“I know we need to move toward predictive operations, but I don’t even know where to begin.”
 

Maybe you’ve heard this sentiment expressed by someone on your team. Maybe you’ve even said this yourself. Despite the incredible benefits of moving toward a predictive operations model, the thought of achieving that ideal state can be overwhelming. 

Fortunately, we’re here to help. 

One of the most common barriers to progress we’ve seen is something we call the “boil the ocean” fallacy – the belief that creating a predictive operations environment is a cumbersome, costly, or time-consuming undertaking. The truth, however, is that game-changing results can be achieved simply by addressing two specific areas: data visibility and data context. 

To truly understand what’s happening, you first need to model the operating environment itself. Your processes may be comprised of a hodgepodge of legacy and new equipment, it might even feature different manufacturers with different communication protocols, and that’s okay. If it’s generating data, that data can be captured, normalized, and leveraged… and doing so is easier than you think. 

The “intelligent agents” capabilities built into the TwinThread platform will scan your network and identify all the different sources of data within your operation. Within minutes, you will be collecting and aggregating data from each source without the use of custom code or extensive manual effort. (Think of it as an optimization easy button.)

As that data is now discovered and starts streaming in, TwinThread will begin creating a “digital twin” of your process – an exact virtual replica of that which you’re trying to optimize. Within this environment, your data begins to gain context and you can see how the interdependencies between systems and devices coalesce to form a single process. 

This added context is what transforms raw data into actionable information, helping you to identify root causes of inefficiencies and errors. More importantly, however, this broader view of your operations will empower you to see how small changes can yield positive results across the business. Whether you’re trying to reduce costs, reduce errors, improve throughput, or “all of the above,” the visibility you’ll gain through this approach will help you to meet those metrics easily, quickly, and affordably. 

What’s more, this approach also provides a firm foundation from which you can scale. We’ve developed our platform to deliver rapid ROI so you can start a pilot, achieve positive results, then roll out across the entire enterprise in a time- and cost-effective manner. 

We know this is the type of support you need because we’ve walked a mile in your shoes. As industry veterans, we’ve always wanted a solution that would deliver the power and promise of Predictive Operations in a way that didn’t require a “rip and replace” approach. That’s why we built the TwinThread platform, and we would love to show you what it can do. 

Hit the “see a demo” button below and we’ll get a demo on the books.

 
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Luis Morinigo
Post by Luis Morinigo
February 16, 2021
Luis Morinigo is passionate about helping enterprise customers solve complex industrial challenges. With a unique cross-section of skills and experiences in consulting and emerging technologies, he ensures clients solve their most pressing, business-critical opportunities for enterprise scale. Luis excels in customer success management by focusing on long-term client satisfaction and retention. In addition to customer success management, Luis has a proven track record in enterprise program management. He adeptly manages high-level initiatives across organizations, coordinating multiple projects and teams to align with overall business objectives. Focusing on customer success and program management, Luis leverages his extensive cross-industry knowledge of technology and strategy to help customers derive the most value from the TwinThread platform to achieve their strategic goals. This ultimately drives significant business impact and fosters lasting customer relationships.