JM

PROJECT SERVICES

Five Services, One Discovery Call Away

All Services

Power BI Dashboard Build

Best for: Retail, FMCG and finance teams without in-house BI capability

Your team is stuck reading static spreadsheets or waiting on ad hoc reports every month-end. I design and build Power BI dashboards, backed by clean SQL data pipelines, that give you live visibility into margin, pricing and trading performance.

  • Timeframe: 2 to 4 weeks depending on data source complexity.
  • Investment: Price on request, confirmed after a discovery call.
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Built a Loyalty KPI Dashboard for Woolworths Sydney Stores

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Financial Forecasting & Budget Models

Best for: Commercial and finance teams needing a rebuilt forecasting model

Budgeting cycles that rely on last year's spreadsheet rarely hold up under this year's pressure. I build integrated revenue and expenditure forecasting models with variance tracking built in, so your budget-versus-actuals reporting tells you something useful, not just something accurate.

  • Timeframe: 2 to 3 weeks per model.
  • Investment: Price on request, confirmed after a discovery call.
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Rebuilt Commercial Reporting Infrastructure, Cut Turnaround by 95%

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Month-End Close Automation

Best for: Finance teams with a manual, time-heavy month-end close

Month-end should not be the week your finance team disappears into reconciliation. I automate accrual journal preparation and reconciliation workflows for rebates, supplier income and high-volume transactions, cutting close time without cutting control.

  • Timeframe: 3 to 5 weeks, phased by process.
  • Investment: Price on request, confirmed after a discovery call.
See It In Action

Turned Reconciliation Into a Continuous Control Across 1,000+ Donor-Funded Stakeholders

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Commercial Finance Advisory

Best for: SMEs and retail businesses without a dedicated commercial finance function

Margin pressure and pricing decisions need evidence, not instinct. I provide ad hoc margin analysis, pricing analysis and CapEx evaluation, so your investment decisions are backed by the same rigour a full-time commercial finance analyst would bring.

  • Timeframe: Ongoing or project-based, scoped to need.
  • Investment: Price on request, confirmed after a discovery call.
See It In Action

Rebuilt Commercial Reporting Infrastructure, Cut Turnaround by 95%

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Predictive Analytics for Finance

Best for: Data-driven organisations ready to move beyond descriptive reporting

Most finance teams have the data to forecast risk and behaviour, but not the modelling skill to use it. I build Python-based predictive models, from credit risk classification to workforce and revenue forecasting, that turn your existing data into a decision-support tool.

  • Timeframe: 3 to 6 weeks depending on model complexity.
  • Investment: Price on request, confirmed after a discovery call.
See It In Action

Built a Credit Risk Classification Model Using Machine Learning

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Not Sure Which Service Fits?

A short discovery call is the fastest way to find out: no obligation, no generic sales pitch, just a conversation about what you actually need.

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