How to choose a profitability advisory firm that changes how your leadership makes financial decisions.
Last year, I sat across from a CFO at a mid-sized bank in the USA. She had spent $1.8 million over fourteen months on what her board had approved as a "profitability transformation." The consulting firm, a well-known technology implementer, had delivered what it promised. She got a fully configured Oracle EPM environment with dashboards, data pipelines, and 42 custom reports.
The CFO pulled up one of those reports on her laptop, turned it toward me, and said, "Pedro, I can tell you that Branch 14 processed 3,200 transactions last month. What I still can't tell you is whether Branch 14 is making us money or costing us money."
That moment crystallized something I've observed across twenty years of profitability work in The Americas and Spain: the market is flooded with firms that sell EPM software and call it profitability consulting. The technology gets installed. The reports get generated. But the question that matters (where are we creating and destroying value?) remains unanswered.
This is the mismatch problem. And if you're a CFO evaluating advisory firms right now, understanding this gap could save you millions and months.
Three Questions Every CFO Should Ask Before Hiring a Profitability Advisor
1. Does this firm sell software implementation or financial decision capability?
2. Can they connect operational cost drivers to strategic value creation? Or do they stop at cost allocation?
3. Will their work change how my leadership team makes decisions on Monday morning? Or will it just produce better-looking reports?
1. Implementation vs. Decision Capability: The $1.8 Million Gap
The consulting market in the Americas has a structural problem. Most firms that position themselves as "profitability advisors" are, in practice, technology implementers. They know how to configure EPM platforms (Oracle, SAP, OneStream), but they lack the financial architecture expertise to design a profitability model that drives decisions.
This isn't a criticism of technology. EPM platforms are essential infrastructure. The problem is sequencing. Lead with technology instead of the decision framework and you end up with a perfectly implemented system that answers the wrong questions.
Most EPM implementations I have reviewed delivered "technical success" (the system worked as designed), but far fewer achieved "decision impact," meaning leadership changed how it allocated capital, priced products, or managed costs based on the new information. The gap between technical success and decision impact is where the mismatch lives.
"We passed every technical acceptance test," the CFO told me. "Every data feed was validated. Every report matched the specifications. But when our credit committee met to review the consumer lending portfolio, they used the same spreadsheets they'd been using for five years. The new system sat there, technically perfect and strategically irrelevant."
What to ask a prospective advisor:"Show me three examples where your profitability work directly changed a client's pricing structure, channel strategy, or product portfolio. I don't mean software deployments." If they can't answer with specific business outcomes, they're an implementer.
2. From Cost Allocation to Value Architecture: The Driver-Based Difference
The second mismatch runs deeper. Most profitability models in the market are built on cost-allocation logic. You take a pool of indirect costs, select an allocation base (headcount, square meters, or transaction volume), and spread the costs across products, customers, or channels. The math is clean. The result is misleading.
Cost allocation tells you how costs were distributed. It doesn't tell you what drives those costs or how changing a business decision would change the cost structure. When a regional retail bank in Colombia allocated IT costs to branches based on headcount, Branch 14 appeared expensive. When we rebuilt the model on activity drivers (transaction volumes by type, channel utilization rates, and customer complexity scores), the picture inverted. Branch 14 was processing the bank's most profitable customer segment through its lowest-cost channel mix. The branch was underinvested.
That is the difference between cost allocation and what I call value architecture. In a value architecture, every cost traces back to a causal driver, and every driver connects to a revenue or margin impact. The framework requires three integrated components:
Driver-Based Planning (DBP): Instead of budgeting by line item, you model how demand drivers (customer acquisition, transaction volumes, product mix) cascade through resource consumption to produce financial outcomes. Change a driver assumption, and the entire P&L recalculates.
Funds Transfer Pricing (FTP): For financial institutions, this is the second pillar. It prices the internal cost of funds so that asset-generating and liability-generating units see their real economic contribution instead of an accounting artifact.
Profitability & Cost Management (PCM): The measurement layer. It traces actual results by product, customer, channel, and segment back to the same driver structure used in planning.
