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Here's How Schneider Electric Is Escaping from Predictive Analytic Pilot Purgatory
Brought to you by WBR Insights
Digital transformation is not just a catchy marketing term. The slow yet inexorable advance of digital technology into global industry has gone from being a simple curiosity to a key brand differentiator in just a few years.
Thanks to today's global marketplace, brands are under more pressure than ever to find ways to give themselves a competitive advantage in their industry, and cutting-edge technologies such as the Internet of Things, artificial intelligence, virtual and augmented reality, and big data analytics are all helping them realize those advantages.
But how do brands implement these new technologies? The answer to this question is found in pilot programs - small-scale, short term trials that help companies learn how a large-scale project might work once implemented. But pilot programs can be hard to finalize. Companies run the risk of their initiatives being stuck in this stage ad infinitum.
Predictive analytics is one of the most promising technologies to enter the field service arena in recent years. With connected sensors feeding back to central servers, powerful artificial intelligence software can go to work analyzing patterns and other data to build models which are able to deduce when components are likely to develop faults and subsequently schedule engineers to attend to them before large scale shutdowns occur.
These models are also able to identify components which are failing regularly, enabling field service providers to find the root cause of the issue and either repair the problem or source a different brand.
"Technology advancements such as IoT sensors are enabling machines to connect to software and provide recommendations to employees to act before a failure occurs," said Schneider Electric in a blog post. "This process is called predictive maintenance, where connected and integrated data is monitored to determine the condition of in-service equipment to estimate the true health of the equipment and detect abnormal behaviors, risk of failure or change in settings."
While the promise of this technology is great, it's a sad fact that only 30 percent of pilots end up reaching scale across the entire organization and 70 percent of pilots fail to capture value for the companies carrying them out. Compounding this issue is the fact that pilots can take a long time to bear fruit, with 85 percent lasting a year and 28 percent taking two years or more.
Schneider Electric has laid out some key principles to help avoid it and start getting the most from predictive analytics.
Implementing Predictive Analytics
First of all, it's important to qualify vendors of predictive maintenance software before the pilot process begins. The key points you need to consider include the vendor's existing customer base/references, their software capabilities and features, their proven software scalability, their domain knowledge, their ability to act as a long-term strategic partner, their support and services approach, the relative cost of a solution, and the total cost of ownership.
Once you have the foundation for a successful strategic partnership, you can go to work building your pilot program with the following key points in consideration:
It's crucial to have the full support of executive leadership as this will enable the pilot to run smoothly without getting caught up in bureaucracy.
Clear Success Metrics
You also need to lay out the parameters of success from the very beginning - how will you measure and determine whether the pilot is working or not? Make sure your staff has the necessary training in place to use the new technology ahead of time to avoid any competence related issues.
A Set Timeline
Creating a timeline - and sticking to it - will help make sure your pilot doesn't drag into infinity. If the end of the timeline is reached and no significant results have emerged, it may be time to try something else.
A Documented Plan
Finally, all this should be documented in a formal and approved plan which lays out the hierarchy of people, timeline, partners, and everything else we've discussed. This will ensure that everyone involved with the pilot has access to the same information and understands their role in the process.
By laying out these guiding principles, Schneider Electric is ensuring it can make the most of digital transformation for predictive maintenance analytics without becoming lost in pilot purgatory. Even better, it's made this information available to the wider community so everyone can benefit from Schneider's wisdom.
"Moving from reactive or planned maintenance strategies to a predictive maintenance strategy can seem overwhelming," says Schneider Electric. "However, there are multiple benefits for implementing a predictive maintenance strategy, including better protection for maintenance staff by avoiding emergency maintenance, reduced downtime, prevention of unnecessary maintenance, reduced costs, and new insights available across the enterprise."
You can hear Schneider Electric's Vice President of Strategy for Global Field Service, Eric Le Joliff, speak at Field Service Europe 2019, taking place this December at the NH Collection Amsterdam Grand Hotel Krasnapolsky.
Download the agenda today for more information and insights.