Industry 4.0 and Big Data Make SMB Manufacturers More Agile
Industry 4.0 and Big Data Makes SMB Manufacturers More Agile

Industry 4.0 and Big Data Makes SMB Manufacturers More Agile

By Joni Girardi

Many small manufacturers I talk to are pleasantly surprised to know that they are well positioned to execute Manufacturing 4.0, the coming of “the smart factory.” Small and medium-sized organizations are actually quicker to make adaptations than larger manufacturers.

Four great forces drive this trend, according to the global consulting firm McKinsey and Company.  First, powerful computing technology, then cloud connectivity.  Third is the Internet of Things (IoT) and finally, big data.

Of those four, big data is most potent and the most easily used by small- and medium-sized manufacturers. Big data’s advantage over regular data has been compared to the advantage that high-definition TV has over old, grainy black and white: the finer resolution lets decision makers see what they could only guess at before.

Big data helps SMB solve previously unidentified problems with dramatic results

Some SMB manufacturers have used big data in fault prediction and finding correlations among once-ignored information points to guide their pre-emptive maintenance for reduction or elimination of catastrophic failure. There are companies who now track employee badge check-ins on factory floors to gain precise insight into where work is done and who completes it.  This data has lead directly to new production efficiencies.

Still, others have found an application in supply chain management. There, relationships between commodity prices and final product cost provide swarms of indicators that come together in coherent pictures.

One pharmaceutical organization used big data to solve for unpredictable variations in production yield.  They were able to identify nine influential parameters in the manufacturing of live, genetically engineer cells which, when tweaked, improved vaccine yield improved by more than 50 percent, at an annual saving of more than $5 million.

Finally, production at a precious-metals mine had declined because of diminished ore grade. After a cleanup and integration of big, fragmented data, a crucial variability appeared in dissolved oxygen, a key in leaching. Minor changes in leach processing produced a 3.7 percent improvement in yield within three months, for a more than $10 million annual profit.

Implications beyond manufactured products

If McKinsey’s vision for Industry 4.0 comes true, those examples are only the beginning.  What McKinsey calls ”platforms” could open products, services, and information to be exchanged like open-source software with the manufacturer as an expert, trusted broker. One marketplace already under development big datawith the 3D printer manufacturer SLM Solutions and the IT services company Atos will coordinate production and shipping of printers and other equipment to customers.

Big data could make pay-by-use and subscription-based services more feasible, helping to turn manufacturing from a capital expenditure into an operational expenditure. Even know-how could be sold. Manufacturers can use big data to license intellectual property, in effect becoming consulting companies.

Even new client acquisition is positively impacted.  Customers used to look to sales people for pricing and product information, but now it can all be found online. Customers can easily answer questions such as: “How do prices compare?” “What do other suppliers offer?” “What features do I need?’

Now, big data can transform sales people into trusted consultants, offering expertise derived from sets of big data few others have integrated and analyzed. They can monitor trends that may influence buying decisions or products on their way up or down. The company who wins the business is the one who can profitably solve their customer’s needs by providing the right information at the right time to guide the client’s critical decisions.

Spreading big data across the board

Big data calls for a wide distribution of intelligence across the organization. Business users have to get their hands on whatever piece of the big data they may need. This is where SMB has the edge over bigger organizations: they have agility. While the big manufacturers plod forward on replatforming or democratizing data for across-the-board intelligence, smaller ones spring into action.

That agility is what can take big data down to size. As one of my customers put it, “In smart manufacturing these days, size counts. Smaller is smarter.”


About the Author

Joni Girardi is founder and CEO of DataSelf, provider of DataSelf Analytics. He launched his venture 16 years ago to help small- and medium-sized businesses to get value from their data using data warehousing and analytics platforms such as Tableau and Power BI.

Bellwether, a Blytheco Magazine



Reprinted from the Summer 2016 issue of Bellwether.

Read more insightful articles for free here.

Subscribe to get a copy mailed to you each quarter for free.


Share This Post