Coexisting with SAP: How Planning in a Box Supercharges Supply Chain Planning with AI and Google Cloud

Blog / Coexisting with SAP: How Planning in a Box Supercharges Supply Chain Planning with AI and Google Cloud

Enterprise operations today face constant disruption—supply shifts, fluctuating demand, and increased pressure to localize and digitize. Traditional ERP systems, while foundational, are not enough on their own to manage complexity at speed. To gain agility, accuracy, and real-time insights, organizations are augmenting existing platforms like SAP with modern, AI-powered tools.

In this context, Planning in a Box – Pi Agent  built on Google Cloud, serves as a critical layer of intelligence that enhances planning precision, responsiveness, and automation – all while coexisting seamlessly with SAP systems. With SAP’s recent AI enhancements and Google Cloud’s scalable infrastructure, enterprises now have a clear path to transforming their planning capabilities.

To ground this discussion in practical terms, we draw inspiration from ACME, a fictitious enterprise navigating supply chain complexity, evolving demand patterns, and the need for real-time, data-driven planning. The scenarios outlined in this paper reflect the challenges and opportunities many global organizations face today.

The Modern Enterprise Challenge

Large organizations like ACME  managing multi-site manufacturing and logistics face a common set of challenges:

• Distributed Inventory Management: Components such as battery modules, cells, or electronics are stored across facilities with varying lead times and risks.
  
• Unpredictable Demand Patterns: Driven by weather, regulatory changes, consumer behavior, or infrastructure shifts.
  
• Profitability Pressure: Volatile input costs, custom project pricing, and global tariff policies impact margin predictability.
  
• Resource Allocation: Balancing labor and equipment across plants with shifting workloads.
  
• Siloed Data Environments: SAP data often remains locked in structured formats, limiting cross-functional visibility.
• Slow Planning Cycles: Reliance on manual processes makes it difficult to react in real time.

To navigate these complexities, planning must evolve from rigid, periodic updates to continuous, data-driven optimization.

Planning in a Box – Pi Agent: Built for Agility on Google Cloud

What It Is?

Planning in a Box – Pi Agent is an AI-driven platform that enhances enterprise planning by integrating directly with SAP systems (ECC, S/4HANA and Datasphere). It is built entirely on Google Cloud, using tools like BigQuery, Vertex AI, and the Google Cloud Cortex Framework to deliver intelligent planning without the need for ERP replacement.

Key Functional Benefits

Real-Time Inventory Optimization

Pi Agent dynamically positions inventory based on live demand signals, cost structures, and tariff inputs – enabling reduced carrying costs, improved service levels, and anomaly detection across complex supply chains.

Predictive Demand Forecasting

Using Google Vertex AI and Gemini models, Pi Agent captures signals from external sources such as search trends, weather, and macroeconomic data to improve forecast accuracy and respond to sudden demand shifts.

Margin Simulation and Planning

With built-in elasticity modeling, organizations can simulate the impact of pricing strategies, lead times, and sourcing decisions – optimizing profit margins under volatile market conditions.

Logistics Adaptability

Planning in a Box can automatically adjust inventory placement and sourcing in response to real-time events such as tariff updates, transportation changes, or geopolitical shifts—providing agility at the logistics level.

Generative AI Support

Using Gemini-powered generative AI, the system helps planners by generating scenario summaries, strategic insights, and executive-ready reports—automating time-consuming tasks and enabling faster, informed decisions.

Autonomous Planning with Agentspace

Through Agentspace, Pi Agent acts as a digital assistant—executing simulations, automating repetitive tasks, and delivering recommendations. This reduces human workload and compresses planning cycles.

Google Cloud Cortex Framework: Unlocking SAP Data at Scale

The Google Cloud Cortex Framework provides the foundation for Planning in a Box – Pi Agent  to integrate with SAP efficiently. Key components include:

• SAP-Aligned Blueprints: Over 40 prebuilt data models and workflows accelerate data onboarding into BigQuery.
  
• Visualization Dashboards: Enable immediate insight into operations, supply chains, and logistics.
  
