Deloitte: The Key to Optimising Holiday Supply Chains

Tim Gaus, Principal and Smart Manufacturing Business Leader at Deloitte Consulting will be well known to regular readers of Manufacturing Digital.

Featured in several of our magazines, Tim has over 25 years supply chain experience and works at Deloitte to drive value chain optimisation using emerging technologies.

Tim has led several supply chain transformations, spanning supply chain strategy, manufacturing optimisation, supply chain planning, inventory optimisation, operating model design and operational excellence for domestic and multinational corporations.

He helps clients use the Internet of Things (IoT) to drive convergence of the IT/OT space and harness edge to cloud – driving the real time insights that create whats often termed the “Factory of the Future.”

In the run-up to Christmas, he talked to us about how software-defined manufacturing can be used to shore up and optimise holiday supply chains.

Who’s your biggest inspiration and the best thing about working at Deloitte?

It’s funny, but I’m inspired by my kids. Their curiosity, they technical adeptness at a very young age and the love of create new things give me a lot of hope.

They truly inspire me to push the boundaries and help create the best future for them. 

And by far the best thing about working at Deloitte and frankly the reason that I’ve stayed with the consultancy, are the people.

It’s energising to come in every day and work with smart, innovative and driven colleagues. In tough times and in good ones, it’s the people of Deloitte that shine through for me. 

Can you give us a summary of the supply chain changes that consumer goods manufacturers must navigate during the holidays? 

Supply and demand inventory is always top of mind for consumer goods manufacturers during the holiday season and previous years have shown that holiday inventory shortages wreak havoc on retailers’ bottom lines, forcing organisations to adapt.

That said, we can’t look at these peak moments in a silo. The taxing holiday season is further exacerbated by an already challenging global supply chain disrupted by geopolitical tensions, natural disasters, shipping routes being shut down and much more. We recently released our 2025 Manufacturing Industry Outlook which found that while supply chain challenges have eased since the height of the COVID-19 pandemic, pressures remain high.

Over 35% of the manufacturers we surveyed cited transportation and logistics costs as a primary business challenge in the third quarter of 2024. While these challenges are expected to persist in the coming year, consumer goods manufacturers are looking to boost productivity, support innovation and move faster—with more agility—to meet the demands of everyday in addition to intense periods like the holidays. 

What solutions do you recommend to optimise supply chains and enhance efficiency in response to these changes? 

Across the industry, we’re seeing a lot of success among manufacturers that focus on balancing optimised cost and resilience versus those that focus on resilience alone. It’s no longer enough to just hold on tight and brave the storm.

Techniques such as diversifying sources, pursuing mergers and acquisitions, enhancing partnerships and building internal capabilities are helping some companies strike this balance. 

It’s priority that organisations continue investing in digital tools and emerging technologies, as they can enable advanced manufacturing techniques, better collaboration with suppliers, simulation and enhanced visibility. Of course, a transformation doesn’t just happen overnight.

It starts with an organisation assessing where it currently stands in terms of data quality, contextualisation and validation, the human side of its operations and how its existing workforce will work with the new technologies, amongst other things.  

Why is it critical that factory floor technology investments are coupled with software investments?

Many manufacturers have invested in technology on factory floors – including AI, sensors and advanced data management – to enable more regular quality checks. The next phase of investment will need to be in software to work with the floor tech.

Much like it revolutionised other industries, software will soon reshape the future of manufacturing, solving the challenges of inflexibility and sluggishness found in traditional techniques.

Businesses will begin to rethink and redesign their production lines, ushering in an era of software defined manufacturing. 

For manufacturing to be truly software-defined, investments need to be made in software that can more accurately forecast supply trends, both macro and down to the individual consumer, using the improved data and tools found on the floor.

This will allow manufacturers to change the design and operation of their manufacturing lines without having to change machinery. Further, it provides a new way to integrate and orchestrate data, systems, and the workforce by utilising dynamic software systems or platforms to control manufacturing hardware. 

The days of investing separately in factory and business software should be left behind.

Instead, it’s important that leaders think about the interplay between robotics and smart sensors that comes with the integration of purchased and custom-built software. It’s all about thinking holistically to get to the scalable outcomes we all want. 

