The five stages of scheduling adoption with Microsoft Dynamics 365

September 10 2020

Scheduling the right resource to perform a task at the right time and in the best way is not easy. Universal Resource Scheduling (URS) is a Microsoft Dynamics 365 solution that allows organizations to plan and optimize the deployment of resources to deliver jobs in a variety of scenarios.

For example, an organization could have jobs that run regularly, or it could have night shifts. It may want to optimize the schedule for many resources at a time. Customers may cancel a service with very short notice, and the cancellation might impact one or multiple resources. Resources, in this context, means people, equipment, and facilities. Resource Scheduling Optimization (RSO) automatically identifies the best equipped resources to complete the identified job. This includes automatically scheduling work orders to field technicians, cases to customer service reps, and any other example based on how you are using Dynamics 365 Field Service, Customer Service, or Project Service Automation.

Stage 1: Manual scheduling

Given the diverse scenarios for resource schedule optimization, five typical stages of scheduling adoption emerge as best practice. The five stages apply from early Field Service adoption all the way up to large deployments with full automation.

About Stefano Tempesta

Stefano Tempesta is CTO at SXiQ, a Microsoft Regional Director, MVP on Azure, AI and Business Applications, and co-founder of 365 Community, a non-profit organization whose mission is to empower communities around the world with better ICT processes for customer relationship management (CRM) and customer service, using modern technology.
A technology manager with 20 years of international experience, entrepreneur CTO and advisor for start-ups in Australia, Singapore and Switzerland, Stefano is an author, a public speaker, a blogger, an event organizer and an ambassador of beautiful software. His interests extend to microservice architectures, blockchain, IoT and A.I. related technologies.

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