Blog #10 Federal Contracting Market Share Trends and Patterns
By: Leif Ulstrup
Tags: Analytics, Open Data, Python Pandas, Strategy, Federal

TL;DR — Uncover competitive insights from information and analytics using Federal contracting #opendata. Analyze > 100GB’s of US Federal spending open data with a few lines of Python code.

Previous Blog Post in this series can be found at this link.

Python code and the jupyter notebook for this analysis is on Github here.

Introduction

Several of the most popular and influential HBR articles on business strategy explore the relationship between market share, market growth, and profitability. In this tenth blog in my series, I show you how you can use Federal spending open data (USAspending.gov) to help guide your analysis of the market and shape your business strategy.

For most companies competing in the Federal contracting market (“Federal market”), the ~$600B/year in annual spending seems like an almost infinite amount relative to their annual revenue and a market with unlimited growth potential. With the exception of weapons systems platforms, most of the aggregated Federal market is highly-fragmented, relative to most commercial markets. However, at the Agency level, market share is more concentrated and it is challenging to dislodge incumbents that have solid past performance records. Competition for that work at re-compete time (~ every 5 years) can be intense. Incumbents have huge advantages in the Federal market. Also, most services contracts are long term (typically, one year with four option years) and incumbent recompete win rates over 75% are not uncommon.

Capturing market share for your firm’s services is often a long game and it can be expensive to displace incumbents in terms of bid and proposal to capture the work and managing profitability after the win.

Many Federal contractors thrive on a steady proposal machine fueled by a healthy pipeline of qualified opportunities.

Is it possible to make better capture investment decisions using insights about analytical features in the market the reveal competitive intensity and Agency-level buyer preferences?

Are there ways to use Federal #OpenData and analytical techniques to guide your planning efforts to yield higher ROI with a more focused strategy?

Natural Limits to Market Share?

For some of the largest segments of the Federal contracting market, there seem to be boundaries on market share by product or service category that reflect market competition, customer preferences, contracting practices, and other factors. Exploring those forces at the Federal, Department, and Agency for the segment of products or services your firm concentrates on can help in shaping your investment plans for new opportunities and retention of incumbent work.

Spending by Federal designated product_or_service code for GFY2019 (~$590B total prime obligations):

PSC_Cat = product_or_service_code which is the dominant type of work within the prime contract.

Selecting a subset of these codes (A, B, D, M, Q, R, S) that are focused more on services than products, you can see the GFY10-GFY19 market share trends for the #1 company each year in that PSC_Cat.

Market share for #1 Company in each PSC_Cat: GFY2010–2019.

Growing market concentration at the top: The top market share firm in PSC_Cat Q Medical Services has jumped significantly (50% increase— from 20% to 30%) between GFY17 and GFY19 over the ~20% baseline earlier in the decade. PSC_Cat B Special Studies has doubled from ~5% to ~10%. PSC_Cat M Operation of Government-Owned Facility has increased from ~12% to %16. Those categories represent ~$54B/year and ~9% of total Federal obligations.

Stable or declining market concentration: The #1 contractor in PSC_Cat A Research and Development has dropped from ~18% market share to ~13% over the decade while PSC Cat D IT and Telecom remained relatively stable at ~6% (with a significant fluctuation between GFY13-GFY17 of 2x) at the start and end of the decade. PSC Cat R Support Services has seen a slight decline from ~4% to ~3.8%. For GFY 2019 PSC_Cat A + D + R => ~$177B which is ~31% of total prime contracting.

Clustering of Market Share for the #1 Contractor each GFY by $ Value and Share Fraction — select PSC_Cat

Note how the PSC_Cat market share values are clustered by type of work. It is possible to capture 20%-30% of the spending in Medical Services (PSC_Cat Q), a > $20B/year market, but the #1 contractors in other major spending categories are only able to capture about 5%-10% of the spending in their work segment.

Exploring PSC_Cat D (IT & Telecom), R (Support Svcs), and A (R&D)

Let’s dive into the large PSC_Cat D, R, and A categories and explore those further.

Top Contractor (“Top_1”) in a GFY and PSC_Cat