Convergence Data Team
Jan 18, 2023
PLM, Part cost, Benchmarking, Spend Analysis, Clusters, Supplier Rationalization, Pricing Data, Spend Rationalization, Value Engineering, Duplicate Analysis, Data Classification, Engineering, Supplier Management, Procurement

Engineering and Procurement: The Unlikely Power Couple That Can Save Millions

⚙️ Engineering is the heart and soul of any business that creates a product. Without a sellable product, the business cannot exist. However, many organizations overlook the sheer potential and power of uniting two divisions that may not always work closely -- Engineering and Procurement. Whether during times of economic downturn or through a corporate

 

 initiative to drive greater spend efficiency to reinvest in research and new product conception, every organization should consider exploring how to better align these two critical corporate functions. Modernizing your parts management process will not only increase productivity -- it can also help the broader team to drive down cost. With a data-driven approach to parts data and supplier management, your team can help to significantly reduce costs across the organization!

 

🎢 Without a data-driven approach, a company that grows through acquisition will likely inherit legacy data and systems. If your team already manually manages their parts in spreadsheets, the addition of legacy data from an acquisition target tends to compound the already complex data sprawl. For those teams integrating an acquired company, it means the potential for

  • more duplication,
  • less consistency across parts data attribution, and
  • proliferation of suppliers
Inevitably, Procurement will inherit this mess, which will make it more difficult to identify the right suppliers for the right parts at the right price.

 

❓ "How do we fix this?" This is easily the most common question our team hears. To control the sprawl of legacy parts data, your team will need to begin with the Engineering function to centralize the purchased parts. This means the creation of a single source of truth for your parts data. It also implies that the underlying legacy parts data will need a classification structure and deep enrichment of the attributes to begin. The approach that your team uses to harvest, structure, cleanse, and validate the data will be critical to the downstream success of your program.  The process should be based on a repeatable methodology that can work at scale across your population of parts. For example, the CDS team harnesses a proven 8-step process to cleanse and unify legacy data. Our underlying process is designed to accommodate and quickly transform large estates of legacy data.

 

💲In addition to consolidating the legacy parts data, your team will also need the ability to integrate supplier pricing data across the newly centralized library of purchased parts. We call this alignment a ✨ "magic cluster" ✨. This is where the power of data attributes can dramatically change the course of your business operations. To do this would require that the organization keep a database where Engineering and Procurement could access this information. However, this can be time consuming to maintain manually and costly to build your own in-house solution. What if there was a software tool that could help you create an electronic parts library, perform analytics on part pricing, and save you time by automating your processes?

 

📊 Clustering purchased parts is a great way to get them organized by category and price. Leveraging the "magic clusters" technique will allow your team to observe how much the organization spends on a purchased part with a given supplier. Having this benchmark and level of price transparency across purchased parts will enable your team to develop an actionable game plan. This means:

  • The ability to identify and segment based on high spend categories
  • Segmenting and prioritizing preferred parts across suppliers 
  • Tracking inventory data to streamline purchased parts inventory
  • The ability to pinpoint areas of potential cost reduction across your organization
  • Deeper collaboration between Engineering and Procurement
  • Gathering valuable inputs to drive improvements in how parts are procured
  • Managing competitive pricing across multiple suppliers

👉 Based on our team's experience and observations, the cost of creating and maintaining a part over its lifetime is between $10,000 - $15,000, on average. When that savings is scaled across a population of parts, it can represent cost savings to the tune of millions of dollars! Whirlpool is an excellent example of the power of spend rationalization in action, where the CDS team paired up with Whirlpool's Engineering division to rationalize and develop a strategy to better manage direct materials spend. The end results included a 20% average reduction in component costs. The savings for Whirlpool was significant and paved the way for a new approach to managing and prioritizing categories and suppliers.

 

➡️ Ultimately, parts management is a must-have for Engineering teams. It's especially critical for teams that have disparate systems, legacy data, and spreadsheets to get their landscape under control. Once the data is centralized, aligning Procurement stakeholders and integrating supplier pricing data and processes can represent the most significant force multiplier for your organization. Leveraging a centralized library that is easy to search and maintain will make it easy for your organization to better manage parts spend by analyzing preferred parts categories and pricing across suppliers. This, in turn, will help your organization to strategize and respond proactively to operational factors such as cost pressures, supplier negotiations, and supply chain concerns.

 

If your approach isn’t working for you or you're looking to expose more opportunities for cost savings, there's likely hidden magic within your parts inventory.

 

Looking to rationalize your parts spend? 👋 Reach out to us. We can help!