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⚠ Job Scam Alert. Bain has become aware of scams involving false offers of Bain & Company employment. These scams use imposter sites, social media pages, and spoofed emails claiming to be Bain. We never conduct interviews via instant messaging or require candidates to purchase products, services, or process payments on our behalf. Be especially vigilant of providing personal information outside of this website.
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        Back to All Case Studies

        The largest baker in the country, Grupo Bimbo US, cuts waste by 50%

        The largest baker in the country, Grupo Bimbo US, cuts waste by 50%

        Grupo Bimbo produces more bread than any other company on earth, and until recently, far too much of it was being thrown away. The level of food waste was twice that of competitors and the company had come to see the problem as “persistent and unrelenting.” Their US division engaged Bain to build a more accurate ordering system.

        Digital teams assembled to staunch the physical waste

        The company’s production errors were largely due to outdated forecasting and ordering systems. To build better ones, Bain contributed designers, engineers, and data scientists to help Bimbo take a technological leap forward, and consultants to help it redesign its frontline worker experience. (Which workers were grateful for.)

        Digital teams assembled to staunch the physical waste

        The company’s production errors were largely due to outdated forecasting and ordering systems. To build better ones, Bain contributed designers, engineers, and data scientists to help Bimbo take a technological leap forward, and consultants to help it redesign its frontline worker experience. (Which workers were grateful for.)

        AI, Insights, & Solutions (AIS)

        Data scientists helped the client build far more accurate forecasts. They identified critical data, built and tested an algorithm, and iterated upon the prototype until it exceeded expectations.

        Digital teams assembled to staunch the physical waste

        The company’s production errors were largely due to outdated forecasting and ordering systems. To build better ones, Bain contributed designers, engineers, and data scientists to help Bimbo take a technological leap forward, and consultants to help it redesign its frontline worker experience. (Which workers were grateful for.)

        General Consulting

        Consultants helped diagnose the issue of waste and identify solutions—both technical and human. They then helped redesign the order process to be simpler and faster, launched pilot programs, scaled them, and retrained frontline workers.

        Digital teams assembled to staunch the physical waste

        The company’s production errors were largely due to outdated forecasting and ordering systems. To build better ones, Bain contributed designers, engineers, and data scientists to help Bimbo take a technological leap forward, and consultants to help it redesign its frontline worker experience. (Which workers were grateful for.)

        Research & Data Services (RDS)

        Research and Data Services utilized a wide range of external data source information to provide operating models of key players in the bakery market, market research reports on the bread production industry and analyst reports on recent acquisitions. A global team of researchers from North America, India and EMEA collaborated to bring the right information to the case team.

        Digital teams assembled to staunch the physical waste

        The company’s production errors were largely due to outdated forecasting and ordering systems. To build better ones, Bain contributed designers, engineers, and data scientists to help Bimbo take a technological leap forward, and consultants to help it redesign its frontline worker experience. (Which workers were grateful for.)

        Technology Solutions Group (TSG)

        Engineers conducted a technical discovery and built the new ordering system. They then trained the client’s internal IT team to manage the ongoing development with a vendor.

        Digital teams assembled to staunch the physical waste

        The company’s production errors were largely due to outdated forecasting and ordering systems. To build better ones, Bain contributed designers, engineers, and data scientists to help Bimbo take a technological leap forward, and consultants to help it redesign its frontline worker experience. (Which workers were grateful for.)

        • AI, Insights, & Solutions (AIS)

          Data scientists helped the client build far more accurate forecasts. They identified critical data, built and tested an algorithm, and iterated upon the prototype until it exceeded expectations.

        • General Consulting

          Consultants helped diagnose the issue of waste and identify solutions—both technical and human. They then helped redesign the order process to be simpler and faster, launched pilot programs, scaled them, and retrained frontline workers.

        • Research & Data Services (RDS)

          Research and Data Services utilized a wide range of external data source information to provide operating models of key players in the bakery market, market research reports on the bread production industry and analyst reports on recent acquisitions. A global team of researchers from North America, India and EMEA collaborated to bring the right information to the case team.

        • Technology Solutions Group (TSG)

          Engineers conducted a technical discovery and built the new ordering system. They then trained the client’s internal IT team to manage the ongoing development with a vendor.

