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Field Service Lightning is equipped with a powerful optimization engine. It allows service operations to automate scheduling processes while aligning system's behavior with organizational KPI's.
Identifying an optimal employee for each service appointment is a two-step process: zooming in only on those who are qualified for the job, followed by identifying the most optimal candidate.
Imagine you run a 100 men strong service operation. A new service appointment just came in.
The work rules, serving as hard yes/no qualifiers - take a split second to narrow down the mobile resource list to the select few who technically got what it takes to get the job done:
Having the right skill
Being available within the desired time frame
Working in the right service territory
And much more - in our next video we will explore the 11 work rules available in FSL.
Now with a few qualified candidates at hand, Service Objectives will help to define the most optimal resource for the job. Clearly, what constitutes “optimal” will vary greatly from one service organization to another:
one might be concerned about top customer service levels aiming to schedule as soon as possible at all costs, while others will look to contain operational costs such as overtime and travel. Most often companies will strive to strike a balance between these.
With Service Objectives in play, we can now zero in on the most optimal - as per the company’s KPIs - mobile employee
This logic is leveraged in every scheduling decision done in field service lighting:
When booking appointments
Smart scheduling on the Gantt or
leveraging the full blown optimization for bulk scheduling of a day, a week, or broader horizon.
