The Growing Need for Industry-Standard Analytics

Many owner-operators have accelerated their digital transformation of maintenance activity due to the COVID-19 pandemic. Remote plant monitoring and staggered technician scheduling, for example, rely on digital solutions to ensure continuity in operations, as well as to protect the health and safety of frontline operators and maintainers.

Industrial intelligence is another key part of this digital adaptation. Analytics powered by the combination of data science, industry experience, and subject matter content are forming the foundation of operational excellence.

This past year has also shown the limits to digital adaptability. The financial pressure of the downturn has left many businesses grappling with fewer resources to develop their own internal analytics programs. At the same time, the transition has shown organizations that they’re able to adopt and implement digital solutions without the headache of significant change management.

In turn, we’ve seen a greater focus on analytics, the limited resources to develop them, and as a result, the growing gap to address that need.

It wasn’t just owner-operators who felt the resources bind this past year.

Various players in heavy industries have common challenges to address, including talent shortages, the so-called “silver tsunami” as a generation of experts retires, greater compliance obligations to regulatory boards, legislators, and industrial partners, and the need to harness the power of vast amounts of data from disparate sources and convert it into a usable format.

OEMs, faced with these industrial challenges, increasingly tapped analytics as a way to set apart equipment offerings. The same goes for independent repair shops and their services in industries like trucking, which are adopting more advanced maintenance strategies to set themselves apart in an increasingly fragmented market for repairs.

The impact of these challenges looks different in each type of organization. Whether they’re original equipment manufacturers (OEMs), owner-operators, service providers, or analytics companies, their responses are shaping how the market meets the acute need for analytics.

In parallel with this trend towards analytics has been the development of industrial connectivity, or the Industrial Internet of Things (IIoT). OEMs have pursued connectivity on assets like turbines, trucks, rolling stock, and power transformers. Native edge devices, wireless connectivity, and cloud software have sped up OT/IT convergence for long-established customer relationships. As embedded software distinguishes OEM hardware offerings, IIoT capabilities have opened up the possibility for better analytics.

Machine owners and operators, wanting to cut maintenance costs and improve repairs and take advantage of connectivity, have expressed a need for industry-standard analytics. Since many have a number of OEM relationships, they have reached out to third-party analytics to prepare data from mixed asset types and manufacturers. That way, they have standardized recommendations on how to precisely operate and maintain their unique combination of equipment.

For their part, OEMs have used third party analytics to improve equipment offerings and service obligations. Winning more business from operators with mixed equipment by making inroads to capture more of those assets in the future relies on the current interoperability of analytics solutions, both among connected assets and within an organization’s tech stack. OEMs, shut out of the proprietary information of other manufacturers, often have to turn to third-party solutions to pave a future path toward equipment competitiveness.

As solution providers scope out specific use cases from various OEMs in different industries, the scale and independence of third-party analytics promises the industry standardization and warranty mediation that owners and maintainers of equipment seek.

We've seen this dynamic play out in the wind industry. More precise conditioning monitoring can substantiate the root cause of pending turbine failures and validate claims of warranted service. With a single, shared source of industrial intelligence, third-party analytics solutions are helping industry players enter into service agreements that better reflect performance. Parties to the warranty don’t have to overhaul existing workflows to integrate third-party analytics solutions or allocate a significant part of their budget.

This dynamic has particular relevance to the wind industry right now. As investment pours into renewable energy generation, many operators have grown their operations and now have the scale to make in-house maintenance more cost-effective than turning to an OEM or independent service provider. Woods Mackenzie estimates the share of OEMs conducting maintenance on wind turbines will fall from 64 percent in 2018 to 50 percent by 2028.

Without the analytics experience to carry out the responsibilities of engineering and maintenance teams, operators are looking to analytics to manage performance — especially given the industry's technician shortage and as many conduct maintenance in-house for the first time.

In a broad range of heavy industries, operators, OEMs, and service providers have realized significant operational efficiency from analytics solutions.

Not all analytics are created equal though. Different levels of analytics — descriptive, diagnostic, predictive, prescriptive, and self-learning — have corresponding degrees of improvement in O&M efficiency. We’ve seen all types of market players capitalize on the value of their data, from early tech adopters building out their own analytics infrastructure in concert with third parties to those looking to leverage external solutions entirely.

Solution providers will fill the analytics gap that last year widened, and the sharing of data and leveraging of connectivity will determine the pace at which the digital transformation of maintenance happens. In 2021, the promise of industrial analytics to make a bottom-line difference will entail more direct cooperation among owner-operators, OEMs, service providers, and solution companies.

Want more industrial insights?