What Preparation Actually Changes.
These outcomes come from engagements where financial data preparation happened before the buyer, lender, or investor arrived — not during due diligence.
What AJM Engagements Deliver
Undocumented EBITDA add-backs surfaced in a single diagnostic engagement
Data room build time for a client with 22 years of pre-cleaned financials
working capital target set and documented before signing — eliminating post-close dispute risk
Typical lead time where preparation produces the largest outcome improvement
Engagements and Outcomes
Details are anonymized to protect client confidentiality. Industry, revenue range, and engagement type are accurate.
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What the Data Diagnostic Typically Finds
These are the categories of findings that appear most consistently across AJM diagnostic engagements. Not every engagement has all of these — but most have at least three.
Undocumented EBITDA Add-Backs
Owner compensation above market rate, personal expenses run through the business, non-recurring costs that should be excluded from normalized EBITDA. Without documentation, a buyer applies their own adjustments — which are never in your favour.
Working Capital Baseline Missing
No documented working capital target or NWC analysis. The business has never calculated what “normal” working capital looks like on a trailing 12-month basis. This becomes expensive when a buyer proposes their own target.
Revenue Quality Not Assessed
Recurring vs. project vs. concentrated revenue is not broken out in any reporting. Acquirers and lenders apply significant discounts to revenue that appears non-recurring or concentrated — even when it’s actually stable.
Cost Structure Not Visible at Management Level
Gross margin and contribution margin by product, service, or customer aren’t tracked. The business may be profitable in aggregate while subsidizing unprofitable lines — invisible to the owner and highly visible to a sophisticated buyer.
Financial Statements Not Buyer-Ready
Three years of statements exist but are in compliance format, not management format. Notes are insufficient. Supporting schedules don’t exist. Building a data room from this state takes 8–12 weeks — compressing the window for everything else.
Operational Risk Not Quantified
Key-person dependency is present but never measured. Customer concentration exists but isn’t calculated. These are standard buyer discount items — knowing the number lets you address it; not knowing means the buyer defines it for you.
These Results Come from Preparation. Not from the Transaction.
The businesses above didn’t get better outcomes because their M&A advisors negotiated harder. They got better outcomes because their financial data supported their position before the buyer arrived. That preparation starts with the Data Diagnostic.
Why the Preparation Gap Exists
The businesses that enter succession processes unprepared aren’t poorly run. Most are well-run businesses with genuine value. The gap is advisory: there is no natural point in a business’s lifecycle where someone says “here’s what your financial data needs to look like before you go to market.”
Accountants handle compliance. M&A advisors engage when the deal is live. Lawyers engage at the LOI stage. No one engages 12–18 months before the process starts to prepare the data.
That’s the gap AJM fills — and the reason the outcomes above are achievable. The work isn’t complex. It just needs to happen before the buyer arrives.
SUPPLY CHAIN SIMULATION RESULTS
Where the Data Took Us Beyond Finance
These outcomes came from applying simulation and operational analysis to supply chain and logistics data — before financial decisions were made.
Energy & Logistics — USA, Canada, Mexico
Rail & road network redesigned across three countries
Asset utilisation improved from 17% to 42%. Profitability up 50%+. Network simulation modelled before a single route changed.
3PL Provider — Canada-wide
LTL consolidation & intermodal shift validated by simulation
39,000 rows of truck data analysed. Every recommendation was simulation-proven before a single route was changed.
Oil & Gas Distributor — Inventory
Unnecessary purchase orders identified in one data snapshot
$60M inventory analysed. $65M in unnecessary POs found. Ordering logic redesigned end-to-end before a dollar moved.
Powered by ARTEMIS simulation via our partnership with ALTS Canada — the same platform used in peer-reviewed supply chain research.
The Next Outcome Is Yours.
Book a discovery call. We’ll assess where you are and what preparation looks like for your specific situation.