As many others in this industry, I’ve worked with FPDS data for a long time. I suppose the good news is that the system has changed little over the years, so time invested in learning its quirks is worthwhile. Below, I’ve outlined a few methods for maximizing its value and pitfalls that you may encounter.
For those of you who are new to federal market intelligence, the Federal Procurement Data System (FPDS) is the primary mode of transparency around government contracting. It’s best to think of this data as a running list of transactions, just like transactions in your bank account. Also just like your bank account, there are details like transaction amount and recipient, etc. However, unlike a transaction in your bank account, there is a vast amount of meta data surrounding each transaction in FPDS. For instance, contract details, socioeconomic indicators for the awardee and details on the procurement method, to name a few.
This is all well and good, but how do you make sense of all that information?
Viewing a single transaction in FPDS is great for a snapshot in history, but in order to derive value, we must look at the aggregate. After rolling up this spending along various dimensions, you begin to answer more meaningful questions:
Of course, that’s only of limited value. It’d be much better to know how these figures are changing over time.
The next level of understanding can come from watching sums and aggregations change over time. Viewing and understanding trends, especially at a granular level (like within an office or a for a specific contractor), can be incredibly valuable. Now, we can begin to see how contracting dollars are moving. How is the dominant contractor performing? Are they losing market share over time? Maybe this particular office is changing their buying patterns and moving dollars away from definitive contracts.
Now that we can see where money is changing hands and how those hands are changing over time, it’s important to take a step back and consider data quality. What do we mean by data quality? Data quality is really just the consistency of categorization and classification of the data. In the case of FPDS, we need to look into each transaction and understand if things like vendors or programs are represented in a consistent fashion. The short answer is NO.
In order to paint a vivid and accurate picture of the world, these data quality issues must be addressed. For instance, let’s say a contractor, “ABC, Inc.”, is represented inconsistently in the data. Some transactions have names like, “ABC INC”, “ABC, INC”, “ABC Inc.”; we could on and on. Although the data that describes the awardee is different, this is in fact the same vendor, and we want to see all their transactions reported together.
Unfortunately, there’s no shortcut to good data quality. It must be cultivated by dedicated analysts, intent on seeking out every discrepancy.
At Federal Compass, we have expert and dedicated analysts doing this every day. We don’t outsource any data normalization because this is fundamental to quality market intelligence.
If you visited our website, attended a webinar, or read one of our blogs, then you’ve heard we are built from industry feedback. Is that just a catchy marketing slogan, or does it create a real benefit and advantage for our users? Visit Federal Compass today, request a demonstration and experience the difference of a solution designed by your peers.
written by Jim Sherwood, published 12/04/2019
When pursuing the next opportunity, it’s [of course] important to understand the competitive landscape—who are the major players? how entrenched is the incumbent contractor? The answer to these questions lies in two fundamental areas of research 1) human intelligence, and 2) data-driven market intelligence. The only way to paint a complete picture of the competition around any opportunity requires both elements and requires them to work in concert.
written by Chad Ganske, published 12/03/2019