daisee Harmonee

Artificial intelligence for supply chain optimisation

Why Harmonee?

Sales Forecasting
Daisee Harmonee accurately predicts sales ahead of time for each product, for each store location based on a range of historical factors. It combines structured data, such as sales, with external data such as weather and calendar.
Inventory Optimisation
Daisee Harmonee monitors inventory and opportunity costs, ensuring that shelves are always stocked with enough of the right products. This minimises loss of perishable while maximising sales and customer experience.
Pricing and Promotions
Daisee Harmonee also determinines the best prices for each product at a given point in time, based on supply and demand. This can be used by companies to identify opportunities and administer promotions at the right time.

Case Study

Challenge

Fresh Flowers Group needed better ways to forecast supply and demand. This was particularly challenging given the perishable nature of its products and the extreme volatility in demand (driven by various calendar events such as Valentine’s Day).

Approach

We fed in historical point-of-sales data and augmented it with significant calendar events (e.g. Chinese holidays). This model was tested with 3 months of hold-out data, comparing losses from overstock/understock scenarios.

Result

The insights generated by daisee Harmonee allowed business rules to be created in order to make predictions about future stock purchases. AI prediction gave significantly better results than a traditional Excel regression method

Peter Lynch
Fresh Flower Group
CEO

“There were peaks and troughs
in our business that I did not realise were there. We had totally missed a couple of
peak periods.”