Planning and scheduling optimization is often the differentiator between a successful operation and one hindered by inefficiencies and cost overruns. Even the best-run businesses will trip at the starting line if planning and scheduling capabilities are not optimized.
This article examines 10 important questions that you should consider before investing in a planning and scheduling optimization solution.
1.Does the solution enable continual optimization of schedules using artificial intelligence?
There is a myriad of scheduling combinations. Relying on humans—or even computers—to create and confirm the best schedule isn’t possible. Especially when you consider the uncertainty of the environment, any unanticipated event, such as a sick worker, missing parts, delayed raw materials, a lack of tools, or even a bad traffic day, can undo a perfect schedule.
Effective planning and scheduling optimization solutions leverage AI to continually tweak and adjust schedules in real-time, factoring in a long list of variables, including costs, time, availability of resources, necessary skill sets, and other considerations. The schedule with the top score is the best one. This optimization process is continuously repeated, incorporating real-time changes to ensure the top-scoring schedule is always in place.
2. Can the solution support multiple types of scheduling?
Planning and scheduling engines must serve different scenarios quickly and accurately. For example, dynamic scheduling supports short-term, volatile environments where frequent changes occur. Perhaps a work crew is stuck in traffic, an urgent request is received, or an emergency service call requires a shuffling of resources to enable an immediate response.
Static scheduling is used in more stable environments—for example, assigning people and resources to attend regularly scheduled service calls or maintenance jobs. Similarly, the solution should allow users to manually adjust the incentive score attributed to an activity.
3. Will you be able to perform predictive analytics?
Predictive analytics support predictive maintenance, a critical business enabler that allows enterprises to maximize asset productivity while minimizing disruptions to the operation. Your planning and scheduling optimization solution must be able to access asset and other enterprise data, leveraging the intelligence to thoughtfully schedule service and maintenance activities – even combining them when possible – while optimizing uptime.
4. Does the solution have planning and forecasting capabilities?
The planning and scheduling optimization solution should allow you to perform data-driven planning and forecasting as your organization requires. Exploring what-if scenarios, like whether your existing resources would be sufficient to support a new contract or if an investment is needed. This is essential to help improve strategic decision-making.
5. Does the technology support multiple business functions?
The solution must be extensible, connecting to data and activities throughout your enterprise to comprehensively understand your entire operation. Can you deploy one solution to plan and schedule teams for manufacturing/production, supply chain, asset maintenance and field service?
6. Is the technology future-proof?
Ask the vendor to share their short- and medium-term product roadmaps for their planning and scheduling optimization solution. A detailed product roadmap reflects the vendor’s commitment to invest, innovate, and grow the technology over time to make it adaptable and scalable, adding support for new use cases. Ensure there is alignment between the future plans for the technology and the future plans of your business.
7. Is the solution truly scalable?
The planning and scheduling optimization solution must be able to deal with and schedule tens of thousands of resources and tasks to support the complexities of your operations, and it should do it in real-time with no artificial constraints or limitations.
8. How will you quantify the value the solution delivers to your business?
ROI is important. The solution must support analytics that help you assign hard numbers to the value it’s providing to your business. Along with measuring improved customer satisfaction, increased productivity, and SLA achievement, the analytics must be more granular. For example, reductions in drive time, increases in technicians to dispatcher ratios, lower average costs per job, decreases subtractor spend, and other KPIs.
9. Does the vendor have a track record of success within your industry?
Every industry has unique requirements, and working with technology vendors already familiar with your space delivers additional benefits. The vendor has experience supporting the specific needs of your industry. They are familiar with baseline use cases. Existing peer deployments offer analytics and reporting models that can be leveraged for your implementation.
Ask the vendor to provide you with examples of real-life implementations that are of a similar scale to your company today and into the future.
10. Is the solution part of a wider end-to-end enterprise application, including ERP, EAM, and FSM?
Modern enterprises are composable, connecting disparate systems and consolidating data across operations. The solution must be embedded seamlessly with enterprise resource planning (ERP), enterprise asset management (EAM), field service management (FSM), and other front- and back-end systems.