Field Services needs Evolution, not Convolution

Field Services solutions have come a long way from calendar-based scheduling and phone-based dispatching to the latest innovations using smart tracking, heuristic algorithms, and AI. However, as an advisor to both large and smaller fleets, I’ve observed over the last decades that the software industry’s trend is to go deep rather than broad. “Deep” here meaning a near myopic focus on function over broader integration, which can lead to over-engineered solutions wrought with unnecessary intricacy. The software industry seems to have been hypnotized into thinking the fancier the technology the better, when the truest solution lies in analyzing the problem from a practical, human-centered point of view.

For field services, the ongoing challenge is being able to consistently overcome high levels of unpredictability; field services are strewn with interruptions, from technician unavailability and missing parts to inaccessible service locations. When facing these challenges, some software integration consultants might give into this fixation with intricacy and formulate an approach that implements tools such as artificial Intelligence (AI) and advanced algorithms as the end-all solution, rather than simply leveraging these software capabilities as a supplemental aid for field service managers’ struggle with unpredictability. A kind of tech-before-practicality approach. Indeed, technologies such as AI and advanced algorithms are keenly adept at optimizing planning, but they can often completely ignore what FS managers ultimately rely on to persevere through the fickle nature of the field: Speedy communication and human intuition.

In the examples below, you will see that field service evolution does not equate to higher complexity and more features. The highest evolved system relies on seamless communication between the office and field workers, and the proper assignment of responsibilities to empower field and office workers at the appropriate level—and all of this executed with the human element in mind.

The first example concerns a large utility company in California serving over five million households and employing close to 1,200 technicians. The software company I worked with at the time was hired to implement a route optimization system for automated assignments and scheduling across multiple regions. The utility performed many different services and deployed techs with several dozen skill levels.

Our algorithms performed superbly in assigning the next day’s work to the right techs with the right skills. The next morning, the route planners in the office looked at the results, shook their heads and manually modified almost all of our calculated routes. You’re probably asking: Why? Because the route constraints did not follow human intuition or exception processing.

For example, on manually planned rural routes, a senior tech would also perform many low-level tasks just to prevent additional drive time. On the other hand, a router would assign a capable junior tech to tasks that typically a more advanced colleague would master.

Our advanced, award-winning routing algorithms were a helpful tool to create an optimized baseline, but could not replace the skilled route planner and dispatcher. Having learned our lesson, we later helped the same customer with a hands-on approach to allow for better tracking and dispatching via mobile devices and improved overall efficiency significantly.

The second example is that of a national pest control company that needed tools to manage recurring services. The company came with a large set of requirements, many rules, and the need for a customized user interface. As a result, the implementation team developed a custom system that handled all requirements with the ability to apply a rules engine to manage the different cases.

The system was a beautifully engineered piece of art that was promptly rejected by the customer services department as too complex. The routing engine crunched through billions of permutations before presenting an optimized result. It took a while to process and even longer for a human to test and verify that these results were really optimal. Frequent schedule changes forced a re-run of these calculations. What they needed in the end was as simple as manually moving a job from one day to another on the calendar. The system had to be much simpler and faster in managing exceptions.

Back then, we learned the hard way that trying to meet all wishes can make systems too complex. It is much more successful to leverage well integrated tools with lower complexity but with the ability to communicate more quickly. It seems that today’s websites and advertisements are full of shiny new tools that have one thing in common: they tend to distract from the basic needs and overcomplicate systems that are meant to support quick decision-making for a team under pressure.

Here’s the gist:

Most technicians are highly skilled and know their territories or customers well—they just need some planning support to take the baseline results and use their experience to create human-optimized routes. If these routes deviate significantly (e.g. in miles or time) from the mathematical-optimized routes, a routing manager may need to help train these techs. Allowing humans to make changes within a set framework creates self-empowered satisfaction, ownership, and a customer-service oriented culture needed for competitive services. The FSM evolution combines tools automation with the intuitive expert knowledge of field technicians.

Here are the essential requirements for the evolved FSM solution:

• Order-taking linked to sales, CRM, and accounting
• Capacity planning and, in some cases, long-term scheduling capabilities
• For a high number of daily services per route: stop sequence optimization as a baseline
• For a large number of technicians with overlapping skills/territories: route assignment optimization as a baseline
• Short-term scheduling tools with resource availability
• SMS/email communication with customers, techs, dispatchers
• Mobile App (with disconnected mode) for field workers that ties to field services, inventory, sales, and accounting
• For techs managing parts, tools, etc.: inventory integration
• List views that allow dispatchers to quickly assign and schedule
• Manual scheduling tools that allow the tech to quickly modify and compare best route sequences.
• Time-line views (Gantt charts) for larger deployments.
• Automated status updates between dispatch, techs, and customers.

These requirements lead to an FSM solution that integrates with other business systems, namely accounting, sales, CRM, inventory management, logistics, purchasing, and mobile enablement.

These non-FSM functions are well supported by most ERP systems. The evolved FSM system needs tight integration with these ERP business systems that handle customer relations and all the financial operations. But which ERP systems integrate well with FSM?

About five years ago, at the request of a customer, I researched ERP and FSM integration in depth. I already had some detailed insight based on work with SAP, IBM, Click Software, and other partners. What I had observed with these partners was also true with other ERPs and services tools: Traditional ERP systems struggle with the seamless integration of FSM as merely an afterthought. Further research showed that Open Source ERPs are much easier to extend and integrate.

In teaming up with OSI and the open source community, we were able to build a flexible open source ERP / FSM solution based on Odoo. This was the solution I was missing all these years ago when working with the utility company, the pest control organization, and many other fleets.

In summary, I recommend that companies looking for an evolved FSM that integrates across all business units should start with Odoo and Open FSM (free downloads are available).

Wolfgang leads Mobile Resource Management and Logistics at Open Source Integrators. His role is to support organizations by understanding their unique business processes and applying analysis, optimization, and technology to increase margins while considering social responsibility and sustainability.

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