The Labyrinth of Lost Margin : Deconstructing the Execution Gap

The Commercial Policy Swamp : Discount Waterfalls and Promotion Mysteries

Significant margin leakage originates within a company’s own commercial frameworks. This is often best understood through the concept of the Price Waterfall—the chain of cascading parameters that connect a product’s list price to the final “pocket price” the company retains. To arrive at a desired sell-out price, a complex sequence of calculations involving multiple taxes, sell-in prices, distributor and retailer margins, and various commercial incentives must be managed.³ Managing this complexity through multiple spreadsheets is not only inefficient but also a primary source of errors that silently erode profitability. This intricate, often country-specific, financial logic is precisely where generic, off-the-shelf software often fails, unable to capture the full nuance required for accurate pricing.

For many consumer goods companies, promotional spending is the second-largest line item after COGS, yet visibility into its effectiveness is alarmingly poor.⁴ Most organizations struggle to identify which promotions genuinely drive incremental growth, how to allocate spend effectively, and whether new offers are simply cannibalizing existing sales.⁴ Without a clear understanding of ROI, this massive investment remains a high-stakes gamble.

The Portfolio Blind Spot: The Hidden Dynamics of Customer Demand

A profound, yet often overlooked, source of margin leakage lies in the complex interactions between products at the point of sale. Capturing these cross-SKU dynamics is crucial to minimize cannibalization and ensure complementary products are jointly available.² While modern software attempts to solve this, their ‘one-size-fits-all’ cannibalization models often miss the unique substitution patterns of a specific brand portfolio, leading to flawed recommendations that a bespoke model would avoid.Traditionally, this complexity has been left to the business experience of category managers—a manual approach ill-equipped for today’s massive product catalogs.² This blind spot has a direct financial impact; estimates suggest that around 30% of a promoted item’s sales uplift comes from cannibalized sales of other full-priced products.⁵

The Channel Arbitrage Trap: When Margins Create Chaos

Margin leakage is frequently an unintended consequence of a complex channel landscape, making it challenging to balance pricing across outlets and geographies.⁴ A manufacturer’s target margin is a channel average, with significant variation at the account level.³ This necessary differentiation creates the arbitrage trap, where “mega accounts” receive deeper discounts, leading to wide price variations for the same product across the market.³ Without a robust governance framework, this variation often lacks a rational basis, leading to channel conflict and the erosion of the very margin the pricing strategy was designed to protect.¹

A Disciplined Framework for Closing the Execution Gap

Navigating the maze requires a disciplined, analytics-powered execution framework. This framework consists of four integrated stages that transform a high-level plan into a profitable reality.

Step 1: Defining the Strategic Pricing Architecture

The foundation of execution is a clear strategic architecture. This stage moves beyond a single price point to establish core principles of value capture, defining price positioning and structure for different segments, regions, and channels. A critical component is mapping the margin distribution across the value chain (D2C, B2B, B2B2C). This architecture provides the guardrails and initial hypotheses to be refined in subsequent stages.

Step 2: Refining Strategy with Advanced Demand Decomposition

With the architecture in place, the next step is to enrich it with a deep, analytical understanding of customer behavior. Crucially, this is not just about building a standalone elasticity model. A truly effective price optimizer must be tightly bound by the business rules, positioning, and architectural constraints defined in Step 1. This is achieved through advanced demand decomposition, which isolates key sales drivers like baseline demand, price elasticity, and halo effects. In complex retail environments, advanced neural-network models can even uncover hidden substitution patterns from millions of purchase receipts.² This data science-led refinement transforms the initial architecture into a nuanced, evidence-based plan.

A prime example is a pricing project for a major food retailer. By deploying an elasticity model and an optimization engine, Artefact identified a potential gain of over BRL 20 million in profit margin with minimal price adjustments. The key was to accurately decompose demand—isolating baseline sales from promotional lifts and seasonality—to distinguish between short-term promotional elasticity and the long-term impact of price elasticity on baseline demand.

Step 3: Building a Bespoke Simulation & Pricing Capability

Here, the “make or buy” decision becomes a reflection of strategic maturity. For companies where pricing is a core business competency, the only viable long-term path is to “make”—to build a bespoke, centralized pricing capability.

