Work.

Most manufacturers can see their direct suppliers. Almost half can't see past them. Nine in ten supply chain leaders dealt with a material disruption in the last year, and fewer than one in ten have a budget set aside to catch the next one early.

One month-long disruption can cost a mid-sized manufacturer up to a quarter of its EBITDA. Two-thirds of operations leaders say their technology spending hasn't delivered what they were promised. The most common reason they give is that their systems were never built to work together.

Our fixed-fee diagnostic looks for those warning signs inside one company, before they reach the income statement. Every finding traces back to something we observed or measured.

DoD relies on more than 200,000 suppliers to build and maintain its weapons systems. Many of them sit two, three or four tiers down, where visibility is lowest and foreign dependency is highest. Today there is no systematic way to tell which suppliers carry real dependency risk, because the government doesn't routinely collect the data needed to assess it.

The cost shows up later. Roughly 70 percent of defense electronics become obsolete before the systems they go into are deployed, because commercial parts change faster than defense programs buy them.

We submitted a Phase I proposal through DSIP to apply our scoring method to vendor economic dependency across Tier 2 to 4 suppliers. It uses the same diagnostic logic as our manufacturing work. A government buyer needs every score to trace back to its source data, and the proposal is built around that requirement.

The submarine supplier base is roughly 70 percent smaller than it was during the last major shipbuilding buildup. The lead boat in the Navy's newest ballistic-missile submarine class is running 12 to 16 months late, with cost overruns approaching six times the shipbuilder's own estimate. The current attack-submarine program is producing at roughly 60 percent of its planned rate. At one shipyard, more than half the skilled tradespeople have less than five years of experience, on work that takes three to five years to learn.

Too few suppliers, slipping schedules and experienced people leaving are the same patterns we look for in manufacturing operations. Here the cost of getting it wrong is measured in years and billions of dollars.

This is where we intend to take the method next.