        Background

        You don’t often think about how supermarket bread, bagels, and donuts get from an oven to store shelves, but it’s a fascinating and complex process involving a network of salespeople, distribution centers, and delivery trucks that must operate in tight coordination. If any piece of the distribution network falls out of sync, you can get a warehouse overflowing with rapidly expiring loaves. This is the situation Bimbo Bakeries USA (BBU) found itself in, and had in fact factored this cost into its model.

        But finally, leaders decided the miscalculations had gone on too long. It was becoming an economic problem, an environmental problem, and a cultural problem, because workers would have to put in extra time away from their families to deal with incorrect forecasts—to the tune of 75,000 excess hours per week across the company.

        Tony Gavin, executive vice president at BBU, hired Bain to help them stem the loss.

        The plan

        BBU’s executive team issued a bold challenge to the company, and to Bain: to create a “perfect” order system that would reduce waste while still helping them grow. This set things into motion and led leadership to realize that such a complete transformation would require starting on the loading dock, asking employees what they were experiencing. “Our frontline associates … they had the answers that we just didn’t have,” says Morgan Smith, vice president, BBU.

        Frontline managers were excited to be involved and relayed two issues: The order forecast was consistently inaccurate, and the aging food ordering software made it easy to do the wrong things and difficult to do the right things. As a result, workers mostly worked off their intuition.

        • What were BBU’s short-term and long-term goals?

        • What were the proximate and root causes of the waste?

        • What were all the components of the ordering system?

        • What were frontline employees experiencing?

        • What approach would yield results in under a year?

        • What talent, expertise, or technology was missing, and needed?

        The approach

        An initial search revealed that there was no off-the-shelf software that solved this particular problem, so the Bain team set about helping BBU assemble the talent necessary to build their own. They started by using Bain Micro-battles System® to assemble a team of consultants, data scientists, design strategists, engineers, venture ecosystem experts, and more.

        In just two and a half months of working directly with employees in distribution centers, the Bain team built a tool that could forecast 35% more accurately. At the same time, Bain teams designed a new ordering tool prototype with a friendlier interface that reinforced the right behaviors when people inputted orders. Both teams rolled out the new solution at three sites and spent months monitoring progress and effectiveness, making hundreds of changes to get it right.

        The results

        At the outset, BBU had hoped to cut waste by 20% without compromising growth. In the end the changes cut waste by 50% without impacting growth, and improved people’s lives in the process. “I get emotional thinking about it,” says Troy Rudd, market sales leader and frontline manager at BBU. “It changed my life dramatically; all those individuals have more time with their families, and they make more money to support them.”

        50%

        less waste without compromising growth

        50%

         less time needed to make and adjust orders

        ∞

        incalculable environmental and societal benefits

        It takes a global village.

        Bain teams all over North America participated.

        North & Latin America

        • Atlanta
        • Austin
        • Bogota
        • Boston
        • Buenos Aires
        • Chicago
        • Dallas
        • Denver
        • Houston
        • Los Angeles
        • Mexico City
        • Minneapolis
        • Monterrey
        • Montreal
        • New York
        • Rio de Janeiro
        • San Francisco
        • Santiago
        • São Paulo
        • Seattle
        • Silicon Valley
        • Toronto
        • Washington, DC

        Europe & Africa

        • Amsterdam
        • Athens
        • Berlin
        • Brussels
        • Copenhagen
        • Dusseldorf
        • Frankfurt
        • Helsinki
        • Istanbul
        • Johannesburg
        • Kyiv
        • Lisbon
        • London
        • Madrid
        • Milan
        • Munich
        • Oslo
        • Paris
        • Rome
        • Stockholm
        • Vienna
        • Warsaw
        • Zurich

        Middle East

        • Doha
        • Dubai
        • Riyadh

        Asia & Australia

        • Bangkok
        • Beijing
        • Bengaluru
        • Brisbane
        • Ho Chi Minh City
        • Hong Kong
        • Jakarta
        • Kuala Lumpur
        • Manila
        • Melbourne
        • Mumbai
        • New Delhi
        • Perth
        • Seoul
        • Shanghai
        • Singapore
        • Sydney
        • Tokyo

        It takes a global village.

        Bain teams all over North America participated.

        • Boston
        • Chicago
        • Dallas
        • Mexico City
        • New York
        • San Francisco
        Further Reading

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