Updated April 17, 2024
Data management is an important topic and many companies struggle with common issues. Resolving these issues is a pertinent step in the process of becoming more data-driven. In this article, we dive into today’s business challenges, including the top seven issues to avoid.
👉 Many businesses face the challenge of finding and reusing their parts and components -- particularly if they have not yet adopted a classification structure for that data. By using an outdated homegrown system or offline spreadsheets, they are typically only able to see things like a part number and partial description, which tend to have limited information. This limited attribution becomes a challenge, in particular, for engineering to reuse these parts.
For example, let's say that an enterprise has 14,000 fasteners in its parts population. However, due to a lack of metadata, engineering cannot find the correct fastener to use. Since it would take far too long to review the inventory to see which one meets their requirements, they instead create each one as a “new” part, a scenario that often leads to a proliferation of duplicate parts! ⚙️
Our recommended solution to this problem is to implement a classification structure and enrich the existing parts. This will help engineering to find parts based upon categories and specific attribute filters to enable a more dynamic search across the enterprise.
Classified data also aids both engineering and procurement to classify and organize their data by specific categories and identify which suppliers they are purchasing the parts from. Complete, concise, and accurate attribute data is critical to the enterprise in that it allows for technical, numeric, meta, and string data to be seen. This becomes a helpful tool for both procurement and engineering to do their job in the most effective manner. Ultimately, better metadata will yield better decisions (and therefore, results) for the enterprise.
🚧 Below are the Top 7 data challenges that engineering and procurement stakeholders typically face:
- Procurement lacks information to source new parts
- Engineers engage suppliers that are not approved
- Procurement either has too many suppliers or is sole-sourced
- Pricing on similar parts varies widely across suppliers
- Procurement lacks the data (and, therefore, the bargaining power) to challenge higher supplier pricing
- Different regions purchase from local suppliers
- Inability to cluster similar parts for market basket sourcing savings
In addition to bringing the engineering and procurement stakeholders together to the table, one key next step to consider is the creation of a cluster analysis. Cluster analysis allows for similar parts that are grouped by key attributes. This will showcase supplier pricing and enterprise spend. By showcasing pricing, engineering will gain visibility into to see where cost-saving measures could be implemented within a given design. In parallel, procurement is better prepared to leverage a deeper view of supplier spend to drive spend rationalization initiatives.
💡For more detail on these “Top 7 Issues,” we highly recommend watching our most popular webinar based upon this blog. Please click on the link to check it out.
