Steve Mason from FieldAware outlines the importance of technology evolution in your service offering.

As a company’s overall field service maturity evolves, one way to move operational maturity to the next level is to invest in technology. Organizations setting out to implement a field service management solution either for the first time or upgrading an existing solution do so to achieve strategic, operational gains. 

While many operational benefits are achieved from different aspects of a field service management project, arguably automated scheduling and optimization deliver group productivity that significantly moves the operational performance needle.  

The gains that drive companies to implement these solutions include:

• Dramatically improving service quality to the end customer by ensuring the right resource(s) arrive at the right location(s) at the right time with the right parts and equipment.
• Increased operational productivity resulting in completing more jobs per day by the same number of field resources.
• Increased first-time fix rates and reduced repeat visits.
• Lowering greenhouse gases emissions and travel costs by reducing the average miles driven per job.
• Improved staff morale by providing a modern and productive working environment. 

While delivering these results is transformative to the way an organization supports its customers and competes in the market, many companies fail to achieve full potential.  We’ll outline an Evolutionary deployment approach that, when combined with an innovative technology solution, addresses common change management barriers and breaks a decades-old mould.

Field Service is Always Evolving

There are two main approaches to implementing scheduling and optimization - Big Bang or Evolutionary. 

Big Bang focuses on designing and building an entirely new service offline and then introducing it in a short-focused transformation program.  It historically worked well in enterprise-wide programs where all the gains are achieved once the project is live and the new operating model is not prone to change.

Evolutionary is an “agile” methodology enabling the introduction of smaller incremental improvements that form a series of steps towards achieving defined business goals. The company achieves incremental ROI with each step and progressively aligns the organization to the evolving new business model.

Traditional scheduling and optimization systems operate by immediately publishing their results live into the field service management solution.   It takes time to configure and model the solution in a safe environment before introducing it and works best in a Big Bang project.  New innovative capabilities provide a fully functional “what-if” environment where planners can work safely, make tweaks, and then publish schedules when they are satisfied with the results.  This new capability allows the Evolutionary approach to be successfully introduced.

Both models require leaders to design how the business will operate at the end of the program.  FieldAware finds the Evolutionary model provides for faster implementation and better adoption by following this approach:

Phase 1 

Implement a baseline solution with just the core system parameters configured The objective is to establish a minimum viable production solution to go live as quickly as possible.   Planners, dispatchers, and field resources use the system to manually schedule and deliver service using defined data plus tacit local knowledge.  While the business may be working very similarly to how it did before the project, the operational transparency achieved through the visibility of resources, jobs, and customers on a scheduling Gantt chart, real-time visual maps, and system reports brings a lift to productivity and quality of service.

Phase 2 

Document and capture tacit or tribal knowledge from the planning team and transform the information into system parameters.  This knowledge transfer enables the implementation of semi-automated scheduling, where planners make decisions with system guidance to take into account the rules and constraints that were defined.  Productivity and service quality improves through more compliant decision making.  The data is further refined based on feedback from the teams. 

Phase 3

Semi-automated scheduling and optimization, introduce business scheduling objectives such as minimizing travel time or balancing work across the team into the system configurations.  Planners and dispatchers can use a safe “what-if” planning environment to interact with the optimizer’s calculated results and refine the schedule iteratively.  They dispatch jobs only when the best results are achieved.  During this period, planners refine the optimization engine for various regions and business requirements, improving optimization performance, and improving result quality.

Phase 4

Achieving fully automated scheduling and optimization.  The planning team has transferred all tacit and tribal knowledge into the optimization settings and parameters.  There is complete adoption because they have engaged throughout the change program. The repetitive tasks of planning and scheduling are automated, freeing up resources to address the higher value work that differentiates the business and drives it forward.

The evolutionary journey approach, when combined with advanced systems that contain “what-if” planning capabilities, break down the change management barriers.  Planners and the field resources are part of the change program and contribute to its success.  Each phase, has wins for every stakeholder, and centrally the company benefits include:

1. Increased customer satisfaction
2. Increased bottom line through group productivity improvements
3. Improved working environment for service delivery teams
4. Reduce greenhouse gas emissions

Further Reading:

• Read further articles and news from Steve and his colleagues at FieldAware here
• Find out more about the solutions offered by FieldAware here
• Follow Steve Mason on Twitter @stevegmason