When these three systems operate in a closed loop, the CFO sees more than what happened. She also sees why it happened, what would change if she adjusted a driver, and where the next dollar of investment creates the most value.
What to ask a prospective advisor: "Walk me through your cost modeling methodology. Do you use allocation bases or causal drivers? Can your model simulate what happens to profitability if I change pricing on one product by 200 basis points?" If the answer involves spreading costs by percentages rather than tracing them through activities and drivers, you're looking at a 1990s methodology wrapped in a modern dashboard.
3. Reports vs. Decisions: The Monday Morning Test
The third mismatch is the most consequential. A profitability project succeeds or fails on one criterion. Does the executive committee make different decisions after the project than before it?
I call this the Monday Morning Test. When leadership walks into their weekly operating review, are they using the new profitability insights to challenge assumptions, reallocate resources, and reprice offerings? Or are they glancing at a dashboard, nodding politely, and reverting to the same intuition-driven process they've always used?
In my experience across PwC, Deloitte, IBM, and two decades of independent advisory work, the firms that fail this test share a pattern. They treat the profitability model as a reporting deliverable rather than a decision system. They hand over the keys to a configured platform and move on to the next engagement.
The firms that pass it work differently. They embed the profitability framework into the organization's existing decision rhythms. The monthly pricing committee gets a new agenda structured around customer-level pocket margins. The quarterly strategic review replaces the old P&L waterfall with a driver-based variance analysis that shows which decisions created or destroyed value.
Take a multi-country insurance group we worked with. We built a product profitability model, and we also redesigned their product approval process so that every new product proposal included a driver-based margin simulation. Within eight months, the product committee rejected two proposals that would have passed under the old system. Both looked profitable at the gross margin level. Both destroyed value once distribution costs and claims servicing complexity were properly traced. The estimated value preserved is $4.2 million a year.
What to ask a prospective advisor:"After your engagement ends, which specific decisions in my organization will be made differently? Name the meeting, the decision, and the data that will drive it." Vague answers about "better visibility" or "improved reporting" are red flags. You want specifics: "Your credit committee will use customer-level cost-to-serve data to set differentiated pricing tiers by risk segment."
The real cost of the mismatch isn't the consulting fee you paid. It's the eighteen months of decisions your leadership team made using the same flawed assumptions they had before the project started, while believing the problem was solved.
Synthesis and Action
Three ideas to carry forward:
1. The market conflates EPM implementation with profitability advisory. They are different disciplines requiring different expertise. A firm that excels at configuring software may have no capability in financial decision architecture.
2. Cost allocation and profitability modeling are different things. Profitability insight requires causal driver logic that connects operational decisions to financial outcomes. It also requires the ability to simulate the future as well as report the past.
3. The only valid measure of a profitability analytics engagement is whether it changes decisions. Reports delivered, dashboards built and data pipelines configured don't count.
What to do this week:
If you're currently evaluating profitability advisory firms, ask each candidate to present a case study built on three elements. They are the business decision that changed, the financial impact measured twelve months later, and the driver methodology that made it possible. Any firm that can't articulate all three is selling you technology.
If you've already completed a profitability project, apply the Monday Morning Test. Identify three strategic decisions your leadership team made last quarter. For each one, determine whether the profitability model influenced the decision. If fewer than two out of three were informed by the model, your investment hasn't yet delivered its potential. The gap is in methodology.
Looking ahead:
Over the next 12–24 months, three forces will reshape profitability advisory in Latin America. First, AI and machine learning will enable the identification of cost drivers directly from transactional data, compressing what used to be a six-month modeling effort into a matter of weeks. Second, cloud-native EPM platforms will lower the technology barrier, making the advisory layer (the decision architecture) the real differentiator. Third, regulatory pressure (IFRS 18, Basel III.1, open banking) will force institutions to demonstrate granular profitability by product and customer segment, turning what was once a strategic nice-to-have into a compliance requirement.
Software certifications won't separate the winners. The firms that thrive will be the ones that can answer the question that CFO in The Americas still couldn't answer after spending $1.8 million: Is Branch 14 making us money?
Pedro San Martín Principal – Asher psanmartin@asher.company
