Victor Chidera Ugwu
Supply Chain Analyst · Excel & AI Automation Consultant · Data Educator
Helping professionals and businesses make smarter supply chain decisions using Microsoft Excel, descriptive statistics, and practical analytics.
Bridging the gap between theory and the shop floor.
DataChain Analytics empowers aspiring and experienced professionals with practical Supply Chain Analytics skills using Microsoft Excel, descriptive statistics, automation, and real business scenarios.
Our mission is to bridge the gap between theory and workplace application through hands-on learning — every dataset, formula, and dashboard mirrors what an analyst actually sees at work.
See how the bootcamp is structured →Two tools. Applied to real supply chain problems every week.
The bootcamp deliberately stays lean — depth in Excel and statistics beats breadth across a dozen platforms nobody masters.
Microsoft Excel
The daily workbench for every session — from procurement logs to inventory ledgers and supplier scorecards.
- PivotTables for supplier lead-time and cost breakdowns
- AVERAGE, STDEV and COUNTIF formulas for KPI summaries
- Conditional formatting & data validation for exec-ready reports
- Structured datasets modelled on real procurement & inventory sheets
Descriptive Statistics
The analytical lens that turns raw order and delivery data into supplier and inventory decisions.
- Mean, median, mode, range and variance on supplier lead times
- Standard deviation and IQR to flag delivery outliers
- Inventory Turnover Ratio (ITR) and Days Inventory Outstanding (DIO)
- On-Time Delivery Rate (OTDR) scoring across supplier regions
Seven weeks, one connected chain of skills.
Every session below is documented from the actual bootcamp materials — study notes, live datasets and reporting exercises used with Cohort 1.
Kickoff & the 7-Week Roadmap
Skills covered
Learning objectives
Understand the full 7-week arc from foundations & analytics thinking through to advanced reporting, and what "beginner to intermediate, live via Google Meet" actually looks like week to week.
Business application
Setting a realistic learning plan that mirrors how a working analyst actually progresses — from asking the right questions to publishing a report.
Key takeaways
- Excel + statistics form the entire toolkit — no unnecessary platforms
- Structured, sequential roadmap from Week 1 to Week 7
Procurement, Inventory & Logistics Overview
Skills covered
Learning objectives
Break down the three core pillars of supply chain operations — procurement, inventory and logistics — and the distinct dataset each one generates.
Business application
- Identifying the most reliable suppliers and how to measure reliability
- Checking whether current vendor pricing is actually competitive
Key takeaways
Procurement is the process of finding, evaluating and purchasing goods at the right price, place and time — and every stage produces analyzable data.
Supplier Lead Time & Descriptive Statistics
Skills covered
Learning objectives
Apply the full set of descriptive statistics to a live supplier lead-time dataset spanning order dates, regions, quantities and delivery windows.
Business application
Turning raw purchase-order records into a clear read on which suppliers and regions are consistently slow, fast, or unpredictable.
Key takeaways
A single well-built PivotTable can surface outlier suppliers that a raw spreadsheet hides in plain sight.
Inventory Turnover & Supplier Performance KPIs
Skills covered
Learning objectives
Calculate Inventory Turnover Ratio and Days Inventory Outstanding from unit cost, opening and closing stock, then build a supplier scorecard using On-Time Delivery Rate.
Business application
- Flagging slow-moving SKUs with high DIO days
- Ranking suppliers on OTDR to guide sourcing decisions
Key takeaways
Two connected datasets — inventory movement and supplier delivery — summarize into one decision-ready KPI table.
Advanced Excel for Supply Chain Reporting
Skills covered
Learning objectives
Use advanced conditional formatting and data validation to clean, transform and present operational data from procurement, warehousing, transportation and customer orders.
Business application
Building reports that management can interpret at a glance — the analyst's job isn't just collecting data, it's presenting it clearly.
Key takeaways
Advanced Excel is what turns daily operational noise into a report a decision-maker can act on in minutes.
Sixteen capabilities, one continuous chain.
By the end of the bootcamp, participants can:
Transform raw business data into actionable insights.
Build interactive Excel dashboards.
Clean and prepare datasets.
Perform descriptive statistical analysis.
Create executive reports.
Support supply chain decision making.
Measure operational performance.
Communicate insights effectively.
Victor Chidera Ugwu
Founder, DataChain Analytics
Teaching analytics the way it's actually used at work.
Victor Chidera Ugwu designed the Supply Chain Analytics Bootcamp around one idea: analytics only matters when it's applied to a real business scenario. Every dataset in the program — supplier lead times, inventory ledgers, procurement logs — mirrors what a working analyst opens on a Monday morning.
As a Supply Chain Analyst, Excel & AI Automation Consultant and Data Educator, he runs the bootcamp live, week by week, alongside his consulting work in 3PL logistics and e-commerce analytics.
- Supply Chain Analyst
- Excel & AI Automation Consultant
- Data Educator
- Founder, DataChain Analytics
Supply Chain Analytics Bootcamp — Cohort 2
Learn practical Microsoft Excel for Supply Chain Analytics through hands-on projects, descriptive analytics, and real business case studies — the same format that shaped Cohort 1's journey above.
Ready to build practical Supply Chain Analytics skills? Secure your spot today or send a DM if you have questions before enrolling.
Victor Chidera Ugwu
Supply Chain Analyst · Excel and AI Automation Consultant · Data Educator