Anchorage Capital Partners: 246 bps of revenue in EBIT gain identified

Client: Anchorage Capital Partners, Sydney

Target: National multi-site services business, more than 50 locations, consumer and corporate customers (name and sector withheld)

Service: Commercial pricing due diligence

Led by: Ron Wood, Founder and Managing Director, Pricing Insight

In brief

Anchorage Capital Partners engaged Pricing Insight to test the pricing case inside its investment plan for a proposed acquisition. We sized the annualised earnings before interest and tax (EBIT) gain from better pricing at about 246 basis points of revenue, tested how much of that gain survives revenue-linked costs and customer response, and reconciled it to the investor’s plan.

Key facts

• Client: Anchorage Capital Partners, Australian private equity
• Engagement: Pricing and margin due diligence, inside the transaction timetable
• Scope: More than 50 active sites, each sized individually
• Competitor evidence: 1,165 like-for-like price comparisons across six brands
• Fees and charges reviewed: 30 charges benchmarked against five competitors
• Annualised EBIT gain (base case): About 246 bps of revenue, before implementation costs
• Share reaching EBIT: 70 cents of each extra revenue dollar, after revenue-linked costs
• Expected realisation within the first 12 months: About 63% of the annualised gain
• Break-even customer loss on price rises: 1.9% of customers
• Output: 71-page investment committee pack, covering letter and 21-point action plan

Client overview

Anchorage Capital Partners is a Sydney-based private equity firm, founded in 2007, that invests in lower mid-market businesses across Australia and New Zealand. Its approach relies on operational change after acquisition, which means the investment case depends on improvements that management can actually deliver. Public sources put its funds under management at more than A$1 billion across four funds.

The target was a national business operating more than 50 active locations, selling to both consumers and corporate accounts through a mix of direct and third-party channels. Its revenue carried several layers of cost that rise with sales: turnover-based rent at its largest sites, channel commissions, royalties and frontline sales incentives. Prices changed by season, by location and by how far ahead customers ordered. Add-on products and service upgrades were a material part of the margin.

Anchorage had already built a value-creation plan that included a pricing component. It asked Pricing Insight to test that component before the investment committee (IC) made its decision.

What problem did the investor need solved?

Private equity plans often carry a pricing line. It is usually one of the larger value-creation items, and one of the least tested. A pricing case built from the vendor’s information memorandum or a top-down assumption (“a 2% price rise across the book”) tends to share three weaknesses.

First, it treats extra revenue as extra profit. In a business with turnover rent, channel commissions and royalties, every extra dollar of price loses part of itself before it reaches EBIT. Second, it treats the business as one average. A national network with more than 50 sites, several customer segments and seasonal demand does not respond to price as one unit. Third, it rarely asks what customers will do in response, or how quickly the gain arrives.

Anchorage needed answers to four questions within the diligence window:

• Is there a real pricing gain, and how large is it? Sized to EBIT, not revenue, and on evidence the IC could test.
• How much of that gain is already in our plan? A diligence finding that confirms the plan is useful. One that shows the plan double-counts or overreaches is more useful.
• What could stop the business delivering it? Customer response, capability, data and contract constraints.
• What should management do first, and in what order?

The information available was typical of a live transaction. Transaction-level data covered the seven largest locations. Site profit and loss data covered the full network. The vendor’s financial model held the cost rates. Some data room documents were protected and could not be opened, and several items the analysis needed, such as conversion rates from enquiry to order, were not supplied. The work had to be clear about which conclusions rested on data and which rested on stated assumptions.

Objectives of the engagement

• Size the annualised EBIT gain from better pricing, lever by lever and site by site.
• Separate gross revenue gain from the EBIT that remains after revenue-linked costs.
• Test the target’s price position against every relevant competitor on a like-for-like basis.
• Reconcile the sized gain to the pricing line in Anchorage’s plan.
• Show how much of the gain is realised within the first 12 months, and what customer loss would cancel it.
• Assess management’s pricing capability and set out a sequenced action plan.

