For the GovCon CEO preparing for a sale—and the investment banker running the process. The firms that get to LOI fastest and trade with the least re-trade risk are the ones that already have what buyers ask for. Arcvue produces it as a byproduct of running the business, not as a sprint before kick-off.
Every experienced deal maker knows the cascade. A buyer finds one inconsistency in diligence—an EBITDA adjustment that wasn't in the CIM, a revenue number that doesn't reconcile to the waterfall, a contract that closed differently than described. They don't move on. They start looking harder at everything. The posture shifts from confirmatory to adversarial. Re-trades happen not because of one fatal flaw but because accumulated doubt changes the relationship. By month three of diligence, even a clean answer feels suspicious because the buyer is no longer looking for evidence that the deal is good—they're looking for evidence that it isn't.
The business that has been running Arcvue for two years arrives at the diligence table with data that has been stress-tested against its own books every month. The first question the buyer asks gets a clean, traceable, current answer. The second question does too. That sets the tone for everything that follows. Buyers who spend diligence confirming what they were told move faster, re-trade less, and close with more confidence. The multiple reflects that confidence as much as it reflects the underlying financials.
The other truth that rarely gets stated plainly: most sellers don't actually need the maximum possible price. They need the price that works for them, with absolute certainty that the deal will close. A partnership dissolution, a health event, a debt maturity, a life transition—any of these makes certainty more valuable than basis points on the multiple. A process that stalls in diligence, re-trades twice, and closes nine months late at a lower number costs more than a process that closes clean at a price that was acceptable on day one. The data room that builds itself is the infrastructure that makes certainty possible.
For sell-side bankers, the dynamic is the same from the other direction. Data gathering and document preparation are the long pole in every engagement tent. The deal is financeable on day one—the banker knows it, the client knows it. Getting the materials to a state where buyers can confirm that, and answering their follow-up questions without a two-day cycle back to the client, is where most of the timeline goes. A client on Arcvue changes that equation from the first week of the engagement.
The firms that command the strongest sell-side outcomes are not the ones that optimized for the process. They are the ones that built the right business for years before the process happened. Value Builder tracks 10 key attributes buyers and lenders evaluate—set-aside concentration, contract concentration, prime/sub mix, recompete risk, customer desirability, capability profile, revenue trajectory, EBITDA margin, addback quality, and management depth—continuously against your live ERP data.
Every close, the assessment updates. The History tab shows how your profile has moved over time. If a banker or lender has given you feedback on specific attributes, set a goal and the platform tracks it automatically—no manual check-ins, no spreadsheet. A CEO who has been running Value Builder for two years walks into a banker meeting already knowing what the banker is going to say. That is a different conversation.
The contract waterfall in Arcvue generates from live ERP data. Active contracts project forward from actual period of performance and funded value. Recompetes are tracked with timelines and probabilities. New growth ties directly to pipeline opportunities in the BD module. The waterfall is always current—not built once at engagement kick-off and then defended as it ages. When a new month closes, the waterfall reflects it automatically. When the buyer's diligence team asks for an updated version, the answer is available before the question finishes.
The format is investment banking standard. Active base, recompetes, and new growth decomposed year by year by division, with pipeline coverage ratios at the bottom. Every assumption is traceable—the active contract projections come from actual ERP data, the new growth ties to specific pipeline opportunities, the recompete probabilities are set by the company and documented. A buyer who challenges any number gets sent to the data, not to someone's judgment call.
Pipeline coverage ratios are unweighted—because in GovCon, every bid is binary. The coverage story the waterfall tells is the one buyers can verify: this is how much pipeline exists, this is what we need to win to hit the number, and here is the gap by division and by year. That's a defensible growth narrative. A narrative without coverage data is a projection.
When the client is on Arcvue, the banker's analyst has direct access to the financial data that answers the majority of diligence questions without picking up the phone. What were the indirect rates for each of the last three fiscal years? Pull from the indirect rate history. What's the contract-level GP% on the top five revenue contracts? Pull from contract performance. What's the funded backlog as of last month? Pull from the contract module. What does the EBITDA bridge look like from net income to adjusted EBITDA with add-backs? Pull from the platform.
The questions that used to require a client call—then a wait while the client assembled the data—then a review cycle before it could go in the data room—get answered in hours, not weeks. The client stays focused on running their business at exactly the moment when distraction is most costly. The process moves at the pace the buyer's diligence team can absorb, not at the pace of the client's availability.
