Case study:

Let the data do the bidding

Wool is bought at multi-day auctions with price variations. This complexity was sure to yield patterns, but how can we take advantage of them?

Case study:

Let the data do the bidding

Wool is bought at multi-day auctions with price variations. This complexity was sure to yield patterns, but how can we take advantage of them?

The challenge

Standard Wool is a multi-million pound group of companies that together make up one of the world’s leading wool trading businesses, with customers in more than 30 countries.

Standard Wool wanted to understand the best time of year, best day and even the best time during the day to buy their wool. This meant they could remain competitive and offer lower prices to their customers.

Our first task was the collection of multiple data points from over 90 spreadsheets and other sources. We needed to add not just the time of purchase, but also transport costs and processing factors to make sure the model was robust.

The solution

SAS was an ideal technology for analysing large quantities of historical data to identify trends. It enables our analysts to find quick answers to long standing questions.

The result

Standard Wool now make confident decisions using reliable data. The buyers now have visual dashboards, allowing confident buying decisions. Data is added after every auction keeping the dashboards continually relevant and up to speed.

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