Realizing the Opportunity in Predictive Maintenance Analytics
Momenta Partners has published a white paper titled Realizing the Opportunity in Predictive Maintenance (PdM) Analytics, written by Ed Maguire, Luca Mazzei and others. In response to interest from our client base, we interviewed key players in the PdM space and landscaped a universe of more than 40 companies over a 6-month period. We found a fragmented market with little industry adoption, and growing demand for cost-effective solutions that solve key pain points using new technologies.
Realizing the Opportunity in Predictive Maintenance (PdM) Analytics
Today industrial maintenance is mostly performed on a schedule - “preventive” in nature - aiming to minimize efficiency losses and the risk of unexpected failure. We see the industry on the verge of an inflection point of adoption in this space, driven by three converging trends:
- Industrial assets are getting connected, often for the first time
- Performance and organizational data is becoming widely available
- Advances in computing and storage power enable unprecedented scale at declining cost
New technologies enable operators to evolve beyond condition monitoring (understanding what is happening) to anticipating problems before they happen. Predictive maintenance is a lucrative, and potentially game-changing opportunity. Dramatic advances in machine learning, declining cost of sensors, and improvement in their accuracy will enable a new class of artificial intelligence (AI)-driven prognostics to deliver compelling benefits to a wider range of users at significantly lower cost. At Momenta Partners, we believe an inflection is at hand within the next 12-18 months.
Predictive maintenance analytics will enable companies to capture more of the product and service value chain than they could have otherwise, by providing operational transparency, helping predict, prevent, and optimize around expected equipment failures.
In our research, we found that despite the compelling economic benefits, initial implementation is proving more difficult than expected. The human element is an intrinsic hurdle to adoption. Advances in artificial intelligence and machine learning are happening so fast that managers in many industries where new technology could be most impactful don’t even realize what is now possible. Another challenge is the inconsistent availability of data and unresolved questions over data ownership.
Interestingly, condition monitoring provides significant value to customers and is popular. It is also commoditized. With PdM still mostly in experimental stages, the pace of technology innovation continues to outpace actual industry deployments. The plethora of new features and the dynamic pace of change in PdM causes many industrial firms to delay purchase decisions until the dust has settled.
At this stage of the market there are dozens of startups, each with modest commercial traction. Many companies still employ preventive, schedule-based maintenance and are only just moving to remote condition monitoring. Moving to higher value forms of preventive and prescriptive maintenance is further out on their road maps. Today there is real demand for solutions that are simple and easy to install, that help customers start their journey along the PdM innovation curve.
For our research, we find that the prediction algorithms are not a key determinant for success. The deployment scenarios and use cases within have unique sensitivity to specific variables (e.g. installation cost, TCO, or data requirements) in different industries. Users firstly identify how and where a solution will be deployed even if the solution is horizontally applicable. For marketing and adoption, applications always need to be positioned in specific verticals.
Most importantly, closing the decision loop is emerging as a compelling differentiator. Solutions that help companies make better decisions, rather than simply predicting failure, are emerging. As analytics get commoditized, true value will emerge where companies can combine data and rules to drive business decisions.
Partners with an understanding of this space, like Momenta Partners, can help companies at all points of the value chain evolve to embrace and benefit from the potential in Predictive Maintenance Analytics.
"Realizing the Opportunity in Predictive Maintenance (PdM) Analytics"