The intersection of artificial intelligence (AI) and field service is not new. While the increasing sophistication and proliferation of AI-driven applications has moved new developments to the forefront, ClickSoftware solutions for mobile workforce management have leveraged AI from day one.
The simplest way to define artificial intelligence as it relates to field service software is as the ability to optimize every aspect of field service delivery—even without prior programming. By processing data and running simulations based on various objectives, ClickSoftware enables a smarter, more efficient workforce with benefits delivered in real time.
The most common use cases for AI in field service include smarter scheduling and route optimization to reduce travel time. But the real advantage comes in mapping optimization to business goals—from SLA compliance to revenue growth—and letting the AI find the right path to each desired outcome.
It’s not science fiction and it’s not a vision for the future. It’s practical AI-based solutions aimed at solving real workforce management problems.
To learn more about how artificial intelligence is reshaping customer expectations and service industries, take a look at these recent articles from ClickSoftware experts:
Customers expect great service when something breaks. But in some cases, equipment failure is not an option. A broken air conditioner in an office building is inconvenient. A broken MRI machine poses a more serious situation.
Leveraging the Internet of Things (IoT) has allowed many manufacturers to let smart devices tell them when they need service. Combined with AI and an unsurpassed ability to process all the data inputs from IoT-enabled machines, ClickSoftware unlocks the ability to predict service and maintenance needs based on historical data, enabling service to be provided before the machine fails.
Instead of waiting for something to break, you can move proactively to address field service needs and prevent failures and interruptions. It’s true for any piece of equipment that consistent upkeep is less expensive than an emergency fix. Prevention is the best medicine—and will keep your customers happy.
Beyond assuring consistent operation and customer satisfaction, the ability to predict service needs enables more accurate forecasting and resource planning. Schedules are optimized to maximize productivity and still leave enough flexibility to manage the unexpected. Predictive travel reduces travel costs and leverages historical data as well as traffic data from Google Maps, also delivered in real time.
As customer expectations change in both consumer and business-facing verticals, field service providers are rising to the occasion with customized SLAs and a broader set of KPIs for service.
One of the biggest challenges in this changing landscape is balancing competing service priorities. Travel costs have to be manageable, but response times defined in SLAs also have to be met consistently. Customer satisfaction is directly tied to profitability, and also has to be prioritized. Many service customers will define KPIs based on their business—missed customer transactions during a busy period, for example.
Whatever factors come into play, ClickSoftware can adjust seamlessly and automatically to plan for the right outcomes. Testing different scenarios and weighting variables in simulations can rapidly uncover which changes will have the biggest impact on the topline and bottom line.
Explore ClickSoftware’s Field Service Analytics in the video below.
Vivint creates smart home solutions, solutions such as home security, energy management, and home automation. In other words, they create homes with connected “smart” appliances that can be controlled remotely or automatically. As more consumers rely on smart devices such as thermostats or security systems, the more important it is that they work. Otherwise, it disrupts their daily life.
Field Service Technology Manager Erik Mikkelsen explains how Vivint uses a mobile workforce management solution to create an efficient field service business model. His team uses AI-driven schedule optimization to assist with dispatch, reduce customer no-shows, and drive customer experience. He also looks forward to implementing solutions for customer engagement. Learn more in the video below.
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