AI and ML Optimization Take Planning and Scheduling to the Next Level for B2B Service Delivery

As part of Solutions Review’s Contributed Content Series—a collection of contributed articles written by our enterprise tech thought leader community—Bob De Caux, the Chief AI Officer at IFS, explains how AI and ML optimization can help B2B service delivery take its planning and scheduling processes to the next level.

Good service delivery is unavoidable, and not just for omnichannel consumer shopping giants such as Amazon—it is now a significant business differentiator for countless asset-intensive industries from manufacturing and energy, utilities, & resources to construction and engineering. A recent PwC report highlighted that for over half of customers, several bad experiences would be enough to sway their decision to purchase again, even from a company they otherwise liked.

Customer demands have escalated, and today, there’s no excuse for not delivering instant responses, first-time fixes, and flexibility as standard—even during the ongoing skills shortages. But as field service teams and dispatchers often find themselves overstretched, finding a solution that allows companies to deliver service-based outcomes is pivotal, even when not at full capacity.

When we turn to assets, the service delivery story is even more essential. Companies are under pressure to juggle service delivery, parts, and logistics to ensure excellent customer experiences; in fact, it can even mean the difference between profit and losses—so it’s where a powerful AI-driven PSO solution can prove its worth in providing a truly optimized schedule.

1) Time is important to customers, so make sure technicians are readily available

The intensity and complexity of a service dispatcher’s work means decisions with different contexts must be made quickly to maximize efficiency. The primary reason why optimization in the moment matters comes down to the impact of delays on customer experience—such as when customers cancel, appointments run over, and parts need to be allocated. Businesses need a system that can react in minutes, not hours. This is where the importance of AI-powered optimization demonstrates its value, as an effective system can do in fifteen minutes what some systems need overnight to compute.

An AI-enabled PSO system can schedule large numbers of jobs in real-time to ensure the right engineer or field worker is in the right place at the right time and with the right skills and parts to complete any job successfully. AI PSO technology can continuously analyze real-time events, considering everything from job location to duration, technician availability, skills, parts, tools, and other dependent tasks to deliver highly optimized plans in seconds. AI can go one step further to enhance the experience of the dispatcher by giving them information that they can understand, particularly when something goes wrong.

The dynamic route optimization function of PSO technology assigns jobs to technicians that will optimize drive time by taking the most efficient route and allocating jobs that are as close together as resource availability allows. The system achieves this by using AI to calculate the time needed to complete each task based on existing data for each technician so that an appropriate timeframe is given to jobs that are more complex or have a larger scale. This guarantees that there is enough time for completion and prevents costly overruns.

2) CX is impossible without employees, so look after what matters!

Prioritizing jobs is challenging when multiple tasks are coming in continuously and encompass a wide range of different geographical regions. Service dispatchers are forced to firefight, which can be highly stressful and likely to negatively impact employee retention. Additionally, field workers may become disillusioned, dealing with significant travel requirements, short notice changes to job requirements, and problems completing allocated work. Morale across the entire field workforce will likely suffer, but asset-intensive businesses can turn the tide with AI.

The right AI-powered scheduling tool can tailor the chosen approach to meet the precise needs of each business. There will typically be a need to blend appointments with reactive and planned work, so companies will need an effective way of aligning appointment times around existing committed work. But that is not sufficient in itself. Organizations need to go beyond this to deliver target-based or value-based scheduling. This approach allows organizations to focus their scheduling directly on the key performance indicators (KPIs) that matter most to the business.

An AI-powered PSO system, for instance, allows organizations to layer values—like company rules (KPIs) or regional rules (regulatory)—over the engine, powering its planning optimization to ensure that appointments are triaged effectively. This could be a reduction in the average cost per job for a white goods repair firm or an increase in the percentage of calls a regional ambulance service responded to within the target SLA (time window). Typically, it is a question of managing complex and even competing priorities to ensure SLA compliance and maximize profit.

3) Efficiency is vital – PSO reduces time and errors

Service dispatchers often have to manage planned maintenance with new jobs coming in real-time. To complicate matters further, many try to optimize the workforce using traditional processes, which are time-consuming and error-prone. So where can businesses cut down on inefficient and time-killer tasks?

Today’s enterprises continuously collect asset performance data. Still, industries from manufacturing to service all struggle with similar dilemmas: how to put data collected in the proper context and take action in real-time. Autonomous enterprises that incorporate AI and ML into their processes can manage data at scale more quickly and accurately than a workforce that is solely human. Equally, AI and ML models with self-learning asset performance anomaly detection can deliver the predictive analytics capabilities needed to help businesses evaluate how they will likely be impacted by a wide range of possible scenarios to pinpoint the best action to take in any given situation.

“What-if” scenario forecasting capabilities in advanced AI PSO systems can run various models for businesses to prepare for any eventuality. Here’s an example—what if a company expects a 50 percent spike in appointments? Scenario planning software can run various models to ensure the business is staffed up or help connect the business to the tools to leverage contingent labor.

4) Ensure AI and humans work together, not separately

The greater precision delivered by AI-driven workforce scheduling enables service managers to plan for the future more accurately. It can also make field workers more productive, reduce their travel requirements, and allow them to complete more jobs without as much hassle—factors that all contribute towards a happier workforce.

But it’s essential for businesses not to go too far down the AI well. Yes, AI has the potential to bring new efficiencies and unlock business value across asset-intensive industries. However, AI must always play a supporting role rather than dictating the final decision. AI can provide businesses with the right intelligence at the right time, but it is in the ability to support the delivery of enhanced customer service that the most far-reaching benefits of AI-driven workforce scheduling lie. For instance, the information collected by an AI PSO system must be shared in the correct form with the dispatcher so that they can consume it quickly and easily and then use it, alongside their own experience and expertise, to make the final decision.

Reap the Long-Term Effects: PSO Delivers on CX

Offering excellent customer experiences is the order of the day for any service-based business and subsequent field service teams—it’s no longer a choice but a necessity. However, CX shouldn’t come at the cost of employee satisfaction or an impacted bottom line, so it’s where AI-powered optimization can provide the perfect tonic to today’s service problem. Not only can AI-powered PSO analyze data at scale and in real-time, but it gives businesses the capability to make informed decisions based on actionable insights to drive service success—and compete in a highly competitive market.