K
Enterprise Operations2025Workforce Planning
This project is delivered under NDA. Client and product identities are withheld; screens are access-gated and shown to prospective clients on request.

Demand & Fulfilment Intelligence

A demand-management platform and mapping interface connecting forecast demand to fulfilment capability across a regional banking portfolio — so gaps surface while there is still time to respond.

Product Designer & Frontend Engineer
2025
Enterprise Technology Services
Client:Regional Banking Portfolio
ReactTypeScriptNode.jsData modellingSpreadsheet integration
Problem Statement

Making committed demand and actual fulfilment capacity visible against each other, early enough to act.

Our Approach

Demand and fulfilment are modelled together so committed work and available capability can be read against each other rather than reconciled by hand.

A mapping interface makes the relationship between demand categories and fulfilment capability explicit and adjustable, instead of buried in spreadsheet formulas.

Views are built around the operational decisions being made — where the gap is, how urgent it is, and what can still be changed.

Challenge

Demand forecasts and fulfilment capacity were maintained separately, in different formats, by different teams. The gap between what had been committed and what could actually be staffed only became visible when it was already a problem.

Reconciling them meant manual spreadsheet work each cycle, which made the picture out of date almost immediately and impossible to interrogate.

Solution

A demand-management platform and mapping interface connecting forecast demand to fulfilment capability across a regional banking portfolio — so gaps surface while there is still time to respond.

Outcome

Common in operations: the data exists, but in parallel spreadsheets nobody can read against each other in time. Modelling the relationship is usually the whole fix.

The constraint that shaped it

The mapping had to stay owned by the business

The demand-to-capability relationship changes constantly and is a business judgement, not a technical one. Encoding it in application logic would have made the system wrong within weeks — so the mapping is explicit, visible and editable by the people who own it.

· Decisions that mattered

Model the relationship, don't hardcode it

Keeping the mapping as configurable data rather than logic is what allows the platform to stay accurate as the business changes.

Lead time over precision

An approximate gap surfaced early is worth more than an exact one surfaced late — the design optimises for how soon a problem becomes visible.

· What I owned
  • Analysed the existing spreadsheet-based process with the operations team
  • Designed the demand-to-fulfilment model and mapping interface
  • Built the application and mapping UI
· Design Process

How We Solved the Problem

01
01

Demand ingestion

Forecast demand across the portfolio brought into a structured model rather than parallel spreadsheets.

    02
    02

    Capability mapping

    An explicit, adjustable mapping between demand categories and fulfilment capability, visible to the people who own it.

      03
      03

      Gap analysis

      Committed demand read against available capability to surface shortfalls early, with enough lead time for the response to matter.

        04
        04

        Operational views

        Interfaces shaped around planning decisions rather than reporting cycles.