The Age of the Real-Time Service Enterprise
As customer expectations for faster service delivery grow, utilities, telcos, home and office computer and equipment suppliers, etc. encounter more challenges in building and maintaining daily work schedules to ensure technicians arrive at jobs on time and work productively. The maturity of mobile devices, GPS and other technologies offer unique opportunities to address these challenges in a cost-effective manner.
In the past five years, service organizations have evolved from having little to no contact with technicians in the field, to communicating with them using cell phones and other mobile devices. Some service organizations still deliver schedules to workers every morning solely by phone, fax or in-person pickup at the office. More and more service companies deliver schedules electronically to technicians' hand held device and, as the day progresses, the companies receive reports of the technicians' jobs status. Many companies have deployed global positioning systems (GPS) to see large maps of where their workers are throughout the day. Some are using street-level routing (SLR) to give drivers the shortest route from job to job.
These are important developments, but are only the beginning. Organizations that use mobility technologies merely for communicating information between the dispatchers and the field force are not leveraging the full potential of mobility technologies because the burden of decision making is left for the dispatchers. With even a small workforce of a few hundred technicians, reacting adequately and in real time to the constant stream of new field data is well beyond the capabilities of any human brain.
Modern service organizations recognize that real-time communication devices (mobile phones, handheld computers, laptops, GPS units, etc.) are not just about data transmission and map displays. Rather they are about the ability to act in real time on these data and produce optimal decisions for resource allocation and job scheduling. By connecting decision support and optimization algorithms to the real-time stream of field data, this objective is achieved and the schedule is continually optimized.
Consider for example, a situation with a field technician (T1) who is already 40 minutes late leaving the first job of the day at customer (C1), jeopardizing the next job's on-time arrival. Focusing on the job at hand, he forgets to report that he is late. By the time he does report his status, he's lost critical time. Imagine now that the field force of the company is equipped with GPS and handheld mobile data devices. Imagine again that a real time automatic optimization algorithm is continually watching the location of all technicians and is "listening" to the data streams that arrive from the technicians' mobile devices. Noticing that T1's location continues to be at C1 beyond the time he was expected to finish, the algorithm will monitor the delay and, at a certain point, will look for a resolution to recover from the chain effect of this delay. It could very well be that not too far from T1, another technician (T2) reports that he completed his first job earlier than expected. If he has the right skills, the algorithm will evaluate the possibility of switching T1's second job to T2. If need be, the algorithm will also inform a customer service representative to notify customers about late arrival or possibly a postponement until the next day.
Decision support and optimization software for service delivery execution is the cornerstone of many leading service organizations. Software agents constantly "listen" to the stream of incoming information from the entire system; including new emergency jobs, jobs that take longer or shorter than planned, or a technician who is stuck in traffic. Algorithms process that information against a broad set of variables and business rules such as technician skill set, geographic region, tools on the truck, etc. and determine how to keep the schedule continually optimized throughout the day and across the entire enterprise.
Other real-time technologies and practices that will streamline scheduling and boost productivity include:
- drip feed scheduling - A field technician gets two jobs to start out the day. When the first job is completed, the system provides the third job.
- online traffic updates - Street level routing gets workers from Point A to Point B in the fastest way. By incorporating into the algorithm real-time traffic updates such as traffic jams due to accidents, closed bridges, construction and other delays better practical routes or re-routes are proposed to minimize the impact on the schedule.
- integrated RFID - Connecting radio frequency identification technologies with scheduling and asset management systems will enable service organizations to know exactly what spare parts each technician has on each vehicle, to better optimize scheduling.
What was optimal an hour ago may not be optimal any longer. Being able to act in real time and modify the daily plan to continually maintain optimality ensures that we squeeze the most out of the available capacity and respond in a manner which is consistent with our business priorities. Advances in real time mobility reporting via handheld devices, GPS, RFID or other, enables service organizations to deliver on their promises to customers while remaining profitable.