Supply Chain Planning FAQs

A 4–6 week exercise that builds and analyses a digital twin of your supply chain to improve inventory health by identifying improvements in people, processes, technology and data

Consolidated forecasts into SO99+
Inventory and service level modelling
Analysis of overstocks and backorders
Optimised inventory deployment
Root cause analysis
Quantification of supply and demand impacts
Identification of improvement opportunities

Forecasting across multiple systems
Lack of integration (spreadsheet consolidation)
Labour intensive and error‑prone processes
Limited end‑to‑end visibility
Difficulty influencing both supply and demand

A sophisticated, end‑to‑end digital twin modelling tool for forecasting, inventory, and replenishment.

Automated, self‑adaptive forecasting
Consolidated demand view
Inventory optimisation
AI-based categorisation
Optimisation of MTO/MTS policies
Detailed modelling of replenishment and constraints

Uses advanced maths, machine learning, and GenAI
Probabilistic forecasting capability
Multi‑echelon inventory optimisation (MEIO)
AI applied to clustering, seasonality, promotions, and new launches
Embedded “explainability”

A specialist supply chain consultancy with an inventory optimisation methodology developed over many years and a track record of delivering results

Designed allocation-aware forecasting models
Enabled dynamic forecast consumption logic
Implemented automated lifecycle / supersession handling

Yes. In many cases, introducing a staging or data warehouse layer improves data quality, simplifies integration, and supports long-term scalability and maintenance. It also creates a stable foundation for consolidating data from multiple sources before feeding planning systems

Planning systems require structured, consistent data formats. In practice, we define and agree formats during implementation to ensure compatibility with source systems and downstream processes

End-to-end planning links forecasting, inventory optimisation, and production planning into a single, coordinated process. Forecasts drive replenishment and production decisions, ensuring alignment across the supply chain

Planning systems generate optimised production proposals based on demand and constraints. Scheduling tools then sequence and execute those plans within production environments

Yes. Modern planning platforms support alternative routing and dynamic capacity planning, allowing organisations to optimise production across different lines or facilities

By linking demand signals directly to production planning and automating decision-making, organisations can move from reactive scheduling to stable, demand-driven production plans

We design forecasting models that account for allocations and constraints, ensuring that plans remain realistic while maximising business value

Yes. Forecast consumption can be configured to adjust dynamically as orders are received, ensuring that forward-looking plans remain aligned with real-world demand

We prioritise usability by implementing intuitive interfaces, improving data input processes, and enabling flexible reporting. This ensures strong user adoption across commercial and operational teams

Yes. Planning systems can support multiple time granularities, allowing organisations to plan in detail in the short term and more broadly over longer horizons

We can enhance or replace tools with more flexible and user-friendly solutions, as well as introduce complementary capabilities to improve collaboration and usability

Planning platforms are designed to scale with your business. Infrastructure can be expanded incrementally to support additional data, users, and functionality

Yes. We often recommend starting with a subset of products, locations, or SKUs to validate the solution before scaling across the organisation

We bring proven implementation frameworks, data models, and planning processes, tailored to each client’s needs while leveraging lessons learned across multiple industries

We combine structured delivery, clear governance, and close collaboration with client teams to ensure solutions are successfully deployed and adopted