service delivery, field service providers must look back on how the day went and whether goals were met. And if they weren’t, what kept them from achieving them? Was it an inaccurate forecast? Were there enough resources to meet demand? What aspects of the business or process need improvement?
Though performance measurement is the final link in the service chain, things don’t really end here. Each link in the service chain is interrelated and interdependent on one another, which holds especially true in the analysis stage. Here, every aspect of service delivery is measured and assessed, and the results are fed back into the forecast and down through the service chain. This insight serves as fuel for continuous improvement of the entire service delivery process.
Benefits of Quality Analytics & Reporting
Field service analytics is more than simply collecting data. To gain actionable insights from the data, it should be complied in a clear, easy to read way. No matter who is reviewing it—whether the C-suite or a manager—they should be able to pull relevant insights at the moment they’re needed. This means the ability to view analytics anywhere at any time on a mobile device, and the option to drill down and only see the information that’s relevant to the user and what they’re tracking.
Armed with these well-organized insights, service providers can make faster and more effective decisions about how to improve service and key performance indicators (KPIs). Consider how analytics insights might be beneficial during a quarterly review with these examples:
- Improve KPI performance: You notice that average travel duration was high last quarter despite a short average travel distance. You look at the resource schedule map and see that the average number of tasks per technician is a lot higher in some regions than others. You experiment with task allocation, and now see a reduction in travel time and costs.
- Uncover trends and take action: You review time allocations compared to actual travel time and notice a trend—a specific task type is being completed much quicker than planned. You decide to reduce allocated execution time, lowering costs and improving resource utilization.
- Drill down to discover more insights: You review SLA compliance and notice there’s a drop in a specific district. You drill down further and see that the drop is specific to a task type. Then you drill even further and see it’s actually a specific technician who is tied to the drop. You decide to keep an eye on him and consider a mentoring program if things don’t improve.
Better analytics and reporting also allows service providers to make more accurate predictions to improve future performance. Service organizations are increasingly incorporating more data sources like weather, traffic, and customer demographics, and applying artificial intelligence and predictive analytics to get even more precise service delivery. Here are just a few examples:
- Weather: Track how weather has affected travel time, traffic, and cancellations in the past and take it into account in your forecast
- Traffic: Track historic traffic patterns to improve scheduling and routing accuracy
- Customer data: Use customer service history and demographics to predict the likelihood of a cancellation or no show and take this into account when capacity planning and scheduling
Field Service Analytics with ClickSoftware
ClickSoftware’s field service analytics and reporting puts role-specific KPI metrics directly into the hands of the business user for real-time and long-term decision making. Whether they’re a C-suite executive or front line supervisor, users can choose to see only the information most important to their role, share it with their department, and modify dashboards as they see fit—without the intervention of IT. With a constant stream of business intelligence and analytic data at their fingertips, users gain actionable insight and accountability for optimizing the business.
Armed with this information in real-time, at any location, managers and other business users can:
- Understand where the organization stands on KPIs at all times
- Proactively pinpoint inefficiencies in the system before they become costly obstacles
- Identify existing or potential problems and determine areas for improvement
- Make adjustments on the fly during the day of service
- Improve resource performance, increase operational efficiency, and enhance customer experience
Dashboard views of each department’s KPIs enable individual managers to track performance and drill down through specific performance levels and groups – territories, products, technicians, and customers. This allows them to view their department holistically or in granular detail.
Finally, with machine learning to analyze historical and real-time data, managers can make better decisions about demand forecasting, workforce capacity, emergency planning, predictive maintenance, travel and routing, scheduling, and more.