Operational Due Diligence Checklist

Executive summary

An operational due diligence checklist exists to answer one question that the financial model cannot: can the operation produce the cash flows in the plan without a hidden bill? Financial diligence validates history. Operational diligence tests whether the machines, people, systems and supplier relationships behind that history will hold when volumes rise, a key person leaves, or the new owner changes the way the business is run.

The output of this work should not be a narrative. It should be a findings register in which every observation is tied to one of four outcomes: a price adjustment, a one-time cost to fix, a run-rate cost change, or a condition in the purchase agreement. Anything that does not land in one of those four is a note, not a finding.

Three habits separate useful operational diligence from a site tour. Test capacity against the plan, not against history. Ask for the evidence behind every claim (maintenance logs, scrap records, supplier contracts) rather than the explanation. And rank findings by dollars and by how soon they bite, so the deal team can decide what to negotiate before signing and what to fix after closing.

This guide is written for buyers, including independent sponsors, search funds, corporate development teams and operating partners at private equity firms. It is also useful to sellers who want to see what a buyer will find. It sits beside the financial due diligence checklist and the quality of earnings work, and it is part of the due diligence hub.

When to use this

Use this checklist when:

• You have an indication of interest accepted and are entering confirmatory diligence.
• The target makes, moves or services physical things, or depends on a delivery operation that scales with labor.
• The investment thesis depends on growing volume, adding a shift or site, or consolidating operations with another business.
• The seller describes the business as "well run" and the evidence so far is the management presentation.
• You are screening an add-on and need a lighter version of the review. The add-on acquisition screening scorecard is built for that.

Do not use it as a substitute for specialist reviews where the law or a regulator is involved. Environmental, health and safety, product liability and regulatory compliance questions belong with qualified specialists and counsel. This guide tells you where to look and what to ask. It does not give legal or engineering sign-off.

Diagnostic questions

Start with these before the site visit. They are answerable from a data request and one management call. Weak or evasive answers tell you where to spend your limited diligence hours.

1. What is rated capacity for each constraint (line, work center, crew, dock, technician pool), how is it measured, and what share of it was used in each of the last eight quarters?
2. What does the plan require in volume terms, and does that volume fit inside current capacity without new capital or new shifts?
3. How much of the maintenance spend in the last three years was planned versus reactive, and is there a log of unplanned downtime by asset?
4. What are the top five reasons for scrap, rework, returns or credits, and who owns each one?
5. Which five suppliers or subcontractors matter most, what share of spend does each hold, and what is the contractual term and the realistic switching time?
6. Which processes live in one person's head or in a spreadsheet only one person understands?
7. How are on-time delivery, quality and cycle time measured, and are the figures produced by the system or typed in by the manager reporting them?
8. What happens when the ERP or the main system is down for a day? Is there a manual fallback that has actually been tested?
9. What capital items has the owner postponed in the last three years, and what would the next owner be expected to spend in the first 24 months?
10. Who are the ten people the operation cannot run without, and what is their tenure, pay position and succession cover?

Framework: six operating lenses

Operational diligence works best when each lens produces a defined output. The table sets out the scope, the evidence to request, and the output for each.

Technology and organization each have their own deeper treatments. Use technology due diligence for operators when systems are central to the thesis, and people and organization due diligence when the management team and workforce are the main risk. This guide covers the operating layer that connects them.

Lens 1: Capacity and throughput

Capacity is the most common place where a plan quietly fails. Management often quotes capacity as a theoretical figure (every machine running every available hour) while the business actually runs at a practical ceiling set by changeovers, maintenance windows, labor availability and the slowest step in the flow.

Define capacity at the constraint, not the plant. Find the resource that limits output (the press, the paint booth, the dispatch team, the lab) and measure it there. Then compute:

Utilization = Actual run (or productive) hours ÷ Rated available hours
Plan utilization = Plan volume expressed in hours ÷ Rated available hours

If plan utilization is above the practical ceiling the business has demonstrated, there is a capital or labor requirement behind the plan that the model may not include. The practical ceiling should be set from the business's own record: the highest sustained utilization it has achieved over a quarter without a rise in scrap, overtime or late deliveries. Do not import a generic figure.

For service businesses the same logic applies with billable hours, technician utilization or ticket throughput in place of machine hours.

Lens 2: Quality and delivery

Ask for cost of poor quality as a dollar figure: scrap, rework labor, warranty, credits, expedited freight and customer returns. Many businesses cannot produce this total. That is itself a finding, because a number that nobody sums is a number nobody manages.

