Leveraging predictive analytics to create accurate production cost forecasting

Background

Our client, one of the world’s most iconic and geographically diverse brewing companies, operates across nearly 50 countries with a strong balance between mature and emerging markets. Since 2011, we have served as a strategic partner in their global enterprise-wide transformation, focused on unifying planning across functions and regions to unlock greater agility and performance. A pivotal component of this evolution has been the development of a production planning and costing solution customized to meet the dynamic needs of each zone and, in some cases, individual countries. This solution encompasses an end-to-end process for budgeting, planning and forecasting, actual reconciliation, and year-on-year comparisons.

Challenge

Just a few years ago, the finance team for the procurement and supply chain function at our client was facing unexpected complexity in answering fundamental cost questions. Questions like: • What is the cost per hectoliter (commonly used to measure the volume of beer in brewing operations and is often used in international reporting of beer shipments) by brand and country? • How have production costs changed year-over-year? • Which specific brands or cost categories are driving the variance? • Forward looking, what is the impact of large market-shifting events? What if? • Which suppliers are above my benchmarks, and where can I find potential savings within our procurement? These seemingly simple questions exposed fragmented landscapes, disconnected processes, and limited visibility into true cost drivers.

Approach

The first step on this journey was aligning and standardizing regional models to enable connection into a consolidated global framework. This was a critical move toward greater transparency and consistency, as there was a pressing need for deeper comparative insights across markets and time periods. As of 2024, we have achieved global visibility. Our client now can answer complex production cost questions at a highly granular level across dimensions such as product, brand, cost category, brewery, country, and time – comparing actuals, budgets, and forecasts with ease. With this visibility, the next important questions arose quickly. Procurement and finance leaders began asking not just what changed, but why. What specific factors are driving shifts in production costs, and by how much? How can those insights be used to better anticipate and influence future outcomes? These questions marked the next stage in the evolution: incorporating AI into the solution with predictive analytics and machine learning. In collaboration with our partner Predikt, we launched a pilot model for a single brewery in Belgium. The Predikt solution was implemented alongside existing planning models, complementing and enhancing them – not replacing them – to provide deeper business insight and enable more informed, data-driven decisions. The objective was to move beyond traditional planning, and move toward AI-powered forecasting. Following a stepwise approach, the result was a dynamic, responsive model delivering accurate production cost forecasts and deep insights into why costs were shifting. With the perfect balance between leveraging ML algorithms and statistical predictive analytics , the Predikt platform has been able to identify the main drivers for the most important cost categories (raw materials, packaging materials, labor). A defining advantage of Predikt is that it uses an AI language learning model to include the right external data sets. Research shows that up to 85% of forecast accuracy is driven by external indicators (e.g., commodity markets, inflation, energy prices), making their inclusion critical to increasing predictive power and forecast explainability. For instance, in the case of packaging materials, the model detected a lagged causal relationship between aluminum and metal market spot prices, and the cost of cans and lids. By using fitted regressions that demonstrate a high correlation, causation, and accuracy, we can conclude that, if for example the price of aluminum increases by 1% today, the magnitude of the effect will be on the total production cost of a beer a number of months from now. With this intelligence, our client can now anticipate the future cost impacts and take proactive measures in pricing strategy and cost control.

Key results

Benefits

The solution empowers our client with a rapid, scalable, and responsive forecasting framework, underpinned by sophisticated AI technology. This enables a deeper understanding of production cost drivers, delivering actionable insights that transform operational effectiveness. The client gains the ability to not only forecast with precision but also to make proactive, informed decisions. Benefits of the Predikt solution: • Streamlined and Enriched Data Preparation: Effortlessly upload, analyze, and pre-process data with automated detection and correction of outliers, data drift, and trend shifts. With real-time integration of external data, easily incorporate inflation rates, market trends, and other macroeconomic signals to add critical context to strengthen forecast accuracy and relevance. • Target Definition and Forecast Optimization: Predikt helps define what to predict, which data to leverage, and the optimal forecasting level to ensure accurate, actionable outcomes. By using a language model and advanced AI to evaluate over 10M+ external indicators alongside internal data, the solution generates unbiased starting points and enables continuous refinement of key drivers for optimal forecasting accuracy. • Proactive Risk Detection. Spot potential disruptions before they impact plans, with AI-drive alerts tailored to the business. Benefits realized by our client: • Insight into Detected Patterns: Finance, procurement, and supply chain stakeholders now have actionable intelligence for strategic decision-making. • Scenario Modeling for Proactive Planning: Generate and compare different scenarios, utilizing likelihood analysis to assess and prepare for potential risks and opportunities. • Actionable Impact Analysis: Perform targeted impact analysis and establish meaningful benchmarks to guide prioritization and accelerate confident, results-oriented actions.

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