Artificial Intelligence Gets Real in Field Service

6/03/2019 / Digital Transformation / Field Service / Katia Loboda

Deliver Smarter Service Through Artificial Intelligence

Artificial Intelligence (AI) is not a foreign concept in field service. In fact, it has been around since the 1950s. Until recently, thought leadership and market outlook reports about AI were predominantly forward thinking. But today, 72% of field service leaders see AI as a central technology tool.

Recent advancements in data analysis and expansion of connected “smart” devices have stirred a new infatuation around AI within the service industry.

In fact, a recent Astea-sponsored Field Technologies whitepaper, Artificial Intelligence Gets Real in Field Service, reports that:

  • 60% of surveyed respondents believe that AI is currently powerful enough to drive business processes
  • 71.8% indicated that AI will have the greatest disruptive impact on any technology
  • AI will create a 1.2% increase in GDP over 10 years and capture additional 25% in new economic benefits
  • AI-fueled factories could add up to $1.5 trillion to the global economy by 2022

Let’s look at where we are in terms of AI adoption in service applications.

Rapid Growth

Across industries, implementation of AI grew an estimated 270% over the past four years while deployment increased by 12% in just 12 months. The adoption of AI is particularly favorable for the field service segment. Artificial intelligence relies on abundance of good data to function properly which is something that field service organizations (FSOs) already provide. Most organizations are already utilizing technologies such as GPS, connected devices like the Internet of Things (IoT) and dynamic field service management software (FSM) tools that collect large amounts of data on equipment, technician expertise, location, service history and so much more.

A NewVantage Partners Big Data Executive Survey 2018, discovered that 97.2% of executives confirmed that their organizations are investing in AI initiatives. This will have a significant economic impact. In fact, the McKinsey Global Institute estimates that AI will create labor shifts that will result in a 1.2% increase in GDP over 10 years.

Applications

With the advantage of already collecting large sums of data, FSOs have been able to identify specific pain points that AI can address by building on automation systems – from online troubleshooting to diagnostics, scheduling and service parts planning.

Deployment of Artificial Intelligence is being greatly driven by the adoption of smart devices for remote diagnostics as well as the shift from reactive to outcomes as a service model. FSOs are altering how field service is delivered through these real-world applications:

Customer Experience today is built around addressing customer needs instantly and effectively. But using a live representative to answer every customer concern often creates delays and frustration. To address this issue, companies have increasingly begun utilizing chatbots.

Gartner’s survey found that 52% of companies have already deployed chatbots.

These interactive interfaces driven by AI are increasingly being implemented for first-level service interactions. Through simple contextual conversation tools, customers are automatically guided through a series of questions and have their issues resolved right away or have more complicated problems escalated to the correct department during their first point of contact. By escalating inquiries faster in a more efficient matter, service providers not only alleviate common help desk frustrations but in fact save time and labor costs and improve customer satisfaction.

Dispatch, Route & Scheduling Optimization is an area where AI already has a strong foothold in field service. Currently, a dispatch scheduling engine (DSE) uses algorithms for route and scheduling optimization. With the help of AI, organizations can automatically change routes and job assignment on the fly. As the technology gets smarter, it allows routing solutions to adjust routes and schedules based on changes in traffic, weather, technician experience and customer preferences, creating smarter scheduling and service solutions.

Inventory Optimization is one of the main concerns when it comes to achieving efficient warehouse operations, technician utilization and a high first time fix rate. By feeding information such as service history and failure codes into an intelligent forecasting tool, FSOs can predict the likelihood of equipment failure, service needed and frequency and the best mix of spare parts to ensure that their service technicians offer proactive maintenance and always arrive to their job site with the right parts. But to maintain accurate inventory, you must streamline manual processes and optimize parts replenishing and picking. This can be achieved through a proper warehouse management solution. Alliance Warehouse Edge brings logistics supply chain data and warehouse operations to your FSM solution, making your warehouse workers fully mobile. By maximizing warehouse efficiency, your organization will benefit from lower inventory management costs, higher service level agreements (SLAs) met and transform the way you deliver service.

Challenges to Adoption

As with any new emerging technology, adoption of Artificial Intelligence doesn’t come easy. When AI initiatives fail, it can be traced back to these main reasons:

  • lack of leadership
  • lack of focus on specific problems to tackle
  • lack of data science expertise

One of the key ways to overcome these barriers is to identify specific pain points and applications where AI can provide value and focus all AI efforts there.

Ask yourself, what parts of your business generate high revenue but low margins? With AI, automation of routine tasks will not only eliminate errors, but allow your employees to focus on activities that add value to your organization.

Furthermore, in a Deloitte State of AI in the Enterprise, Second Edition survey, 69% of respondents were concerned about their moderate to extreme AI skill gaps.

In order to successfully deploy, corporate leadership must be 100% on board with the AI program. Moreover, a project leader should oversee all participating sectors from sales to service to IT and beyond. In order to fill the above mentioned skills gap, the project leader should invest in internal data science or AI expertise.

When selecting a field service management software, it’s critical to look for a solution that empowers your organization to identify issues, opportunities and launch digital initiatives to drive operational efficiency and deliver return on investment (ROI). A dynamic field service management (FSM) solution like Astea’s Alliance Enterprise can play a critical role in helping you adopt new technologies like AI and machine learning. By integrating to IBM Watson, Astea’s platform enables you to unlock new value from existing data and restructure your practices and workflows to optimize:

  • Dynamic scheduling
  • Technician dispatch and routing
  • Call center operations
  • And more

To learn more about leveraging AI to transition to an autonomous service model, download the Astea-sponsored whitepaper Artificial Intelligence Gets Real in Field Service to understand:

  • Key challenges of adopting AI
  • Importance of data science expertise
  • How to identify pain points where AI can generate value
  • How AI will create a 1.2% increase in GDP over 10 years

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To learn more about how Astea can help your field service organization embrace emerging technologies like artificial intelligence, request a demo today.

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