In a world where headlines and quick sound bites often substitute for deeper dives into conversations around a myriad of topics, it’s important to make sure you have complete information before making decisions.
This advice applies to field service management (FSM) too. A key component of FSM, schedule optimization, is an area that warrants particular attention to detail and specifics.
There is barely a field service management solution on the market that does not check the schedule optimization box. But there are important specifications within this broad topic.
While Serena Williams and Roger Federer check the “play tennis” box and some of the rest of us might too, those players are obviously at a completely different level of the game than the rest of us.
The Schedule Optimization Endgame
The ultimate goal of schedule optimization is to ensure the best result for the consumer while simultaneously maximizing the field service organization’s operational efficiency. This means ensuring the following for the consumer:
- the best technician or other field worker resource services the job
- the technician or other field service worker is armed with the right parts and information for all jobs
- the field worker selected costs the least and is the most profitable given all constraints
- the technician/field service worker is dispatched within the least amount of time possible.
Traditional schedule optimization attempts to reach these goals but typically has limited tools to accomplish them.
For example, finding the best technician may result in dispatching an acceptable one -- one that services a particular brand and has a certain number of years' experience. But it does not take into account unforeseen major weather or traffic events or other technicians’ schedules.
Furthermore, when taking into account blended workforces – those that include employees as well as outside contractors – the challenge of delivering the optimal field resource, which may be an employee or may be a contractor, is usually too much to ask of traditional field service management systems. This shortcoming is becoming even more of a liability in today’s gig economy and with many companies struggling to find and keep employees.
True Schedule Optimization – the Ultimate Goal
To really find the best field resource and also support them with the exact parts and other information needed to service the job accurately, at minimal acceptable cost without sacrificing service quality, and dispatch the job quickly, a field service management system needs to account for a plethora of variables. Only by accommodating an organization’s wide range of unique requirements can a system truly optimize the schedule.
The system should consider unmovable or unchangeable constraints. For example, limitations such as an employee’s work schedule or a contractor’s stated availability cannot change -- and the schedule optimization tool must be aware of that. If a technician needs to work in a facility that is not open or does not allow access during certain hours, the system must be mindful of that. Particular skills also need to be recognized. For example, if a technician only knows how to work on GE appliances, they should not be assigned to work on other manufacturers’ products.
Similarly, organizations typically have their own set of variable constraints based on their unique business or other requirements. This can include travel policies and costs, preferred customers, overtime policies, KPIs (e.g. efficiency, training, profitability), and more – the list is long, but critical to achieving an organization’s goals and priorities.
Importantly, conditions can and do shift throughout the day. If a schedule “optimization” system does not adjust accordingly, the optimization fails. What good is it if the identified technician is completely unavailable because of a major traffic problem – this type of event will throw off an organization’s entire schedule if not considered. And the big loser in this scenario is the customer experience.
Real-time, AI-based Schedule Optimization
Addressing the numerous and variable constraints to optimize these complex service schedules in real-time is literally impossible without sophisticated, AI-based technology. Combining AI technology with real-time route optimization provides a field service organization with the means to help its field workers deliver an exceptional customer experience on every job.
Stuff happens – best and best-laid plans go astray. It’s another long list that can cause this – weather and traffic events, sickness, job changes can all lead to mid-day or late-day complications. Only with an AI-based system can these all be addressed immediately, and all schedules adjusted accordingly.
With real-time, AI-based true schedule optimization, customer experience soars – and along with it, customer retention, employee retention, contractor loyalty, and profitability.
Ready to start your journey to true schedule optimization? Contact us today.