Get out of the datacenter before you focus on shiny objects

Blockchain, IoT, deep learning, and other emerging technologies have incredible potential. But don’t let these shiny new objects distract you from the core of your business: your legacy applications

open door with sunlight shining through

I recently presented at IBM Think, where I was glad to see a packed room with folks from a wide range of industries gathered to learn how to modernize legacy applications and infrastructure. The talk was a success, but afterward I was caught off guard by the number of people who asked me how to implement a blockchain strategy in their company.

Wait. I just presented on migrating old, but important, applications to the cloud. Now we’ve fast-forwarded to blockchain? I realized more people than I would have guessed need to slow down when it comes to new technology.

The big question CIOs ask themselves over and over is “How do I spearhead transformational projects that create value for my company?” Given they’re looking to drive major change, it’s easy to see why CIOs get distracted by the shimmer of shiny tech topics like blockchain, internet of things (IoT), and deep learning, imagining the myriad ways these technologies could be implemented. But when you’re running an enterprise that relies on legacy technology (hint: all enterprises do), you need to understand that most of applications and data that the shiny objects will rely on are still stuck in the data center.

This doesn’t mean you should avoid these new technologies—they have real potential for increasing your business’s bottom-line value. But you’ve got to focus on where your data lives, what it enables, and what depends on it before you adopt any of these shiny objects.


Blockchain is in the headlines daily, either by itself or in the form of the cryptocurrencies that all rely on the infrastructure it creates. Blockchain is essentially a collection of digital records linked and secured through cryptography. It’s an especially hot topic for technology leaders because of its ability to organize and secure data like never before. These capabilities hold potential to dramatically improve the security and workflow for processing contracts, bringing value to the bottom line of industries like finance, real estate and law. The problem is that these are all longstanding industries with, you guessed it, lots of legacy technology. So, before they can truly wield blockchain, they’ll need to modernize the systems running their businesses.


Another hot topic in technology right now is IoT—the idea that all of your devices can be connected to each other wirelessly to do more, smarter things via the internet. In short, IoT lets your smartphone talk to your thermostat. In the enterprise, we’ve seen IoT show up in the prolific use of mobile devices or BYOD workplaces during the last decade. Of course, you can’t simply discard your legacy applications because your devices are communicating more effectively. Nest is awesome technology, but at the end of the day, it’s still a thermostat that runs the oil furnace at the bottom of your building. IoT enables devices to do cool new things, but the foundational product is still the same stuff you’ve been working with for years. To power big data analytics or deep learning, you will eventually need to know where your IoT data lives, and ensure it is easily accessible. The cloud fills this need, enabling you to organize, secure and rapidly access your data in ways a data center can’t support. Not to mention the cloud’s potential to reduce overall cost of ownership.

Deep learning

Of all the shiny new objects in technology, deep learning is the one that, as you might expect, requires the most data. Technologists and scientists are loading massive amounts of data into computers and training the computers to recognize patterns that produce conclusions faster than any human, and it’s already making a tangible impact in our world. Recently, a startup called Antidote demonstrated how deep learning can democratize clinical trials, while a company called Aquabyte is using it to reduce the environmental and financial costs for fish farming. The power of deep learning is undeniable in sectors like health care and life sciences, but to take advantage of these capabilities, you need specialized workloads, new analytics tools, and lots of CPU/GPU power—all of which come after modernization, not before.

Blockchain, IoT, deep learning, and other emerging technologies have incredible potential. But don’t let these shiny new objects distract you from the core of your business, your legacy applications. You need to use the right technology to meet the needs of your business, not the other way around. Your business’s core value lies in data produced over years and often housed on-premises in legacy applications. The best way to leverage the promise of technology advances is to first unlock the value of your data through modernization, thereby laying the foundation to get the most from technology’s brightest ideas.

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