Building a Future-Proof Data and AI Strategy in Manufacturing: The Experts Weigh In

In This Article

Industry 4.0: The Fourth Industrial Revolution, or the digital transformation of manufacturing, wherein leaders are utilizing technology to improve productivity and flexibility. 

The world is changing, and manufacturing is no exception. 

Initial studies have AI increasing manufacturing productivity by a sizable 10%. It’s also shown advantages when it comes to flexibility, quality, consumption of natural resources, capex allocation, labor savings, and more. 

But how can manufacturers effectively apply AI? What does strategic innovation look like in an Industry 4.0 world? 

We’re already seeing a wealth of opportunity. 

Innovation in Manufacturing with the Help of AI 

Some leading manufacturers are well aware that leveraging modern technology to address business objectives is how competitive advantages are built, or margins are increased. Sure, some are still a bit skeptical of AI, but other early adopters are excited about the seemingly endless possibilities. Those with the foresight and determination to leverage technology see that AI will position them to take advantage of endless opportunities as they arise (and they’ll arise quickly). 

When considering how AI can transform our industry as we move into the future, the manufacturing strategy and industry tech experts at MCA Connect predict: 

Hyper-Customized Value Chains 

With AI, manufacturers have more paths to providing value in unique, innovative, and near-instant ways.

“Imagine someone automating the creation of t-shirts featuring a quip from a social media trend. They could use AI avatars to create marketing videos, automate the postings of those videos, accept payment through Shopify, print a customized t-shirt via a third party, and even outsource the shipping.” 

Dag Calafell, Director of Technology Innovation at MCA Connect

This entirely automated pipeline is possible with today’s tech. 

But that’s just the beginning. Remember: If our hypothetical example is based on a slogan from social media? It’ll probably be relevant for less than a month. This means that a new t-shirt endeavor could crop up every few days to every few weeks.   

Growing Communication Volume

With AI, expect to see a lot more communication, both incoming and outgoing. 

Sure, some of it will be the standard, script-like, human-generated messaging you’re used to. But, moving forward, much will be AI.  

Dag: “This means that, with today’s tech and certainly with future improvements, we could slot AI agents directly into Electronic Data Interchange (EDI) roles. This would help manufacturers avoid those costly projects and rigid solutions.” 

So you don’t have to ask the internet: 

Electronic Data Interchange (EDI) is the computer-to-computer exchange of business documents in a standard electronic format between business partners.  

An Increase in Spam Messages

Spam is likely to escalate, too. Our estimation is a 5x increase or more. 

As a result, spam filters will need to get much smarter and much more effective. Or the alternative is assigning AI agents to sift through our inboxes, shuffling the “real” messages to the top of the pile. This way, only the ~5% of communications that are actually relevant will reach you. 

And it won’t be just email, either… 

Dag: “This applies to phone calls and text messages too. Ugh.” 

Improved Processes 

“Digital for the sake of digital” is rarely a worthwhile approach. The opportunities with AI are virtually endless, which means decision-makers will need to be discerning in their applications. 

Dag: “The most important thing, when deploying AI agents, is ensuring they address a certain portion of some particular process. In other words, the agents are a form of process optimization and not just an automation.” 

Any solution that does not address the process itself or solve an identified problem or goal will be, ultimately, unnecessary extra weight. 

Getting Started 

Today’s AI can help with data collection, recommending actions to achieve desired outcomes, automating repetitive tasks, predictive demand planning (like Demand Genius^TM), decision-making, overall efficiency, and so. Much. More. 

Whether you’re looking to launch a new AI-driven strategy or fine-tune existing processes, here’s what we’d recommend:  

Choose Your Approach

When it comes to data and AI strategy, there’s no “one-size-fits-all” approach. In our experience, though, there are a few key elements. 

“A well-designed data and data and AI strategy should include ‘quick wins,’ data governance, a modern data platform (MDP), a single-source-of-truth for analytics, and collaboration with key business stakeholders.” 

Darin Witten, Director of Advanced Analytics at MCA Connect

Whatever you choose to tack on, a phased approach usually works best. A roadmap for tracking progress and taking advantage of all the benefits along the way is also a great idea. 

Set a Timeline

Unfortunately, industry-shaking improvements don’t often happen overnight. 

Start by assessing current-state technologies and talent to help clarify how long it might take to reach your ideal future state. And don’t forget to factor in training time… user adoption among experienced business intelligence (BI) professionals will be key to continuous improvement and avoiding technical debt. 

Then, buckle in for the long ride. 

Darin: “Implementing a solid manufacturing data and data and AI strategy can take a few years or more, and that’s when all the right people are involved.” 

But if you really want to fast-track things, we recommend two things:  

1. Acquire more talent (direct hire or consultant) to work on the initial development of the solutions as well as the ongoing advancements. 

2. Implement a full-scale, continuously improving modern data solution designed for manufacturing like MCA Connect Inspire Platform^®, a subscription-based offering ready to go in a matter of weeks.