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Predion Field Service Management optimizes the strategic decision of how many (and of what type) service personnel to staff by location, 1-12 months out, across a range of industries.

Predion Field Service Management

Created by Olena Panasovska from the Noun Project






Why it matters

Many organizations with large field service operations deploy tactical tools to help operational managers optimize scheduling within a constrained set of resources. However, they typically lack support for the executive-level decision of how many resources of what type to make available at each location over the next year. These decisions have enormous service and profit implications.


Of course, these aren’t easy decisions, as they involve complex tradeoffs between the cost of excess labor and the cost of unserviced demand. This is particularly true for organizations where demand fluctuates due to uncontrolled factors such as weather, equipment failure, and customer orders. Additionally, servicing this fluctuating demand often requires balancing between a base of fixed resources like employees vs. more expensive, flexible resources like third-party contractors. 


Modern AI systems can address this complexity by generating many different realistic futures and identifying not only the optimal decision under the most likely future but also the risk-reward tradeoff of each decision. The executive judgment call can then be a fully informed view based upon risk tolerance and other organizational objectives. There is almost always a direct relationship between staffing levels and realized profit, and identifying the size and shape of that relationship, and how it varies by location and time, can be an enormous profit opportunity.

What is it?

Modern AI techniques allow for improved forecasting. This is particularly relevant for businesses with hundreds or thousands of sites staffed by hundreds or thousands of technicians. These new techniques allow us to create forecasts that learn from other locations which boosts performance by identifying shared patterns. For example, the ability to predict the probability of several high demand days in a row, or multiple adverse weather days that coincide with a demand spike, can have a significant impact in terms of servicing customers effectively and reducing backlogs. These types of refinements improve performance, as does the incorporation of novel data sources such as local events.

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How it works

Determineresource deployment - quanity, type, & location Forecast demandfor and upcoming period

Predion FSM is a cloud-based software that integrates data from both corporate and external sources, models it into a unified format, and then pushes staffing and resourcing recommendations into existing workforce systems. We have a single-minded focus on improving the profitability of the key decision step using data and modern AI techniques.

Let's talk about how Predion FSM can help your business