The Secret Behind Partstat’s Ability to Predict Obsolescence & Allocation

In addition to our ability to confirm component lifecycles, Partstat offers the only BOM Monitoring Solution on the market that can predict allocation before it occurs.

Especially when OEMs are facing the most significant electronic component shortage in over a decade, this feature has become an indispensable part of our customers’ supply chains. Instead of reacting well after allocation occurs, users of our BOM Monitoring Solution have the means to take a proactive approach to inventory management before increased competition drastically complicates the market.

How we manage to do this so accurately for our customers isn’t magic, nor is it an ability we keep shrouded in secrecy. It is actually quite simple. First off, Partstat defines “allocation” as a lead time that stretches to 16 weeks or more. We determined this window based upon our experience in the industry and what our customers deem allocation to be. From this baseline, we then created a set of algorithms to analyze our Big Data and look for a set of very specific trends.

The trends that determine whether or not a component is about to go on allocation are as follows:

When, and only when, these two directives are met, we will inform our BOM Monitoring customers that the component on their bill of material is predicted to go on allocation. This gives them a precious window of opportunity to react accordingly before an inconvenient supply chain disruption becomes unmanageable. The amount of time, money, and resources this feature has saved OEMs is almost incalculable.

As an example of our Big Data in action, let’s have a look at part number C0402C271J5RACTU. When this part is found using Part Search, we can easily view a chart displaying average lead times that looks like this:

In this case, the jump in average lead time in May, 2018 was quite drastic – over 388%. It’s easy to see how an OEM might be inconvenienced by such an unexpected event – within a week, a component expected to arrive within 9 weeks of ordering is suddenly denied for nearly a year.

Dig a little deeper into our Big Data, and we can also view how inventory quantities from Partstat uploaders have decreased:

Note: Blue is inventory from franchised suppliers, and yellow is from non-franchised suppliers. For the purposes of our allocation prediction algorithms, only franchised distributor data is used.

As you can see, our Big Data noticed a significant decrease in inventory quantity levels back around February – an approximately 20% drop. This, combined with lead times rising above 11 weeks at the same time, fulfilled the parameters needed for our algorithms to accurately predict this component was about to go on allocation. In this case, a BOM Monitoring customer with this component on their uploaded bill of material would have been alerted of this trend about four months in advance, giving them ample time to pivot their supply chain accordingly.

Now, for a more recent example, let’s look at the trending lead times and quantity levels for part number 08055C104JAT2A:

Note: Only the blue line, or inventory quantities from franchised suppliers, is used for allocation prediction purposes.

Not only does this part indicate an average lead time consistently above 25 weeks, it also shows quantities consistently dropped well into November (after a brief surge that also saw drastically extended lead times). Combined, these trends indicate to our algorithms that this is a part that will continue to be on allocation. A BOM Monitoring customer, however, would have been alerted of these fluctuations as far back as October when inventory quantities decreased over 80%, allowing them to get their orders at the lowest lead time available until 2019.

Predicition of Allocation Alerts can be viewed right from the customer dashboard. Here is what an allocation prediction notification looks like on the customer’s dashboard for part number RC0402FR07100KL:

Partstat does not restrict BOM Monitoring to a single bill of material at a time; instead, we monitor and predict obsolescence and allocation across an unlimited number of BOMs. From this alert, we can see that this customer has 4 BOMs uploaded that contain the component in question. With a click of a button, they can view each individual BOM in more detail, as well dig into our data through generated reports and datasheets.

Our ability to predict allocation across the electronics industry is unique, intuitive, and, according to our customers, absolutely integral to the success of their supply chain. It’s a truly one-of-a-kind feature, and it can only be found on Partstat.

To see it for yourself on your own bill of material, sign up for a 14-Day Free Trial by clicking here!