Field service management is vital to almost all enterprises in today’s world. It can often make or break a company’s reputation and its customer relations. For clients in certain fields like healthcare, where hospital devices need to be up and running continuously, service delayed can be tantamount to service denied. Saving the customer’s time and providing prompt assistant always leads to higher consumer ratings for the service provider, and harnessing the power of predictive analytics in the utilization of information can work wonders for your enterprise.
The field service sector is no stranger to Big Data. With the advent of digitization, the flow of information in every industry has been dizzying. Field service organisations help bear the brunt of this binary onslaught too – data is generated by various sources ranging from GPS and location systems to client details. With Internet of Things (IoT) thrown into the mix, the unprecedented connectivity and integration of devices that it fosters has increased information assets of field service organisations manifold. The dormant potential of these heaps of unused data gathering dust in company servers and applications is slowly being realized, and many enterprises have begun to invest resources in channeling this data flow into improving efficiency and productivity.
Predictive analytics has been steadily gaining importance over the last year with business to business (B2B) enterprises. 89% of B2B marketers planned to employ this form of analytics, as was seen from the study commissioned by Everstring. The study elaborates on the benefits of predictive analytics to businesses, stating that marketers employing these techniques are 1.8 times more likely to exceed organisational goals and 2.9 times more likely to see a growth in revenue at higher-than- average rates.
This branch of analytics is a goldmine for the field service management sector to exploit, too. Data obtained from fleet vehicles can be used to predict maintenance requirements and avoid the inconvenience of having a vehicle breakdown in the middle of a job. Data received by back offices from customers’ devices can be used to anticipate service visits, thus allowing dispatch to schedule repair jobs before the need arises for the customer to seek urgent help.
Field Service Management software tools can improve performance considerably by using this technology. The FieldEZ software application for field service management also offers enterprises the use of its IoT and Analytics tools, using data received from IoT-connected client devices to automatically generate service tickets, schedule appointments and assign the best-fit technician based on factors like skill-set, proximity, etc. Machine learning algorithms and predictive mechanisms are used in conjunction with IoT to analyse the data transmitted by sensors embedded in company vehicles and derive the likelihood of equipment failure.
Field service management is not a luxury, but a necessity for both large companies as well as small and medium enterprises. FSM is the key to bridging the distance between the needs of the client and the company’s solutions. Introducing innovative ways to maximize customer satisfaction and optimize processes is the need of the hour, and predictive analytics brings the future ever closer to now – literally!
https://www.fieldez.com/wp-content/uploads/2017/11/The-role-of-Analytics-in-field-service-management-.jpg9601956fieldez-adminhttps://www.fieldez.com/wp-content/uploads/2020/02/FieldEZ-Logo.pngfieldez-admin2017-11-16 11:31:362017-11-16 11:34:04The role of Analytics in Field Service Management
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