The past year has posed many challenges for service organizations, from continued supply chain disruptions to record inflation to rising customer expectations. The pressure has been on to evolve to keep up with customer demands, accelerating many digital transformations in the process.
As we look back on the year, there are several themes that stand out. To close out the year, let’s take a look at five of the biggest topics covered by the ServiceMax team and the learnings we can take into the new year.
Service organizations have been pulled in several directions over the past two years. On one hand, their supply chains continue to be impacted by global events creating uncertainty in their ability to deliver service. On the other hand, these organizations now must support multiple service models such as self-service, remote support, depot repair, and onsite support. These counter forces have made it even more essential for service organizations to align with their supply chain teams in planning for and executing on customer and business needs.
In response, we’ve seen a shift in organizations prioritizing and investing in resiliency, digitization, and sustainability. Resiliency often looks like investment in technology to get more predictive and identify supply chain breakages before they occur. Digitization looks like more investment in IoT and remote diagnostics. Sustainability looks like more investment in reverse logistics to repair and refurbish parts.
Here are five ways our customers have been adapting to supply chain challenges:
- Technician inventory – While continuing the work with their partners, organizations have turned their focus inwards to locate and identify the actual parts stock held in technician vans, customer locations, and other stocking locations. With this improved insight, they can transfer material from areas of surplus to areas of need. Organizations with a good understanding of their installed base have found it easier to build forecast models for parts and identify how their current stocking locations needed to be rebalanced.
- Local partnerships and reverse logistics – Originally done to meet short-term needs, many organizations have chosen to continue their local partnership plans as part of an overall risk mitigation strategy. They are also pursuing a greater level of discipline when it comes to the management of part returns.
- Revisiting order processes – Bringing back or reallocating unused and excess inventory has been vital in ensuring a more adequate supply of service parts. Organizations have also taken a step further to investigate their parts ordering and replenishment processes to understand why this excess exists in the first place.
- Loaner and rental return – Many service organizations have adopted a more depot-centric mindset where applicable assets are brought back in-house for repair and loaner or rental assets are provided to customers to keep their operations running.
- Artificial Intelligence – Technicians are using mobile tools to view local inventory and make technician-to-technician transfers. These tools also allow for a complete record of required parts tied to service resolution. With the aid of this data, organizations have been able to train AI models to predict which parts would be needed for future events. This focus of AI on triage and dispatch ensures that only the right parts are sent to fix customer issues.
Asset Data and Digital Transformation
Asset data and asset centricity have long been a focus at ServiceMax. This year, we supported research from Field Service News on the impact of asset data flow across the organization. The research found that more than three-quarters (82%) of respondents are tracking asset data. But a more important question was asked alongside–is your organization able to effectively leverage that data to positively impact field service operations? A large portion–57%– responded that they have the data but were not using it effectively within the organization. The reason for this ultimately came down to a lack of proficiency. As one respondent stated:
We are currently collecting data but are not proficient or aware enough of how to use that data to make or drive improvements.
This lack of proficiency, even at a basic asset data analytics level, undermines field service sector progress. The talk of servitization and its benefits to business, products and customer satisfaction, is fruitless without addressing the key barriers to entry. Service leaders have to start asking the right questions to ensure the whole organization is aware of and can benefit from asset data. If it is relevant to field service, it should also be relevant to the entire structure.
This is something underscored in two other reports we published this year. The Power of Asset looks at the value and impact of asset data for operational, commercial and strategic stakeholders across the organization. Refining Digital Transformation Through Asset Centricity, a whitepaper we sponsored with Harvard Business Review Analytic Services, dives into what an asset-centric approach to digital transformation looks like and how asset-centric organizations like Schneider Electric are creating greater customer value and meeting sustainability goals by understanding the way their customers use their assets across the asset life cycle.
A key finding in this whitepaper notes that companies that have been unsuccessful in their digital transformations have approached them in a siloed nature with a very limited view of digital customer experience and customer outcomes. These organizations have also lacked the rigor of end-to-end data across the customer experience to make the best use of their internal resources. As a result, organizations are pausing their siloed digital initiatives and looking for a common thread to build and deliver business outcomes.
Outcome-based models and Equipment-as-a-Service
By all estimates, only 1 in 5 companies or even less have made a significant transformation in their business models, but the path to accomplishing this is clearer than before. The likes of TSIA and Bain & Company have wonderful frameworks to guide organizations considering their pathway to Equipment-as-a-Service or Product-as-a-Service models.
For manufacturers to deliver equipment-as-a-service, there are many transformational elements that need to take place, including connectivity into assets, recognition of the installed base, validation of output delivered, and commercial infrastructure to support these models. Organizations must also reshape their selling, marketing, and financing models.
While the decision to at least pilot outcome-based models might seem like a simple one, business leaders have been slow to pull the trigger. The short-term loss experienced in capital revenues is hard to justify and plan for, even though the long-term impact may be more profitable. But the shift is starting, and customers are beginning to lay the groundwork for their interest in outcomes. Manufacturers can either wait till those requests become explicit demands or can start proactively supporting their customers’ ambitions for better outcomes.
Talks of a looming recession have dominated headlines this year. As businesses face tough decisions, they are looking for ways to become more efficient and productive. The challenge is to not just keep the lights on, but also remain competitive and grow the business. We saw service companies leverage the following tactics to stay competitive despite difficult times ahead:
- Self and remote service – The pandemic showed just how valuable these services are–companies found efficiencies in reduced journeys and customers often enjoyed quicker fixes, at least for smaller problems. The shift to self and remote service is one that has continued this year and is enabling companies to both improve fix times and reduce costs.
- Predictive maintenance – Predictive maintenance is key to driving efficiencies in how engineers manage jobs—less journey time, more accurate part ordering, reduced customer downtime, and increased customer satisfaction. We saw 3D Systems leverage AI and ServiceMax to power its predictive maintenance service, enabling a reduction in truck rolls and parts consumption and an improvement in first-time fix rate, mean time to repair rate, and customer satisfaction
- Actionable asset data – Many companies are facing the challenge of poor data quality and disparate systems of record due to legacy technologies and piecemeal solutions. As companies look to stay competitive, creating a clean data foundation and leveraging data engineers to make the data actionable is a top priority.
A big challenge that companies face is in believing that if they build long-lasting products, they’ll be setting themselves up for reduced revenue and profitability in the future. For example, if a manufacturer develops a washing machine that will last 25 years, that will depress the future sale of new machines and ultimately cut into top-line revenue. But as we move further into the digital age, we see everyday products—refrigerators, HVAC systems, and even doorbells—becoming software enabled. By focusing on new features that are software-based, manufacturers can design and produce hardware that lasts for many years, and still profit by selling new features as downloadable upgrades. Better still, software is typically a high-margin endeavor, especially when compared to designing and developing new hardware products.
Additionally, as we hold onto products longer, more servicing will be required. Instead of selling new equipment at the five-, seven- or ten-year mark, companies can sell a variety of parts and services that could include product viability guarantees for some number of years. That services upsell would improve the customer experience and act as a recurring revenue generator spread out over the life of the product, helping to negate any revenue lost against entirely new purchases.
In the new year, we hope to see more companies explore innovative ways to participate in the circular economy and use it to drive new revenue streams.