When a company takes on a parts classification project, it tends to be primarily focused on what engineering needs to make it easier to find and re-use preferred parts. While engineering may put in significant effort to classify their parts and create a classification data model, the benefits will be limited to engineering.
🚧 Resource constraints, homegrown classification pilots, or lack of budgetary funding to complete the project may sometimes crop up, leaving the engineering team to explore alternative approaches including shape-based search as a "quick fix" to achieving part reuse.
To increase the value proposition of cleaning up your parts data, a company should consider the needs of other functions that work with parts, like the purchasing organization. This article discusses the large potential value proposition that is unlocked by uniting the engineering and procurement functions as joint stakeholders in a classification effort.
Uncovering Hidden Spend
One of the biggest expense items for any manufacturing company is their direct material spend. Direct materials are parts that are used on products. That said, direct materials are a recurring expense - products can be made in high volumes which means parts are purchased in high volumes.
If procurement doesn’t have access to classification data on parts they've previously purchased, it becomes challenging for them to find the best supplier for a part or be able to rationalize spend with preferred suppliers. They are really handcuffed and can't do their jobs effectively, which can cost a company millions in unnecessary direct material spend. 💸
A best practice approach is to include your procurement team in the classification project from the beginning. Find out what information purchasing needs to be able to be able to do their jobs more efficiently. Some basic things a classification project can do that would help purchasing, should be captured at the beginning of the project as part of requirements gathering. 📝
💡 One "quick hit" area to explore is the category of electronic parts. Purchasing can often buy electronic parts from more than one supplier. If engineering links their classification data to the suppliers and manufacturers that produce the part, that results in a significant benefit to the enterprise.
👉 This allows purchasing to determine which parts they buy from suppliers, while also providing a more granular spend view of the data versus only being able to roll up spend by a commodity code. In addition, commodity codes are often incorrect and the classification project can fix them at the same time -- another benefit! For more information on component supplier management, click here.
For many organizations, engineering and procurement are siloed and not working together. Typically, engineering sends new part requests in an ad hoc fashion to procurement every day (and with limited information). This relationship is too costly to industrial manufacturing companies, meaning they cannot be cost competitive in the marketplace due to this lack of efficiency, manual efforts, and siloed communications. ⛔
When to Engage Procurement
Engaging procurement in the early stages of the classification project is a best practice and can be hugely beneficial. If you bring them in too late after the data's been captured for each part, it may result in having to redo the classification project or worse, lead to procurement doing their own duplicate data work. ⚙️
Why Procurement?
Procurement has limited ability to rationalize spend on similar parts when they lack the data to identify and group similar parts. With the right data, they can uncover powerful and actionable insights with this information.
How To Get Started
By combining the technical attribute data with the supplier commercial data (e.g. supplier, pricing, etc.), the enterprise is able to rationalize spend. However, to be able to rationalize spend and suppliers, clean and normalized data a must-have. To get started:
- All supplier names must first be normalized.
- From there, each supplier will need to be mapped to the components they provide to the enterprise today.
- Once all of this data has been linked up, technical and commercial, companies can now cluster the data.
Example of a cluster of 22 Motors - all have very similar characteristics, bought by different suppliers at different company locations.
In conclusion, if you're considering a classification project, purchasing makes up a significant component of the value proposition. If they are not included, the value proposition to the broader enterprise is greatly diminished. In addition:
- Don’t allow functions within a business to do classification work independently of other divisions. That defeats the purpose of integrating operations across the digital thread.
- Make sure you include the requirements of other business functions before you make the investment in cleaning up the data associated with your parts. The investment in a cross-functional enterprise classification project is minimal when compared to the significant benefits derived when more of the key stakeholders in the enterprise are included.
✍️ Contact us today to learn more about the driving deeper value out of your parts data and how it can save the enterprise millions in direct materials spend!