ThingWorx Customers: Should You Extend the IoT to Parts Management?

Written By: Leslie Paulson
  • 6/21/2018
equipment availability vs fill rate service parts

There’s been a lot of buzz around ThingWorx lately.

For one thing, Gartner just named PTC a “Visionary” in its Magic Quadrant for Industrial IoT Platforms. Gartner’s analysis highlighted the ease with which manufacturers currently using Windchill, Servigistics, and other PTC solutions can “leverage the natural synergies of [the] ThingWorx IIoT platform.”

Conversely, existing ThingWorx users are in an excellent position to tap into Servigistics’ Connected Service Parts Management solution, a capability that includes equipment utilization and population data to forecast parts demand.

Would Connected SPM strategically benefit your business?

Should every organization using ThingWorx utilize Servigistics? Any organization stocking service parts to support an installed base of connected equipment should consider using Connected SPM.

Suppose you manufacture MRI machines, and your organization is actively offering aftermarket services. The accuracy of your parts demand forecasts directly impacts your ability to guarantee hospitals can use those machines when patients require procedures. The better you can eliminate parts-related unplanned downtime, you have the foundation needed to offer (or deliver on) uptime agreements.

The key data that ThingWorx provides

Whenever someone mentions a “connected” solution, many assume that solution requires real-time data to operate to its full capacity. As my colleague, Ed Wodarski, has stated, that’s not necessarily the case.

If you want to forecast equipment failure rates over a three-month period, he or she doesn’t need real-time data to do so. He or she simply needs the following data:

  • the location of each asset across the installed base
  • the number of assets across the installed base
  • the utilization rate of each asset

Servigistics would take this information, as well as the asset’s maintenance history and other causal factors, to forecast demand for parts across your global installed base. You can run these forecasts every week, month, three months, or whenever.

This is just the tip of the iceberg. We’re currently working on ways to leverage machine learning to better take advantage of the power of connected devices, ensuring organizations can deliver the right part, at the right place, and at the right time. If you want to learn more about what connected SPM is as a practice, as well the obstacles you’ll face when implementing such a strategy, check out our definitive guide below:

Read: The Definitive Guide to Connected Service Parts Management

  • CAD
  • Industrial Internet of Things
  • Service and Parts
  • Digital Transformation

About the Author

Leslie Paulson

As General Manager of the Servigistics Business Unit, Leslie has responsibility for worldwide sales, marketing, business development, customer success, and research and development. She brings a wealth of experience from her 29-year career at Caterpillar, with 16 years as a member of executive management teams. Leslie is known for her passion and focus on driving change to deliver customer value and growth. She has a superior command of disruptive technology and its impact on service operations. She has brought her vision and experience to Servigistics and is leading an era of rapid innovation, further fortifying Servigistics as the industry-leading service parts optimization solution. 

Leslie has degrees from Southern Illinois University, Carbondale (MSME, BSME, Engineering), Bradley University (MBA) and Stanford (Executive Program).