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Modern BI: From Reporting to Predictive

Modern BI: From Reporting to Predictive

Over the last few months, I’ve seen more and more examples of organizations moving to modern analytics approaches based on real-time, actionable data, with greater use of predictive technology.

For example, Julian Pimm-Smith of Pret a Manger gave a great overview of the company’s analytic projects at a recent UK Innovation Forum event in London.

Since 1986, Pret A Manager restaurants have proudly provided handmade, natural food prepared each day in the kitchens attached to every store.

The company is headquartered in the UK but has over 350 stores around the globe, including New York, Boston, Chicago, Paris, Hong Kong, Shanghai, and Dubai, serving over 300,000 customers every day.

Pimm-Smith explained that the company is working on three main initiatives. He started by emphasizing the critical importance of what he called “boring reporting”:

The company uses SAP WebIntelligence to deliver real-time sales performance figures directly to front-line employees on mobile devices. For example, operations managers can access maps with the live status of stores, showing up-to-the minute sales compared to the prior day or week, and drill down to see detailed sales for every item.

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Store managers also get a full profit and loss report for every shop as soon as they close their day, and a detailed financial breakdown for the week’s operations. This helps them quickly identify potential areas of concern and fix them before they become real problems.

The second analytics initiative is a new predictive analytics project, aided by SAP consulting partner itelligence.

Traditionally, the morning production at each Pret store aims to create roughly 60% of the salads, sandwiches, and soup that will be needed for the day. The remaining 40% is freshly-made during the afternoon, based on demand. This helps ensure that customers get the products they want while minimizing waste — but the process requires deep expertise from the store managers to manage the production of the right quantities of food at just the right time.

The company is now turning to SAP predictive analytics to operationalize the process.;

 



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