Illustrative Work & Reference Material

Most AI projects and data products fail because insufficient resources are allocated to the planning phase. Without a solid foundation, even sophisticated solutions cannot deliver value. Too often, foundational work is rushed or driven by political considerations rather than technical requirements and proper risk assessment.

The examples below are provided to help leadership teams understand the type of thinking, structure, and output typically produced during advisory engagements.

PDF Reports

Data Strategy

Coffee Roaster: Production and Financial Data Insights

Demonstrates how production and financial data can be analyzed together using big data analytics to uncover operational insights and improve decision-making.

Data Strategy

Logistics: Integrated Data & Automation Platform

Presents a practical strategy for introducing an integrated data and automation platform to a privately owned logistics business currently relying on manual, paper-based, and legacy workflows—connecting operations, finance, and analytics to improve efficiency, visibility, and profitability.

Accounting Automation

Fuel Retail: From Reactive Spreadsheets to Automated Finance

Illustrates a fuel retail business transitioning from reactive spreadsheet accounting into a proactive, automated finance function where the team gains hours back each week, the owner has real-time visibility into every station's performance, and AI handles routine tasks while humans focus on insight and control.

Accounting Automation

Law Firm: Accounting Automation Assessment

Explores how an accounting automation assessment can guide attorneys and finance leaders in a mid-to-large law firm through their finance and billing data flows. The objective is to identify risk, leakage, and governance gaps without disrupting operations or requiring system changes.

Accounting Automation

Accounting Firm: Tool Selection and Evaluation

Examines how an accounting firm can choose the right automation tool to manage hundreds of clients without hiring additional staff—assessing current bottlenecks, modelling different solution options, and weighing cost, control, and scalability before making any recommendation.

Articles

Data Strategy

After the Data Platform Failed — Restoring Decision Confidence Without Another Build

How independent advisory helped an organisation understand why a multi-million rand data platform failed — and restored leadership confidence before any rebuild was considered.

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Data Strategy

Investor Due Diligence — Separating Data Reality from the Investment Narrative

How an independent data strategy assessment helped an investor distinguish between presentation-level data strategy and operational reality during late-stage due diligence.

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Data Strategy

Manufacturing Plant with PLC–ERP Gaps

An example scenario of how we would help a manufacturing plant connect PLC data to ERP, fix inventory variances, and give finance reliable production insights—using our data product lifecycle.

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Interested in How This Works for Your Organisation?

These examples illustrate typical data strategy engagements—from diagnostic assessments and big data analytics projects to ongoing governance oversight. If you're facing similar data decisions, let's discuss how independent advisory can help.

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