Despite what the hype surrounding big data might lead you to believe, the widespread existence of data is not a new concept, nor has there been some sudden "aha!" moment when decision makers realized that data could be put to use to better their businesses. Data -- and lots of it -- has always existed, and companies have always understood that it has value. There just wasn’t a whole lot they could do about it.

That is, of course, until the development of so-called big data technologies -- a wave of new tools that make it possible to store, integrate and analyze data more efficiently and affordably than ever before. These technologies have transformed data analysis from a cost-cutting mechanism into a primary vehicle through which companies make money and find new revenue streams.

When people talk about the power of big data, they’re really talking about this transformation. And perhaps no industry is a better embodiment of it than manufacturing.

Manufacturers have long been able to track and monitor much of what’s happening on the production line, as well as some of what happens to products after they come off the line. Historically, much of this data was analyzed after the fact in the name of lowering operational expenditures. Manufacturers were in a way the poster children for what’s become derisively referred to as traditional business intelligence. But now they’re poised to be among the primary benefactors -- if not the primary benefactor -- of the big data analytics boom.

Relative to other vertical markets, manufacturers enjoy three primary advantages that leave them uniquely positioned to benefit from big data.

  • Every industry and every individual is touched by manufacturing in some form or fashion. You’re either doing business directly with a manufacturer, or you’re purchasing something that at some point emanated from one
  • Because manufacturers were among the first to make widespread data collection a standard practice, they can quickly and easily scale their data collection efforts. Put more simply, a manufacturing company can get to a point where it’s tracking virtually everything a heck of lot faster than most other companies can
  • Manufacturers typically don’t face the data collection barriers that many other companies encounter. Whether they know it or not, many consumers readily provide valuable data to manufacturers on a daily basis

Put it all together, and you can see why manufacturers are essentially sitting on a pile of big data dynamite, with an explosion of new revenue streams well within grasp. Here are three ways they can take advantage of the opportunity:

Cross-Sell and Upsell

Given the vast amounts of customer usage data they collect, manufacturers are optimally suited to leverage cross-sell and upsell opportunities. This is really a fancy, less frightening way of saying manufacturers have a ton of data they can sell as a means to creating new revenue. Let’s take the example of auto manufacturers. You probably know that cars have sophisticated computers in them that track everything from your mileage and gas consumption to your position at any point in time through geo-location systems. What you may not know is that all of this data is transmitted back to the manufacturer and saved in a central location for analysis.

As a manufacturer, the opportunities to put this data to work for your bottom line are many. Mileage use data can be sold to oil change and repair specialists, who can in turn proactively contact you about your next servicing. Or perhaps a coffee chain would be interested in having a car’s navigation system notify drivers any time they are within two blocks of one of their locations.

Automakers are just one example. Maybe it’s a manufacturer of heart-rate monitors clueing in a running shoe retailer as to when you’ve past a certain mileage threshold. Whatever the case, the key is that as a manufacturer, you have the captive audience that retailers are so desperately seeking.

Deliver Premium Customer Experiences

Certainly, manufacturers can use data to improve the overall quality and efficiency of the products they make, but that may only help them maintain their current revenue streams. New revenue streams are most often opened when you can deliver a premium experience or service for which your customers are willing to pay more.

Going back to the example of the auto manufacturer, GPSs were once a great example of a premium service based on data for which customers were willing to pay more. Today, GPSs have become normalized as a standard offering. But when you have access to data, the possibilities are virtually endless. What if, for example, you offered a service that allowed drivers to sync their Outlook calendars with their cars’ navigation systems, such that the navigation system could then advise them as to the best route to optimize fuel consumption based on the stops they needed to make that day?

The admittedly made up specifics are immaterial here. What matters is that manufacturers are better positioned than most to leverage data into premium experiences for which customers will gladly pay the extra buck.

Expand Into New Markets

This one requires some out of the box thinking, but isn’t that what big data analytics is all about? Manufacturers, sitting on mountains of information, are uniquely positioned to predict customers’ needs for a new product or service, then proactively manufacture that product themselves. They can do so with a fair degree of confidence as to the likelihood of it gaining widespread customer acceptance.

Let’s return to the automaker one last time. Perhaps changing weather patterns in a given part of the world are rendering traditional sealants increasingly ineffective. Instead of asking their sealant distributor for changes, couldn’t the auto manufacturer -- the one with access to the customer data -- seize the opportunity directly and begin selling a sealant that addresses the changing market need? Through better analysis of the data they’re already collecting, manufacturers can create new revenue streams by moving into tangential markets they would not have otherwise known were available to them.

Manufacturing the Future

It’s ironic in some ways that it's manufacturers that sit on the precipice of a big data breakthrough, because so much of big data and data analytics is about manufacturing – manufacturing new ideas, new opportunities and new revenue streams. The once-in-a-lifetime opportunity that has been promised to businesses by way of big data is finally there for the taking. It’s time for manufacturers to lead the way.

Title image Creative Commons Creative Commons Attribution 2.0 Generic Licenseby  Hugo90