Case Study: Consumer Staples

🏢 Case Study: Enterprise Analytics Transformation – IberiaCasa Consumer Brands (Vision 2035)

Theme: Integrated intelligence for safer, equitable, and demand-ready enterprise-wide operations

🌍 Architecting for a Better World: The IberiaCasa Vision 2035

In an era where data flows like lifeblood through the veins of enterprise, IberiaCasa Consumer Brands stands at the frontier of a transformative journey—one that transcends spreadsheets and siloed systems to architect a future where intelligence, equity, and sustainability converge.

By 2035, IberiaCasa envisions a world where every decision—from the smallest SKU forecast to the grandest strategic pivot—is powered by integrated, real-time intelligence. This isn't just about planning; it's about planning for humanity. It's about ensuring that the products that nourish millions are delivered safely, equitably, and sustainably across every market, every channel, every community.

The Mission: To build an analytics-first enterprise where transparency replaces opacity, collaboration eclipses hierarchy, and foresight replaces reaction. Through SAP Analytics Cloud, IberiaCasa is weaving together demand forecasting, promotional effectiveness, supply chain synchronization, and financial stewardship into a single, living ecosystem—a digital nervous system that anticipates needs, optimizes resources, and safeguards value for stakeholders and society alike.

This is more than transformation. This is architecting for a better world—where consumer staples become instruments of equity, where supply chains honor planetary boundaries, and where every byte of data serves a higher purpose: a healthier, more connected, more resilient tomorrow.

🚀 Welcome to the future. Welcome to Vision 2035.

📖 Background: IberiaCasa Consumer Brands

IberiaCasa Consumer Brands is a leading multinational consumer packaged goods (CPG) company headquartered in Madrid, with operations spanning across Europe, Latin America, and emerging markets in Asia-Pacific. With a diverse portfolio of over 200 brands across food, beverages, personal care, and household products, IberiaCasa serves more than 500 million consumers daily through multiple retail channels including hypermarkets, convenience stores, e-commerce platforms, and traditional trade.

Founded in 1987, IberiaCasa has grown through strategic acquisitions and organic expansion, building a reputation for quality, innovation, and local market adaptation. The company operates 45 manufacturing facilities across 18 countries, managing a complex supply chain that spans raw material sourcing, production, distribution, and last-mile delivery to over 150,000 retail points.

Annual revenue exceeds €12 billion, with key categories including dairy products (28% of revenue), beverages (22%), snack foods (18%), personal care (17%), and home care (15%). The company employs over 35,000 people globally, with a strong emphasis on sustainability, local community engagement, and responsible business practices.

🚨 Current Challenges: The Imperative for Transformation

Despite its market leadership, IberiaCasa faces mounting pressures that threaten its competitive edge and operational efficiency:

1. Fragmented Planning Landscape

Siloed systems and processes: Demand planning, promotional planning, supply chain operations, and financial budgeting operate on disparate platforms (legacy Excel spreadsheets, standalone demand planning tools, ERP systems) with minimal integration.

Data inconsistency: Different versions of truth across departments lead to misalignment—sales teams plan promotions based on optimistic forecasts while supply chain struggles with inventory shortages or excess stock.

Manual reconciliation burden: Finance teams spend 30-40% of their time reconciling data across systems rather than driving strategic insights.

2. Promotional Planning Inefficiencies

Low promotional ROI visibility: Trade promotion spending accounts for 18-22% of gross revenue (€2.2-2.6 billion annually), yet the company lacks real-time visibility into promotional effectiveness across channels and regions.

Reactive promotional adjustments: Promotional plans are often locked months in advance with limited flexibility to adjust based on market dynamics, competitor actions, or demand signals.

Channel complexity: Managing promotional calendars across traditional retail, modern trade, e-commerce, and emerging quick-commerce channels creates coordination nightmares and frequent execution errors.

3. Demand Forecasting Gaps

Forecast accuracy challenges: Current demand forecasting accuracy at SKU level averages only 65-70%, leading to stockouts (impacting 8-12% of potential sales) or excess inventory (tying up €450 million in working capital).

