Big Data, the Supply Chain, and Deja Vu

There’s a phenomenon that’s been discussed a lot in recent weeks that goes something like this: In spite of incontrovertible evidence that a statement or fact is true, people disregard the evidence and hold fast to their original but incorrect belief. (It’s one way that researchers are explaining the current U.S. presidential election.) We’ve also seen this same phenomenon play out in business. Remember the dotcom boom? Even though the supply chain could not possibly sustain hundreds of “unique” online component trading sites, hundreds were launched anyway. I’m beginning to feel a sense of déjà vu in regard to big data. (Note the lowercase letters—it’s not Big Data or BIG DATA no matter what your marketing department tells you.)

Here’s what’s happening: thanks to robust data-processing power and cloud storage, companies are collecting data like crazy. I just had a refreshing conversation with an analyst that’s neck-deep in the big data movement. The upshot? Data for data’s sake is a complete waste of time and money. Only a small portion of all the big data collected is actually meaningful to any specific business.

That doesn’t mean that big data in unimportant if applied sensibly. Take the supply chain, for example. If a components distributor can collect information on an engineer that buys a sample kit, the distributor can get a pretty good idea what product that engineer is designing. That product will call for a whole bunch more components than the engineer actually buys. The product the engineer is designing probably won’t be built at the engineer’s location, but the company he or she works for has been known to outsource its manufacturing to a certain EMS. A savvy distributor will make a note to call the OEM company or the EMS to see if there’s anything they need. Better yet, that distributor will alert its component suppliers that they’ve established a solid sales lead.

Here’s the problem: the distributor will have to sort through terabytes – or even zettabytes -- of irrelevant data to get to that information. The engineer’s shipping preference – overnight or second day; UPS or FedEx; envelope or cardboard box—won’t matter to the distributor. It might matter, however, to the distributor’s logistics partners.

So the distributor shares that data with its partners, and a new set of questions arise: was the process secure? Should the data only be shared with a preferred shipping partner? What if that partner also supports a competing distributor? Will shipping data get aggregated and then possibly shared with the competitor? Could the competitor then extrapolate what kind of components are being shipped to what company? Could the competitor then pay a call on the design engineer?

These are not far-fetched scenarios, analysts say. Companies that are too overwhelmed to analyze their own data may very well outsource that function. The risk of data being compromised just rose exponentially.

How does this compare with the dotcom boom? Businesses have capabilities that they didn’t have before: online procurement and exponential data collection. In both cases, business have the opportunity to transform their business models. But similar to the internet, business is racing to adopt big data without asking “why?” Before many electronics companies developed their own online capabilities, they “joined” e-commerce sites that bought and sold another people’s inventory (OPI). Sure, companies reached a broader base of customers by posting their inventory on every available site. But what happened? Inventory became one giant pool of stuff that buyers could find everywhere. Brands became diluted. Even worse, online auction sites posted devices that came from questionable sources and counterfeiting ran rampant. As it turned out, brand owners found they could implement e-commerce themselves and the demand for auction and aggregation sites dried up.

I think companies are facing the same danger from big data. Like inventory, data holds an intrinsic value. Companies want to unleash that value. But what happens that when data is added to a large pool of information and is then available to everyone? Data that once “belonged” to a single company is now available to a direct competitor. The value of that data becomes diluted. As Dave Padmos, EY Global Technology Sector Leader, Advisory Services, said, companies are collecting data for data’s sake. In the late 1990s, companies went online for online’s sake. The electronics supply chain is still cleaning up from unintended consequences.

Many businesses seem convinced that big data is crucial to their future success. Yet the world is rife with examples of data mismanagement. Wells Fargo used data to set up fake accounts. Yahoo’s user information has been hacked. Then there’s WikiLeaks. In spite of evidence that big data has many pitfalls, businesses are moving full throttle toward data nirvana. The facts don’t seem to matter: if companies believe that big data is a business imperative, nothing’s going to change their minds.

I think there are still consequences associated with big data that we can’t anticipate. In 15 years or so, we’ll know what they are.