Migrating from manual service scheduling to total optimisation

In spite of advances in automatic scheduling technologies, some service organisations still use manually intensive methods to schedule and track their service workforce.

Despite the options available, many organisations still use rudimentary methods such as manually updated work order dispatch tools, whiteboards, magnetic boards, chalkboards and even sticky notes; as well as database applications or spreadsheets that track pending or in-progress work orders and service personnel availability or assignments.

Each of these methods requires constant human monitoring and intervention. Whiteboards, magnetic boards and spread­sheets must be updated manually every time a new service call is received, service personnel are assigned and dispatched, a work order is closed or a part ordered for a service call. More sophisticated software tools can consider staff skills, locations and other factors to automatically assign and schedule service work. These applications may ease the burden of assigning and tracking service activities, but even they must be frequently monitored and manually updated as circumstances change.

These methods are appropriate for some service operations, like those with a small staff or relatively few work orders per day.

Basic software scheduling applications may suffice for somewhat larger service operations. But no manually intensive method is capable of producing a truly optimised service delivery schedule — one that instantly analyses multiple criteria and constraints to develop the most cost-effective, efficient, productive and customer-aligned service delivery schedule possible.

Truly valuable service scheduling software allows users to define a wide variety of rules and conditions, which the software analyses in real time to create an optimal service schedule. The software then continuously evaluates that schedule and refines it as circumstances and service requirements change throughout the day, a common scenario in complex and intensive service operations.

In-depth scheduling optimisation software must continually evaluate the following conditions to create and refine an optimised service delivery schedule:

• Customer or asset service entitlements (eg, warranty)
• Service level agreement (SLA) commitments
• Service call priority/urgency
• Problem type
• Customer criticality/priority
• Service history, such as repeat and/or recent service calls
• Skills and/or certifications required
• Staff skills, certifications and availability
• The need for multiple service staff or crew
• Service site and field staff locations
• Best routes to service site
• Travel impediments, such as accidents, construction and weather
• Customer-defined criteria or constraints, such as operation hours
• Service appointment commitments
• Part availability and/or proximity
• The possibility of combining visits with scheduled maintenance
• The availability and location of tools or other specialised resources
• The required sequence of service activity

Users must be able to define a wide variety of conditions and constraints that drive the analysis and decision-making processes of the schedule optimisation software.

For instance: a service call within 30 minutes of missing an SLA commitment must be automatically elevated to the highest priority and the responsible service manager must receive a text alert; or a service call received within three days of a previous call for the same equipment must be dispatched immediately to the nearest qualified field worker and management must be notified via email, text or telephone; or a service call must be automatically reassigned and dispatched to alternative service staff if the person originally assigned will not complete his/her current job in time to comply with an SLA response commitment.

In other words, users must be able to specify rules that drive the scheduling software to automatically and correctly react to virtually any service situation. Service priorities and circumstances are rarely static; they change throughout the day as new service calls arrive, others are cancelled, some are completed early or late, staff become unexpectedly unavailable and so on.

Comprehensive schedule optimisation software will monitor these and other factors through­out the day and maintain an up-to-the-minute service delivery schedule optimised to coincide with user-defined parameters.

Following are two examples of how optimised service scheduling is used in real-life environments.

Hardware maintenance

A major mass transit service provider is responsible for maintaining thousands of automatic gates and ticketing machines for a metropolitan commuter railway. If a gate or ticketing machine malfunctions, it can result in long lines, cause passengers to miss scheduled trains, frustrate commuters and potentially result in lost revenue.

Failure to respond on time, or incorrect technician skills or parts, can result in extended downtime or repeat service visits, jeopardising SLA commitments — which can trigger penalties from the railway company. When a gate or a ticketing device fails, a technician must often be on-site within 30 minutes to one hour. If multiple machines are down at a single location, the required response time can be as low as 15 minutes.

The organisation has deployed IFS scheduling optimisation software to ensure all SLA commitments are met or exceeded. The software analyses all the factors affecting required service response and restoration times, including the technical skills needed, staff proximity, part and tools availability, problem severity and service urgency. It then selects the proper technician and routes them optimally, whether that be driving, walking or by train or taxi. It can also design a route so staff can pick up needed part(s) and/or tools on the way.

The schedule optimiser also automatically adjusts and updates the schedule throughout the day, ensuring an optimum service delivery schedule is always in effect. An executive for the service provider has observed that they would not be able to function without optimised scheduling.

Facilities services

A facilities services company with a large contingent of mobile workers is responsible for maintaining and replenishing bathroom supplies for a large number of hospitals, restaurants and other facilities. Much of the work is done on a planned basis, so delivery schedules are planned in advance.

An IFS field scheduling optimisation solution analyses SLA obligations, geographic considerations and other relevant parameters to design service routes that minimise travel times and costs with the highest possible productivity. The company must also respond quickly to unanticipated situations such as a broken bathroom dispenser. Unexpected employee absences also require rapid schedule adjustments to avoid delays and meet agreed-upon delivery schedules. The organisation has saved millions in fuel costs alone thanks to the optimal routes and schedules the software generates.

Image credit: ©stock.adobe.com/au/ demango23

*As Vice President of Enterprise Service and Asset Management for IFS, Patrick Zirnhelt is responsible for regional strategy, development and execution in the service management and asset intensive industries. He has more than 20 years of information management experience, including enterprise software implementation, development and training.