Case Library
Real decisions, worked through quantitatively.
Selected analytical case studies and demonstrations from Toledah's Business Analytics & Optimization practice.
Should an EdTech Platform Raise Its Prices?
How quantitative pricing analysis identified a 36.7% contribution opportunity without simply raising the headline price
Why the Most Profitable Product Isn’t Always the Best Product to Make
Consider a Nigerian woven-packaging manufacturer producing four types of bags: Standard 50kg rice sacks Printed 50kg rice sacks Fertilizer bags Animal-feed bags Each product earns a different contribution per bag. Each also consumes different amounts of the factory's scarce resources. The management problem is therefore not simply: “Which product makes the most money?” but, “Given the resources we have available, what combination of products produces the greatest total contribution?”
How Much Should a Manufacturer Produce When Future Demand Is Uncertain?
A PP woven sack manufacturer had to decide how much to produce for September. The forecast was only the beginning of the analysis.
How Do I Know Which Promotion Will Actually Make Me Money?
A customer promotion experiment revealed that the biggest discount wasn't the most profitable option.
Should You Hire More Employees or Pay Your Existing Staff More?
A growing business eventually runs into an uncomfortable question: Do we need more people, or can the people we already have simply work more?
How Should a Distributor Spend ₦2 Million on Inventory?
A business owner has ₦2 million to restock. What should they buy?
.png)
When Everyone Has a Theory, Test It. (How a manufacturer can use experimental data to find the real cause of production defects)
A manufacturer produces about 120,000 units every month. Recently, something has gone wrong. The percentage of defective products has risen to around 8%. At that rate, approximately 9,600 units are being rejected every month. At an estimated cost of ₦85 per defective unit, that represents roughly ₦816,000 in direct monthly waste before considering rework, delays, customer complaints and other consequences.