“Counting is hard.” That’s kind of a running joke in our office. Of course, our eAlchemy team members have written hundreds of thousands of lines of code in our 10 years of building business applications that help our clients make data-driven decisions. The code and formulas we write can execute all kinds of equations and even predict outcomes based on complex and dynamic data sets. Counting, in that context, doesn’t seem hard.
“Every single piece of the supply chain has a friction point when your forecasts aren’t accurate. When your numbers aren’t right, you end up blowing your margin.”
However, counting isn’t always as simple as it should be. Especially when you are a global Fortune 500 retail giant with several brands, dozens of product lines, and thousands of apparel items for sale in hundreds of countries. In our most recent case study, we cover how we helped one of the world’s largest retail apparel companies create an automated reporting system and standardize how the company “counts” the number of apparel items in the market at any time — up to two years in advance.
And in so doing, we dramatically improved the accuracy of a report that the company’s global planning team uses to forecast and make purchase decisions on materials — months before apparel shows up on store shelves.
“Every single piece of the supply chain has a friction point when your forecasts aren’t accurate,” said our client’s director of product management. “When your numbers aren’t right, you end up blowing your margin.”
The end result of the project:
- A report that used to take 3-5 days for one person to build and run can now be completed in five minutes.
- Between our client’s different groups, the estimated time savings that the automated report saves is the equivalent of more than 10 full-time jobs.
- Business analysts who were burdened with previous report tool could invest more time in high-value analysis. Our client contact said the tool actually improved employee satisfaction, and helped the company retain key talent.
- This project is expected to return more than 15 times the invested value in the first three years of use.
- The new automated report is expected to improve accuracy from 65% to 95% within two years.
- The methodology for how to count products and make related planning decisions was standardized across brands and regional groups.
And also important for us, the new tool made for one happy client:
“eAlchemy really understands retail — and that was a big deal for us. There are a lot of developers who write code, but there aren’t many that know the retail business like they do.”
Read the full case study about the project here.