How did Pricing Insight approach the diligence?

Seven workstreams. Each one answered a specific question the IC would ask, and each fed the same sizing model, so that every figure in the final pack traced back to a source and a stated rule.

1. Market position: where does the target actually sit against competitors?

We built a like-for-like competitor survey of 1,165 price comparisons across six brands, covering the target’s main product classes, its largest locations and three demand periods: low season, peak season and short-notice orders. Competitors’ prices were adjusted to a common basis, for example where one brand quoted a pay-now price and another a pay-later price, so that the comparison measured price and not payment terms.

The survey produced a finding that shaped the whole engagement. Counted equally, the target’s prices sat about 3% below the market average. Weighted by what the target actually sells, they sat about 5% above it. The difference came from product mix: the target’s highest-volume classes were priced at a premium, and its cheaper positions were concentrated in lower-volume classes. A diligence report that relied on the simple average would have told the IC the business was cheap and had room to rise across the board. The mix-weighted view showed the opposite in aggregate, with specific pockets that were underpriced.

We used the mix-weighted index for sizing. It is the more conservative of the two, and it is the one that reflects the revenue at stake.

2. Price spread: are prices set with discipline?

Averages hide inconsistency. We plotted the spread of the target’s prices against the market for each demand period, showing the median, the middle 50% and the extremes.

The pattern was not “too cheap” or “too dear”. It was inconsistent. More than one in five low-season prices sat more than 10% below the market, with the lowest concentrated in one city. At the same time, almost a third of short-notice prices sat 20% or more above the market, most of them in one product class across three locations. Management confirmed in interview that prices were set by rules and judgement rather than customer data, and that late discounting was common.

For an investor, this matters more than the average position. Inconsistent pricing points to a process problem, and a process problem can be fixed without a broad price rise.

3. Fees and add-ons: what is each charge earning?

We reviewed 30 separate charges against five competitors and set them out on a single page, grouped into six families, showing where the target sat above, at or below each rival. For each charge we asked three questions: is it priced in line with the market, how many customers take it up, and does it cost more to administer than it earns?

Take-up of the main add-on product was analysed by location and product class. We benchmarked each of 89 location-by-product cells (each with at least 250 transactions) against the top-quartile location for the same product. Ten of those 89 cells held 61% of the take-up gain, which gave management a short, specific list of where to start rather than a network-wide target.

We also flagged charges that were due to change for reasons outside pricing, including a card surcharge that was ending and a planned administration fee intended to replace it. These affected first-year earnings in both directions and were shown separately from the pricing gain.

4. Site-by-site sizing: no single average for a national network

The seven largest locations were sized from transaction-level data. The remaining active sites were each sized from the site profit and loss file and the customer mix by site in the vendor’s financial model. Each lever followed a written rule: for example, low-season price rises applied in full at the largest sites and at half strength at smaller city sites, and contract price steps applied only to each site’s corporate share of revenue.

This matters because a shortcut is tempting. Scaling the large-site result to the rest of the network would have been quicker. The site-by-site sizing showed that smaller sites earned about half the gain per unit of volume of the largest seven, which was close to our initial scaling assumption, but the detailed sizing also showed which sites would carry the gain and which would not. Where part of the network was due to change operating model over the plan period, we restated the gain on the future structure as well.

5. Margin flow-through: how much of each dollar reaches EBIT?

Every lever was taken from gross revenue to EBIT using the cost rates in the vendor’s own financial model: turnover-based rent at the large locations, channel commissions by customer segment, royalties and frontline sales incentives on add-ons sold in person.

Depending on location and product, between 56 and 92 cents of each extra dollar reached EBIT. Across the whole case, 70 cents did. Had we assumed that extra revenue was all profit, the EBIT gain would have been overstated by about a fifth. Turnover rent accounted for more than half of that gap and channel fees for about a quarter.