Accurate demand forecasting is a massive advantage for consumer goods manufacturers in general, especially during the holidays. What software investments can make this a reality for manufacturers?

To accurately answer this, we need to take a step back and look at how the consumer manufacturing industry has evolved. In the past, the consumer industry operated on economies of scale. This meant mass production, mass distribution and mass marketing was needed to cater to a relatively homogeneous market with few choices. Today, however, consumer goods manufacturers are faced with diverse consumer profiles and a fragmented tech-driven market, requiring them to transition from a mass to micro approach. This pivot is driving organisations across the industry to transition from a supply-focused to a demand-driven model that supports strategies that can prioritise relevance for specific consumer groups. 

Fortunately, modern technologies like AI can enable hyper-nuanced consumer demand forecasting. By embedding granular customer insights into every facet of the value chain, AI helps brands progress from a mass-supply planning approach to a demand-driven model.

In the evolving consumer landscape, AI is more than a technological leap; it’s a vital part of the strategic toolkit for consumer companies. AI helps equip businesses to explore new market segments and helps meet evolving consumer needs with precision and agility. The interplay between AI’s potential and diversifying consumer preferences will likely be key in defining the consumer industry’s future.

We’re helping clients adapt by developing solutions like ConvergeCONSUMER by Deloitte, which enables consumer organisations to rapidly deploy AI-powered tools that help them more accurately forecast demand, personalise marketing campaigns and optimise product pricing, can help organisations tap into the impact that AI is creating in demand forecasting.

How can these investments enable superior long-term planning for manufacturers and alleviate costs for retailers?

Manufacturers used to rely either on financial forecasts or internal history-based forecasts for planning. But now, using AI along with different data sources (including lots of external data) gives a much-improved long term planning signal around which to organise. 

AI can predict when consumers will be shopping and where – at both the macro and micro level – as well as who is expected to be in-store or shopping online, giving retailers the opportunity to plan for inventory needs in advance and meet customers where they are.

In addition, the push toward software-defined manufacturing will enable automated reactions to demand, offering greater flexibility and resilience during high-pressure seasons. This can help lessen costs for retailers and allow manufacturers to better plan for and execute during high demand time periods.

It’s the best path to achieve agility, which will define the next generation of manufacturing operations.

Can you lay out the ideal strategic approach you'd take if you were a manufacturer seeking to become more software-defined?

I would recommend starting small and focusing on achieving some quick wins to demonstrate attractive ROI to key leaders within the organisation.

Often, when embarking on a transformation of this magnitude, there's a tendency to aim too big right from the start, which can make scaling the plan challenging. By identifying specific areas of focus and having a clear vision in place, you can ensure a more manageable and successful approach.

Now given that, I’d start at the foundation. While delving into essentials like industrial data and manufacturing executive systems (MES) may not be the most glamorous of trends, it’s crucial for mastering new technologies at scale. Skipping this step has left many organisations with varying degrees of digital readiness.

When prioritised, however, a cohesive technology strategy that emphasises a robust data foundation empowers manufacturers to harness the potential of software-defined manufacturing and the incredible technologies that come with it such as AI, GenAI, metaverse/digital simulation technologies and more. 

Now, here is the larger one that we see. It’s important that manufacturers address potential barriers to adopting a software-defined approach such as technical debt.

A challenge for a lot of organisations is that they have made investments into or acquired companies with technology that was built over 40 years ago. With that, technical debt is often a disparate set of data and lack of an ontology that can be built upon and utilised for cross system awareness and insights. If that data is not considered, it creates large barriers towards more SDM capabilities.

Addressing this technical debt – even simply starting with cost-effective upgrades – will create a stronger foundation for improved software.

Finally, an essential principle of becoming more software-defined is to address the human element of the manufacturing process. Software-defined manufacturing requires a workforce that has a combination of technical manufacturing, digital, and soft skills. For employers, this means taking an ecosystem approach to talent development and leveraging digital tools that offer advanced talent planning and workforce management capabilities as well as enable workers to hit the ground running from day one.

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