Value of Optimized Resource Planning

Most service planning in catastrophes is highly manual, involving multiple spreadsheets and guesswork; AI-driven capacity planning is seamless.

Fairly or not, many consumers regard insurance as a commodity, so, for insurance providers, a hefty investment in customer experience is imperative to customer retention. And the biggest driver of a positive experience? Quick, fair resolution of claims — shortening the time between claim and resolution. In urgent situations, there are a lot of moving parts, and, in 2017 and 2018, the U.S. experienced 30 natural disasters, each causing more than $1 billion in damage, according to the U.S. Household Disaster Giving in 2017 and 2018 report. Claims representatives, such as adjusters, inspectors and appraisers, may need to be relocated from other parts of the country. Existing work will likely need to be rescheduled and completed upon returning to normal conditions. Not to mention, insurance companies must coordinate their efforts with customers, independent adjusters and mutual aid responders. Catastrophes are largely unpredictable — but capacity planning solutions empower insurance providers to best respond to them by optimizing their extended teams to ensure the right resources are activated to handle additional claims. In its simplest form, capacity planning involves assessing available resources against the expected work, identifying any gaps and making decisions on how to best meet any anticipated or “unplanned” work, using historical data to guide predictions. Ultimately, capacity planning drives better customer service, even under the most trying conditions. Preparing for Disaster Every customer-centric business is ultimately measured by how it performs on the day of service — especially in the case of insurance providers, where that day of service could easily be the worst day of your customer’s life. With September as National Preparedness Month, it’s the perfect time for insurance companies to formulate a solid resource plan to better service their customers. To effectively address the influx of claims brought about by disasters, insurance companies need flexible systems and processes—to speed the claims process from first notice of loss to resolution. In times of instability, customers crave predictability — knowing when they are going to interact with your adjustors, assessors and inspectors, down to the minute. Whether capacity is measured in points, quotas, hours or number of jobs, the ultimate goal for insurers is to understand whether they have the bandwidth for the planned, forecast and unexpected work in the coming weeks — and make changes accordingly to ensure they do. See also: A Tough Lesson in Disaster Preparation It seems daunting considering that most insurance providers are managing resource plans and schedules in disparate spreadsheets and claims management systems. But there are alternatives that provide a single view of work and resources: field service management (FSM) software. Used primarily for scheduling and dispatch, leading-edge FSM solutions now include the ability to optimize resource planning. Filling the Capacity Gap When a severe storm is forecast, a planner can load the expected increase in demand into the resource planning solution. This is immediately reflected in the planning tool, as well as real-time changes in the existing schedule, location of resources and adjuster skills. Using artificial intelligence (AI) and machine learning, capacity planning solutions empower planners to identify areas at risk, and allocate resources to ensure all work gets completed. Insurance companies can use these solutions to anticipate gaps in capacity coverage and take corrective action, such as:
  • Temporarily relocating field resources
  • Allowing for additional overtime
  • Relaxing travel rules
  • Training additional employees to take on expanded roles
  • Hiring independent adjusters from multiple sources
Unlike most service planning processes, which are highly manual and involve multiple spreadsheets and guesswork, AI-driven capacity planning seamlessly accounts for historical demand data, scheduled and unscheduled work and available resources to ensure business priorities are enforced across the service lifecycle. When there are schedule disruptions — say, for example, an adjuster calls in sick or can’t travel due to weather situations — the capacity planning solution alerts the service organization of the problem, and swift action can be taken to reshuffle low-priority work. See also: Untapped Potential of Artificial Intelligence   Capacity planning arms insurance providers with the visibility, control and agility required to handle catastrophic situations, ensuring the right resources are in place to meet customer needs at an incredibly critical time.

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