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January 18, 2021 | 4 Mins Read

Predictive Service: From Objective to Reality in 2021

January 18, 2021 | 4 Mins Read

Predictive Service: From Objective to Reality in 2021


By Sarah Nicastro, Creator, Future of Field Service

Like most of the major service trends, predictive capabilities come up in almost every conversation I have. Some organizations have already achieved this nirvana, but many are still at the point of recognizing the potential but not yet translating it into their reality. I expect we’ll see significant evolution in this area in 2021 and that’s because while there are challenges to overcome, as with any change, the opportunities are simply too immense to delay in pursuing.

IFS conducted a global study with 3,000 participants in the Spring of 2020 to examine digital transformation priorities, and as Bob De Caux discusses in this article, found that intelligent technologies (AI, machine learning, predictive analytics and cognitive services) lead the charge with 64 percent identifying investment in this area as important. This aligns with what we see within service, because the role intelligent technologies play in enabling the shift from reactive to predictive service is a natural progression for organizations that have mastered the basics of service management.

This natural progression makes perfect sense. We know that customers are demanding far more from the service experience than for an issue to be resolved when it occurs, regardless of how efficiently. Customers want peace of mind, they want guarantees, they want uptime. Intelligent technologies and the move to predictive service are how you deliver upon these expectations. We know that predictive models eliminate or at least minimize downtime, reduce costs for both company and customers, improve customer satisfaction, and enable you to expertly orchestrate both your resources and assets because you’re gaining insights into what will happen instead of reacting to what already has. In many instances, the superior level of predictive service can be monetized to create additional revenue.

So, with all this potential, why haven’t we seen more companies master predictive service already? Well, there are a number of reasons. First, before the progression to more advanced intelligent technologies you must master some foundational aspects of optimizing service. This simply takes time – companies have been hard at work standardizing, optimizing, and automating service in order to reach a point where they can successfully move to predictive. I see that time as now for more and more organizations. Second, the shift can be a bit overwhelming. The potential is vast and opportunity significant, which means the stakes are high and the change is big. One point to consider if this rings true to you is the idea of thinking big but starting small. Just because the opportunity of intelligent technologies is vast doesn’t mean you have to realize the whole of the opportunity at once. Moreover, as De Caux discusses in the article linked earlier, these technologies build their learning upon data, so the sooner you start, the more sophisticated you can become – when you’re ready.

In addition to “think big, act small,” here are a few points to consider as you chart your path to predictive service success:

  • Choose your intelligent technologies wisely. The idea here is to master complexity in order to delivery the ultimate simplicity to your customers – uptime. To do so, you need to choose technologies and technology providers that will streamline, simplify, and offer cohesiveness – not complicate matters. Doing as much as you can in one platform is helpful – which means finding a provider that can not only address your short-term objectives but build upon your success over time.
  • Be ready to feel uncomfortable. In a reactive service world, most everything is manual. In a predictive environment, you must begin to trust the technology. Using AI where you’ve previously used manpower can be an uncomfortable feeling, for you and for your employees. You have to remember why you’re introducing the technology and what it can do and fight the urge to step in and override out of habit.
  • This is because predictive tools learn over time, and if you don’t allow them the space to do that, they won’t achieve the optimal output they’re capable of. Give the tools time to learn and time to work and be ready to be in awe of what they can do.
  • Harness the wins. As you see success, shout it from the rooftops – internally to help manage change, and externally as you recreate the customer experience. Once you start down the path of leveraging intelligent technologies, you’ll be on a path of continual opportunity – once you achieve success, you can look for ways to build and expand. At first this may feel overwhelming, but once you experience those first wins, you’ll quickly transition from overwhelm to excitement at all the possibilities.