Opting to “buy” an off-the-shelf solution might seem faster, but it introduces significant risks. First, these platforms are notoriously difficult to integrate with a company’s unique commercial processes and core systems (like ERPs), often resulting in a fragmented ecosystem that requires costly and brittle customizations. Second, and more critically, they rely on generic “vanilla” AI algorithms. Such black-box models are incapable of capturing the unique DNA of a business—the nuances of local tax structures, specific cross-product cannibalization effects, or regional demand patterns—leading to imprecise and potentially flawed recommendations.

In contrast, building a bespoke pricing engine transforms this capability from an operational expense into proprietary intellectual property. It allows for the development of custom-tailored algorithms that learn from the company’s own data, ensuring full process integration and delivering far greater accuracy. This engine, featuring a powerful simulator, becomes the single source of truth, allowing leaders to model the P&L impact of any decision before it reaches the market and turning pricing into a true strategic weapon.

Step 4: Governing the Execution with Policies, Incentives, and Monitoring

The final stage is governing the price, which evolves from a static set of rules into a dynamic, intelligence-powered framework. This system ensures the pricing strategy is not only executed correctly but also remains effective in a changing market.

Internally, this requires the continuous monitoring and update of all price waterfall attributes—from client segment margins and commercial conditions to market taxes. This ensures the pricing engine’s logic is always current, which in turn empowers commercial support tools to show salespeople the accurate, real-time P&L consequences of any proposed discount.

Externally, a robust Business Intelligence (BI) “control tower” connects this internal execution data with market intelligence from sources like Nielsen or Neogrid—a level of deep integration with both legacy and external systems that typically requires a custom-built solution. This provides leadership with a clear, automated view of the strategy’s real-world performance, flagging deviations between the planned price and the price on the shelf. It closes the loop by assessing the effectiveness of the strategy against competitors, providing the crucial feedback needed to refine and adapt over time.

The Business Impact: From Strategic Theory to Financial Reality

Measurable Financial Gains

The adoption of this disciplined framework delivers clear financial returns. Across industries, pricing excellence initiatives produce an uplift in Return on Sales (RoS) of 2 to 7 percentage points.¹ One company that reset its prices using a new analytics-driven process saw its RoS increase by 3-5 percentage points with no significant volume change.¹ This capability creates a lasting advantage, with confident firms realizing a profit margin premium of 3 percentage points over their peers.²

Enhanced Strategic Agility and Decision Support

A bespoke intelligence framework transforms decision-making itself, providing category managers with scientifically-backed tools for assortment and promotion planning.² The agility it creates is not in the ability to change prices frequently, but in the ability to understand performance, enforce the correct price, and strategically adjust the underlying policies when necessary. This data-driven foundation allows companies to improve forecasting, reduce surprises, and respond to market dynamics with surgical precision.⁸

This level of strategic agility is a direct benefit of owning the technology stack. Unlike being tied to a vendor’s development roadmap and release cycles, an in-house capability can be adapted and evolved in real-time as business priorities shift.

Conclusion: Are You Solving for Price or for Profit?

As Warren Buffett noted, pricing power is the ultimate test of a “very good business.”¹ In today’s market, that power is not a theoretical concept but a tangible outcome forged in the reality of execution. The critical challenge for leaders is to recognize that a perfect price on paper is worthless if its value erodes in the final foot of the customer journey. The question is no longer simply “What is the right price?” but “Do we have the disciplined framework, bespoke capabilities, and governance to deliver that price—and its intended margin—profitably and consistently to our customers?”

