Predictive Maintenance as an Opportunity (Part 1)

Industrial assets age, lose efficiency and eventually fail. More generally, the efficiency of industrial production processes is subject to numerous variables – the price of energy, product demand and price, maintenance schedules, and unexpected outages for any number of reasons from weather disruptions to labor shortages. 

These challenges represent a significant cost to the manufacturing industry – each year Oil and Gas operators lose between USD 49-88mn from equipment downtime.  This, in turn, generates a very large industrial maintenance market, accounting for over 14% of the entire industrial services market.

Today this maintenance is mostly “preventive” in nature, aiming to reduce the loss of efficiency and the risk of unexpected failure. In recent years, this has been augmented by increased equipment condition monitoring, with the goal of further extending repair and maintenance intervals: in 2015, industrial firms spent over USD 1.9bn on machine condition monitoring, a number expected to grow to USD 3bn by 2022.

 How do Predictive Maintenance Solutions work? 

Oddly enough, the general industrial production process has not changed much since the industrial revolution. Companies buy industrial assets, put them into service based on pre-set schedules, adjust those schedules based on seasonal cycles, repair assets when they fail, and replace them when they reach a certain age.

This centuries-old production cycle is on the cusp of disruption driven by three converging trends: 1) industrial assets getting connected, 2) data on their performance and on the overall organization becoming available, and 3) compute and storage power achieving scale. As that happens, the factory floor stops resembling a static group of assets, but rather becomes a dynamic, complex system that can be managed as such – much as data networks have been since their inception.

Increasing data and compute availability allows operators to move from condition monitoring to anticipating problems before they happen, thus making predictive maintenance a game-changing, and potentially lucrative, opportunity.

Inevitably industrial firms will be able to eventually predict the performance of entire production processes under varying conditions – and thus modify not only individual assets and their maintenance cycles, but entire factory floors, wind farms, and other interconnected groups of assets.

It will be possible not only to know what may fail when, but to recommend what the operator should do about it (prescriptive maintenance).

This entire class of solutions is expected to grow to be an over USD 24bn market by 2019. However, it is in the more advanced segments of the market – predictive and prescriptive – that growth will be highest. This segment will account for the majority (over 60%) – of the maintenance analytics market by 2019, from only 23% in 2014.

Maintenance Analytics Market Size and Growth

                                                                                      Source: ABI Research

This transition represents a disruption, with enterprises moving from incrementally improving the delivery of products and services to using real-time data to make positive changes on the fly to both individual assets and overall processes. It also presents a massive opportunity for businesses and investors. The predictive maintenance analytics market – a market that until a few years ago did not exist – is expected to reach USD 24.7bn in 2019, driven primarily by Connected Industry innovation and applications.

The opportunity, however, comes not only from reducing maintenance costs or the cost of operations, but in developing new business models and changing how much of the margin in manufacturing supply chains accrues to different players – the asset manufacturer, owner, system integrator, and maintenance provider.

Luca Mazzei, Venture Partner at Momenta Partners says,

“The era of real-time, inexpensive, and reliable data from industrial equipment is finally here and the race is on for the killer maintenance app that goes above and beyond the niche applications we have seen to date.”

Responding to questions from our Momenta Partners' corporate clients we recognized substantial opportunity in and demand for such solutions and set out to develop our own investment thesis. Over the past 6 months we landscaped more than 80 companies, meeting with key ones. What we found was a fragmented market with many small players, early industry adoption, a need for solutions over new technologies, and a desire from operators for cost-effective solutions that solve key pain points.

Since the maintenance analytics market is very young and fragmented there is substantial opportunity for innovation and investment. What are the barriers to operating or investing in this space and where should you be positioning yourself?

Stay tuned to our next blog post and full report for a predictive maintenance market analysis.