Yet, the paradigm shift is not a perfect transition for everyone. For those who did not have enough time to prepare and achieve organizational alignment, the shift was sudden and business silos lingered.
According to the latest benchmarking report by ServiceMax and Field Service News—The Impact of Asset Data Flow Beyond the Silo of Field Service Operations—it is those business silos that stem from a lack of organizational alignment that prevents FSOs from deriving meaningful and actionable insights from their data.
Disruptive forces changing field service operations
Within the past 18 months, the most significant change for the majority of respondents was adding the provision of remote services to their portfolios. This change was brought about by evolving customer expectations regarding responsiveness, increased remote service options, and a better understanding of asset conditions and performance. And to meet those expectations, FSOs are not solely relying on delivering remote services but also on connecting assets and expanding their workforce.
Although servitization adoption, changes in customers’ perception of value, and rising labor and material costs are considered critical concerns for field service operations within the next three to five years, the workforce crisis continues to be on the top of the concern list for 79% of FSOs.
As the role of the field technician is evolving, FSOs are turning toward upskilling and reskilling solutions. Likewise, they are increasingly seeking data scientists that can help them improve their analytics and derive more actionable insights from their asset data for informed decision-making.
According to research, asset data is one of the central pillars of effective field service operations. And although most FSOs receive enough data from the connected assets in their installed base, more than half of them are unable to effectively leverage the data they track and monitor.
The main reason behind this issue is not having access to enough data that is adequate for practical analysis or that can provide operational insights. Another key issue is lacking proficiency in deriving actionable insights from available data. Many believe that improving their processes, upgrading their systems, and further investing in the Internet of Things (IoT) will help them solve those problems.
While IoT is becoming ubiquitous, not all organizations have implemented the requisite IoT infrastructure for a fully automated collection of asset data. At the present, only 52% of FSOs are collecting their data through direct connectivity to the asset. Many organizations are still service-workforce-driven, meaning that they capture data manually through field service and technical support. Undoubtedly, FSOs are currently using a combination of these methods for data collection, especially as they transition to data-driven service operations.
How FSOs leverage the available asset data
In previous years, asset data has been increasingly used to drive operational efficiency and customer satisfaction. However, the benchmarking report shows that the way companies leverage asset data has changed recently. Although uses range from improving field service operations and product design to driving customer success, the top use case for asset data is creating new services and revenue opportunities, something that also drives customer experience (CX) design for many FSOs.
FSOs are beginning to realize the potential of asset data beyond the confines of service operations. The servitization and digitalization trends that have been guiding organizations enabled them to expand their offerings and look at data from a different perspective.
In fact, 81% of FSOs stated that the asset data they collect is being shared across the organization and is also being used by the technical support, customer service, and sales departments. However, core business units such as supply chain and product design and development don’t receive as much asset data as expected, despite the fact that such data can reveal vital information about asset maintenance, failure, performance, and availability.
Overall, the flow of asset data across different business units is rather optimal and it reflects a higher level of organizational alignment, and ultimately, servitization. Departments such as compliance, customer service, sales, corporate social responsibility (CSR), and research and development (R&D) are well-aligned with the field service unit, considering it a strategic driver for revenue growth.
However, cross-departmental collaboration is not as cohesive as expected. Despite the increased flow of asset data and a deeper understanding of field service operations across the organization, many respondents have revealed that they seldomly work together with senior colleagues or leaders from other departments, especially R&D, CSR, and compliance, showing that there are still units that work within silos and disparate IT systems—and that often results in missed opportunities for further enhancements.
Breaking organizational silos for servitization success
Unlike their counterparts whose disparate IT systems limit the flow of data, highly or fully servitized FSOs claim that their asset data is readily available and used effectively within their organizations. Moreover, it is also effectively shared with other business units, which facilitates a higher degree of cross-departmental collaboration.
As research shows, there is an undeniable link between servitization, asset data flow, and cohesive collaboration. The three elements can even be considered as mutually-dependent, especially for modern FSOs that are now operating on a hybrid model. When managing onsite and offsite operations, it’s important to break down silos and ensure that data flows freely between relevant business units to drive more informed decision-making.
Digitalization has enabled FSOs to adopt servitization and supplement their offerings, but many have yet to evolve their infrastructure and transcend their organizational silos. As long as they exist, those silos will continue to hinder cross-departmental collaboration, limit the data exchange between key business units, and compromise the decision-making process.