The Historical Costs of Obsolescence Management With Big Data

By Logan Wamsley

One of the most significant features of all of Partstat’s obsolescence management solutions — BOM Monitoring, Part Search, Excess Inventory, and API — is our access to Big Data. Through the inventory uploads from thousands of manufacturers and authorized suppliers, Partstat allows our users access to over 50 billion points of Big Data. This provides our customers with an unprecedented view of the state of market for any individual electronic component, semiconductor, or related computer product.

While developing these solutions, we conducted a thorough analysis of dozens of similar offerings across the electronic manufacturing industry, and time and time again we determined that access to a comprehensive Big Data pool capable of consistently calculating average prices, inventory quantities, and lead times in an easily accessible format was the missing piece of the obsolescence management puzzle. Solutions that did not offer adequate Big Data could only provide a small, incomplete snapshot of the market at any given time, and solutions that did offer such data only offered it to customers unfiltered and raw — with the expectation that it would be up to the customer to analyze it and uncover any trends relevant to their needs.

Both of these options come with significant costs — as well as significant risks. The former option means that each decision regarding electronic inventory procurement is not made taking the full state of the market into account. Without the use of a comprehensive, real-time model, OEMs may initiate a last time buy when it wasn’t necessary, purchase inventory at a significantly higher premium than was necessary, or even be forced into transactions with third-party distributors with less-than-ideal transparency standards.

The latter, however, incorporates a different sort of cost. Historically, Big Data in itself requires a substantial upfront financial investment. For raw market data for components on a single bill of material alone, OEMs can expect to spend as much as tens of thousands of dollars. But even this does not give an accurate depiction of the true cost; once such data is acquired, the task then becomes analyzing it. There are a variety of ways OEMs can accomplish this. One option is to pull professionals with data analysis experience away from their normal position, which could potentially result in disruption of other elements of the business. If that is not an option, OEMs could also opt to invest in the proper training and development of current staff members, or expand their workforce to include new hires with such experience. Although recent signs of recovery have been positive, many electronic manufacturers still feeling the strain of the most significant electronic component shortage in at least a decade do not have the capital bandwidth to invest into hiring at this time. With the rise of automation also set to fundamentally alter the makeup of the manufacturing industry workforce, there may be even less available positions in the near future than there are today.

By offering Big Data to our customers without the burden of a significant investment, our solutions avoid the costs and risks associated with both of these two options. In fact, users with a Partstat account can conduct a Part Search for any electronic component absolutely free on the world’s largest free electronic component search engine. In seconds, they will be able to view a series of intuitive real-time trending charts that show trends related to price, quantities, and lead times.

Big Data has becomes a necessity in today’s market, but the electronics manufacturing industry is reaching a point where such data is no longer inaccessible behind an insurmountable paywall. To see for yourself how access to such data could permanently change your supply chain, click here to sign up for a free Parstat account today!