
COMMENT ON THIS ARTICLE While beer has been known to diminish intellectual - and other - performance, business intelligence (BI) is being used to boost an international brewer's performance and corporate smarts. Labatt Breweries of Canada has created an enterprise-wide business intelligence (BI) system that helps identify and respond more effectively to customer needs . The new BI system has also helped the beer manufacturer enhance the accuracy and timeliness of strategic decisions such as: what kind beer to produce, how to package it, for what demographic or market, and at what time of the year. At the core of Labatt's new environment is technology from Ottawa-based BI and performance management software vendor, Cognos Inc. The company reviewed several enterprise BI vendors' products before settling on Cognos. However, even before Cognos technology could be introduced into the project, Labatt needed to make major structural changes, specifically around its data gathering, reporting and analysis model. "Integration" and "consistency" were the magic words – the driving force – behind this entire exercise, according to Mike Ali, change management manager at Labatt. Ali said there was previously a disconnect between Labatt's data management processes and its corporate structure, which has changed significantly over the years. In the past, he said, the company was required to produce beer in the province it was sold, so data was "bounded in provincial silos." Over time, however, as those regulations disappeared, Labatt's data and processes needed to change as well, Ali said. The Labatt executive noted that his company has grown well beyond its Ontario roots. Today, it produces 50 beers for local and international markets, with Brazil being one of the company's larger markets. This dramatic expansion – and accompanying changes in Labatt's corporate structure – called for fundamental changes in its data management processes as well. The challenge, Ali said, was to create one set of tools and technologies for the organization as it moved from a provincial to a regional to a national model. So in recent years, the company devoted a great deal of time and resources to building up consistent data structures that support multiple views across various functions and subject areas. |