How to implement AI and recognize its value
By and large, field service providers have approached new technologies with caution — after all, it’s known as the quintessential ‘clipboard, pen and paper’ industry. The apprehension towards AI is usually an issue of transparency, which could stem from miscommunication between teams or infrequent training sessions. As such, there are four strategies service organizations can use to convince skeptics and reap the benefits of AI-enabled technology:
- Communicate clearly: An organization’s IT department and product management team should train executives and technicians on the advantages of AI-enabled technology. AI should be seen as a tool to inform decisions, rather than a black-box replacement of essential business processes.
- Start small: When implementing AI, it’s important to slowly build up organizational trust in its capabilities. Companies should start small by using AI to solve minor issues that could the greatest impact on the customer service experience.
- Identify uncertainty: From changes in weather patterns to unforeseen road closures, there are many uncertainties in the decision-making process that can affect how service is delivered. Field service providers should identify which uncertainties can be removed by using AI-enabled technology.
- Pick a leader: The most successful AI initiatives typically have a business sponsor — which could be a thought leader, executive or member of an advisory board. This sponsor should be willing to consistently evangelize the initiative itself, as well as its anticipated benefits.
Every business process is a candidate for AI
Every business can benefit from data-driven metrics, which is a key feature of AI-enabled technology. AI is especially useful in meeting ‘points of uncertainty’ in the decision-making process – or in other words, using data to inform decisions rather than relying on institutional knowledge.
Typically, the onus is on industry experts to identify challenges in service delivery and which strategies will improve the holistic customer service experience. An example of this is the scheduling process for technicians who depend on the expertise of dispatchers to estimate accurate repair times. In many cases, these systems fail to account for important factors like traffic accidents or a technician’s set of skills. Automated scheduling and dispatching takes the guesswork out of estimating accurate repair times — a huge asset for the time-sensitive field service industry.
Since the value of AI-enabled technology is embedded in its application, it’s important to see AI for what it will do rather than what it can do. Taking an outcomes-based approach will not only help diminish the concerns of deploying new technologies on the field, but will help companies measure how AI will improve business processes. In the case of scheduling and dispatching, more accurate estimates of repair time will have a snowball effect — shortening response times on the field, cutting unplanned downtime, and increasing worker productivity.
At first glance, automated scheduling doesn't seem like a massive undertaking for an organization that has already embraced the capabilities of AI and cutting-edge technology. But when digging deeper, it becomes apparent that more precise estimates of repair times will ultimately have a positive effect on a company’s bottom line — allowing technicians to deliver more streamlined, efficient service than ever before.
Although AI-enabled technology has proven to be far more than just a passing fad, field service providers are only beginning to understand its implications on essential business processes. At its core, the contribution of AI to any application is to provide assistance at any point where a decision must be made. The impact of AI on business process varies from organization to organization but in the end, it’s all about the results.