Real-world AI: lessons from the field

February 22, 2017



Everyone’s talking AI at Mobile World Congress. See it in action—and saving money—in field service.

Artificial intelligence (AI) has never felt like a human-friendly term. The very notion of intelligence that is artificial is a little, well … unsettling. Will machines ultimately replace us? Are humans becoming obsolete?

As we gather at Mobile World Congress, in part to explore the ultimate reach of AI in an increasingly mobile business world, one thing is clear: AI and machine learning technologies won’t replace humans in the enterprise, but they’re going to change the game considerably. AI and machine learning promise to enhance and complement, taking on labor-intensive tasks while giving workers capabilities and access to information we’ve never had before.

As an example, consider field service, which has a huge impact on customer experience—and your bottom line. In a traditional field service organization, a company manages a fleet of technicians and uses a ticketing system to dispatch them to jobs, typically on a first-in, first-out basis. This is simple, but it’s also slow, expensive, and inefficient, leading to frustration for both the technicians and the customers. So let’s smarten that up a bit. We can start doing things like prioritizing tickets based on severity, or sending technicians with a particular skillset to the jobs where they are most needed. It’s a small improvement, but it does involve using intelligence—human intelligence—to make more informed decisions.

Now, let’s amplify the impact of those informed decisions through the power of AI. Instead of sending every service ticket to a dispatcher, we can route it first through an algorithm and determine the best avenue to solve the problem. Is there an online FAQ that provides the customer a quick path to resolution? Would a simple customer-performed troubleshooting step, like restarting equipment or replacing a simple component, solve the issue?

By leveraging AI in this way, we estimate that up to 80 percent of customer requests could be resolved through machine learning techniques without ever having to involve a human being. And as the AI bot handles more of these routine customer requests, it learns—and its success rate only gets better. That frees dispatchers to focus on those unique, and often higher-value, customer interactions where human insight, intuition, and experience are crucial.

PwC looks at AI across a continuum, and this type of AI in which machines and humans learn from one another and redefine ways of working is what we refer to as “augmented AI.” Any application of new technology and capability is a journey—and it’s clear this journey is well underway.

Paying at the pump

Oscar W. Larson Co., a family-owned business now in its third generation, has been building gas stations and managing other petroleum-centric construction projects in the Midwest United States for 71 years. Larson’s reputation as an innovator in its industry is rooted in its efforts to reduce redundancies by doing each job right the first time. The company’s brand is based on customer satisfaction, and it knows the best way to lose that—and its revenue—is through truck re-rolls.

Truck re-rolls are the industry term for multiple service calls to the same customer because a technician didn’t have the right tools, parts, or expertise. We’ve all been there: When the appliance repair company shows up an hour after the scheduled repair window, but still can’t fix your refrigerator because the right replacement part isn’t on the truck. The customer’s time is wasted, translating into higher labor costs and lower customer satisfaction.

By bringing AI to bear on its field service operation, Larson is aiming to keep customer satisfaction high while managing its growth rate. In a pilot project that PwC and Google Cloud are rolling out with the company, machine learning systems have already reduced truck re-rolls by up to 20 percent by confirming that technicians have everything they need to complete jobs before departure.

Larson is also getting smarter about the inventory it has on those trucks, which is particularly important when technicians are far away from a warehouse full of parts. Our AI-driven inventory system has helped Larson reduce inventory levels on its trucks by up to 35 percent, which is not just keeping satisfaction high for customers by making service calls more expedient, it’s also freeing up cash for the company that would otherwise be tied up in inventory.

Together, these efforts represent a huge impact on the bottom line, and we’re only at the beginning of this effort … opportunities abound with what AI can do and we’re eager to see how far it can take us.

Boots on the ground

AI may feel like it is on the bleeding edge, but that doesn’t mean it has to be overwhelmingly complex. Our system integrates directly with Larson’s ticketing system, using solutions designed by PwC that leverage the Google Cloud infrastructure and its enterprise G Suite, including Maps and Calendar.

Again, it takes smart people out in the field, not just machines, to make this all work. To kick off the engagement, our team rode side by side on truck rolls with Larson techs. Our team sat with the dispatchers. We went through the inventory process with Larson, working with the team across every level of the organization. We saw the trouble spots firsthand, and based on those experiences together we deployed AI tools to remedy them.

Some have characterized the advent of artificial intelligence (and the complementary technologies of machine learning, ubiquitous connectivity, and the internet of things) as the fourth industrial revolution.  We are still in the earliest days of AI and machine learning, but market leaders know that these technologies are key signposts on the road to future growth and success. Even a simple pilot project can lead to astounding business results. Adopting emerging technologies always presents some risk—but don’t wait for AI to fully mature before you start thinking about an implementation strategy. By then, your competitors may well have passed you by.

Learn  more about the PwC and Google Cloud  solution Larson is using at Mobile World Congress. (Come see us in Hall 1, booth 1A48.)  Or watch an overview of it below.



Chris Curran

Principal and Chief Technologist, PwC US Tel: +1 (214) 754 5055 Email

Anand Rao

Global Artificial Intelligence Lead, PwC US Tel: +1 (617) 530 4691 Email