The Minority Report outlines a dream scenario for supply chain managers. In the movie, the police uses AI and analytics to predict and prevent crimes before they’re committed. You can imagine the implications for your day-to-day role. You’d be solving problems before your customers even noticed them, ordering parts just before you needed them, and preparing service engineers to fix technical difficulties before they affected your customers’ productivity. If only…
Well, now’s the time to stop imagining, because there is a real-world parallel for supply chain leaders. With the right platform, you can predict equipment failure before it happens so you can orchestrate parts, inventories and service engineers to optimize your whole service supply chain. And it all starts with data.
Two problematic solutions
You bear a huge amount of responsibility. And with so much equipment to manage across so many locations, often to tight SLAs, it can be tempting to hedge your bets. If, for example, you provide a fleet of MRI machines that need to be back up and running within two hours, you might consider over-stocking on replacement parts to avoid being caught short.
But excess inventory and wasted truck rolls are expensive. Once you’ve paid for extra engineers and vans to stand by, ready to deliver parts that will never be used to fix problems that will never arise, you’ve needlessly affected your budget, and harmed your sustainability credentials too.
The alternative is just as problematic. If you minimize the parts and resources you deploy to keep costs down, you’ll pick up a repetitive strain injury from crossing your fingers day-in, day-out. And when things do go wrong, you might pick up a fine for breaking an SLA, and bear extra costs as you scramble to rectify things. Even worse, you’ll have customers wondering whether your competitors would have dropped the ball in the same way. This approach can also affect morale among field engineers, who are left to plug gaps in your service with little to no notice, preparation or information.
Foreseen issues
If you recognize either of the solutions above from your own work, it might be time to harness the power of predictive analytics. With the right data, you can actually anticipate equipment failures, and map these to customer impacts, parts, engineers, locations, warehouses and SLAs. In turn, you can optimize all your resources, so your parts and people are in the right places at the right times.
And guess what: you already have all the data you need. It’s in your service histories, manufacturer data, job reports, inventory logs, SLA fulfillment records, and other databases. All you’re missing is a way to consolidate and make sense of it, so you can use it to improve processes throughout the service supply chain.
If you could bring it all together, you could generate this precious insight and use AI to predict when each of those MRI machines is likely to need parts and services. Then, you could activate this insight through automated processes and just-in-time information in self-service portals for field engineers and customers. In the process, you’d be providing your supply chain strategists with an unprecedented level of visibility, so they can optimize across the Plan/Deliver/Recover cycle.
Minority Report, major improvement
To achieve this Minority Report level of predictive service, you need to have a number of things in place. Once you’ve unified your data and used AI to generate predictions, you’ll need to feed that insight into all your service management platforms, including inventory, engineer resource planning, reverse logistics workflows and decisioning, engineer portals, and even customer portals.
But can you imagine the complexity of a solution that could bring all of these sources together? The integration alone would take years of work, significant expertise, and a serious cash injection. If only this functionality was already available as a managed service…
OnProcess Agora dramatically improves the KPIs that matter most to service management leaders. Armed with advanced predictive planning and real-time analytics, you’ll be able to keep your customers happy by meeting your SLAs on a more consistent basis. At the same time, you’ll be able to keep costs down without adding unacceptable risk, by optimizing your parts inventories, minimizing truck rolls and utilizing your engineers in the most efficient way possible.
Because all of your staff will know exactly which models your customers are using and how long they’ve had them, you’ll also be able to retrieve, recycle or dispose of parts and equipment in a much more cost-effective way: minimizing wastage and maximizing value recovery. And just like in the Minority Report, there’s a happy ending. You’ll gain total visibility into your reverse logistics cycles—so you never stop learning and improving.
If you’re interested in enhancing your supply chain using advanced AI, book your free Agora demo today, or get in touch to find out more.
Learn more here
