With the rapid rise of AI, ML, Big Data, exponential growth in computing power, paired with phenomena like the experience economy, product-as-a-service, and servitization, technology as we know it is dramatically changing the products we buy and how we deliver and experience service.
Service Lifecycle Management is understood by many as “the practice of aligning service parts management, technical communication, field service management, and product support operations to maximize customer uptime.” Having an “end-to-end solution for growing your after-sales service business” has been a challenge for many organizations due to wide variability in use cases and buyers by industry. Historically, this has led to organizations procuring numerous point solutions to solve individual service use cases or adapting their strategies to deal with diluted ERP capabilities that were never designed for service, and deliver negligible outcomes.
It is a challenging and rewarding opportunity. Organizations who manage aftermarket service well experience higher service revenue, greater profit margins, and soaring customer satisfaction. There is a strong correlation between service outcomes, brand equity, and brand loyalty. In fact, one of the greatest leading indicators for manufacturers of repeat purchases is “when I needed service, did they fix it the first time.”
Technology innovation is raging like a tsunami, dramatically changing products and how we deliver and experience service. With that change, we must reassess how we define Service Lifecycle Management, which now more closely aligns with the definition of digital thread.
What is a digital thread? A digital thread creates a full lifecycle closed loop between the physical and digital worlds from product design and engineering through manufacturing to service (and back again).
The term Service Lifecycle Management signals for point solutions to solve challenges and build efficiencies throughout a product’s serviceable life. Solving one aspect of the service lifecycle with one point solution and another challenge with a different point solution. Point solutions and siloed thinking, while it may have been the best there was at the time, leave significant value on the table. Silos create islands of data and limit collaboration and innovation.
A recent McKinsey study found that about two-thirds of siloed transformation efforts fall short of their goals or are ultimately unsustainable. Similarly, PTC's State of Digital Thread survey revealed a significant "data gap" in how enterprises are sharing and leveraging data; 34% said that data created within their department is widely available on their enterprise systems.
Enter digital thread and powerful technologies that solve challenges and create opportunities more cohesively. This concept organizes data within the organization for all to benefit. Equipment utilization data is valuable to service technicians and also to product engineers. Why serve it up through a collection of point solutions to different audiences? With a digital thread, the data is available and accessible by all parties, from product design and engineering through manufacturing and service.
There is a ubiquitous market need for asset uptime and availability, and a digital thread delivers the data to ensure that assets stay up and running when and where required. Access to up-to-date, accurate data is imperative to meet the customer’s needs and keep assets and equipment operating.
Boeing Global Services offers a glimpse into the art of the possible. Servigistics is their enterprise standard for service parts optimization. Together with Capgemini, they embarked on a journey to identify all data within the organization that can further extend the value Servigistics delivers. Dubbed the “12 Week SCM Assessment”, this program brought supply chain experts from each of their five major cross-country government sites together to set benchmarks and create a blueprint for aftermarket service. Meeting every day for 12 weeks allowed for a detailed examination of people, processes, and tools. The outcome showed that aftermarket service creates a significant value gain across the entire enterprise.
Their powerful case study describes it well, “adding Planning Data Layer (PDL) is just one example of how BGS is building a digital thread with an integrated flow of data that delivers the right information to the right place, at the right time—enabling improved communication and collaboration among sites and across the enterprise and ultimately reducing costs and accelerating overall maintenance times, not to mention improving customer satisfaction.”
Running a successful aftermarket service business is complex and challenging. Improving collaboration and communication and leveraging common data are paramount to maximize outcomes for the customers while maximizing the bottom line for the OEM. The use cases around service parts management, technical communication, field service management, and product support operations are still valid. The service lifecycle is a crucial subset of the digital thread. The lens of a digital thread, sewn from engineering and manufacturing through all these service use cases, provides a view that replaces the Service Lifecycle Management siloed approach with one based on leveraging up-to-date, accurate data efficiently and effectively across the entire supply chain, enhancing results even more.
Servigistics innovations in artificial intelligence, machine learning, big data & IoT will optimize your service supply chain and unleash the full potential of your service business.