Microsoft: Monitoring & Mastering Manufacturing Performance

Simon Floyd is the General Manager for Manufacturing and Mobility Industries for the Americas at Microsoft, leading an advisory team that works with top customers across the US, Canada and Latin America.

A former Director of Global Manufacturing Industries at Google Cloud, Simon is a manufacturing expert with a vital perspective on emerging technologies and a rich personal and professional history in the industry.

Here, he shares his expertise on performance monitoring solutions for industry, reflecting on the industry’s future, his role at Microsoft and his passion for manufacturing.

How have you come to work at Microsoft in such a manufacturing-focused role? 

You could say that I was born into manufacturing. My parents were both owners of small businesses with a backbone in the sector.

My father made children's furniture, my mother made children's toys and together they co-owned a direct-to-customer retail business. My grandparents on my father’s side also made children’s toys and sold them through specialty retailers.  We lived above our factory and retail store, so I grew up with the  manufacturing value chain and experienced it firsthand.  

My grandfather on my mother’s side was also one of the original inventors of plastic processing, specifically a plastic called Bakelite using a method called thermoforming. He created the first commercial application of Bakelite for electrical fuse boxes around the early 1900s. In the 1950s he was a true plastics pioneer, inventing plastic injection moulding and building a business that created kitchenware. 

Growing up with him, I had access to fantastic equipment in his garage – it was sort of a prototype lab and place to experiment. This early exposure gave me easy access to manufacturing technology and expertise and I developed an affinity for the industry.

I've worked as an industrial designer creating products from handheld electronic banking terminals and architectural products. I’ve also worked as a design engineer for automotive components. In the late 1990s, I chose to specialise in software, forging my entry into product life cycle management and manufacturing execution software. This led me to join Microsoft in the early 2000s to build their industry expertise, offers and partners. 

I was attracted to Microsoft’s commitment to driving positive change in the manufacturing industry. 

With my grassroots experience, I saw numerous opportunities where digital solutions could make a significant impact: improving lives, enhancing products, creating economies and generating jobs.

I felt Microsoft was the ideal company to realise this potential. Dare I say that I may be striving to achieve what my parents and grandparents were able to achieve, but on the world’s stage. 

Joining Microsoft has been one of the highlights of my career, and I remain dedicated to the digital transformation of manufacturing and fostering positive change in the industry. 

How would you describe your leadership style? 

I would describe my leadership style as transformational. My team and I all perform best when we focus on shared purpose, vision and our ongoing development. As a leader, I prioritise clarity in our goals and vision. 

I believe in providing my team the freedom to contribute in their own way – and I advocate this through my coaching. I provide everyone with the latitude to achieve these goals in the best way they can, while ensuring that quality and customer-centricity is the foundation of our work. 

I'm a lifelong learner and I love to learn from others.  I believe this fosters an environment where everyone can improve through collaboration. I also develop our team goals in tangent with everyone’s core skills and interests, which is why my team is aligned by industry verticals. 

This enables everyone to bring their industry expertise, skills and interests to the foreground.

Which current development in manufacturing do you find the most exciting? 

The most exciting development for me is AI. It captures so much attention due to its unprecedented accessibility, allowing people to quickly derive tangible benefits.

It’s remarkable how generative AI (Gen AI) has permeated consumer experiences, making its relevance and potential more apparent to individuals and businesses alike. This familiarity has facilitated rapid adoption within the manufacturing industry.

I think we made a wise choice at Microsoft to name our AI “Copilot”. It really embodies the nature of being assistive but also being a very capable partner.

AI can be the heart of automation or perform autonomous actions but with supervision – just like a copilot in the real world.  It can also traverse large volumes of data to obtain insights into current or future events.

People can now see the possibilities firsthand and, at Microsoft, we have demonstrated practical applications that deliver real business value. It's truly gratifying to witness this transformation. 

While AI as a concept isn’t new—we’ve been working with machine learning, anomaly detection and various AI technologies for years—Gen AI has rejuvenated interest. Manufacturers now view it as an essential tool for innovation and advancement.

Why is monitoring performance so critical for manufacturers today?

Without question, monitoring forms the foundation of any decision that's made in a factory. This could be monitoring equipment, the supply chain or end customer deliveries. Monitoring is incredibly important because, in manufacturing, the time to respond is what matters. 

Monitoring plays a crucial role in mitigating events that hinder manufacturing, such as machine downtime or operational inefficiencies. 

Using machine health as an example, by continuously monitoring performance we can detect early signs of any issues that might jeopardise its reliability or the quality of its output. When a machine's relative health indicates potential problems, it becomes essential for human intervention to address and rectify the situation. 

If the machine is no longer effective in its role, we may even need to consider replacing it with a more efficient model or changing the process itself.

Thus, monitoring not only helps in maintaining the current performance levels but also plays a pivotal role in planning for future improvements and replacements. 

A key benefit of monitoring lies in its potential for energy conservation. When a product isn't being created, the power can be reduced or shut off, providing an immediate opportunity for cost savings for manufacturers. 

AI's ability to synthesise multiple sources of information and make rapid decisions makes it far superior to static algorithms or even human intervention for managing power usage.

How does Microsoft Cloud for Manufacturing help manufacturers monitor and enhance performance? 

Microsoft Cloud for Manufacturing offers a comprehensive foundation for seamless data connectivity and integration, regardless of whether the data originates from field devices, equipment or existing systems like a manufacturing execution system (MES) or a quality management system (QMS). 

This connectivity empowers manufacturers by consolidating diverse information sources, thereby facilitating informed decision-making. This capability is instrumental for functions such as monitoring, advanced analytics and AI-driven automation. 

By leveraging these integrated data streams, manufacturers can optimise processes, enhance performance and drive innovation. For instance, the cloud for manufacturing can support monitoring functions or enable advanced analytics that yield actionable insights for real people.

Alternatively, it can drive autonomous AI agents to perform tasks with minimal human intervention. 

How is Microsoft helping manufacturers use data for performance monitoring?

The essence of maintaining, growing and optimising manufacturing performance boils down to the right information shared with the right roles, at the right time, so that people can make informed, impactful business decisions.

We offer a range of solutions tailored to individual roles and skill sets to facilitate access to information and tools that people need to perform in their roles. 

We ensure secure and role-specific access to information, crucial for effective collaboration

while maintaining privacy and security standards.  

We no longer need individuals to specialise solely in manufacturing. With modern digital tools, a wide range of professionals can now thrive in this industry; people from diverse fields, like financial services, who have data science skills can greatly benefit manufacturers by bringing new perspectives and capabilities. It's non-traditional but invaluable.

This opens up opportunities for a new class of professionals to advance their careers and help manufacturers progress. There's no better time for manufacturers to embrace this shift, despite concerns about the current and future workforce. I see this as a great opportunity. 

Do you have any further advice you’d like to give to manufacturers about performance monitoring?

I used to advocate for starting small with just one-use cases. Now I say they should start with scale in mind.  There are so many proof of concepts undertaken that never see the light of day because they were never scaling up and out to the enterprise.  

For many organisations this is their way of limiting the risk of failure. However I would argue that by not designing for scale, they are exposing themselves to a higher risk of failure from the start. 

Please consider the use cases where it can have maximum impact beyond just one machine or process.  Monitoring is a multidisciplinary function, spanning machines and processes to provide the real-time intelligence that defines manufacturing itself. 

This is how the value of AI will become self-evident and how Industry 4.0 will become the norm.

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