Harnessing the power of smart factories for future growth

In previous posts, we’ve outlined brand and speed as differentiators that can help FMCG (Fast Moving Consumer Goods) companies gain momentum and generate revenue growth. In this, the third installment, the key differentiator revolves around creating a better, more efficient supply chain through smart factories.

Build better processes with smart factory concepts

Big FMCG players have established production and supply-chain networks. The highest levels of productivity, global reach, consistent quality, and fast, accurate delivery will remain important post-COVID. To stay competitive, FMCG companies must identify the next level of productivity gains and reduce the costs of production, supply chain and back-office processes.

The smart factory concept addresses this by combining technologies like IoT, AI, software automation, robotics, advanced analytics and big data to deliver an understanding of the true status and performance level in their operations at any point in time.

However, a smart factory is not a one-size-fits-all or an off-the-shelf solution. A smart factory is created by a unique set of investments in the most appropriate set of enabling technologies for a company’s specific situation, performance challenges and business objectives.

Boundless possibilities

A smart factory predicts events with greater accuracy (market demand, equipment failures, inbound delivery times, etc.) and helps drive improvements in productivity, quality, inventory and operating costs.

It tracks production status and downtime events in real time, enabling operating teams to adapt and optimize production schedules to maximize efficiency and prioritize maintenance activities.

Reduce downtime

A smart factory can accurately measure and track energy consumption using sensor technology – use findings to adapt production schedules, working practices and maintenance/asset replacement as levers to cut energy costs sustainably.

Track and trace

It can trace inbound supply chain shipments in real time and analyze historical performance to build predictive models that enable inventory levels to be reduced with confidence.

It can use AI-enabled natural language processing to identify patterns in non-conformance events to accelerate root-cause analysis and reduce defect rate and investigation costs.

A smart factory reduces downtime by 20%-50%1 with predictive maintenance while reducing costs by 5%-10%. It uses additive manufacturing (3D printing) of critical spare parts as a major advantage2.

It uses data analytics to measure and track material usage and consumption to accurately identify sources of loss — which enables corrective action to be taken to reduce waste and material loss.

Some smart factories use AI-enabled image recognition technology to conduct fast and accurate visual inspections and measurement activities in confined spaces or hazardous areas.


The most visible element of a smart factory probably is the digital workplace on the shop floor. It integrates data into mobile devices from systems that previously operated in isolation, like ERP, PLM and MES. The right data, delivered to the right people at the right time to inform better decisions, enables collaboration and remote work — and saves cost by simplifying processes.

Supervisors can record incidents on a mobile device as they occur, enabling automatic workflows, populating performance dashboards and enabling trend analysis to identify systematic problems. Artificial intelligence algorithms can even recommend a course of action.

A smart factory is created by a unique set of investments in the most appropriate set of enabling technologies for a company’s specific situation, performance challenges and business objectives.

Other considerations

When building out new technologies to help your factories compete in a virtual world, there are pitfalls to avoid:

  • Thinking it’s all about the technology
  • Over-analyzing and designing, rather than moving quickly into pilots, trials and experiments to test new ideas and get feedback
  • Expecting technology investments to deliver overnight success
  • Failing to involve your people adequately in defining challenges and shaping/evaluating solutions

We recommend using a solid framework for technologies, processes and roles that allows for a flexible, stepwise and parallel — yet purposeful — approach.

For a more in-depth review of the potential growth prospects for the FMCG industry in today’s dynamic business environment, please read the Atos white paper, “How FMCG can win in a virtual world: Grappling with the new retail reality.”

1. https://www2.deloitte.com/us/en/insights/focus/industry-4-0/using-predictive-technologies-for-asset-maintenance.html#endnote-sup-16

2. https://www.sciencedirect.com/science/article/pii/S0925527318303785

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About Lee Fosbrook
Consulting Partner, Regional Leader - Northern Europe
Lee is an experienced manufacturing and supply chain expert with over twenty-five years of strategy, operational improvement and digital transformation experience on an international scale across a broad range of manufacturing sectors including consumer products, aerospace, engineering and automotive. He has held senior roles in international consulting firms and large manufacturing companies including a period as interim-COO for a global engineering firm. Lee provides pragmatic guidance and expertise on how to leverage digital technologies.

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About Dr. Matthias J Förster
Partner, Vice President and Global Consulting Industry Leader, Manufacturing
As Global Consulting Industry Leader for manufacturing, Matthias Förster brings to life multimillion-euro implementations of artificial intelligence, analytics, software factories, automation, robotics and customer experience solutions. Before Atos, Matthias held leadership positions at Computer Sciences Corporation, IBM and PricewaterhouseCoopers. He has decades of experience advising large organizations on how to use technologies to improve business performance and was, in fact, first appointed partner in July 2000. Matthias earned a master’s degree in Industrial Engineering and a doctorate in Economic Sciences from Berlin University of Technology, and today he lives near Frankfurt, Germany.

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