AI in Service Management Is Here to Make New Winners and Losers

10/15/2019 / Digital Transformation / Katia Loboda

Astea-branded banner shows hand pointing to brain icon, captioned, “Artificial Intelligence Gets Real in Field Service.”

Artificial intelligence (AI) was once the stuff of science fiction. But today, AI in service management is making service delivery smarter and more efficient.

Over the last four years, enterprise AI implementation grew 270%, according to Gartner’s 2019 CIO Survey. A majority of service leaders see AI as a central technology tool poised to transform the industry and create new revenue opportunities.

Recent data analysis advancements and the expansion of connected “smart” devices have stirred new interest around AI within the service industry. Astea’s special report Artificial Intelligence Gets Real in Field Service reveals:

  • 60% of survey respondents believe AI is currently powerful enough to drive business processes.
  • 71.8% indicate AI will make the greatest disruptive impact of any technology.
  • AI will create a 1.2% increase in GDP over 10 years and capture an additional 25% in new economic benefits.

Let’s look more closely at how AI is transforming the service industry, and what this transformation could mean for your organization.

Service Management Is Ripe for AI Adoption

Companies selling industrial products and services are making relatively lower AI investments but extracting higher returns, a recent Deloitte study found. This trend suggests field service organizations (FSOs) are particularly well-positioned to reap this technology’s benefits.

Artificial intelligence needs good data to function properly—and FSOs already collect data in abundance! Most organizations use such technologies as GPS, Internet of Things (IoT) devices, and dynamic field service management software (FSM) tools that collect large amounts of data on equipment, technician expertise, routing, service history, and more.

When they feed this data into self-learning AI programs, field service companies receive beneficial output including:

  • Automated customer service support, which leads to faster resolution times.
  • Routing and scheduling optimization, which drives down fleet management expenses and boosts service response times.
  • Inventory optimization through advanced data management, which reduces standing inventory costs and helps avoid asset downtime.

AI Service Industry Applications In Practice

Customer Experience

Businesses build positive customer experiences by addressing customer needs instantly and effectively. But using a live representative to answer every customer concern can create delays and frustration.

More than 100,000 companies already use AI-powered chatbots to address this issue, according to Forbes. Service-centric companies increasingly implement these interactive experiences in first-level service interactions. Using simple contextual conversation tools, the chatbots guide customers through a series of questions. They either resolve issues right away or refer them to a customer service agent, who is informed of the issue in advance.

By escalating inquiries more efficiently, service providers not only alleviate common help desk frustrations but also save time and cut labor costs, all the while improving customer satisfaction.

Dispatch, Route & Scheduling Optimization

AI already has a strong foothold in this area of the field service industry. Dispatch scheduling engines (DSE) use algorithms to automatically optimize routes and schedules by changing jobs and assignments on the fly.

As the AI program is trained on more data, it gets “smarter” and can further optimize routing based on customer preferences, technician schedules and experience, parts availability, traffic, and weather factors.

Smarter scheduling yields better service experiences for not only your customers but also your staff.

Inventory Optimization

With parts inventory spread across different depot locations, customer sites, and vehicles, keeping accurate inventory records can be a challenge. To overcome it, many FSOs digitize inventory management processes with barcoding and mobile technology. Scanning incoming and outgoing parts with a mobile device makes possible real-time visibility to parts availability, parts usage, purchasing, and replenishing needs.

AI tools can analyze this inventory data along with service histories, error codes, and machine vitals to help FSOs achieve preventative service. These programs can predict likely equipment failure, needed maintenance, and what mix of parts technicians must have for service calls.

With these advanced tools at your disposal, your FSO can eliminate cumbersome manual warehouse processes, maximize technician utilization, and reduce or even prevent asset downtime.

Be Ready to Meet These 3 AI Adoption Challenges

As with any emerging technology, challenges to adopting artificial intelligence in service management remain.

Male warehouse worker scans a package while female supervisor watches, using AI-powered management app on a tablet computer.

When AI initiatives fail, three primary factors are typically to blame:

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

One key way to overcome these barriers is to identify specific pain points where AI can provide quantifiable value.

For example: Which parts of your business generate high revenue but low margins? In which areas do most errors occur? In these cases, AI-based automation can help not only eliminate errors but also reduce labor costs and free up your staff to focus on value-added activities.

In addition, corporate leadership must champion AI programs and recruit the talent needed for successful implementation. A chief information officer can act as the project manager, or appoint one who oversees all participating sectors—sales, service, IT, and beyond. This approach will ensure the organization understands the project, and increases the project’s chances of moving forward cohesively.

Choose a Platform With Built-in AI Capabilities

Dynamic field service management (FSM) solutions like Astea’s Alliance Enterprise can play a critical role in helping you adopt new technologies like AI and machine learning.

By integrating with IBM Watson, Astea’s platform harnesses AI’s power to unlock new value in:

  • Dynamic scheduling that uses data on technician profiles, availability, and customer preferences to bost first-time fix rates.
  • Technician dispatch and routing based on real-time traffic conditions, weather, and geolocation batching to reduce expensive truck rolls.
  • Call center operations that use AI contextual tools to swiftly resolve or elevate customer issues resulting in more satisfied customers.
  • And more!

To learn more about leveraging AI in service management so your FSO can cut costs and boost customer satisfaction, download the Astea-sponsored whitepaper Artificial Intelligence Gets Real in Field Service. The report covers:

  • What major AI adoption challenges your FSO must navigate to reap these technologies’ revenue-enhancing benefits.
  • Why data science expertise is non-negotiable in your company’s AI adoption efforts.
  • How to identify pain points in your FSO where AI can generate significant value.

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