Limited predictive capabilities: Reliance on historical averages and manual adjustments fails to capture complex demand patterns influenced by seasonality, weather, promotional cannibalization, and emerging consumer trends.

New product launch uncertainty: Forecasting for new product introductions relies heavily on judgment and analogies, with 35% of launches missing first-year volume targets by more than 20%.

4. Supply Chain and Financial Planning Disconnect

Demand-supply misalignment: Production planning and procurement decisions lag behind demand signals, resulting in suboptimal production schedules, rush orders (increasing COGS by 4-6%), and customer service issues.

Financial planning delays: Monthly financial closing and budget vs. actuals analysis takes 8-10 working days, limiting agility in responding to market changes.

SG&A allocation opacity: Selling, general, and administrative expenses are allocated using static percentages rather than dynamic, driver-based logic reflecting actual business activities across brands and channels.

5. Regulatory and Sustainability Pressures

Data governance and compliance: Increasing regulatory requirements (GDPR, local data protection laws, financial reporting standards) demand robust data security, auditability, and traceability—capabilities difficult to achieve with fragmented systems.

Sustainability accountability: Stakeholders demand transparency on carbon footprint, water usage, and waste reduction targets at product and facility levels, requiring integrated data collection and reporting.

6. Organizational and Change Management Barriers

Planning culture resistance: Entrenched planning processes and Excel-centric workflows create resistance to adopting new technologies and collaborative planning approaches.

Limited analytics talent: While IberiaCasa has strong domain expertise, there's a gap in advanced analytics skills (predictive modeling, data science, process automation) needed to fully leverage modern planning platforms.

🎯 Vision 2035: Future Roadmap and Aspirations

IberiaCasa's Vision 2035 represents a bold commitment to transform from a traditional CPG company into an analytics-driven, agile, and sustainable enterprise. The transformation roadmap is anchored on three strategic pillars:

Pillar 1: Unified Intelligent Planning Ecosystem

Goal: Create a single source of truth for all planning activities—demand, promotional, supply chain, and financial—powered by SAP Analytics Cloud.

Integrated planning models: Seamlessly connect demand forecasts, promotional plans, production schedules, inventory targets, and financial budgets in a unified data model.

Real-time collaboration: Enable cross-functional teams (sales, marketing, supply chain, finance) to collaborate in shared planning environments with role-based access, workflow management, and approval processes.

Dynamic scenario planning: Empower planners to run what-if scenarios (e.g., impact of price changes, new promotional strategies, supply disruptions) and instantly visualize financial and operational implications.

Target outcome (2027): Reduce planning cycle time by 50%, improve forecast accuracy to 85%+, and achieve cross-functional alignment score of 90%+ (measured through process maturity assessments).

Pillar 2: AI-Powered Demand Intelligence and Promotional Optimization

Goal: Leverage augmented analytics, machine learning, and predictive modeling to transform demand forecasting and promotional planning from reactive to predictive.

Advanced demand forecasting: Deploy machine learning algorithms that incorporate multiple demand drivers (price, promotions, seasonality, weather, social trends, competitive activity) to generate SKU-level forecasts with 85%+ accuracy.

Promotional effectiveness analytics: Build promotional response models that predict lift, incrementality, and ROI for different promotional mechanics across channels, enabling data-driven promotional planning and budget allocation.

Price elasticity insights: Embed price elasticity models directly into planning dashboards to support dynamic pricing strategies and optimize revenue-margin trade-offs.

Automated exception management: Implement intelligent alerts and recommendations that flag anomalies (demand spikes, forecast deviations, inventory risks) and suggest corrective actions.

Target outcome (2029): Increase promotional ROI by 15-20%, reduce forecast bias to <5%, and optimize trade spend allocation to high-performing channels and products, unlocking €200-300 million in value annually.

Pillar 3: Sustainability-First, Equitable Growth Framework

Goal: Embed sustainability metrics, equity considerations, and stakeholder value creation into every planning decision.

Carbon-conscious planning: Integrate carbon footprint metrics into supply chain and production planning, enabling planners to optimize decisions not just for cost but also for environmental impact.

