Big data and analytics have changed the way services are delivered across the world. It is vital for businesses engaged in field services to keep a close check on the satisfaction levels of their customers. Only if you score higher on this index will there be organic growth and scalability in your business. But where do you begin? This fundamental question arises in all sectors but only very few realize that the answer lies hidden in their organizations IT systems. We are talking about the huge pile of data residing in multiple IT systems across your business. Studies have shown that nearly 72% of organizational data remains untapped for further analytics in a typical company. Here is where analytics can create new dimensions for customer satisfaction.
Today, some of the world’s leading field service management organizations utilize predictive analytics to foresee the needs of their customers and ensure a seamless service experience every time they are engaged. Thanks to rapid strides in mobility, the field service sector have witnessed a digital transformation exercise wherein service records, job reports, bills, and other job essentials have begun to be communicated as digital offerings. In other words, it only takes a mobile app to guide a service agent to the customer location, get info about service requests, find help regarding service routine, generate bills, track service completion time and acquire feedback from customers. This digital initiative provides enough data for field service organizations to drive more innovations with predictive analytics for their operations. Let’s explore the top 5 scenarios where predictive analytics can become a game changer for companies having a major role to play in field service.
The consumer landscape has changed drastically over the past decade. Even though the phrase “Customer is King” has been around for ages, it’s only since the past couple of years that it became a mainstream phenomenon. The more you center your offerings around customers, greater will be their satisfaction levels and if you take a step back, your competitors are right at the door to pounce on your market share. With predictive analytics, customer insights can be used to deliver a more personalized service. An example could be assigning a field service job according to the preferred time schedules of the customer. Their preferences can be recollected from past interactions and can be initiated to drive personalized value to improve the organization’s customer satisfaction levels.
For a quicker solution to a problem at a customer location, it is vital for field service professionals to be aware of problem scenarios, and technical guidelines to work more efficiently. By deploying analytics, past service data and records can be analyzed to arrive at insights which could be helpful to resolve problems more faster, improved maintenance practices and even equip field associates with knowledge on what keeps a particular customer interested. Updating field associates with customer preferences can be particularly useful if most of your field service activities deals with sales and marketing. Faster diagnostics of problems are made possible when service history is known for analyzing data patterns of similar cases. Thus, predictive analytics go a long way in empowering staff with better skills to match precise customer needs and thereby deliver faster and more efficient field service.
The previous point explored how analytics could make your workforce smarter. Now we look at how it can help you choose the smartest workforce for every field service assignment. Thanks to digital records and data collection involved today, it is easier to monitor every service fulfillment task to evaluate each member in your field service workforce. Trends that have been previously ignored could now be used as a beneficial factor in the company’s favor. Insights from such initiatives can also be used to plan better training and awareness programs for your workforce so that they can improve their performance every time.
This scenario is especially true for organizations that have after sales service offerings. Based on the analytics of operational and maintenance data, it is possible to predict visits to customer locations for maintenance services. In fact, preventive maintenance is expected to save $630 billion over the next 15 years according to studies. Although, this requires the support of IoT as well to achieve maximum results. Nevertheless, maintenance forecasting will reshape field service requests in the future. In fact, companies can schedule visits well in advance based on expected service timelines. Past data regarding service history, asset logs, etc. can be run through predictive analytical systems to develop a preventive maintenance schedule for services.
This is a benefit that can be seen as a culmination of the other scenarios we have explored earlier. By improving customer service, a field service organization can build a more loyal brand reputation which will reflect in their future sales prospects positively. Better scheduling and worker assignment can result in more fulfilled work orders and better workforce engagement. Performance evaluation also becomes more streamlined as it is based on data points collected throughout their career lifecycle. It can also help in bringing down operational costs significantly by allocating resources faster and closer to the field service location and with transparent billing. The company can use insights from analytics solutions to plan their recruitment activities in advance for anticipated demands arising out of seasonal expectations, industry trends and a pool of other factors.
Predictive analytics has the potential to be a massive game changer in the field service industry. Organizations that tap into its strength can utilize rich insights derived to meet their end customer expectations exceptionally well. Additionally, it can form a backbone for decision making within your organization and help considerably in bolstering bottom line profits in the long run. With the growth of AI, IoT, and other innovations, there are numerous avenues wherein predictive analytics can transform the way field service management occurs today. Having the right technology advisory becomes crucial in this context to ensure that you achieve maximum results from your investment. Talk to us to explore possibilities in predictive analytics for your organization’s field service assignments.
Ashmitha works with ReachOut Suite as a creative writer. She collaborates with the Digital Marketing team to deliver engaging, informative, and SEO friendly business collaterals. Being passionate about writing, Ashmitha frequently engages in blogging and creating fiction. Besides writing, Ashmitha indulges in exploring effective content marketing strategies.
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