Recently General Motors announced that they’re building a new, $258 million enterprise data center in Moring, Michigan. With it, they are going from 23 outsourced data centers around the world to 2 data centers that are, in essence, in-sourced. This move of bringing the data centers back to Michigan and back to the full control of GM is a complete reversal of where they were.
So why are they doing this? To reduce costs? Remember that they initially outsourced their data centers to reduce costs. However, with this new move, GM says they can reduce costs by an additional 40%. In other words, they initially outsourced to reduce costs, but now they’re in-sourcing to reduce even more costs, and they’re consolidating and getting all the data in one location. On the surface, this almost doesn’t make sense.
Actually, it makes perfect sense. To better understand why this is a strategic move for GM, we have to look at our three change accelerators—processing power, storage, and bandwidth. The exponential advances that have been taking place in all three areas have reached unprecedented levels. You’ve likely heard the story about what happens when you double a penny every day. Tomorrow you’d have two cents; the next day, four, the next eight, and so on. By the end of the week, you would have a whopping sixty-four cents. By the end of week two, your cache of cash would have grown to $81.92. Not too exciting. But by day twenty-eight, just two weeks later, your pile of pennies would exceed $1 million; on day thirty it would be over $5 million. If this happened to be a thirty-one-day month, you would end the month with more than $10 million.
If doubling a penny and suddenly reaching $10 million seems dramatic, imagine this: what if the next month, you started with that $10 million and kept doubling? That’s the change level we’re approaching with the three accelerators. Consider this: what was considered the world’s fastest super computer two years ago was recently disassembled because it was obsolete. And of course, as the power of those three change accelerators continue to increase dramatically and exponentially, their price continues to drop. So we can do much, much more with much, much less.
But that’s not the only thing driving GM’s decision to in-source their data. The nature of big data and high speed data analytics is changing too. Not only are companies creating more data than ever before, but the data they are creating is much more valuable. Here’s an example.
The latest plug-in electric vehicles produce 25 gigabytes of data an hour. Some of that data is sent to the driver’s smart phone so they know about the car’s battery life, tire wear, vehicle performance, where the nearest plug-in stations are, plus many more things. Thanks to all this data, the driver as well as the service center can do predictive analysis of the car, which is basically being able to predict car troubles before they occur. Now the driver can fix the problem before it manifests, thus eliminating the car from unexpectedly breaking down.
The data the car produces also goes to the car maker so they can track customer satisfaction and vehicle performance, enabling them to make better vehicles in the future. In fact, the car maker can learn what’s happening with the cars in real time, which enhances their ability to continuously innovate. In this sense, data increasingly becomes the company jewels. Because there is an amazing amount of data being generated, and because the data is far more strategic, companies can get active intelligence from it to make better decisions in real time. No wonder GM wants all their data in-house.
Now, this doesn’t mean that every company should have their own data center or copy what GM is doing. Many companies utilize software as a service (SaaS) to lower their software and hardware costs, and hardware as a service (HaaS) for the data storage. Those are valid options for many organizations. There are so many services that can be cloud-enabled and virtualized that we are now seeing everything as a service (XaaS) rapidly emerge, for example collaboration as a service (CaaS).
The key is to do what’s best for your company today, based on the hard trends that are shaping the future and regardless of what may have worked in the past. Therefore, you need to ask yourself:
° What kind of business are we?
° What industries are converging to create new opportunities?
° What is the size and reach of our business?
° What are the ideal short, mid, and long range goals for our organization?
° How much agility do we need to stay ahead of the competition?
° How much data are we producing now and how much do we plan to produce in the near future?
° What is the value of the data we have and are now capable of collecting?
° What kind of competitive advantage can our data help us create?
Not every company generates as much data as GM. And not every company has to track hundreds of thousands of parts and supplies. But every company creates data and will create much more in the future, and that data is increasingly becoming the key to your organization’s growth. Therefore, it’s imperative that you think through your data plan so you can leverage your data to solve problems faster, make smarter decisions, and reach your goals faster.
Remember, too, that because the three change accelerators of processing power, storage, and bandwidth are still growing and will continue to do so, you need to re-evaluate where you are often. Even though GM is bringing their data centers back home, they’ll have to look at their current strategy again in just a few years.
Times are changing fast, and the rate of change will only increase as times goes on. So what works today may not work two years from now. Therefore, whatever your company does or decides is best for today, re-evaluate that strategy often. Look at your data and where your competitive advantage is coming from so you can take advantage of the newest technologies and not be trapped in the past.
If you keep doing what you’ve always done in the midst of rapid change, you’ll lose your competitive advantage. You either change with the times, or you get left behind. Which option makes the most sense for your company?