References – EN

  1. McKinsey & Company. The Hidden Power of Pricing: How B2B Companies Can Unlock Profit. New York: McKinsey on Marketing & Sales; 2014.
  2. Désir J, Auriau V, Možina M, Malherbe E. Better Capturing Interactions between Products in Retail: Revisited Negative Sampling for Basket Choice Modeling. [Academic Paper, publication and year unavailable].
  3. Qureshi J. A comprehensive guide to Pricing and Trade Promotion Management for Consumer Packaged Goods using a shelf-back approach. actionableinsights.online [Internet]; 2017. Available from: https://actionableinsights.online/?p=83
  4. Bedford Consulting. 3 tactics to optimise trade promotion management. Bedford Consulting Blog [Internet]; [date unknown]. Available from: https://bedfordconsulting.com/3-tactics-to-optimise-trade-promotion-management/
  5. Herrala O. Evaluating cannibalization between items in retail promotions [Bachelor’s thesis]. Espoo: Aalto University School of Science; 2018.
  6. Vertex, Inc. Global tax implications for scaling businesses [Internet]; 2024. Available from: https://www.vertexinc.com/resources/resource-library/global-tax-implications-scaling-businesses
  7. Fielitz C, Khanna M, et al. The art of software pricing: Unleashing growth with data-driven insights. McKinsey & Company [Internet]; 2023. Available from: https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/the-art-of-software-pricing-unleashing-growth-with-data-driven-insights
  8. Sinha A, Izaret JM. Five Trends Will Define the Future of Pricing. Boston Consulting Group [Internet]; 2025. Available from: https://www.bcg.com/publications/2025/five-trends-define-future-pricing
  9. Symson. What is a Price Engine? The Ultimate Guide. Symson Blog [Internet]; [date unknown]. Available from: https://www.symson.com/blog/what-is-a-price-engine
  10. Cortado Group. Why Pricing Governance is a Powerful Asset to Maximize Valuation. Cortado Group [Internet]; [date unknown]. Available from: https://cortadogroup.com/insights/maximize-valuation-with-pricing-governance/
  11. tgndata.com. Pricing Strategy: From Gut Feeling to Data-Driven Decisions [Internet]; [date unknown]. Available from: https://tgndata.com/pricing-strategy-from-gut-feeling-to-data-driven-decisions/

References – PT

  1. MCKINSEY & COMPANY. The Hidden Power of Pricing: How B2B Companies Can Unlock Profit. New York: McKinsey on Marketing & Sales, 2014.
  2. DÉSIR, Jules et al. Better Capturing Interactions between Products in Retail: Revisited Negative Sampling for Basket Choice Modeling. [S. l.: s. n., s. d.].
  3. QURESHI, Junaid. A comprehensive guide to Pricing and Trade Promotion Management for Consumer Packaged Goods using a shelf-back approach. actionableinsights.online, 8 jan. 2017. Disponível em: <https://actionableinsights.online/?p=83>. Acesso em: 21 ago. 2025.
  4. BEDFORD CONSULTING. 3 tactics to optimise trade promotion management. Bedford Consulting Blog, [s. d.]. Disponível em: <https://bedfordconsulting.com/3-tactics-to-optimise-trade-promotion-management/>. Acesso em: 21 ago. 2025.
  5. HERRALA, Olli. Evaluating cannibalization between items in retail promotions. 2018. Trabalho de Conclusão de Curso (Bacharelado em Engenharia Física e Matemática) – School of Science, Aalto University, Espoo, 2018.
  6. VERTEX, INC. Global tax implications for scaling businesses. Vertex, Inc., 10 dez. 2024. Disponível em: <https://www.vertexinc.com/resources/resource-library/global-tax-implications-scaling-businesses>. Acesso em: 21 ago. 2025.
  7. FIELITZ, Christian et al. The art of software pricing: Unleashing growth with data-driven insights. McKinsey & Company, 2 jun. 2023. Disponível em: <https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/the-art-of-software-pricing-unleashing-growth-with-data-driven-insights>. Acesso em: 21 ago. 2025.
  8. SINHA, Arnab; IZARET, Jean-Manuel. Five Trends Will Define the Future of Pricing. Boston Consulting Group, 2025. Disponível em: <https://www.bcg.com/publications/2025/five-trends-define-future-pricing>. Acesso em: 21 ago. 2025.
  9. SYMSON. What is a Price Engine? The Ultimate Guide. Symson Blog, [s. d.]. Disponível em: <https://www.symson.com/blog/what-is-a-price-engine>. Acesso em: 21 ago. 2025.
  10. CORTADO GROUP. Why Pricing Governance is a Powerful Asset to Maximize Valuation. Cortado Group, [s. d.]. Disponível em: <https://cortadogroup.com/insights/maximize-valuation-with-pricing-governance/>. Acesso em: 21 ago. 2025.
  11. TGNDATA. Pricing Strategy: From Gut Feeling to Data-Driven Decisions. tgndata.com, [s. d.]. Disponível em: <https://tgndata.com/pricing-strategy-from-gut-feeling-to-data-driven-decisions/>. Acesso em: 21 ago. 2025.