The field service management (FSM) industry revolves around incidents that are handled by end employees. The incident life cycle begins with the initial submission and ends with a resolution to the problem. Incident tracking or ticketing systems have been around for years. Moving these systems to the cloud has been the biggest tech-based evolution in the industry so far.
The Current State Of Service And Why It Needs To Change
Today, the customer service industry is complex. Support technicians need lots of time to resolve issues, use more parts than they need, and are bombarded with having to support multiple products and versions. At the same time, hardware and software product companies are shifting toward service-driven revenue growth. Unfortunately, all aspects of service and FSM / ITSM systems are workflow-driven, time-based or monitoring-based and reactive. Automation of these systems alone will not fulfill the needs of the enterprise. It requires a new class of solutions that taps into the systems of record to create a system of intelligence through which decisions can be made.
There are four primary reasons why faster resolution of service incidents should be made more effective:
1. The scaling issue: Incident tickets do not come from humans alone; there are also product-generated alerts. The assignment of a remote service agent can take a while. Agents need to be quick in diagnosing the problem as well as the resolution to the problem. Even with human-generated tickets, products getting so complex, with shorter product life cycles, that remote staff members need help in diagnosing problems and providing quick resolutions. It costs an average of $250-$1,000 per ticket. For hardware companies, costs go further up when having to send a technician for repeat fixes. SaaS companies resolving 86% of customers say they will pay more for better service. By 2020, customer service will drive sales more than product or price.
2. Complexity: According to Field Service’s Future Trends report, 81% of companies believe smart connected products will be implemented in the next five to 10 years. With the advent of robotics and innovations in manufacturing and materials, digital equipment out in the field is complex. Problems are diagnosed remotely. When an issue can’t be diagnosed, a dispatched technician goes in to diagnose the problem and then makes multiple visits to install the part in place. Instead of worrying if a technician has expert knowledge in regard to a particular problem, automation can help identify a problem, make sure the parts are in place and provide detailed instructions for fixing the issue so a field technician can focus on the customer relationship and procuring new opportunities instead of the diagnosis. 63% of agents are solving difficult problems in high-performing organizations versus 43% at under-performing companies.
3. Staff skills are changing: Service staff that supports legacy systems also need to be trained to support new systems. Baby boomers are retiring at a rapid rate, and as they ride off into retirement, companies are losing tribal knowledge. Sixty-five percent of service training is outdated. I’ve seen firsthand how millennial recruits no longer have the touch-and-feel experience or understanding of the equipment, and they don’t consider field service as a long-term career.
So, new recruits need to be trained constantly. These new recruits come in with college degrees that companies want to utilize. Businesses also want to put the soft skills of new recruits to good use to increase revenue in customer-centric environments. Before a dispatch happens, a problem is identified, the part that’s required is procured, and cheat sheets on how to resolve the issue are readily sent to the field technician’s device. Having an automatic problem and solution resolution with cheat sheets on how to replace a part allows staff to focus on the customer rather than figuring out how to solve the problem.
4. The business model is evolving to a “pay as you go” model: As companies explore this model, the only front end to the customer is field service. With the new model, companies are forced to have an efficient way for incidents to be automated. As the business model evolves, there is also a servicing model evolution with democratized field service. As of this article, there are around 9,000 data science engineer jobs versus 34,000 field service engineer jobs posted on LinkedIn worldwide.
If your company is considering automating aspects of its field service operations, here are a few tips to consider to ensure it’s a successful endeavor:
Understand the evolution of data within your organization.
Make sure you have the relevant data for the business problem you are trying to solve.
Get agreement on the usage of automation from all stakeholders. The last thing you want is to implement something that has organizational pushback in regard to adoption. One of the best ways to increase adoption is via a value calculator.
Changes in the field service business environment warrant new technology to help take it to the next level. In the next article, we will discuss the long-term benefits and value calculation/return on investment (ROI) of solutions that address the automated service world.