Circular economy modeling: Build planning scenarios that incorporate recycled materials, packaging reduction, and waste minimization targets, aligning with Vision 2035's commitment to 50% reduction in plastic usage and zero waste to landfill.

Inclusive distribution planning: Ensure equitable product availability across all markets, including underserved communities, by incorporating accessibility and affordability metrics into distribution and promotional planning.

Stakeholder transparency: Provide executive dashboards that transparently report on financial performance, sustainability KPIs, community impact, and employee well-being—demonstrating commitment to stakeholder capitalism.

Target outcome (2035): Achieve carbon neutrality in Scope 1 and 2 emissions, reduce water consumption by 40%, and establish IberiaCasa as a CPG industry leader in sustainable and equitable business practices, recognized by ESG rating agencies and consumer advocacy groups.

Enablers: Technology, Talent, and Culture

Achieving Vision 2035 requires foundational investments beyond technology implementation:

SAP Analytics Cloud deployment: Phased rollout starting with demand and promotional planning (2025-2026), expanding to supply chain and financial planning (2027-2028), and achieving full enterprise-wide adoption by 2030.

S/4HANA integration: Deep integration between SAP Analytics Cloud and S/4HANA to ensure seamless flow of actuals (sales, COGS, inventory) into planning models and export of plans for execution.

Talent development: Launch IberiaCasa Analytics Academy to upskill 500+ planners, analysts, and business leaders in advanced analytics, data visualization, and collaborative planning methodologies over the next three years.

Change management: Implement structured change management program focused on storytelling, early wins, champion networks, and continuous feedback loops to drive user adoption and cultural transformation.

Governance and security: Establish enterprise-wide data governance framework, robust security protocols (SSO, role-based access, data encryption), and audit trails to ensure compliance and build stakeholder trust.

🌟 The North Star: A Better World Through Better Planning

At its core, Vision 2035 is not just about operational excellence or financial performance—it's about responsibility and impact. IberiaCasa recognizes that as a company touching millions of lives daily, every planning decision carries weight:

A more accurate demand forecast means fewer stockouts—ensuring families can access essential products when they need them.

Optimized promotional spending means resources can be redirected to innovation, sustainability initiatives, and employee development.

Carbon-conscious supply chain planning means a healthier planet for future generations.

Transparent, data-driven decision-making means greater accountability to shareholders, employees, communities, and the environment.

Vision 2035 is IberiaCasa's commitment to architect a future where consumer staples are delivered with intelligence, integrity, and impact—creating shared value for all stakeholders and contributing to a more sustainable, equitable world.

60-Hour SAP Analytics Cloud Planning Curriculum: Instructor Lesson Plan

Phase 1: Enterprise Foundation & Secure Access Architecture (8 Hours / Days 1–4)

Day	Topic & Case Study	Daily Focus (80% H/A)	Pre-Reading (Contextual)	Post-Activity (Deepening)
1	Advanced Connection Strategies	H/A:Creating and managing complex live and import data connections to diverse on-premise and cloud applications. Implementing connectivity security checks.	Review: Unit 3: Establishing Data Sources and Connections (19 min).	Hands-on Practice: Using the Practice System, establish a secure, complex hybrid connection scenario (e.g., S/4HANA live + flat file import).
2	User Management, Roles, and SSO	H/A:Configuring authentication, implementing SSO mechanisms (acknowledging the prerequisite knowledge of SSO/SAML), and designing a scalable user access matrix.	Review: Administrating SAC—Goals on user/role creation and authentication.	Research: Find helpful information and best practices on user provisioning on the SAP Community.
3	Data and Content Security Deep Dive	H/A:Mastering content and data security. Implementing planning-specific row-level security and data locking rules essential for regulatory compliance.	Review: Administrating SAC—Learning outcome on securing content and data.	Activity: Design a solution blueprint detailing how to secure sensitive planning data across three distinct user groups.
4	Transport Strategy & Initial Tuning	H/A:Executing the process totransport content within the system. Defining the transport structure for planning models and stories across environments.	Review: Performance Tuning for SAP Analytics Cloud (Live Session overview).	Hands-on: Execute a test transport of a planning model and apply initialPerformance Tuningprinciples to the model structure.

Phase 2: Mastering Planning Logic and Automation (18 Hours / Days 5–13)

This phase focuses on complex data manipulation, automation, and applying advanced planning features.

Day	Topic & Consumer Staples Case Study	Daily Focus (80% H/A)	Pre-Reading (Contextual)	Post-Activity (Deepening)
5-6	Model Optimization for Consumer Staples Planning	H/A:Optimizing planning dimensions for product hierarchies, store/channel dimensions, and promotional calendars. Configuring aggregation settings for SKU-level to category-level planning in FMCG environments.	Refresher: Unit 4: Using Modeling (32 min). Note: assumes prerequisite:Designing Data Models.	Activity: Refactor a consumer goods product planning model with 50,000+ SKUs to improve query performance and planning efficiency.
7-9	Advanced Data Actions for Consumer Staples: Trade Promotion & SG&A Allocation	H/A:Creating complex, multi-step Data Actions for retail and FMCG scenarios including: dynamic trade promotion budget allocation, SG&A cost distribution across brands and channels, and promotional lift calculations based on multiple drivers (revenue, volume, market share).	Review: Learning Outcome onadvanced planning features.	Hands-on: Develop a Data Action that dynamically allocates trade promotion spend across retail channels based on historical ROI, planned volume growth, and strategic priorities. Include SG&A allocation logic based on revenue and headcount drivers.
10-11	Cross-Model Planning: Integrating Supply Chain & Financial Planning	H/A:Designing Data Actions that synchronize data between supply chain planning models (inventory, production volumes) and financial budget models (COGS, working capital). Critical for consumer staples companies managing complex supply networks.	Review: Planning requirements for source and target models when executing data actions.	Activity: Build and test a cross-model solution that transfers planned production volumes to financial planning and calculates corresponding COGS and inventory carrying costs.
12-13	Demand Forecasting & Promotional Planning for Consumer Staples	H/A:UtilizingBasic Augmented Analytics in SAP Analytics Cloudto generate demand forecasts at SKU and category levels. Integrating promotional calendars and adjusting forecasts for planned promotional activities. Building what-if scenarios for new product launches.	Review: Unit 7: Using Basic Augmented Analytics in SAP Analytics Cloud (18 min).	Activity: Apply predictive functionality to a consumer staples demand planning model. Generate baseline forecasts, then overlay promotional uplift assumptions and document forecast accuracy metrics across different product categories.

Phase 3: Development, Customization, and S/4HANA Integration (22 Hours / Days 14–24)

This phase builds the specialized Developer skills needed for highly customized client solutions and critical integration points.

Day	Topic & Consumer Staples Case Study	Daily Focus (80% H/A)	Pre-Reading (Contextual)	Post-Activity (Deepening)
14-16	Planning Process Flows and Collaboration for Consumer Staples	H/A:Setting up process management (tasks, steps, deadlines) and leveragingUsing Collaboration Featuresfor structured planning cycles across product categories, sales regions, and promotional planning teams. Critical for coordinating cross-functional planning in FMCG environments.	Review: Unit 8: Using Collaboration Features (40 min).	Activity: Map and configure a three-stage promotional planning review and approval process flow involving brand managers, trade marketing, and finance teams.
17-19	Integration Deep Dive: S/4HANA Actuals for Consumer Staples	H/A:Practical scenarios demonstrating how tointegrate SAP Analytics Cloud for planning with SAP S/4HANAto import actual sales, COGS, and inventory data. Focus on exporting planned promotional spend, production volumes, and revised forecasts back to S/4HANA for execution.	Review: Learning outcome on integrating SAC Planning with S/4HANA.	Research: Investigate integration patterns specific to consumer goods planning shared on the SAP Community, particularly for promotional planning and demand-supply synchronization.
20-22	Scripting for Dynamic Promotional Planning Stories	H/A:Applying prerequisite JavaScript/JSON coding experience tocreate extended stories using scripting. Building dynamic promotional planning input forms that adjust based on promotional type (TPR, Display, Feature), calculate ROI metrics in real-time, and validate promotional budgets against trade spend caps.	Review: Learning outcome on creating extended stories using scripting.	Hands-on: Build a dynamic promotional planning input form with custom validation logic that ensures promotional spend stays within approved trade budget envelopes and automatically calculates expected volume lift.
23-24	Advanced Analytics: Price Elasticity & Promotional Response Modeling	H/A:Leveraging prerequisite R code experience tocreate R visualizations in stories. Embedding price elasticity models and promotional response curves directly into planning dashboards to support data-driven decisions on pricing strategy and promotional effectiveness across product categories.	Review: Learning outcome on creating R visualizations in stories.	Activity: Write and integrate an R script to model promotional response curves based on historical promotional data, visualizing expected volume lift vs. promotional investment for different product categories.

Phase 4: Optimization, Advisory, and Deployment Strategy (10 Hours / Days 26–30)

This final phase focuses on optimization, governance (Administrator role), and strategic advisory skills.

Day	Topic & Consumer Staples Case Study	Daily Focus (80% H/A)	Pre-Reading (Contextual)	Post-Activity (Deepening)
25	Deployment Strategy & Advanced Transport(Consumer Staples)	H/A:Advanced transport scenarios for consumer staples planning models involving complex dependencies across product hierarchies, promotional calendars, and supply chain models. Handling transport errors in multi-brand, multi-channel environments and reviewing best practices for content governance in FMCG production environments.	Review: Administrating SAC content transport mechanisms.	Activity: Document a rollback and recovery strategy for a critical promotional planning model deployment affecting multiple retail channels and product categories.
26	Deep Performance Optimization (Modeling & Data)(Consumer Staples)	H/A:Advanced techniques derived from thePerformance Tuning for SAP Analytics CloudLive Session guidance. Focus on optimizing SKU-level planning models with 50,000+ products, promotional planning data loads, and trade spend allocation queries to ensure speed in monthly planning cycles typical of consumer staples environments.	Review: Key concepts from the "Performance Tuning for SAP Analytics Cloud" Live Session.	Hands-on: Audit a trade promotion data loading process and demand forecast update job for efficiency and recommend specific optimization changes to reduce processing time from hours to minutes.
27	Performance Optimization (Extended Stories)(Consumer Staples)	H/A:Techniques tomanage and optimize performance in extended storiesbuilt with scripting for consumer staples use cases. Debugging poor-performing promotional planning input forms, optimizing dynamic ROI calculators, and managing large widget loads in executive dashboards showing category-level performance across multiple markets.	Review: Learning outcome on managing and optimizing performance in extended stories.	Activity: Identify and resolve three performance bottlenecks in a complex promotional planning story that includes real-time ROI calculations, promotional calendar visualizations, and cross-category comparison widgets.
28	End-to-End Consulting Project Review(Consumer Staples)	H/A:Taking adeep dive into an end-to-end scenario in SAP Analytics Cloudfor consumer staples—analyzing the entire lifecycle from importing S/4HANA actuals (sales, COGS, inventory) through demand forecasting, promotional planning, SG&A allocation, to final financial budget consolidation and executive reporting, ensuring alignment with consumer goods business needs.	Review: Discover Analytics End-to-End Use Case.	Activity: Draft a final client presentation summarizing the integrated consumer staples planning solution deployed (covering demand planning, promotional planning, and financial budgeting) and its value realization in terms of forecast accuracy improvement and trade spend optimization.
29-30	Advisory Workshop & Continuous Learning(Consumer Staples)	H/A & Discussion:Simulating client advisory sessions on complex consumer staples issues including: multi-brand portfolio planning, trade promotion effectiveness measurement, demand-supply synchronization across production facilities, and managing planning for new product launches. Reviewing how to utilize resources like theSAP Communityand engaging withLive Sessionsto connect with consumer goods planning experts and peers for ongoing solutions.	Review: The value proposition ofInstructor-led trainingand peer engagement (SAP Community).	Final Assignment: Prepare a comprehensive advisory response addressing a complex consumer staples client challenge requiring integration of demand forecasting, promotional planning, supply chain coordination, and financial budgeting—demonstrating mastery of both planning and administrative knowledge in an FMCG context.