Addressing Operations & Maintenance Business Cases

Submitted by Erik Udstuen, CEO & Co-Founder at TwinThread

An article from the Harvard Business Review has made it clear that executives understand the importance of AI being meaningfully implemented within their respective organizations - “...84% know they need to scale AI across their businesses to achieve their strategic growth objectives…”. However, “...only 16% of them have actually moved beyond experimenting with AI”.

Gaining insight into how an asset is functioning or how a particular process is impacting efficiency can certainly allow your problem-solvers to make strategic adaptations that improve performance.

Actioning insights that improve the performance of a particular process or machine will, of course, save your organization money. However, the way you garner substantial cost savings is to implement a predictive operations solution that empowers you to scale learnings across your operational spectrum.

To accomplish this, you need a platform that is not only capable of collating a large pool of data, and cutting through the informational overload to deliver the insight that’s pertinent to overcoming the targeted challenge – you need a platform that enables comparing and contrasting of assets and processes at the enterprise level. Your data can’t be as powerful as it is capable of being if information is siloed and contained to the asset it came from.

Without the ability to easily and quickly interpret what assets are exhibiting greater performance, as opposed to others, it would be too time consuming to identify top performers and evaluate what circumstances are causing them to function more optimally.

Conversely, with a comprehensive Predictive Operations Platform at your disposal, these kinds of cross-operational insights will be made plain to see for your domain experts – allowing them to operationalize efficiency efforts across the organization. What’s more, a comprehensive predictive platform allows your experts to scale knowledge over time. That is, apply what the data is telling them to positively influence maintenance cycles.

This way, your organization is not only saving money through greater efficiency in the now (operations business case), you’re also maximizing profits into the future by considerably reducing wear and tear, and failure events (maintenance business case). It is these efforts that implement wide sweeping standardization of optimization at scale that result in very noticeable improvement of profitability.

To scale operations and maintenance optimizations within your organization, get started here.