We also tested the booking channel. Commissions ranged from nil on the target’s own website to 22% through some intermediaries. Moving one percentage point of sales to direct channels added a modest but real gain, which we sized at half the commission saved to allow for the offers needed to shift customers.

6. Downside: what could cancel the gain, and how fast does it arrive?

Three tests.

• Customer response. We costed each lost customer at the price and add-on margin forgone. The average price rise in the base case was about 2%. Price rises stopped paying for themselves only if 1.9% of customers were lost, and each 1% of customers lost reduced the total gain by about 31%. The IC could see exactly how much volume the case could absorb.
• Service cost of add-ons. Some add-on products carry a cost when customers use them. We showed the gain at 0%, 10%, 20%, 30% and 40% of the extra add-on revenue consumed by that cost, rather than assuming it away.
• Timing. Each lever was given a first-year realisation share based on how quickly it can be implemented: about 90% for simple fee changes, 75% for list price changes, 50% for take-up and channel changes, and 25% for corporate contracts that re-price only at renewal. Overall, about 63% of the annualised gain is expected to be realised within the first 12 months.

All figures for future years were stated in nominal terms with at least 2.5% CPI. Sizing figures were kept at current prices and volumes, and labelled as such, so the two were never mixed.

7. Capability: can management deliver it?

We ran a recorded working session with the target’s senior commercial team and drew eight management imperatives from it, quoted in management’s own words. They ranged from stopping late price cuts to setting prices from customer data, and they matched what the price spread analysis had already shown.

We scored pricing capability at 2.3 out of 5 across strategy, people, data and systems. The gaps were specific: a small, junior analytical team, pricing rules with no link to customer behaviour, and no reliable measure of how many enquiries became orders. We costed the pricing team and systems needed to close those gaps. They absorbed just under a fifth of the annualised gain, and we showed the result both before and after that cost.

Key issues identified

• The target was not cheap overall. Mix-weighted, it sat about 5% above the market. The upside lay in specific underpriced pockets, not a general rise.
• Prices were inconsistent. Deep low-season discounts sat alongside high short-notice premiums, driven by rules and late discounting rather than customer data.
• Add-on take-up varied widely by location. Ten location-by-product cells held most of the take-up gain.
• Revenue-linked costs were material. Only 70 cents of each extra dollar reached EBIT.
• Nine data gaps limited the evidence. Each was named, with the effect on the estimate and the question to put to the vendor.

What did the investment committee receive?

A 71-page IC pack structured on the pyramid principle: the answer first, then the evidence. It opened with a one-page summary a reader could act on without turning the page, followed by total value, current position, management and capability, actions, barriers, decisions, method and supporting analysis. Every content page carried a source line. A three-page covering letter to the IC set out the conclusion, the conditions attached to it and the decisions required.

The finding

Better pricing could add annualised EBIT equal to about 246 basis points of revenue at current volumes, before implementation costs. Price changes made up 61% of that gain, add-ons and upgrades 36%, and direct channel sales 3%.

Reconciliation to the investor’s plan

We reconciled the sized gain to the pricing line in Anchorage’s plan, lever by lever, so the IC could see which parts of the plan the evidence supported and which rested on assumption. We recommended that any higher pricing case be carried as upside only, to be adopted if price tests at selected sites showed that volume held.

Scenarios over five years

Three scenarios, all nominal and net of the service cost of add-ons: a base case built on the levers above; a top-quartile case in which each price moves to the upper quartile of the market for its class and season; and a full-match case against the market’s highest-priced brand. By the fifth year the top-quartile case was about two times the base case and the full-match case close to four times, with break-even customer loss rising in step. The IC could see how far the evidence went and what each step further would demand of the business.

Action plan

Twenty-one actions across three horizons: pricing strategy, prices and fees, and how pricing is run day to day. Each carried an owner, a sequence and a first-year value where one could be sized. Quick wins included price floors in the low season, starting in the city with the deepest discounts, price bands between cities, the ten highest-value add-on take-up cells, and a weekly check of the target’s price index by season, product class and location. Actions that needed tests before scaling, such as a smaller short-notice premium on one product class, were marked as tests and not counted in the base case.

