Case Study

Specialty retailer improves forecast accuracy 50%+

Specialty retailer improves forecast accuracy, reduces overstock, and reduces time to forecast with Ikigai's core Demand Forecast solution and New Product Introduction (NPI) module

Customer overview

$1B+

annual revenue

10,000+

unique SKUs

1,500+

stores

Business challenge

Accuracy of retailer's existing forecasts was sub-optimal

Improving forecasts was made difficult by complex business hierarchies, shifting customer behavior, and high number of SKUs

Retailer had been using spreadsheet-based forecasts, which were slow and inflexible

These highly manual forecasts limited the business’s ability to adapt to market conditions in real-time

Retailer had no historical data for new products and new stores introduced each season

With limited data to inform traditional forecasting methods, this retailer was highly uncertain on how to plan for critical SKUs

Ikigai’s solution

Core Demand Forecasting solution:

Built best-in-class demand forecasting using both historical & live data to continuously discover patterns
Incorporated external event data to refine forecast precision
Retailer now able to produce accurate, auditable, and adjustable forecasts that update weekly

New Product Introduction module:

Modeled similarities between existing SKUs & new products to predict demand for new releases without direct historical data

Key outcomes

50%

increase in forecast accuracy

15%

reduction in overstock

80%

decrease in time to forecast

“Our goal is to achieve the most accurate forecast possible – which is why we love working with Ikigai’s aiCast. Right out of the box, it outperformed our existing solution.” - VP Supply Chain