Private equity, supply chain, and the evidence that creates value

Private equity now earns more of its return in operations. Deals that once needed 5% annual EBITDA growth now need 10 to 12%. Supply chain touches every lever: cash, margin and growth. Buyers want evidence that AI creates value, so sellers need a track record and buyers need a trajectory. Optaro delivers both. It goes live in 72 hours at a fraction of the legacy cost, starts with one decision, and scales as one playbook across the portfolio.

This one is for private equity: the deal teams and operating partners, the leadership teams of portfolio companies, and the businesses preparing to become someone’s next acquisition.

You share a common language. Every plan, every board pack and every exit story comes back to the same question: where will the value come from, and how will we prove it?

I’ve worked on several sides of that question. I’ve done integrations and operations transformation in consulting, and run the P&L, working capital and supply chain in the CFO and CSCO seats. Here’s how I think AI fits into it, and where it doesn’t.

The value creation ethos

Private equity creates value in a handful of ways: grow the top line, expand margin, release cash, and exit at a stronger multiple than you entered. For a long stretch, financial engineering did much of the work. Apollo estimates that from 2010 to 2021, about two-thirds of value creation came from leverage and multiple expansion.

That era is over. Bain’s 2026 Global Private Equity Report captures the new math in four words: “12 is the new 5.” In the 2010s, a typical deal needed about 5% annual EBITDA growth to return 2.5 times invested capital over five years. With today’s borrowing costs and record purchase multiples, the same return needs 10 to 12% a year. Holding periods have stretched to around seven years. Alvarez & Marsal’s 2026 survey of European sponsors and portfolio executives reaches the same conclusion: operational value creation is now the primary driver of returns.

So value creation has become an operating discipline. The best plans name the levers, put numbers on them, set a timeline, and measure progress against it.

Why supply chain sits at the center

Few parts of a business touch every value lever at once. Supply chain is one of them.

• Cash. Inventory is often one of the largest uses of working capital. Sizing it to real demand releases cash, and net working capital is negotiated in nearly every deal.
• Margin. Freight, expediting, obsolescence and manual effort are recorded as operating expenses, so each reduction flows directly to EBITDA..
• Growth. Service levels protect revenue and retention, and they underpin the growth story a buyer is asked to pay for.

Sponsors know this, but execution lags. FTI Consulting’s 2026 PE Value Creation Index finds that consumer and retail sponsors rank procurement and supply chain among their top three value creation priorities. Yet those functions are consistently among the weakest performers after close. Too often, supply chain is managed as a cost center rather than engineered as a value lever.

Supply chain also runs on decisions, thousands of them every week: what to buy, hold, make, move or expedite. Each one carries a number. That is where AI value lands hardest, and where it is easiest to measure.

The buy side and the sell side are asking for the same thing

AI is now part of how buyers assess a business. Software Equity Group surveyed roughly 150 private equity and strategic buyers for its April 2026 report:

• 86% said AI is already affecting valuations.
• 61% expect future targets to be meaningfully AI-driven within a year.
• Two-thirds said they see only limited AI adoption in the companies they evaluate today.

The direction is clear. Buyers want AI working in the business, and most targets can’t show it yet.

Diligence is moving the same way. PwC’s AI diligence offering sets out to “assess a target’s real ability to build, scale, and govern AI before you commit.” RSM’s guidance for PE deals argues that any AI bet treated as a value driver should rest on validated use cases with a measurable path to EBITDA within about six months.

Strip the frameworks back and a buyer is asking three things:

1. What changed? Cost, revenue, cash or cycle time, in numbers.
2. What did it cost? Build, run, change and govern.
3. Will it last? After close, after the people who built it move on.

Those questions define what each side needs.

The seller needs a track record. Evidence that value has already been created, and that it held up. Not a headline saving that pushed cost somewhere else but results that trace back to real decisions.

The buyer needs a trajectory. Confidence that value will keep coming after close, from something that stays with the business rather than a team or a one-off project.

A list of AI pilots gives you neither. A record of decisions, each tied to value, gives you both.

Where Optaro comes in

We built Optaro to deliver both sides of that story, starting from the value creation lens rather than the technology.

Value first. Every recommendation Optaro makes is tied to cash, EBIT or top line, with its value, its drivers and its trade-offs shown. We didn’t start by asking what AI could do in a supply chain. We started by asking which decisions move the number.

Speed and price are part of the value case. Every hold period runs on a clock, and Bain puts it at around seven years. With the EBITDA growth bar doubled, late value costs more than it used to.

