michaelfaniyiLet’s talk

DATA · AUTOMATION · AI ADOPTION

Built for real work.
Designed for people.

From complex data
to better ways
of working.

I’m Michael Faniyi. I build analytical tools, simplify operational workflows and help teams put AI to practical use.

Explore my work Download CV
200+

Federal government staff trained
in data analysis and AI adoption

2 bureaus

Using my analytical tools
across Abuja and Lagos

Days → minutes

Turnaround on selected
routine workflows

01 / SELECTED WORK

Useful is the
real innovation.

Tools that solve recurring problems.
Skills that stay with the team.
Improvements that show up in the work.

01OPERATIONAL ANALYTICS

Better analysis.
Inside Excel.

An analytical add-in that brings financial ratios, Benford’s law screening and pattern-based grouping into the environment colleagues already use.

THE OUTCOMEAdopted across both
departmental bureaus.
Behind the work

The challenge

Recurring investigation tasks required repeated financial calculations and manual review of large datasets.

My contribution

I built a reusable Excel add-in to combine ratio analysis, anomaly screening and grouping of records with common patterns.

In practice

The tool is used in the Northern and Southern bureaus, including Abuja and Lagos. Screening highlights records for further investigation; it does not establish wrongdoing.

FINANCIAL ANALYSIS TOOLKITEXCEL ADD-IN
A clearer view.
A better next question.
01Financial ratios
02Anomaly screening
03Pattern grouping

Capability illustration · not a product screenshot

02DATA EXTRACTION

Make the data
ready for the work.

I created Xvert to turn source documents into usable analytical data, including PDF-to-Excel conversion.

Behind the work

The challenge

Useful information often arrives in formats that are difficult to analyse. Reformatting it manually slows down the actual investigation.

My contribution

I translated that recurring problem into a data parsing and extraction application, connecting document conversion to downstream spreadsheet analysis.

Visit Xvert
OPERATIONAL IMPROVEMENT
DaysMinutes.
Selected routine tasks, redesigned.
03WORKFLOW AUTOMATION

Less repetition.
More room to think.

Automation for routine memos, objective tracking and source-data conversion, with departmental recognition for the improvements.

Behind the work

The challenge

Everyday administrative and data-preparation tasks could take days, delaying the analytical work that followed.

My contribution

I automated recurring steps in memo preparation, objective tracking and data conversion. Selected workflows now take minutes.

Recognition

The department recognised these improvements with an award for operational efficiency.

A SMALL DEMONSTRATION

Find the pattern.
Focus the review.

Different descriptions can refer to the same supplier. Try a simple example of standardising records and grouping them for review.

Illustrative logic with synthetic records. This is a portfolio demonstration, not the Excel add-in or Xvert.

SAMPLE TRANSACTION DATA6 source records
Synthetic supplier transactions
DescriptionReferenceAmount

Inspect the supplier names, then group the matching patterns.

02 / PEOPLE MAKE IT WORK

200+

staff trained.
Practical skills, passed on.

A tool only matters
when people
can use it.

I train federal government staff in data analysis and AI adoption, connecting new capabilities to the work in front of them.

My approach starts with the task: understand the process, identify the repetitive steps, and make the new way of working easier to apply.

01

Understand the work

Start with the actual process and where effort is being lost.

02

Make it practical

Build tools and instruction around everyday tasks.

03

Help people adopt it

Connect technical capability with usable skills and working habits.

03 / RESEARCH & CURIOSITY

Why good ideas
don’t always stick.

My interest in adoption extends beyond technology—to the incentives, trust and investment decisions that shape whether people participate.

Invited to present
University of Groningen, Netherlands

CO-AUTHORED RESEARCH

The Hold-Up Problem as a Barrier to Green Industrial Symbiosis

An Agent-Based Model of Sunk Costs, Trust, and Institutional Design

A NetLogo model examining how investment barriers, market conditions and institutional arrangements affect cooperation between firms.

4,320Simulation runs
6Parameter dimensions
Read the extended abstract

THE PERSON BEHIND THE WORK

Analytical by training.
Practical by instinct.

My background spans tax investigation, financial analysis and energy economics. Over eight years in regulatory operations have taught me to ask careful questions, work through messy data and make findings useful.

Today, I bring that same mindset to building tools, redesigning workflows and helping teams adopt AI.

MSc Energy Studies · University of IbadanBSc Economics · Afe Babalola UniversityAssociate Member · Chartered Institute of Taxation

LET’S MAKE WORK BETTER

Have a problem
worth solving?

mikefaniyi@gmail.com Download my CV

Interested in AI adoption, operational analytics and workflow improvement opportunities. Open to relocation to Auckland.