When a customer exclaims, “we need this part right now and can’t complete our project without it,” OEMs spring into action! This real-world scenario unfolds thousands of times per day when a customer experiences equipment downtime and service parts are required to restore the equipment and complete important projects.
When OEMs move heaven and earth to keep the client operational, it often means getting critical service parts on the next flight, truck, or train. The total cost can be high when considering fuel consumption, transportation costs, person-hours, warehousing costs, and more. Still, with customer commitments (SLAs), the penalties for downtime can be even higher. Ending critical downtime for high-value customers can be priceless, but at what cost? Are OEMs being short-sighted to the longer-term sustainability implications? As the world moves ever closer to legislating how each of us impacts the environment, service supply chains are coming under scrutiny on what they can do better to serve the customer’s service event and the environment.
A solution could be to rethink the traditional models of the service supply chain away from simply focusing on getting products and parts out efficiently and considering how to sustainably get products and parts back into the supply chain rather than just discarding them.
This means getting your Planning (defining what inventory is needed, when and where to satisfy SLAs), Delivery (getting that inventory to customers according to SLAs), and Recovery (getting as much value back from service parts no longer needed in the field) processes working in tight harmony around serving the customer efficiently AND driving environmental impacts down.
Thankfully, with advanced data science and the exponential growth of technology, help is at hand. Sophisticated software and services are available to automate and streamline most service parts stocking decisions. They are also available to minimize unnecessary transportation by applying advanced artificial intelligence (AI) and propensity modeling and ensure products and materials are retained within the supply chain for as long as possible to ensure minimum environmental impact.
The inherent complexity of the service supply chain means it is ripe for optimization and is open for dramatic impact improvements on the environment. Consider the many touchpoints, metrics, and decisions, including first-time-fix rates, no-fault found rates, whether to repair or send to the landfill, repair with new or used parts, new product introduction, or end of life scenarios, expediting materials, determining which parts are under warranty, etc. These represent numerous inter-connected decision points where even small degrees of error or poor efficiency can explode into thousands or millions of dollars in impact on the business and its environmental footprint.
Case in point, end of life – how can your planning team make an accurate assessment for last time buy? It’s challenging buying parts now to service equipment for many years. Without software and finely-tuned algorithms, a planning team makes estimates chock-full of inaccurate assumptions, leading to over procurement, which bleeds over into increased warehousing costs, transportation costs, and the eventual cost of obsolescence.
Likewise, ensuring delivery processes are driven efficiently will ensure the customer service event is solved quickly – keeping customers happy along the way – and reducing unnecessary shipment costs and reducing harmful transportation emissions.
But how does parts recovery fit into the model? Done well, an efficient parts recovery process that ensures the maximum amount of value is retained from parts no longer needed in the field, can feed directly back into planning processes in near real-time, highlighting more accurately what stock is likely to be needed, what inventory does not need to be purchased new, and crucially what materials can be saved from going to land-fill.
The core principle is – if you don’t need something, don’t make it. That being said, optimizing the service supply chain is not a trivial endeavor and has stages of maturity. Some service parts management solutions lack sophistication and deliver limited value above and beyond rudimentary spreadsheets.
Servigistics is a purpose-built solution for service parts optimization. Sophisticated algorithms model and forecast demand, factor in maintenance schedules and real-time utilization data to proactively recommend the minimum required inventory to meet the target service level goals. When partnered with other providers such as OnProcess, who specializes in the outbound provision of service parts as well as the recovery of no-longer-needed parts from the field, the entire service supply chain can be configured to run seamlessly; with each function of Plan, Deliver and Recover providing valuable data and information into each other ensuring that inefficiencies are minimized and sustainability opportunities maximized.
Underneath all of this is data, which is the starting point of any good service parts supply chain.
For that reason, OEMs should invest time and resources to gather, clean, and consolidate available data. Tools and infrastructure such as the OnProcess’ Agora platform can help, especially in defining what data is needed and how to capture, integrate and structure it. However, the key is to keep the end customer as the focus. Remember, a service event is about providing service to the customer. All the logistics, planning, delivery, and recovery of parts to fulfill that service event should keep the customer’s experience in mind.
You don’t have to compromise between service levels and customer commitments and sustainability priorities with purpose-built solutions like Servigistics. Servigistics can optimize the inventory within the service supply chain, recommending when to move parts between echelons and distribution centers to maximize equipment uptime and readiness. The algorithms are tuned to maximize equipment utilization, avoid downtime, and only when necessary, procure new parts. Since it’s proactive, OEMs can capitalize on existing shipments, so parts tag along and get where they need to be without excessive transportation (planes, trains, trucks, etc.).
The enlightened VP of Service understands that optimizing the service business is good for business (maximum equipment availability, customer satisfaction, minimal inventory for maximum service levels) and, at the same time, a massive contributor to long-term sustainability. Capitalizing on technology to minimize excess expense and better material utilization leads to exceeding corporate sustainability goals and customer agreements at the same time.
Investing in service parts optimization is a proven successful sustainability play. OEMs will make the most significant impact and can exceed corporate sustainability goals using purpose-built, state-of-the-art technologies. It’s applauded when organizations successfully reduce truck rolls, optimize technician routes for fuel economy, transition the fleet to EV, etc. These are fantastic wins and improvements. Successful service parts optimization has a much greater impact to exceed corporate sustainability goals, improving the bottom-line and top-line performance, and maximizing customer service and loyalty. That’s why service parts optimization is the linchpin of sustainability.
As General Manager of the Servigistics Business Unit, Leslie has responsibility for worldwide sales, marketing, business development, customer success, and research and development. She brings a wealth of experience from her 29-year career at Caterpillar, with 16 years as a member of executive management teams. Leslie is known for her passion and focus on driving change to deliver customer value and growth. She has a superior command of disruptive technology and its impact on service operations. She has brought her vision and experience to Servigistics and is leading an era of rapid innovation, further fortifying Servigistics as the industry-leading service parts optimization solution.
Leslie has degrees from Southern Illinois University, Carbondale (MSME, BSME, Engineering), Bradley University (MBA) and Stanford (Executive Program).