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How leaders can make the right digital manufacturing investment decisions

0 minutes read · 18th March 2024

Q&A with Max Winchester, Principal and Head of Digital, Chartwell

How leaders can make the right digital manufacturing investment decisions

Q&A With Max Winchester, Principal and Head of Digital, Chartwell

Learn how investment decisions in digital manufacturing are missing the mark from Chartwell’s Max Winchester.

What is digital manufacturing?

Digital manufacturing is the use of technology in a production process and covers a wide range of functions, from the connection of physical sensors to advanced control systems to the use of software to inform better purchasing decisions. Wherever digital tools and equipment are used in the manufacturing process, we can consider this part of the digital manufacturing ecosystem.  

We’re currently witnessing a big drive in almost every industry for manufacturers to improve how they connect their operations, their data, and their people via the introduction and use of digital tools. The potential benefits of this are clear, with a fact- and data-based approach being the only way to realize rapid and sustainable performance improvement. 


How can manufacturers make good digital manufacturing investment decisions?

This is an important question as companies commit substantial budgets to digital manufacturing initiatives, with entire new divisions created to achieve bold digital goals. 

Digital teams need to be able to show quantifiable returns from these investments and – in our experience – money, software, and AI ambitions do not directly translate to the near- and medium-term benefits that manufacturing leaders expect. Many such investments remain in the ‘blue sky’ realm, rather than tangibly improving the operations they are designed to support. 

Whilst it’s important to be ambitious and to future-proof your business, this must be balanced by pragmatic initiatives to capture near-term opportunities to stay ahead in a fiercely competitive market. 

Our advice is to balance the long-term digital manufacturing investment decisions with short-term initiatives that drive immediate results and set your team on the path toward utilizing the full potential that digital manufacturing can unlock. After all, an investment in AI isn’t going to achieve its potential if paper records are still used throughout your process. 

Augmenting new technologies with fundamental manufacturing practices that are known to drive results is necessary to get the full value out of your investment. Doing one but not the other might leave you with impressive software but an inability to use it to generate the improvement you need. 

There have been multiple cases where we’ve been brought in after a manufacturer has heavily invested in software without an understanding of what they are trying to achieve and how they want to leverage those tools. We then help those teams uncover opportunities to show value in their digital transformation and highlight how traditional manufacturing and digital manufacturing can intersect for the greatest outcomes. 


Where should manufacturing leaders prioritize their digital manufacturing investments?

Manufacturing leaders should start with their business priorities and establish a clear vision for the short and long term, before diving into digital investments. Only by having a clear vision can you begin to understand how your investment decisions will help you add immediate value, while also setting you up for long-term success. 

An approach that we find successful is to pair our Chartwell Consulting and Chartwell Digital teams to support clients in realizing their vision. Combining a fundamental understanding of manufacturing improvement and the development of a digital roadmap helps leaders generate results quickly, prove value to internal stakeholders, and build momentum for the digital transformation as it progresses. 

Where should manufacturing leaders focus their digital manufacturing efforts in the short term?

In the short term, we would say that manufacturers should be looking at capacity improvement, cost reduction, or working capital reduction to demonstrate immediate financial value. 

In the case of capacity improvement, focus on finding hidden opportunity in your bottleneck assets via a deeper understanding of the process data, including how relationships between variables relate to the physical system and the levers available to increase throughput. When done rigorously, we have found +10-30% more headroom in complex and high-performing processes. 

If your focus is on reducing cost, you may prioritize digital tools that help your team become more effective and productive with their time and raw materials. Process visualizations and performance dashboards can effortlessly inform an incoming shift of potential quality deviations or equipment failures before they occur. 

Depending on the need, we collaborate with our clients’ teams to embed a rigorous use of the Chartwell methodology, linked to existing and new data sources, to realize opportunity and deliver value quickly. 


How can manufacturing leaders choose a strong a software partner?

There are many options out there, with varying approaches to data collection, cleansing, analysis, prediction, and visualization. Picking a generic option off the shelf is a thankless task. Manufacturing leaders should therefore think carefully about how the platform is going to help in both the short term and long term. Does it have the capabilities to embed into your current process and quickly add value to your specific situation? Is it able to grow as you grow? 

Chartwell Digital offers tools that deliver value in months not years. Our methodology is centered on building a holistic understanding of your business, allowing us to prioritize digital transformation efforts and tools that improve the metrics critical to your business. Our software is designed and developed by experts in manufacturing and data science because you shouldn’t settle for one without the other. Learn more about our Chartwell Digital offerings.