These days, most businesses with field-based workers have adopted some form of mobile workforce management software. Customers’ expectations of service are very high, and employees expect the latest tools to help them do their jobs.
Even with the most sophisticated and ‘joined up’ systems (and, let’s face it, many are not), some companies are being let down by their mobile workforce management solutions. They have plenty of field service data, but lack the analytical tools and skills to gain insight into how to improve their field service operations. And with ongoing cost pressures and increasing competition, there is increasing pressure on field service professionals to make any improvements, large or small, that will add up to significant gains in productivity and customer satisfaction.
Sometimes top-level mobile workforce data can only give a top-level view of performance – you need to look deeper to understand what is really happening out in the field. Each of the following scenarios comes from a real-life situation that one of our customers experienced. In each case, top level data seemed fine, but it was hiding a problem that only more detailed analysis could reveal.
Task Duration: Hidden productivity improvements
One field service company we worked with had assigned expected task durations to a range of typical tasks that their engineers undertook in the field, based on experience and analysis of previous work. When they looked at the overall Task Duration metric, it appeared that they had pretty much got it right, as the total amount of actual time that tasks were taking was close to the plan. All well and good, except they had a problem with a high level of missed appointments. Why were so many appointments being missed, when tasks were taking the right amount of time? We worked with them to undertake a more detailed analysis of task durations, and discovered that the average was hiding some inaccuracies. Some task types were always taking longer than planned, which meant that engineers were missing the subsequent appointment. But because some other task types were always taking less time, the average still looked OK, and engineers with the shorter tasks were left with unproductive time. We adjusted the planned task durations, and our customer found they could improve engineer productivity, and stop missing so many appointments.
Dislocated tasks: When things aren’t going to plan
If you use your mobile workforce management solution only to see the status of tasks, but not the location of the engineer, you may be missing inconsistencies and inefficiencies that could be improved. If you can link task status to location, you can begin to build a more detailed picture of how your team are performing in the field, and take action to improve that performance. For example, what do you do when your mobile workforce management solution shows that your engineer has started a task, but you can see he or she is physically located 10 miles from the task location?
Another of our field service customers told us they were experiencing these ‘dislocated tasks’. They were able to trace the root causes by following up the individual engineers involved. There were a number of explanations including: the engineer started the task on leaving home, rather than on arriving; the engineer had gone to pick up missing parts or tools; the engineer had completed the task and forgotten to end it on their mobile app. Each of those situations had the potential to derail the plan for the day, and cause our customer’s operations team a management problem. Each needed a different approach to resolve it. Sometimes it was simply human error, and once alerted, the engineer was less likely to make a similar mistake. Sometimes it was a training issue, easily resolved by sending a broadcast message to engineers to clarify the procedure. On other occasions it required changes to the processes – for example the operations team reviewed its inventory processes and adjusted which parts and tools need to be on the vehicle for particular tasks. All of these small adjustments contributed to keeping the field service operation running smoothly.
SLA compliance: Extra time for more tasks
Another of our customers operated in a B2B field service environment, and had strict SLAs around appointments and arrival times on most contracts, with financial penalties for breaches. As a consequence, the company was really good at meeting SLAs, and prioritised compliance above other metrics. However, what they didn’t realise was that they were too good. Detailed analysis showed that they were typically meeting the SLA within the first 25% of the allotted time. For example, if they had a two hour window within which the engineer was planned to arrive, the engineer would be there in the first half hour. This was great for customer service, but not so good for operational efficiency. We worked with our customer to conduct more detailed analysis that revealed that if they could shift to meeting SLAs in the 75th percentile – 90 minutes into the two hours – they could schedule another task per engineer per day, and still keep their great compliance record. With a workforce of around 100 engineers, this gave the company significant efficiency improvements, and much less downtime
Overall, these stories demonstrate the seen the value of advanced analytics tools, such as Cognito’s Insight Hub; the application offers a window into field service data, organised by key dimensions such as utilisation, efficiency, quality and effectiveness. Using Insight Hub, field service professionals gain visibility of what is happening in the field, in real time, so they can act to correct any issues. It also enables them to review past performance by ‘replaying’ the operational flow, and the events of the last shift, day, week or any other time period, to analyse when, why and how exceptions occur, in order to make the changes that will prevent similar exceptions in the future. If you’d like to know more, visit https://www.cognitoiq.com/resources.