mplsystems Launch AESOP Module for Scheduling and Optimisation

148
Filed under - Archived Content,

mplsystems aim to transform field service efficiency with new AESOP scheduling & optimisation module.

The Advanced Engineer Scheduling Optimisation & Prediction (AESOP) module was created to ensure that organisations can offer rapid response to in-day jobs, provide precise slot times and manage delays, changes and overruns, all without compromising on workforce efficiency.

What is it?

The AESOP scheduling and optimisation module will be launched at the Field Service Management Expo this month.

The Advanced Engineer Scheduling Optimisation & Prediction (AESOP) application combines real-time feeds, predictive analytics and flexible rules to enable organisations to manage the complexity of today’s field service.

Using the latest self-learning genetic algorithms, this grant-funded development builds on mplsystems’ leading dynamic scheduling engine, by providing real-time optimisation.

The module combines real-time data feeds concerning exceptions, such as traffic flows, the weather and job overruns, with data from deployed equipment through IoT devices. This is then correlated with an organisation’s specific preferences, for example rules for engineer workload, regions, ideal working times and travel times, parts and skill set.

These priorities are unique to every business and so the system allows users to configure and evolve their own rules, in order that the AESOP algorithms provide the optimum schedule for their unique scenario.

Also, AESOP provides the ideal solution, accepting new reactive requests, monitoring delays and jobs in jeopardy, as well as calculating the optimum plan and routes in real time.

Intelligent Real-Time Scheduling

Companies typically rely on inefficient manual, or partly automatic internal processes and are therefore unable to react quickly to the constant changes and exceptions that keep the service desk busy each day.

With continuous customer requests, delays, overruns, etc., being logged at the service desk throughout the working day, staff usually spend the majority of their time rescheduling field engineers’ diaries and playing the ‘middle-man’ to keep the customer informed.

Real-Time Scheduling

Proving itself intelligent and flexible, the software solution is also able to automatically respond to basic customer queries or emergency work orders, thus minimising the repetitive workload for the service desk staff.

This could lead to the company reducing the number of staff required to manage exceptions at the service desk and allow them to relocate their resources to more value-adding tasks.

What does this mean for the customer?

Being able to react to requests as and when they come in, rather than backlogging them, means that customers are attended to on the same day if there is an emergency, and not long after, if they in a position to wait.

With a reactive service team, customers feel looked after and valued, thus improving customer satisfaction.

Intelligent Routing

The AESOP scheduling and optimisation module also calculates the most efficient routes for engineers to take between their jobs.

Presenting the field technicians with detailed information about the distance between jobs, travel time and the best route to take can save up to 80% of time spent scheduling jobs at the service desk. Furthermore, this process can help technicians get to jobs almost twice as fast as before.

The solution also ensures that the customer is automatically sent a message when the engineer is on their way and/or if they run into any potential delays.

What does this mean for the customer?

Having a system to optimise field technicians’ diaries and send out automated messages with journey and job updates means that customers are continually kept well informed and are able to better manage their day.  Rather than having to wait around for vague half-day time slots, they are now able to work around the hour within which their service visit is due. This is a vast improvement for customer experience within the service industry as the sector is notorious for delayed scheduling and ineffective systems.

Predictive Maintenance

Through the digital connectivity that comes with the IoT, devices will be able to self-diagnose problems and immediately alert the service organisation of the issue, often before the asset fails and the customer realises something is wrong.

mplsystems’ AESOP module integrates these data feeds to ensure preventative visits can be scheduled in and aligned with other visits in the local area to minimise travel times.

What does this mean for the customer?

Through the efficiency of preventative scheduling, customers’ machine downtime will reduce by over 30%. They will no longer experience any disruption, as their machine will be revitalised before it fails.

Find out more by visiting mplsystems at the Field Service Management Expo | June 20 – 22 | Stand N650

Or, you could visit mplsystems.co.uk

Author: Robyn Coppell

Published On: 9th Jun 2017 - Last modified: 14th Jun 2017
Read more about - Archived Content,

Follow Us on LinkedIn