We talk quite a bit about the importance of planning and scheduling optimization. We know the business value, we know what constitutes best-in-class optimization, and we know that optimization is a lot more that auto-scheduling and recommending a couple parts.
True best-in-class optimization automates repeatable tasks, provide real-time resource adjustments that are scalable to meet the number of technicians in a firm (whatever that number might be), and can provide planning insights for a day, a season, a year, or whatever unit of measurement that your business is in need of.
An automation system, at its best, actually automates activities. And like any AI-powered system, you can’t just provide inputs without matching criteria for how to catalog, rank, and execute those inputs into practical outputs.
So it’s necessary, then, to build a set of criteria that moderates your service system to prioritize outcomes, which will ultimately be passed on to your customers. I’ve written about this previously as a function of AI-based learning. Let’s outline some criteria areas that best-in-class systems can employ in this capacity: