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    Home»Artificial Intelligence»Forecast demand with precision using advanced AI for SAP IBP
    Artificial Intelligence

    Forecast demand with precision using advanced AI for SAP IBP

    big tee tech hubBy big tee tech hubMay 4, 2025015 Mins Read
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    Supply chain leaders know the pain of misaligned inventory. A high-demand product sells out just as a promotion goes live. Meanwhile, pallets of obsolete stock gather dust in the warehouse. 

    These aren’t just planning hiccups — they’re costly missteps that eat into margins, tie up working capital, and erode customer trust.

    But what if your forecasts could finally keep pace with today’s volatility? 

    Imagine accurately anticipating demand – even when trends shift overnight, new SKUs launch, or external shocks like tariffs, inflation, or weather disrupt the plan.

    If you’re already using SAP Integrated Business Planning (IBP), you’re in a strong position to take forecasting further. By layering advanced AI into your SAP IBP workflows, you can dramatically improve forecast accuracy and planning agility—without changing how your teams work.

    The forecast gap that’s costing you millions

    No matter your industry, the margin for error in demand planning is razor-thin:

    • Retailers lose revenue and customer loyalty when popular products sell out, while slow-moving stock ties up capital.
    • Distributors face freight chaos and missed service levels during seasonal peaks, unable to predict and respond quickly to shifting volumes.
    • CPG brands risk under- or over-producing when promotions or regional shifts aren’t accounted for.
    • All planners struggle with cold starts: new or low-history SKUs that traditional models can’t forecast reliably. 

    These challenges are only intensifying.

    Economic volatility, shifting consumer behaviors, tariffs, and climate-related disruptions introduce new variables that make demand harder to predict — and even harder to respond to in time. 

    Even in robust, enterprise platforms like SAP IBP, traditional forecasting models often rely too heavily on limited historical data and rigid assumptions. They struggle to adapt quickly to new signals or scale across complex planning environments with thousands of SKUs, channels, and geographic regions.

    Staying competitive requires more than minor tuning. It calls for intelligent systems that can learn from change, adapt to complexity, and deliver insights at scale.

    That’s where the DataRobot Demand Planning App adds value. 

    It enhances your SAP IBP workflows with AI to provide a more agile, intelligent, and precise forecasting engine.

    Add demand planning precision to your SAP IBP 

    The DataRobot Demand Planning App integrates directly with SAP IBP, infusing your existing planning environment with advanced AI forecasting. It works within your existing workflows, requiring no complex implementation, retraining, or disruption to planning processes. 

    Here’s how it helps:

    • Improve accuracy where it matters most: Confidently forecast volatile demand patterns, including new product launches, promotional spikes, and macroeconomic disruptions.
    • Right-size inventory and reduce waste: Align supply chain with actual demand to minimize stockouts and overstocks, freeing up capital and reducing excess carrying costs.
    • Drive adoption with seamless integration: Forecasts appear  directly within SAP IBP, so planners don’t need to learn a new tool or adjust their process.
    • Accelerate impact without overwhelming AI teams: Prebuilt templates automate data prep, model training, and deployment so your data science resources can stay focused on strategic priorities.
    Screenshot 2025 04 29 at 10.40.59 AM

    How AI is changing demand planning   

    Organizations across industries are already using DataRobot for demand planning to deliver measurable ROI and reduce forecast risk :

    • Global fashion retailer: Improved forecast accuracy by 9% at the SKU level, saving hundreds of thousands from overstock losses through better inventory alignment.
    • European CPG company: Maintained 99% stock availability and reduced held stock by £500K per month, freeing up working capital and improving service levels.
    • Fortune 100 retailer: Increased Black Friday forecast accuracy to 95%, saving $2M per week through optimized workforce and inventory planning.
    • Fortune 500 tech company: Predicted sell-out volumes four weeks in advance, enabling more strategic inventory placement around retailer promotions. 

    These aren’t edge cases. They’re evidence that the right AI solution, when integrated into the tools your team already uses, can deliver fast and sustainable value.

    What sets the Demand Planning App apart

    The DataRobot Demand Planning App wasn’t built to replace SAP IBP. It was built to enhance and extend it. It complements your existing investment with differentiated AI capabilities purpose-built for the real-world complexity of demand planning.

    Why it’s different:

    • Prebuilt, customizable forecasting templates designed for cold starts, promotions, seasonality, and high-SKU environments help you get started quickly and adjust as needed without starting from scratch.
    • The app adapts in near real time,  providing flexibility to easily incorporate broader factors from other data sources to identify the impact of emerging trends, geographic variation, and external factors like weather, inflation, or regulatory changes.
    • Built-in monitoring, drift detection, version control, and auditability support enterprise-grade accuracy, compliance, and governance.
    • Forecast outputs flow directly into SAP IBP, so planners can see and use improved forecasts in the tools they already know, without retraining or manual work. 

    Four ways to strengthen demand planning in a volatile market 

    For supply chain and AI leaders looking to reduce risk, drive agility, and future-proof your operations, here are four practical actions to take now:

    1. Incorporate external signals: Go beyond historical data by integrating real-time signals like inflation, weather, or social sentiment to anticipate shifts in demand. 
    2. Tackle  cold starts with proxy data. Use intelligent modeling to accurately forecast demand for new SKUs so they don’t become blind spots in your planning process.
    3. Align on shared KPIs. Strengthen collaboration by ensuring  supply chain, finance, and AI teams are working toward common goals and measurable outcomes. 
    4. Automate what slows you down: Improve accuracy and speed by automating data prep and model deployment using  tools designed for scale and repeatability.

    Ready to enhance SAP IBP with AI?

    In volatile markets, every planning decision carries more weight. Forecasting missteps can ripple across your entire supply chain, eroding trust, tying up cash, and compromising customer satisfaction.

    The DataRobot Demand Planning App enhances SAP IBP with advanced AI-driven forecasting that learns, adapts, and scales as fast as your business moves — without disrupting the systems or workflows you rely on.

    Want to see what this could look like in your SAP IBP environment? Schedule a demo.



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