Then test the KPI source. A reported on-time delivery rate is only as good as its definition. Ask whether on time is measured against the original customer request date, the confirmed date, or a date that was reset when the order slipped. A rate measured against reset dates will look healthy while customers are unhappy. The on-time delivery root cause attribution guide describes how to break late orders into causes, and the same method works as a diligence sample.

Lens 3: Supply chain

You are looking for concentration, term, and price exposure. For each of the top suppliers, record the share of relevant spend, the contract end date, whether pricing is fixed or indexed, whether there is an alternate qualified source, and the realistic time to switch. Single-source parts and sole-supplier subcontract steps deserve a named line in the findings register.

Lens 4: Assets and maintenance

Compare maintenance spend to the asset base over time and read the work orders. A pattern of reactive repairs on the same assets, a rising share of outside repair spend, or a gap between budgeted and actual maintenance points to deferred upkeep. Ask for the original equipment manufacturer service reports on critical assets and the age profile of the fleet. The output is a catch-up capex estimate: what the next owner must spend in the first two years to run assets in prudent condition. Where it is material, it is a price conversation, because the seller's cash flows were flattered by spending less than the assets required.

Lens 5: Systems and process

Map the systems that run orders, inventory, production and reporting. Look for work done outside the system, such as spreadsheets that carry the real schedule. Each is a control gap and a key-person risk.

Lens 6: People and key roles

List the operational roles whose loss would stop or degrade output within 30 days. For each, note tenure, pay relative to the market for the role, whether anyone could step in, and whether the person is a seller, a relative of the seller, or someone who may leave after a change of ownership. Retention arrangements, employment terms and any legal questions here are for the buyer's counsel and HR advisers.

Step-by-step process

Run operational diligence as a sequence with named owners and an output at each step.

1. Set the plan hypotheses. List the five or six operational assumptions the investment case relies on (volume growth, margin gain, headcount held flat, a site consolidation). Owner: deal lead. Output: one page of hypotheses to test.
2. Issue a focused data request. Ask for capacity data, maintenance logs, quality records, supplier contracts, system map and org chart for operations. Keep it to what you will actually read. Owner: operating partner or diligence lead. Output: request list with due dates.
3. Run the desk review. Compute utilization, cost of poor quality, supplier concentration and maintenance trend from the data. Owner: operations analyst. Output: first draft of the findings register.
4. Hold the management interviews. Interview the plant or operations head, the quality lead, the supply chain lead and the IT or systems owner separately, using the same diagnostic questions. Differences between answers are findings. Owner: operating partner. Output: interview notes.
5. Visit the site and sample. Walk the flow from receiving to shipping at a normal production time. Trace five recent orders from customer request to delivery. Pull a sample of maintenance work orders and scrap records and check them against what you were told. Owner: operating partner with an independent technical adviser where needed. Output: sampled evidence.
6. Price the findings. Convert each into one of four outcomes (price, one-time fix cost, run-rate change, deal condition) and add timing and a confidence rating. Owner: deal lead with finance. Output: completed register.
7. Reconcile with financial diligence. Check that the run-rate costs you identified are reflected in the quality of earnings adjustments and in the model. Owner: finance lead. Output: signed-off adjustment list.
8. Hand over to integration. Convert open findings into the first-100-day plan, with owners. Owner: operating partner and integration lead. Output: the 30/60/90 plan below, linked to the PMI playbook.

Templates

Findings register (copy into a spreadsheet)

Capacity test

Metrics and KPIs

Setting targets without invented benchmarks. Use three anchors: the business's own best sustained quarter, contractual floors in customer agreements (service levels, quality thresholds), and filings of named listed peers where a comparable metric is published. Set the practical capacity ceiling from the first anchor. Do not take a utilization or scrap figure from an article and apply it to a different process.

Common mistakes

1. Testing capacity against history. A plant that ran at three-quarters of rated hours last year looks comfortable until the plan asks for another 30% of volume.
2. Trusting reported KPIs without checking their definition. Reset dates, excluded orders and manually typed figures make metrics look better than the operation feels to customers.
3. Letting the tour replace the sample. A clean floor on a Tuesday tells you about the tour. Traced orders and work orders tell you about the operation.
4. Treating deferred maintenance as a negotiation afterthought. If cash flows were flattered by under-spending, the shortfall belongs in the price conversation before signing, not in a surprise in month four.
5. Treating findings as a list instead of a ranking. Forty observations with no dollars attached are noise. Rank by dollars and by timing.
6. Giving engineering, environmental or legal sign-off without the specialist. Use qualified advisers where the risk is technical, regulatory or legal.

Worked example

Illustrative. The numbers below are invented to show the method. They are not benchmarks.

A target runs three production lines. Each line is staffed for two shifts of eight hours, five days a week, 50 weeks a year.