A multi-quarter build with a large SI bill pushes value out to year three. The cost of that build also comes out of the same EBITDA it’s meant to improve.

Optaro takes a different route:

• Live in 72 hours on the company’s own data.
• No SI build.
• Roughly a tenth of the cost of the legacy alternative.

Value shows up in the first quarter, well inside the window diligence looks for, and without a large upfront bet.

Start with one decision, not a package. Optaro is a set of competencies across the supply chain, and each one can create value on its own:

• Demand and inventory. Sizing and positioning stock to real demand, releasing cash without hurting service.
• Procurement and supply. Getting purchasing cycles, supplier lead times and supplier performance working for the business.
• Production and materials. Aligning what gets made, and when, with real demand and supply.
• Logistics and fulfillment. Taking expedite and freight cost out while protecting delivery.

A portfolio company can start with the one decision that matters most to its P&L and prove the value there.

Connect related decisions for a multiplier. Supply chain decisions depend on each other. Inventory depends on supplier lead times, purchasing cycles and the demand signal. Optimize inventory alone and you get value. Connect it to the decisions that drive it and you get more:

• Steadier lead times lower the buffer needed.
• Better purchasing cycles bring down cycle stock.
• Fewer shortages mean fewer expedites, and freight cost follows.

Each improvement makes the next one larger. The business chooses when to connect, at the pace the evidence supports.

Track record for the seller. Every decision is recorded with its value, its reasoning and who approved it. Inventory down with service held, and freight down without supplier performance slipping. That is evidence a diligence team can test.

Trajectory for the buyer. The value lives in a platform running on the company’s own systems, not in a team that might leave after close. The next connected competency is the next step in the value-creation plan. It compounds over the hold period, because every accept and reject trains the model.

One playbook across the portfolio. An operating partner can’t run a bespoke, multi-quarter AI program in every portfolio company, especially in the mid-market. A platform that goes live in days, at a fraction of the legacy cost, on whatever data each company already has, can be repeated across the portfolio. It is measured the same way in every company, in cash, EBIT and service, which gives the fund a consistent view of where value is being created.

Standalone or integrated. The same approach serves both theses.

• Standalone. Optaro shows the value a company can create on its own data, network and suppliers. That is the case for the business as acquired, and the case it carries to exit.
• Integrated. In a buy-and-build, the value pool grows as businesses connect, through shared suppliers, combined freight volumes and stock positioned across overlapping networks. Synergies that usually sit in a deal model as assumptions become decisions, executed and measured.

A portfolio rarely runs on one ERP. Optaro works from the data each company already has, so that value doesn’t wait for a systems consolidation. Each company runs in its own isolated, encrypted environment.

How it works

Sense. Analyze. Execute.

1. Sense. Connect to the systems and files the company already runs on: ERP, planning, warehouse, transport, procurement and spreadsheets.
2. Analyze. Our Supply Chain Language Model, purpose-built for the domain, reasons across connected decisions and shows the value, drivers and trade-offs on each one.
3. Execute. The AI recommends, your team approves, and Optaro writes the decision back into your systems. Humans stay in control, which answers the governance question before diligence asks it.
4. Learn. Every accept and reject trains the model. TokenOps routes each task to the cheapest sufficient model, so run cost stays lean as usage grows.

Optaro has been proven in production on a customer’s own data, where it met the modeled outcome. Across the value drivers we model, potential outcomes include:

• 5 to 10% of inventory freed
• 5 to 10% lower OpEx
• 2 to 5 points of OTIF
• 50% faster decision cycles

These are potential outcomes, not guarantees, and every one is measured at the decision.

Value first

AI won’t earn a higher multiple by itself, and no one should promise that it will. AI that starts from technology produces activity. AI that starts from value produces evidence. When it’s fast, priced to pay back inside a hold period, and able to grow one connected decision at a time, it keeps producing that evidence after close.

If you’re a deal team or operating partner building a value-creation plan, a portfolio company leader with a number to hit, or a business preparing for sale, send me a message. We’ll start with the one decision that matters most to EBITDA and prove it on your own numbers.

Learn more at https://optaro.ai/ and read the full series on our blog.

Sources: Bain & Company, Global Private Equity Report 2026. Apollo, “Private Equity Returns to Its Roots,” January 2026. Alvarez & Marsal, European Private Equity Value Creation Report 2026. FTI Consulting, 2026 Private Equity Value Creation Index. Software Equity Group, survey of approximately 150 private equity and strategic buyers, April 2026 (software sector). PwC, AI and technology due diligence. RSM, “Evaluating AI readiness in due diligence for private equity deals,” October 2025.