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IFS Enterprise Service Management provides service organizations with complete end-to-end service management, reducing overall expenditure with multiple vendors and providing unrivaled efficiency and automation with a fully integrated solution that addresses all aspects of the service chain from backend to front end.
Our robust service management product simplifies your service processes while providing asset focused businesses with a complete service solution.
IFS customers report:
employees in 17 countries
IoT-triggered work orders created within 6 months
revenue growth and 5% margin growth within 1 year in Finland underpinned by IoT enabled solution from IFS
houses managed
month implementation
further improvement of service efficiencies within 12 months of going live
IFS Enterprise Service Management provides extensive service and asset management capabilities with all of the benefits of a comprehensive ERP solution. Whether you’re an independent supplier, work within a service function in a large corporation, provide basic services, or huge, complex service projects, our enterprise service management application offers service-centric ERP.
Using AI and a range of sophisticated algorithms the IFS dynamic scheduling engine solves extremely large scheduling problems with multiple constraints in seconds. The system continuously analyzes real-time data, considering a huge number of parameters including job location, traffic, technician availability and skills, the parts and tools they are carrying, interdependent tasks, SLAs and the relative value of each job.
The system balances competing priorities and looks ahead for opportunities to combine jobs and blend planned maintenance activity. Evaluating thousands of alternatives in seconds, the engine determines an optimized plan, freeing your staff to manage genuine exceptions.
The engine is truly dynamic, allowing it to respond to intraday changes such as new urgent jobs, job overruns or traffic delays, recalculating in real-time, and continuously adapting the schedule.
The system continuously monitors what is being achieved and evaluates improvements. If it finds a schedule with a better service margin, the system will change the part of the plan that has not been committed, reallocating work to resources in a just-in-time decision-making approach.
Find out more about our Planning & Scheduling Optimization solution
Using AI and a range of sophisticated algorithms the IFS dynamic scheduling engine solves extremely large scheduling problems with multiple constraints in seconds. The system continuously analyzes real-time data, considering a huge number of parameters including job location, traffic, technician availability and skills, the parts and tools they are carrying, interdependent tasks, SLAs and the relative value of each job.
The system balances competing priorities and looks ahead for opportunities to combine jobs and blend planned maintenance activity. Evaluating thousands of alternatives in seconds, the engine determines an optimized plan, freeing your staff to manage genuine exceptions.
The engine is truly dynamic, allowing it to respond to intraday changes such as new urgent jobs, job overruns or traffic delays, recalculating in real-time, and continuously adapting the schedule.
The system continuously monitors what is being achieved and evaluates improvements. If it finds a schedule with a better service margin, the system will change the part of the plan that has not been committed, reallocating work to resources in a just-in-time decision-making approach.
Find out more about our Planning & Scheduling Optimization solution
Are you getting the best out of every service scenario? This fact sheet will explain how this component of IFS Applications will enable the best results.
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With an eye to the future and a desire to push today’s technologies to their limit, Artificial Intelligence has begun to creep into a variety of service technologies. On its surface, AI might still seem like science fiction, but the number of practical use cases will only increase over time. Find out more.
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