by Stuart Finlayson

Fosters streamlines data management

Dec 31, 2010
Data MiningData WarehousingERP Systems

At the last count, brewing giant Foster’s boasted 238 products in its ever expanding portfolio — although, interestingly, it no longer owns the eponymous ‘amber nectar’, made famous by those 1980s TV ads featuring Paul Hogan, in any market other than Australia.

Famous for its beer brands, which include VB, Carlton Draught, Crown Lager and Cascade, the company also owns a plethora of wine, spirit and soft drink brands, including Penfolds, Lindemans and Cougar Bourbon.

A series of mergers and acquisitions by Foster’s in recent years has resulted in the group now having to manage a dizzying array of more than 350 IT systems. Senior enterprise architect at Foster’s Group, Michael Davis, said the situation left the company with information stored “all over the place” and the resulting inefficient business processes meant that it wasn’t really getting the most out of the businesses it was combining.

It also proved to be hugely costly for the company in terms of its annual IT budget.

“To put it into perspective, we were spending around 4 per cent of our net revenue on IT, which is obviously not good,” Davis said.

The startling statistic prompted the enterprise architect group at Foster’s, led by Davis, to devise a strategy and plan out a roadmap to address the issues.

The project was built in several streams — supply and demand, procurement, fulfilment and so on. Considerations such as product lifecycle management, the transformation of the company’s interaction with its customers and the consolidation of 60-odd data centres were paramount in the discussions that followed.

Another consequence of the company’s merger and acquisition activities was that it inherited five different enterprise resource planning systems, so another priority for Davis and his team was to consolidate those down to a single system across the enterprise.

To drive to program forward in its initial stages, the team worked to gain a common understanding of the information management in the organisation; evaluating the capabilities and aligning them correctly to execute its information management strategy.

“Gaining support for data quality was also critical for us in this project,” Davis recalled. “And how you use component-based architectures for data quality, thus creating reusable assets.”

Davis realised the company would not be ready to invest in information management without a clear understanding of what the project aimed to achieve. And, with a disparate group of brands all having come together under the one banner, he was mindful of potential problems with how his ideas would be interpreted.

“The question I asked when I came to Foster’s was: ‘Do the people I work with understand what information management is?’ I was working with different groups and I had the sense that they were all talking different languages.” It proved to be so. Different terms within the organisation meant different things to different people. It meant aligning semantics from an organisational perspective, using a framework to communicate the capabilities and clarify the scope.

“Not many organisations have a good picture of what they has (in terms of IT systems),” Davis said. “If you don’t, the best place to start is your procurement group — find out what it have under licence, as you can almost guarantee that nobody else will be able to tell you.”

It’s also necessary to build a case that describes the benefits of closing the gaps in your current capabilities. Discuss the impact of the return on investment with the project sponsor.

“You need to find the right people within your organisation,” Davis said. “If you simply say, ‘we need to improve data quality’ nobody’s going to listen; you need to discover the context of why data quality is important and communicate that to those who you wish to help you with the project.”

In all likelihood, there will already be people who are concerned because they are responsible for the impact of poor quality data. They may have service level agreements or key performance indicators (KPIs) that are continually impacted by poor quality data.

Project leaders need to calculate the quantitative benefits, identifying hard cost savings where possible and look for positive impacts on KPIs.

A final ace up the sleeve for anybody trying to secure approval for a project, Davis said, is to look for legal and statutory risk.