Genentech: oncology and specialty therapy planning

Executive summary

Genentech’s short-term operational demand forecasts (0–24 months) operated independently from its long-range strategic supply and capacity plans (3–10 years), creating structural disconnects across manufacturing capacity, finished-goods inventory, and financial projections in three critical therapy franchises.

Working with RoadMap Technologies’ forecasting and demand planning practice, Genentech unified multi-horizon statistical forecasting, Forecast Value Added (FVA) override governance, and automated SKU-to-portfolio reconciliation inside a single enterprise architecture. The engagement restored forecast discipline, reduced inventory imbalances across short-dated specialty therapies, and established a single consensus numbers baseline across commercial, finance, and technical operations.

The challenge

Genentech manages global demand and supply across three high-complexity specialty therapy areas, each governed by distinct clinical, commercial, and supply chain dynamics:

• Oncology: Characterized by rapid new-patient start shifts, stacked label and indication expansions, regimen duration changes, and abrupt biosimilar or competitive erosion curves.
• Neurology: Governed by chronic patient cohorts where long-term therapy persistency, titration schedules, and payer or formulary policy shifts drive gradual but compounding volume swings.
• Transplant anti-infectives: Driven by episodic, procedure-linked hospital procurement, seasonal viral patterns, strict cold-chain handling, and tight expiration and shelf-life constraints.

Beyond the clinical complexity of each franchise, Genentech faced a structural planning divide. Monthly operational forecasts (0–24 months) were compiled separately from multi-year strategic financial and manufacturing capacity plans (3–10 years). Because the two horizons relied on disconnected spreadsheets and unaligned assumptions, the organization experienced simultaneous excess stock on maturing SKUs, stockout exposure on expanding indications, misallocated biologics capacity capital, and conflicting revenue outlooks across portfolio reviews.

The solution

RoadMap Technologies designed and implemented a unified demand and supply planning architecture in a structured three-phase rollout to consolidate data inputs, reconcile planning horizons, and institutionalize cross-functional S&OP/IBP governance.

Implementation Phase	Core Architecture Delivered	Operational & Strategic Impact
Phase 1: Unified Baseline & Bias Visibility	Consolidated commercial patient models, wholesaler/specialty distributor shipments, and hospital demand signals into an automated statistical baseline	Surfaced systematic management bias and isolated the true accuracy impact of manual commercial overrides
Phase 2: Multi-Horizon Reconciliation & Scenario Modeling	Bridged 0–24 month operational SKU plans with 3–10 year strategic brand projections; introduced oncology pipeline scenario modeling and dynamic confidence bands for high-volatility SKUs	Aligned near-term biologic lot scheduling and vial/syringe packaging directly with long-range bulk drug substance capacity and finance outlooks
Phase 3: FVA Governance & IBP Cadence	Deployed automated Forecast Value Added (FVA) tracking, stop-light exception highlighting for high-override SKUs, and a structured monthly S&OP/IBP workflow	Institutionalized accountability across commercial, supply chain, and finance teams with executive-ready portfolio dashboards

Core capabilities delivered

• Therapy-calibrated statistical forecasting: Multi-model time-series, seasonality, product lifecycle, S-curve launch, and loss-of-exclusivity (LOE) decay curves tailored to oncology, neurology, and transplant profiles.
• Automated hierarchical reconciliation: Seamless bottom-up and top-down roll-up from presentation SKU and dosage strength to brand, indication, and therapeutic area portfolio.
• Pipeline and LOE scenario simulation: Interactive what-if modeling for clinical trial readouts, regulatory approval timing, indication expansion uptake, and biosimilar entry scenarios.
• Override governance & FVA analytics: Automated tracking of statistical baseline versus commercial and executive overrides, complete with stop-light alerts flagging recurring bias.
• Consensus S&OP / IBP workflows: Role-based review cycles connecting commercial brand leads, demand planners, supply chain operations, and FP&A on a single governed dataset.

Results & business impact

Consolidating operational and strategic planning into one governed workflow delivered measurable improvements across forecast accuracy, inventory health, and executive decision-making:

• Unified multi-horizon alignment: Reconciled 0–24 month operational execution with 3–10 year strategic capacity and financial plans across all three therapeutic portfolios.
• Eliminated cross-functional planning silos: Commercial brand teams, supply chain planners, and finance analysts operated from a single hierarchical source of truth rather than competing spreadsheet models.
• Granular volatility visibility: Dynamic confidence bands and driver decomposition gave planners early warning into SKU- and indication-level demand swings.
• Stronger long-range revenue predictability: Linking clinical lifecycle and LOE curves directly to unit volume projections improved multi-year financial planning precision.
• Reduced specialty inventory imbalances: Better integration of hospital, distributor, and patient demand signals reduced both expiry write-offs on shelf-life-constrained SKUs and safety-stock shortfalls.
• Disciplined capital and capacity allocation: Portfolio-level scenario bands enabled leadership to size long-lead manufacturing and fill-finish investments with quantified risk bounds.
• Elevated executive confidence: Transparent FVA metrics and exception reporting gave senior leadership clear visibility into where human judgment added value and where statistical baselines should hold.