Flagship Finance Systems

Selected Finance-Transformation Systems

Four systems that best demonstrate applied finance transformation, reporting, controls and workflow design.

Live

Management Reporting Platform

Challenge: Senior management needed faster, more consistent visibility than periodic spreadsheet reporting allowed.

Solution: A finance-led reporting platform with live dashboards, built to progressively expand across operational modules.

Management value: Provides senior management with a current, consolidated view of performance without waiting for the next spreadsheet-consolidation cycle.

Read the case study
Next.js PostgreSQL Supabase
Live

Fuel Consumption & Equipment Performance Monitoring

Challenge: No systematic way to monitor fuel consumption or flag abnormal usage across a large mixed fleet.

Solution: Asset-specific benchmarking, operator-level monitoring and exception reporting for a fleet of 100+ vehicles.

Management value: Gives finance and fleet supervisors a shared, current view of where fuel cost is concentrated, with earlier visibility of abnormal consumption.

Read the case study
Next.js Supabase Auth Row-Level Security
Live

Supplier Document & Payment Control System

Challenge: Document tracking and payment readiness across suppliers relied heavily on manual checks.

Solution: A workflow-controlled system strengthening duplicate-payment prevention and document visibility.

Management value: Strengthens duplicate-payment prevention and gives finance and procurement continuous, system-backed visibility over payment readiness.

Read the case study
Next.js SQL Constraints Row-Level Security
Prototype

Export Proceeds & LOC Compliance Tracking

Challenge: Export proceeds needed structured tracking from inflow through invoice/LOC matching to closure.

Solution: An operational prototype with bank-mismatch flagging and a 60-day follow-up escalation view.

Management value: Gives finance earlier visibility of bank mismatches and overdue cases, well before they become compliance issues.

Read the case study
Next.js PostgreSQL Audit Logging

Approach

How I Approach Finance Transformation Work

The same discipline used in financial reporting and control also guides the development of these tools: begin with the business problem, not the technology.

Understand the business problem

Every project starts from a real reporting, control or decision-making gap observed in day-to-day finance leadership — not from a generic template.

Identify the control and reporting requirements

Define what needs to be measured, who is accountable for it, and what thresholds or exceptions matter before any solution is designed.

Design practical workflows and information structures

Map how the information and approvals should actually flow, so the resulting system fits how finance and operational teams work.

Build or configure the solution

Develop or configure the required reporting platform, workflow or monitoring tool while keeping the solution practical and aligned with finance-control standards.

Validate, refine and support adoption

Test the system against real data and real users, then refine it until finance and operational teams rely on it day to day.

Analytics & Decision-Support Projects

Additional Analytics and Decision-Support Work

Projects demonstrating analytical modelling, planning, automation and evidence-based decision support.

Internal Tool

Budget Compilation Engine

A standalone Python-based executable that consolidates departmental budget workbooks into a controlled master template, with an audit-output workbook and a simple interface for non-technical staff.

More detail

Built to remove the manual, error-prone reconciliation of separate department budget files into one controlled workbook, while preserving a clear audit output of how the master template was assembled.

Python Budgeting
Analytics Study

Workforce Task-Achievability Analytics

An analytics study examining task-achievement rates across a large historical workforce dataset, with scope to explore seasonality, field-condition and crop-age effects.

More detail

Part of the broader workforce analytics work covering 1,560+ employees, aimed at giving operational leadership a quantitative view of task achievability rather than relying solely on anecdotal reporting.

Analytics Workforce Data
MSc Coursework

Machine Learning Yield Forecaster

A block-level machine learning study using historical production and climatic variables — rainfall, rain days, temperature, humidity and solar radiation — to evaluate yield-prediction performance.

More detail

Completed as part of MSc Business Analytics coursework, applying machine-learning methods to an agricultural production dataset.

Machine Learning MSc Coursework

Get In Touch

Need clearer reporting, stronger controls or a more practical finance workflow?

I am available for remote consulting, fixed-scope diagnostics and finance-transformation project work.