• Data Enrichment: Combines SAP data with external Google signals (e.g., Maps, Trends, Ads) for a richer, more contextual view.
• Enterprise-Grade Scalability: Cortex enables building and extending use cases securely across business units.

With Cortex, SAP data becomes more actionable, more accessible, and more valuable.

Evolving SAP with Embedded AI Capabilities

As digital transformation accelerates, SAP has continued to enhance its suite of embedded AI tools, bringing intelligence directly into the heart of enterprise operations. These capabilities are designed to streamline workflows, automate repetitive tasks, and enable smarter, faster decisions within the SAP environment.

SAP Business Data Cloud (BDC)

• Enterprise-Wide Data Visibility: BDC provides a governed architecture for accessing and integrating both SAP and non-SAP data, enabling better collaboration across business units.
  
• Real-Time Access Without Duplication: Through features like zero-copy sharing, SAP ensures that data remains consistent and readily available across platforms.
• Context-Rich Decision Support: Knowledge graphs allow SAP to uncover relationships and dependencies within complex enterprise data, driving more contextual insights.

SAP Business AI and Joule Copilot

• AI-Powered Workflows: Joule, SAP’s embedded AI assistant, integrates directly into core applications such as S/4HANA to assist with task execution, surface relevant data, and enhance user decision-making.
  
• Pre-Built Industry Models: SAP offers pretrained AI capabilities tailored to industries like manufacturing and logistics, accelerating deployment without the need for extensive customization.
• Process-Level Automation: From predictive maintenance to procurement approvals and invoice reconciliation, embedded AI helps reduce manual effort and improve consistency.

Together, these tools strengthen SAP’s position as an intelligent system of record. When combined with advanced planning platforms like Planning in a Box – Pi Agent, organizations can achieve the best of both worlds: operational efficiency within SAP and predictive, autonomous decision support at the planning layer.

Agent2Agent Protocol: A New Paradigm for Connected AI

Planning in a Box also utilizes the Agent2Agent (A2A) protocol, enabling seamless communication between AI agents across platforms. This allows digital agents inside Google Cloud to collaborate with enterprise apps – including SAP – without custom integrations, ensuring that intelligence flows securely and without manual intervention.

Strategic Implementation Recommendations

To realize maximum value while managing complexity, organizations should take a phased approach:

1. Start with a Pilot

Begin with a targeted planning problem, such as inventory optimization for a specific product category or region. Use Pi Agent and the Cortex Framework to demonstrate quick wins.

2. Expand Use of Predictive and Generative AI

Scale demand forecasting, margin simulation, and generative summaries across planning workflows. Leverage Vertex AI and Gemini for insight generation and planning automation.

3. Activate SAP Business AI for Embedded Process Optimization

Deploy SAP-native tools like Joule to automate procurement tasks, enable predictive maintenance, or streamline finance operations directly within S/4HANA.

4. Harmonize the Data Foundation

Ensure that BigQuery and SAP Datasphere are integrated for unified analytics. Use Business Data Cloud to establish governance and consistency across the data landscape.

5. Avoid Capability Overlap

Assess AI features carefully to prevent investing in redundant tools. For example, if advanced forecasting is handled through Planning in a Box – Pi Agent, embedded forecasting in SAP may not be required at full scale.

Planning with Agility and Intelligence

By integrating Planning in a Box – Pi Agent  on Google Cloud with existing SAP systems, enterprises can elevate their planning capabilities to meet modern challenges:

• Real-time optimization of inventory, logistics, and resource allocation
  
• Forecasting and scenario simulation enhanced by external signals
  
• Autonomous planning support to reduce manual intervention
• Seamless integration with SAP and scalable cloud infrastructure

With embedded intelligence from SAP and generative, predictive capabilities from Planning in a Box, businesses are empowered to move from reactive planning to intelligent, proactive decision-making – accelerating outcomes across their entire value chain.

Ready to see it in action?

Experience how Planning in a Box – Pi Agent can transform your SAP environment.