Updated numbers work the same way. When a new month closes during the process and the buyer asks for an updated financial model, the analyst refreshes it from Arcvue. The waterfall updates. The trailing twelve months P&L updates. The indirect rate history adds a data point. Nobody has to call the controller. Nobody has to wait for an export. The process doesn't stall because the calendar moved forward.
EBITDA adjustments are one of the most consequential—and most disputed—elements of any GovCon acquisition. Owner compensation normalization, one-time transaction costs, non-recurring legal expenses, above-market rent on related-party leases—each one is legitimate if documented and challenged if assembled under pressure. Buyers discount adjustments that appear for the first time in the CIM. They accept adjustments that were tracked monthly throughout the hold period.
Arcvue tracks EBITDA adjustments continuously. Each item is entered with a category, a description, a dollar amount, and a date. The adjustment schedule accumulates over time so by the time a process begins, you have twelve or twenty-four months of documented add-backs—not a list assembled by your CFO the weekend before the banker presentation. The EBITDA bridge from net income to adjusted EBITDA, with every add-back dated and described, is generated from the platform in the format buyers and lenders expect to receive it.
When a buyer challenges a specific adjustment, the documentation is already there. The first time it appeared in the schedule. The amount in each subsequent period. The total across the trailing twelve months. Defending an adjustment with a dated record is categorically different from defending it with a verbal explanation—because a dated record ends the conversation, while a verbal explanation invites more questions. That distinction matters enormously in a diligence process where one challenged item that isn't cleanly resolved becomes the reason the buyer starts auditing everything else. The adjustment that's been tracked in Arcvue for eighteen months doesn't get challenged the same way as the one that appeared in the CIM for the first time. Buyers know the difference.
Strategic buyers and financial buyers evaluate past performance differently, but both care about the same underlying questions: What agencies has this business served? What work types? What's the concentration—is one customer 40% of revenue and one contract 25%? What's the recompete track record? What do the CPARS ratings say about delivery quality?
The Arcvue past performance library is a structured, searchable database of every contract the firm has performed. Agency, dollar value, contract type, period of performance, work type, labor categories, and CPARS ratings are all indexed and filterable. Export only the fields the buyer's diligence team asked for—formatted, clean, ready for the data room. Not a reformatted Word document. Not a spreadsheet someone built overnight. The records have been maintained throughout the hold period, so the data is complete and consistent.
Customer concentration analysis runs automatically from the contract database. Revenue by customer as a percentage of total, trending over the last three years. The top five contracts and their periods of performance, funded value, and recompete timeline. A buyer evaluating concentration risk gets the answer in a form they can analyze, not in a document they have to parse. That's the difference between a diligence process that builds confidence and one that generates follow-up questions.
The math is straightforward. A 6-8 month sell-side engagement on a GovCon business in the $15M-$100M range typically generates $1.5M or more in fees. Getting to close two weeks faster—or spending two fewer weeks on data gathering—is worth far more than $2,000/month to the firm running the process. Recommending Arcvue at engagement kick-off isn't a favor to the client. It's a decision that makes the engagement run more efficiently from day one and meaningfully improves the probability that the deal closes at all.
The red flag cascade is the real deal killer in GovCon sell-side processes. One inconsistency in the data room—a revenue number that doesn't match the waterfall, an EBITDA adjustment that wasn't tracked—changes the buyer's posture from confirmatory to adversarial. From that point, every subsequent question gets answered under suspicion rather than good faith. The engagements that close clean are the ones where the first ten diligence questions all get clean answers. That's what Arcvue makes possible—not by hiding anything, but by ensuring that what's been said is exactly what the data shows, continuously maintained, without assembly.
With the client on Arcvue, the banker's analyst has direct access to the financial data behind the majority of diligence questions. Updated waterfall? Pull it. Trailing twelve months by division? Pull it. Indirect rate history for the last three years? Pull it. EBITDA bridge with add-backs dated and documented? Pull it. The questions that used to require a client call, a wait, a review, and a data room upload happen in hours. The analyst works from the platform instead of from email chains.
When buyers ask for updated numbers mid-process—which they always do—the update happens without disrupting the client. The controller doesn't get pulled off month-end close to rebuild the waterfall. The CEO doesn't spend a day on financial model maintenance during the most important sales process of their career. The process maintains momentum because the data infrastructure is already in place, not because everyone is working nights to keep it current.