A repeatable demand baseline
Reduce repeated spreadsheet preparation and make forecast assumptions easier to inspect.
Blend history, promotions, and external signals into forecast inputs.
Build this with usFROM POSSIBILITY TO PRACTICE
Build a demand estimate using historical orders and relevant business signals such as promotions or seasonality. A scoped solution compares the estimate with your current method and gives planners the assumptions and uncertainty they need to decide how to use it.
These are the improvements to evaluate against your current process. We agree the scope and test the value with your team.
Reduce repeated spreadsheet preparation and make forecast assumptions easier to inspect.
Bring demand estimates and their uncertainty into purchasing and replenishment planning.
Compare predictions with what happened and identify where the model or inputs need improvement.
EVIDENCE FROM OTHER BUSINESSES
These named businesses implemented related workflows. Their deployment results provide a reference for the opportunity; they are not appana projects or a promised return for your business.
Blue Ridge SCP
307%Reported annual deployment ROI
Average inventory fell from $120 million to $90 million, with approximately $1.75 million in annual carrying-cost savings reported.
Supply-chain planning across forecast validation, purchase orders, inventory and container optimisation. The return combines staffing and stock-carrying benefits.
Nucleus Research · Published 2025-06-23 · Source checked 2026-10-05
Read the published case study ↗Reported annual ROI uses Nucleus Research’s method: average annual net benefit across three years divided by initial investment. Assessments can include indirect benefits and projected years. Figures cover the named deployment, including software, integration and process changes; they do not isolate AI’s contribution or predict your return.
Nucleus Research’s calculation method ↗STEP 1
Select the relevant information from your inventory platform, ERP and transport-management tools. Agree what a good result looks like with your supply chain and logistics team, including the rules, examples and permissions the workflow needs.
STEP 2
Blend history, promotions, and external signals into forecast inputs. Prepare the inputs, state the assumptions and compare estimates with a suitable baseline. Show uncertainty and where the available data is insufficient.
STEP 3
Give planners an estimate or scenario comparison they can challenge, with the underlying assumptions and a way to compare it with actual outcomes. Planners validate recommendations against capacity and service commitments before changing orders or routes.
AN EXAMPLE IN PRACTICE
A planner tests forecasting for one product group. The workflow uses historical periods to compare predictions with actual demand, then presents a replenishment planning view. The planner checks unusual events and supplier constraints before committing stock.
Choose one workflow, one team and a representative set of real tasks. We establish the current baseline, build the first version and review the results together before expanding it.
Depending on the scope, useful inputs include:
We agree access and integration with your inventory platform, ERP and transport-management tools as part of the design.
Planners validate recommendations against capacity and service commitments before changing orders or routes.
LET’S BUILD IT TOGETHER
Tell us how your team works today and what you would like to improve. We’ll explore the opportunity, shape a practical first step and build it with you.
Talk to us about this use case