Climbing The Servitization Staircase Using Asset Data
By Mark Wilding, Vice President, Global Customer Transformation, ServiceMax
Outcome-based business models thrive on unifying data from machines and devices
For anyone thinking that the past few years have been a bit of a rollercoaster ride, strap yourself in because it’s probably not going to get any easier. Economic volatility will, according to most economists, be a fact of life for business from now on, at least while Russia continues its invasion of Ukraine. So, for any organisation transforming, trying to create and operate models that enable greater business resilience, this is a testing time.
In manufacturing and product-led businesses, one of the biggest transformation models is servitization. According to a Forrester study we commissioned before the pandemic, entitled From Grease To Code: What Drives Digital Service Transformation, 85 percent of firms said servitization was a high or critical priority, as were outcome-based business models. Then Covid-19 took over, pushing transformations in different directions as businesses went into firefighting mode.
Today, the determination to evolve, to build greater resiliency through multiple revenue streams, improved customer satisfaction and efficient operations is refocusing efforts on servitization models. The absolute bedrock of this is asset data. As Harvard Business Review (HBR) refers to it in a recent report entitled Refining digital transformation through asset centricity, asset data is “the common thread” by which organisations can unite traditionally siloed business functions.
What this means is that by focusing on connectivity through technologies such as IoT, 5G and AI-enabled data analytics, organisations can start to build pictures of products and customers. For most organisations this is the key relationship, the one that really matters. So, using data that adds intelligence to this relationship makes commercial and operational sense but how do you take this a few steps further? Delivering the level of service that customers really want means using this intelligence to shape service functions and refocus efforts on delivering business outcomes, not just product outcomes.
However, to reach this level of servitization can take time. HBR references Tim Baines, professor of operations strategy and executive director of the Advanced Services Group at Aston Business School, who, with his colleagues analysed case studies on what successful firms did to get there. One deliverable of that research was an eight-step staircase model charting the evolution. This ‘servitization staircase’ Baines believes can form the basis of a plan to help companies reach their transformation goals.
At the core of this value proposition is, according to HBR, an understanding of customer value, specifically attached to the assets those customers use. Leveraging insights derived from these assets to shape customer experiences and outcomes enables an organisation to develop longer-term relationships with customers.
“The deeper the understanding of a particular customer and its unique use cases, goals, and metrics, the more precisely the entire organization can tailor the value proposition, from the products it designs to the deals it structures to the type of service model that works best for it,” says the HBR report. “When the asset is delivering on desired customer outcomes in a way that also delivers profitability for its manufacturer, it not only extends the relationship but also tends to reduce risk on both sides.”
The challenge for any organisation is how to get the data flowing and talking. While qualitative data can often be collated through automation, in field service so much data is still derived from human contact, with field engineers inputting into mobile devices. Asset data, however, is generated across the entire product life cycle, from its design and testing stages, through to production, installation, and customer usage, and finally to decommissioning, whether that leads to repurposing, refurbishment, or disposal.
This data can put customers into context for any organisation and drive insights into assets across lifecycles. Comparable asset data across customers can also enable optimisation of design and services, as patterns emerge and recommendations can be made on how to improve those assets. For any company looking to climb Baines’ staircase to outcomes-based models, this is essential. No asset data means no chance of servitization.
As HBR concludes, “to truly be effective, digitization must be part of a larger reorientation of business models and value propositions,” it says. “Asset centricity, which allows organisations to tap into new business models and revenue streams, is all about delivering a value proposition to customers that helps them achieve the outcome they desire.”