Limits of the evidence

One page set out what the analysis could not show: locked data room documents, missing conversion data, unconfirmed fee treatment under key leases and supply contracts, and customer mix by location. Each gap came with its effect on the estimate and the question to resolve it before completion.

Why did a private equity firm choose a pricing specialist for this work?

General commercial due diligence covers market size, share and customer sentiment. It rarely sizes pricing to EBIT, site by site, with the cost stack applied. Pricing specialists bring three things to a transaction that generalists usually do not.

Method. Pricing Insight has run more than 160 engagements since 2007, across sectors including building products, freight and logistics, healthcare, retail, industrial distribution and consumer goods. The techniques used here, including mix-weighted competitor indices, price spread analysis, take-up benchmarking by cell and flow-through sizing, come from that work and from the firm’s 16-technique pricing methodology and nine-domain pricing diagnostic.

Speed. Diligence windows are short. A team that has built these models many times can move from data room to IC-ready evidence without first working out how to do it.

Independence. The purpose of pricing diligence is to tell the investor what the evidence supports. In this case, that meant sizing the gain on the evidence available, naming the gaps and recommending price tests before any higher case was adopted.

What this means for private equity firms and acquirers

For a buyer, the pricing line in a value-creation plan deserves the same scrutiny as the cost line. Four practices from this engagement apply to most acquisitions:

• Size pricing to EBIT, not revenue. Revenue-linked costs such as rent, commissions, royalties and incentives can remove a fifth or more of the gain.
• Weight competitor comparisons by the target’s own mix. A simple average can point the wrong way.
• Size by site, segment or customer group. A network average hides where the gain sits and who has to deliver it.
• Reconcile to the plan. The most useful finding is often how much of the pricing gain the plan already assumes, and how much it assumes without evidence.

For vendors preparing a business for sale, the same analysis done before the process starts puts evidence behind the pricing story and reduces the discount a buyer applies to it.

Frequently asked questions

What is pricing due diligence?

Pricing due diligence tests the pricing assumptions in an acquisition case. It measures the target’s price position against competitors, sizes the earnings gain from better pricing, identifies pricing and margin risks, and reconciles the result to the buyer’s value-creation plan.

How is pricing due diligence different from commercial due diligence?

Commercial due diligence covers market size, growth, share and customer views. Pricing due diligence goes further on one lever: it sizes pricing to EBIT, location by location and product by product, after revenue-linked costs, and tests how many customers the business could lose before the gain disappears.

How long does pricing due diligence take?

It is designed to run inside the transaction timetable. The engagement described here ran within the diligence window using the data room, the vendor’s financial model and a management session.

What data is needed?

Transaction-level sales data for the largest sites or customers, site or segment profit and loss, the vendor’s financial model with cost rates, the price list and fee schedule, and access to management. Where data is missing, the gap is named and its effect on the estimate stated.

Can pricing upside be realised in the first year?

Partly. In this engagement about 63% of the annualised gain is expected to be realised within the first 12 months. Fee changes move fastest; corporate contracts move only at renewal.

Does Pricing Insight work with vendors as well as buyers?

Yes. Vendors use the same analysis before a sale process to evidence the pricing case in the information memorandum and to fix the quickest gains before buyers arrive.

About the author

Ron Wood is the Founder and Managing Director of Pricing Insight, an Australian pricing strategy consultancy he established in 2007. He has worked in pricing for around 30 years, first as a pricing and commercial manager in consumer goods, building materials and capital equipment, and since then across more than 160 pricing engagements. He also founded Pricing University.

Talk to us about pricing due diligence

If you are assessing an acquisition, preparing a business for sale, or testing the pricing line in a portfolio company’s plan, contact Ron Wood at info@pricinginsight.com.au or on +61 410 534 099 to arrange a call.