This article was originally posted on the Forbes Technology Council. Click here to read the original article.
On a quiet street in Bend, Oregon, the world’s last Blockbuster Video sits between a nail salon and a take-and-bake pizza chain.
For many, the store is a source of nostalgia, bringing back memories of VHS tapes and weekly trips to rent a movie. But it’s also a stark reminder of just how quickly technology can upend an industry. In less than 15 years, Blockbuster went from 9,000 locations to a single store because it could no longer compete with the speed and convenience of on-demand streaming platforms.
Companies like Netflix and Uber have used technology to reshape our expectations on how services should be delivered. Even something as simple as walking outside to hail a cab now seems archaic. People want to do everything from the comfort of their couch, whether it’s scheduling rides, ordering meals or downloading movies.
When I talk to service leaders today, the conversation usually centers on the customer experience. No matter the industry, companies are looking for ways to deliver better, faster service. For many, that means leveraging the latest advances in artificial intelligence (AI) and automation to support their existing workforce and drive productivity.
Rethinking The Nature Of Work
According to a survey by Deloitte, about half of those surveyed said their organization was “deeply involved in automation projects, with 24% using AI and robotics to perform routine tasks.”
Already, we’re seeing the impact of automation on workforce productivity. From monitoring a network of smart devices to turning thousands of data points into hyper-personalized marketing campaigns, companies are using AI to work smarter and scale faster. It may still be a writer crafting that perfect tagline, but it’s a machine deciding when, where and how you receive the message.
Working Smarter, Faster And More Efficiently
Just about every company can benefit from building more automation into their processes, but field service organizations are placing special emphasis on using AI to drive productivity and deliver better service.
Right now, most organizations I’ve worked with employ roughly one back-office coordinator for every four field technicians. These coordinators handle a high volume of tasks, from creating work orders to tracking down spare parts and providing ad hoc field support. It’s a slow, labor-intensive process that can and should be optimized. With just a little bit of automation, back office coordinators could potentially support 20 technicians.
Driving Productivity With Automation
If there’s one metric that’s top-of-mind for field service leaders today, it’s availability. In an industry where every minute of downtime is money out the door, even a slight increase in asset uptime is significant.
For many organizations, the answer lies in predictive maintenance. Instead of relying on the traditional break-fix model where a technician isn’t dispatched until something fails, artificial intelligence can help identify problems before they occur.
Imagine there are two identical towers — one in cold, wintery Chicago, the other in sunny Los Angeles. Despite being the same structure, these towers go through markedly different wear and tear.
Predictive maintenance solves this problem by using AI and sensor-equipped devices to determine the right maintenance schedule for each tower, based on real-time device monitoring and historical data from similar sites. Only as a last resort are technicians dispatched to replace parts or identify the root cause of an issue.
As companies grow increasingly reliant on AI to drive operational efficiency, the annual spend on intelligent automation is skyrocketing. Whether it’s looking at historical data to predict failure or using natural language understanding to develop more conversational chatbots, companies are using intelligent automation to drive efficiency and innovation.
Before you decide when, where and how to deploy AI within your organization, it’s important to take stock of your current business processes and ability to capture data. Legacy software and dated practices can get in the way of true transformation, preventing you from realizing the full benefit of intelligent automation.
Finding The Right Blend For Your Business
As customer expectations around the speed and quality of service continue to rise, organizations will need to move away from manual methods of creating, assigning and executing work and instead focus on automation.
According to a recent McKinsey study, 6 out of 10 jobs today have more than 30% of their tasks that could be automated. After talking to customers, I believe that number should be closer to 70%. There are very few things a machine can’t learn to do well, provided it has the right data and algorithms.
Of course, automation cannot happen overnight. As you look for ways to bring more automation into your organization, be sure to consider the following:
• Define roles and priorities: No matter how many processes are automated, there will always be the need for human workers. Let them focus on areas that require a human touch, whether it’s handling unique escalations or putting a friendly face on customer interactions.
• Iterate, iterate, iterate: There’s no sense in automating poor, inefficient processes. Your automated workflows should be driven by constant observation and analysis. Don’t forget to include the human perspective, either — if a back-office coordinator is continually overriding an AI recommendation, the system should try to understand why and adjust accordingly.
AI is getting better at doing human jobs, but it’s not ready to stand on its own. People still need to be involved, whether it’s providing feedback on automated processes or handling escalations. The most successful organizations will be the ones that find the right blend of human involvement and AI-driven automation.