Stanton Chase uses cookies to ensure you get the best experience on our website. Learn More I accept

Leveraging Big Data in Manufacturing, Now and in the Future

November 2019
Flemming Riber
Share LinkedIn Share E-mail
Leveraging Big Data in Manufacturing, Now and in the Future Cover Image

Vestas Wind Systems Lead the Way

The Information Age that began several decades ago has reached maturity with the advent of big data, but big data’s full effects on companies remain to be seen. While the advent has transformed the business-to-consumer sector and given rise to new consumer-facing companies that were previously unthinkable (e.g. Facebook, Amazon, Netflix, etc.), change in the business-to-business sector has lagged. In particular, the manufacturing industry is well behind in utilizing big data for positive change.

Even though over half of all companies in the manufacturing industry now recognize that big data has huge potential, IBM notes that manufacturers still remain well behind their peers in other industries in this regard (not to mention B2C businesses). Manufacturers who are able to capitalize on the potential of big data will gain substantial competitive advantages and improve their businesses in multiple ways. In addition to generally improving operational efficiencies and streamlining processes, here are six ways manufacturers might be able to use the information they gather to improve and increase the B2B services they offer.

Better Meet Customers’ Needs and Improve Operational Efficiencies

For the majority of manufacturers, the most immediate effects of big data pertain to existing customers and operational processes.

1. Predict Business’ Needs in Advance

First, manufacturers who accurately analyze customer behavior will be able to better predict — and thereby better meet — the needs of the businesses they serve. Even if past behavior isn’t a guarantee of customers’ future actions, it’s often highly indicative and can be used to provide an enhanced customer experience.

Businesses in B2C spaces have greatly increased how much they rely on customer data in recent years as the information has become more available. While customer experience might be less important in manufacturing B2B settings, it’s still one way manufacturers can ensure their business customers remain content.

At the very least, predicting customer behavior can help ensure fewer products end up on backorder because of parts shortages. In some situations, this type of analysis might eventually lead to suggesting a better way of meeting a business’ production needs.

2. Increase Precision in Products

Second, having more details about products themselves lets manufacturers produce items with greater precision. Of course, there has been a slow but steady increase in precision for about as long as people have made things. Few periods in the past, however, saw the advancements in this particular area that computer-aided drawing, three-dimensional modeling and printing, laser measuring and other advancements have recently brought.

Whether taking more measurements or increasing the accuracy of an existing measurement, both can potentially improve the quality and usefulness of an item. In some manufacturing sectors, such as aerospace and technology, precise tolerances can be the difference between producing serviceable components and useless items. In other sectors, precision may matter less but still can benefit a company.

3. Better Manage Supply Chains

Third, a triangle of customer, market and supply chain data makes it possible for manufacturers to now manage their supply chains with previously unthought-of accuracy and precision.

As mentioned, this is essential to meeting the needs of businesses that manufacturers serve and fulfill orders in a timely fashion. It also gives manufacturers more chances to take advantage of market opportunities, minimize supply chain disruptions and adapt quickly when backend changes need to be made.

When combined, the faster order fulfillment timeframes and increased operational efficiencies can make a big difference to both a manufacturing company’s bottom line and long-term prospects.

Grow New Potential Revenue Sources

As beneficial as these immediate effects are, the real potential of big data lies not just in how it can improve current operations. Instead, the long-term promise of big data is largely in how it could revolutionize many manufacturers’ business models and lead to new revenue growth.

4. Subscription-Based Pricing Provides Regular Revenue

The path toward a subscription-based pricing model might not be as obvious in B2B manufacturing as it is for many B2C companies, where Netflix made streaming movies standard, Amazon has long offered premium delivery through Prime, and there’s a subscription for everything from clothing and coffee to carnivorous plants and slime.

Other businesses in B2B settings have added subscription services, such as a higher service tier for an annual fee, and creative executives in manufacturing might be able to find a way. Even if this is only used to supplement a manufacturer’s revenue, subscriptions can provide reliable, regular and additional revenue.

5. Use Customer and Product Data to Innovate New Goods

Perhaps more obviously, manufacturers in all sectors can use existing customer and product data to develop improved products in the future.

This was one opportunity that IBM specifically highlighted in the above-cited report. The company’s researchers saw broad opportunity for manufacturers to install sensors on their products that can collect data as the items are used. This data, IBM said, can then be used to improve predictive maintenance schedules (e.g. for a car or farm equipment) or better predict quality (e.g. for underwriting warranties).

Of course, the information gathered also might lead to insights that show how an existing product or where there’s a need for something new. Just one example of a product that’s improved by customer data is Amazon Alexa (and most similar competing assistants), which learns from any mistakes that the system makes when interacting with people. There are far too many products that have been developed based on customer data to highlight any one.

Again, bringing this type of learning into a B2B manufacturing setting might be more challenging than it is for many B2C-based companies. The opportunities certainly exist, though, and tomorrow’s most successful manufacturers will have executives who figure out how to innovate with big data today.

6. Sell Gathered Data for Additional Revenue

Finally, manufacturers themselves can become data brokers as they gather information through their products. Gathered data could be sold outright, access to it could be leased, or it might be used to form new business ventures and partnerships. The possibilities are wide open once a manufacturer has sufficient and relevant information to sell.

As an example of how this might play out for a manufacturer, EY imagines a car manufacturer that installs sensors that gather road condition data as the automaker’s vehicles are used. This information would be useful to traffic planners, and it could be sold to them as an additional revenue stream.

Case Study: Vestas Wind Systems Sees Success

Importantly, these concepts aren’t just theory but have already been proven in real-world scenarios. For a case study, we at Stanton Chase looked to Vestas.

Vestas is a Danish manufacturer, seller, installer and service provider of wind systems around the world. Thus far, the company has already leveraged data gathered through its turbines to:

  • Lower operational expenses
  • Reduce overall maintenance costs
  • Improve turbine performance
  • Develop new products and services

The company’s new products and services include an application that helps turbine owners preemptively address critical component failures, but also services that will likely be among the most advanced wind and solar forecasting tools. Those platforms have potential far beyond improving turbines themselves and will likely lead to new partnerships.

Find Leaders Who Understand Big Data

Manufacturing executives don’t just have to be knowledgeable about manufacturing processes, but they increasingly also need to appreciate the importance of big data. For help finding someone who can lead your company into the information-based future, let us at Stanton Chase use or own expertise and data to help you find the right next executive who will be able to adeptly lead your manufacturing company.

 

 

Featured Articles

Panelists Discuss Board Engagement at PEI UK Conference

Read

Stanton Chase Names George Sphiktos a Director in Washington, DC

Read

Incentivizing Invitations Attract Incoming CFOs

Read

Contact a Stanton Chase office near you

Find an office