Resilience in retail: How to move your SAP data to minimize waste

Before he became Apple’s CEO, Tim Cook was the architect of one of the most operationally efficient supply chains the world had ever seen. He didn’t start with new product categories or flashy robotics. He started with simplification: cutting Apple’s sprawling supplier network from nearly 100 vendors to just 24. Then, he doubled down on collaboration, just-in-time (JIT) delivery and vertical integration, giving Apple control of everything from factories to forecasting.

That control translated into speed, agility and accuracy — attributes retail supply chains desperately need, especially today. Apple had end-to-end visibility over its production pipeline, and the result was a supply chain that could handle demand spikes and disruptions alike, without compromising quality.

What if you could apply the same mindset Cook used to optimize Apple’s supply chain to your data? Instead of waiting and reacting, you could respond to change as it happens.

If your data sources are fragmented, refresh on schedules that don’t take current or relevant events into account or depend on manual intervention, you’re not able to resolve problems or confidently make decisions, and the shift to proactive methods won’t be possible. But with continuous orchestration of your most valuable digital asset, you can win in an industry where most companies are merely fighting to uphold razor-thin margins by avoiding spoilage, waste and lost revenue.

Perishable profits

Consider the most direct example of waste potential in the retail space: grocery. Fresh retail items don’t just sell quickly; they expire quickly. Between the farm and the fridge, there’s a complex, fragile chain of vendors, distribution centers and stores.

The smallest delay in your data pipeline is a chance for product to go unsold, unstocked or wasted. The shelf life of perishable goods is short, and demand can shift hourly. If your inventory forecasts are built on delayed or inconsistent data, the results can swing in either direction: Overorder and waste inventory or understock and miss sales. Either direction is costly. 

To prevent these outcomes, you need real-time visibility into what’s arriving and what’s already on your shelves. Plus, what’s moving fastest. Since you have to stitch together a view of field data, supplier inputs, distribution center updates and data from POS and other systems, you must have orchestrated, intelligent data pipelines.

That’s why more retailers are adopting modern data management architectures via offerings like SAP Business Data Cloud, which brings together SAP Datasphere, SAP Analytics Cloud and Databricks to unify data and AI-driven insights. But these platforms can’t work in isolation. They require clean, orchestrated tasks, steps, activities and transfer across an IT landscape to generate the relevant, quality data necessary to inform daily decisions.

Why retail data spoils

Unfortunately, it’s common in retail to know what needs to happen but be stuck in reactivity mode because your data is stale or simply late.

You might have a perfectly calibrated model in SAP Integrated Business Planning (IBP), but if it’s pulling incomplete or old data, there’s no chance it reflects your real replenishment needs. You may receive vendor data in flat files, but if they have to be manually validated and uploaded, your cycle slows down. Or maybe you have all the right tools, but your pricing team and planners aren’t seeing the same information in the same format at the same time.

This is the hidden challenge of retail: achieving consistency and speed at scale. When your supply chain spans multiple regions and partners, minor data issues amplify quickly. 

See how global retail collective Centric Brands achieved end-to-end visibility and control across its complex SAP environment and a variety of non-SAP systems.

Keep your data flows from expiring: The automation fabric way

A resilient supply chain for fresh goods runs on fresh data across your SAP and non-SAP systems. You must continuously collect, transform, enrich and act on it without delay. A mere technical upgrade won’t do, either. You have to build a foundation for repeatable execution.

On a high level, that might look like:

• Ingesting real-time inventory and shipment data directly into your SAP S/4HANA systems from farms, warehouses and distribution centers
• Using tools like Informatica Cloud to extract and transform data from external sources, including environmental sensors for temperature, humidity and shelf life
• Feeding POS data to SAP IBP to do short-term forecasting using recent demand patterns
• Normalizing data formats and units across suppliers and geographies automatically
• Triggering dynamic adjustments in SAP, like store delivery windows or pricing recommendations, based on updated transit times, spoilage risk or demand spikes
• Alerting supply chain planners the moment a shipment is delayed or a product batch falls below freshness thresholds
• Routing enriched data into SAP Datasphere, then feed it to Microsoft Power BI or SAP Analytics Cloud for real-time inventory and margin analysis

How do you bring all of this together in a way that’s scalable and automated? 

Build your forecasting-and-replenishment (F&R) automation fabric

An automation fabric is a cohesive framework that connects and monitors your applications, processes and data sources with zero friction. What sets this approach apart from individually integrated point solutions is its ability to control data movement with a high degree of autonomy. Instead of waiting on rigid schedules or scrambling to react to delays, you can operate with precision. 

Think of it as air traffic control for your data. It monitors every source and route to make sure nothing arrives late, out of order or without clearance. That level of control gives you agility that’s unmatched in retail.

Processing incoming data

• Load daily sales data from SAP POSDM or your POS platform into SAP IBP
• Validate and post documents in SAP S/4HANA for reconciliation and further processing
• Import promotional updates and sales uplift data from SAP IBP or third-party campaign tools
• Trigger structured data exports to SAP Datasphere for enrichment and modeling

Nightly forecasting and replenishment cycles

• Full forecasting and replenishment
  • Stage datasets from SAP S/4HANA and external systems (e.g., supplier APIs) and validate readiness 
  • Generate promotional impact estimates using SAP F&R, enriched with Databricks or Azure ML
  • Wait for inbound shipment confirmations, trigger replenishment calculations and create and dispatch pick orders to warehouses or store distribution systems
• Processing negative stock
  • Identify and count negative inventory positions from SAP S/4HANA and store systems
  • Create physical inventory documents (PIDs) to trigger reconciliation and downstream updates

Planning and reporting system updates

• Push refreshed stock and forecast data into SAP IBP for next-day planning
• Enrich and route datasets to SAP Datasphere and Microsoft Power BI or SAP Analytics Cloud for visualization
• Notify supply chain teams and store planners of updates via email or workflow triggers
• Log and monitor every job to meet SLAs for stock updates, pick orders and forecast refreshes 

[Insert GIF of RunMyJobs F&R workflow template]

Your competitive advantage: Orchestration that delivers

Already using RunMyJobs in your retail environment? Download this forecasting-and-replenishment workflow template to move faster while maintaining accuracy and quality.

Planning to attend SAP Sapphire Orlando 2025? Visit booth #457 to see how leading retailers are turning fragmented data flows into automation fabrics using RunMyJobs.