Selected Case Studies

Problem

A global planning environment needed a credible modernization path across legacy SAP planning, fragmented master data, and region-specific operating patterns.

Approach

Reviewed the planning operating model, integration landscape, master data readiness, business process variation, and fit for IBP, PP/DS, APO, and S/4HANA planning capabilities.

Solution

Defined a phased roadmap with target capabilities, sequencing logic, data dependencies, governance checkpoints, and executive decision gates.

Business Impact

Created clearer ownership, reduced program ambiguity, and gave leadership a practical path from fragmented planning to a more governed SAP planning architecture.

Problem

Planning leaders needed a low-risk way to test AI-enabled forecasting concepts before committing to a broader enterprise investment.

Approach

Used safe simulated data, statistical baselines, classification logic, and scenario comparisons to test where AI could support planner decisions.

Solution

Delivered a proof-of-concept framework for comparing baseline, risk-adjusted, and scenario-informed forecast views in planning review cycles.

Business Impact

Clarified how AI can improve exception focus, forecast confidence, and business readiness without replacing planner judgment or governance.

Problem

Clinical supply planning needed a clearer way to interpret enrollment variability, site activation changes, inventory constraints, shelf-life, and supply risk.

Approach

Mapped demand and supply decision points across trial planning, then structured scenario inputs around enrollment, dosage, country, site, and supply assumptions.

Solution

Designed an intelligence framework for scenario-based clinical supply planning, risk review, and stakeholder-ready planning narratives.

Business Impact

Improved planning clarity in a regulated setting where patient continuity, supply assurance, and decision traceability require disciplined support.