• Rated hours per line: 2 shifts × 5 days × 50 weeks × 8 hours = 4,000.
• Rated hours across three lines: 12,000.
• Actual productive hours last year: 9,000.
• Utilization: 9,000 ÷ 12,000 = 75%.

The investment plan assumes volume grows 30% over two years.

• Plan hours: 9,000 × 1.30 = 11,700.
• Plan utilization: 11,700 ÷ 12,000 = 97.5%.

Management says capacity is not a constraint because 75% is comfortable. Plan utilization tells a different story. In the target's own records, the best sustained quarter ran at 85% before overtime and scrap began to climb. Take that as the demonstrated practical ceiling.

• Practical available hours: 12,000 × 0.85 = 10,200.
• Shortfall against plan: 11,700 − 10,200 = 1,500 hours.
• That is 1,500 ÷ (4,000 × 0.85) = about 0.44 of a line's practical output, so a fourth line, a third shift on one line, or process improvements that lift the ceiling are needed in the plan period.

The findings register for the same target, with illustrative dollars, might look like this:

What this tells the deal team: the growth plan is not wrong, but it is not free. The buyer can ask the seller to share some of the cost of catch-up, or accept it and price the plan accordingly. Either way, the discussion is about dollars and timing rather than impressions from a site walk.

AI prompt assistance

AI can speed up the desk review and the register. It cannot see your site, and it will accept whatever numbers you give it. Supply the data yourself and verify every figure against the source before acting.

1. Compute capacity and plan utilization.

I will paste rated available hours per line, actual productive hours by quarter for the last eight quarters, and a plan volume growth assumption. Calculate utilization per quarter, the highest sustained quarter, plan utilization, and the hours shortfall against that highest sustained quarter. Show each calculation.

Check: recompute one quarter by hand and confirm the inputs match the source system, not management's summary.

2. Classify scrap and return causes.

Here are 60 scrap and return records with free-text notes. Tag each with one cause from this list: material, machine, process, operator, design, supplier, customer-driven, other. Return a table with counts and the dollar value by cause. Flag notes you could not classify with confidence.

Check: spot-check ten rows against the physical evidence or the customer note. Do not assign a root cause without confirming with the quality lead.

Implementation guide

Governance: the deal lead owns the register until close, and the CEO owns it afterward. Report open items monthly to the investment committee or board until they close. The PMI playbook covers the wider integration cadence, and IT integration covers system actions that come out of Lens 5.

Downloadable assets

The findings register, capacity test, supplier concentration table, key-role dependency table and sampling plan above are designed to be copied into a spreadsheet. For the working capital side of the same deal, see the working capital peg estimator.

Related resources

• Due diligence hub: all the diligence guides in one place.
• Financial due diligence checklist: the financial counterpart to this checklist.
• Quality of earnings report before you close: where run-rate cost findings should be reflected.
• Add-on acquisition screening scorecard: a lighter screen for bolt-ons.
• PMI playbook: Day 1 to Day 365: where the findings go after close.

Frequently asked questions

What is operational due diligence?

Operational due diligence is the review of how a target actually runs, covering capacity, quality, supply chain, assets, systems and key people, to test whether the business can deliver the plan. It complements financial diligence by finding the costs and risks that historical financial statements do not show, such as deferred maintenance or dependence on one person.

What should an operational due diligence checklist include?

A useful checklist covers capacity and throughput, quality and delivery, supply chain, assets and maintenance, systems and process, and key roles. For each area it names the evidence to request and the output expected, so that every observation becomes a price item, a one-time cost, a run-rate change or a deal condition.

How do you test whether a target has enough capacity?

Measure capacity at the constraint, compute utilization from actual hours over rated hours, and then compute plan utilization from the volume the investment case needs. Compare plan utilization to the highest sustained level the business has achieved without rising scrap or late orders. A gap means capital or labor is needed.

How is operational diligence different from financial diligence?

Financial diligence validates what the business earned and how it accounted for it. Operational diligence tests whether the operation can keep earning that and what it will cost to fix fragile areas. The two should reconcile: run-rate cost findings from the operational review belong in the quality of earnings adjustments and the model.

How this works in a System of Performance

An operational findings register only helps if it stays connected to what happens after close. The observations, the dollars attached, who owns each fix and whether the fix delivered usually end up in a deck, then a spreadsheet, then someone's memory. A Performis routine can take on a recurring job like this, with the scope and fit agreed with you: it works from the records your team supplies, prepares the work for your named reviewer, and keeps each approval on record. If you want to see where your own operation is fragile before the next deal, bring it to us as a launch partner.