Results
Proof that AI and automation can improve the way a business runs
These are practical projects I have personally designed, built, and deployed across finance, hospitality, retail, corporate reporting, and operational analysis.
Commercial proof matters more than technical theatre
The pattern across these examples is consistent: pick a painful operational process, connect the data properly, keep finance and management controls visible, and ship something people can use every week.
Mid-market reality
These projects sit inside existing finance, retail, hospitality, and infrastructure operations. The work connects the systems already running the business.
Measured outcomes
The value is expressed in time saved, close cycles shortened, reports automated, and decisions made faster, not vague transformation language.
CFO-level control
Finance judgement shapes the build: auditability, exception handling, board confidence, and handover matter as much as the automation itself.
Financial forecasting automation for a multi-site hospitality business
The Challenge
A hospitality group with 15+ sites was producing monthly forecasts manually in Excel. Each site took half a day. The finance team spent more time compiling numbers than analysing them, and forecasts were outdated by the time they reached the board.
The Approach
Built an automated forecasting system pulling live data from SAP, EPOS, and payroll systems. Implemented two forecast methods - run-rate and seasonal - with automatic daily cache refresh. The finance team now reviews and adjusts forecasts instead of building them from scratch.
Commercial Proof
- Reduced month-end pressure by replacing spreadsheet assembly with controlled daily refreshes.
- Gave leadership a current view of site performance instead of a retrospective monthly snapshot.
- Kept finance ownership in the process, with human review still built into the workflow.
“We went from dreading month-end to having real-time visibility. The board gets better numbers faster, and the finance team actually has time to think strategically.”
Finance Director
Multi-site hospitality group
ERP and retail system reconciliation eliminating manual processes
The Challenge
A retail business with multiple farm shops and outlets was manually reconciling stock between their EPOS system and SAP every day. The process involved CSV exports, manual matching, and journal entries - consuming 40+ hours per month of skilled finance time.
The Approach
Built an automated daily reconciliation pipeline connecting CBE EPOS directly to SAP B1. The system generates stock journals, goods received notes, and reconciliation reports automatically. Includes drift monitoring and exception alerting.
Commercial Proof
- Removed a recurring finance bottleneck without replacing the ERP or retail platform.
- Improved control by moving exceptions into a monitored process instead of spreadsheet checks.
- Freed skilled finance time for analysis, review, and operational support.
“What used to take someone most of their week now happens automatically overnight. The accuracy is better than manual processing ever was.”
Operations Director
Multi-site retail group
Board governance and reporting automation
The Challenge
A group with multiple subsidiary companies was producing board packs manually - pulling data from SharePoint, SSAS cubes, and Excel models, then formatting into PDF reports. 13 reports, produced weekly, each requiring manual intervention.
The Approach
Built an automated report generation system that pulls from SharePoint and SSAS Tabular models, produces formatted Excel reports, converts to PDF, and distributes via email - all on a weekly schedule with zero manual intervention.
Commercial Proof
- Turned reporting into a repeatable governed process rather than a weekly manual scramble.
- Reduced version-control risk by generating the same pack from controlled source data.
- Improved cadence for directors and managers who rely on timely information.
“Every Monday morning, the reports are there. No chasing, no formatting errors, no delays. It just works.”
CFO
Group holding company
AI-powered operational analysis for infrastructure optimisation
The Challenge
An EV charging network needed to understand utilisation patterns across their estate to inform investment decisions. Data was scattered across multiple systems with no unified view.
The Approach
Built a natural language query interface over their operational data, enabling leadership to ask questions in plain English and receive formatted reports. Includes pivot tables, time-period analysis, and automated exclusions for non-comparable data.
Commercial Proof
- Made operational data easier for leadership to interrogate without waiting for bespoke reports.
- Supported investment decisions with faster access to utilisation and performance patterns.
- Kept the reporting structured enough for repeatable analysis, not one-off AI answers.
“I can ask a question about our utilisation data and get an answer in seconds. No need to wait for someone to build a report - I just type what I need.”
Managing Director
Infrastructure operator
The same pattern can be applied to your own processes
Most mid-market businesses have a few processes like these: important, recurring, spreadsheet-heavy, and too dependent on manual effort. Those are usually the best places to start.
Month-end reporting and reconciliation
ERP, EPOS, CRM, and finance system data flows
Board packs, management reports, and recurring PDFs
Operational data questions that currently need analyst time