Even before the pandemic disrupted industry in 2020, the manufacturing sector was experiencing one of the most exciting periods in its history. Products are being quickly commoditized, and new competitors are disrupting markets in many sectors. For example, the tech giants are capitalizing on their position in “value networks” that rely on data by delivering products such as Amazon’s Alexa or Apple’s electric car projects. These companies have set a precedent and brought a new awareness of the potential of data to deliver better business outcomes.
To continue to be competitive, manufacturers need to get serious about service and product innovation. Otherwise, they risk being trapped in an unsustainable price-driven race to the bottom. The inexorable rise of the Internet of Things (IoT) offers manufacturers an opportunity to revolutionize their business models by focusing on business outcomes rather than product sales.
“Manufacturers need to ensure that the value from the digitalization of manufacturing machinery is captured by those who create the machines, rather than by big technology firms, which integrate and derive insights from diverse machine data,” explains Dr. Andreas Schroeder, Associate Professor and Reader, The Advanced Services Group, Aston University.
They need to create digitally-enabled, services-led business models that use the data created by connected devices. A services-based business model places the product – and the expertise in how to operate and innovate with it – at the core of the offering, thereby reinforcing the role of the manufacturer in the value chain.
“The adoption of these business models, and the organizational transformation required to deliver them, is known as servitization. We describe servitization as the innovation of an organization’s capabilities and processes to deliver services rather than products alone,” explains Eleanor Musson, Senior Partnerships Manager, The Advanced Services Group, Aston University.
By creating service-based business models, manufacturers can directly address their customers’ business requirements. Instead of selling an engine, an aircraft engine manufacturer would sell thrust and be responsible for delivering and managing the equipment that provides it. Through this model, they can more accurately meet changing customer expectations and build customer loyalty.
Furthermore, servitization also incentivizes manufacturers to take a more sustainable approach to product development. Because they have responsibility for the maintenance, uptime and disposal of the product, they will aim to maximize uptime, use as few materials as possible in their creation and re-purpose products at the end of their life.
Moving towards this new business
Developing a services-based value proposition requires an in-depth understanding of the customer’s business requirements and challenges. This needs to go into much more detail than traditional product or service design.
“Innovators need to be able to get “into the customer’s shoes.” This will allow them to work out what the potential customer of a new product or service thinks, hears, tells and feels about upcoming or existing solutions for its needs,” explains Aston’s Schroeder. “They will also need evidential historical data about how the product is used and operated, how it fails and how it responds to interventions.”
While predictive maintenance or performance advice is a frequent starting point into servitized business models, customers are looking for more than that. Ultimately, they want the service they buy to be directly linked to their business outcomes. They will expect data and advice to come as part of the package and want to buy peace of mind and a capability that lets them focus on their core business.
While digitalization is a critical part of enabling these business models, there needs to be a clear strategy for its use. For example, it is pointless capturing a vast amount of data from IoT devices without a clear strategy to monetize it. Ultimately, new digital technology alone will not deliver growth and new revenue streams.
Collecting data is only the first part of the digitalization revolution. Analyzing this data and gaining insights are key in helping manufacturers to optimize the reactive or preventative repair process. Artificial intelligence and machine learning can help manufacturers get ever-more-valuable insights into their service offerings. For example, embedded machine learning applications can continuously analyze the product use data and identify when maintenance is required without sending large amounts of raw data and putting a strain on the network.
“Data de-risks services business models by giving the provider visibility of the product and prior warning of factors that may cause service interruption. It can also alert the manufacturer to any misuse of the product or changes to its environment,” explains Aston’s Schroeder.
These data insights can also be fed back into the product design to improve it moving forward in a process called Engineering Design for Service. When a product is explicitly designed to enable service delivery, the design process needs to incorporate how easily the product can be maintained, repaired, upgraded and recycled.
To find out how to move towards servitization, overcome common challenges and build a competitive service, read the paper in full here. The Advanced Services Group is a center of excellence at Aston Business School, Aston University in the UK. Its work helps global manufacturers and technology innovators to develop services-led strategies.