Life in the Fastlane. It’s the day-to-day life of a CIO. Last year I shared my view on the evolution of this role and how the “I” is shifting from information to innovation and I’ll touch more on the evolving role of the CIO in a future blog. A big part of this shift is being driven by data.
Today, businesses are scrambling to harness their data and regardless of your company’s size, age or industry, the process is daunting at best. Consider the following numbers from IDC:
- In 2018, humans generated 33ZB of data
- By 2023 that figure will rise to 103ZB
Let’s put this in perspective—a zettabyte is so large that it would take about a million supercomputers (or a billion powerful home computers) to store this amount. Or said differently, 1 zettabyte of data is the equivalent of all the grains of sand on all the beaches in the world.
To say that businesses are struggling to keep up with this data deluge may be the biggest understatement of the year. Consider this figure from the IDC Analyst Connection—only 2.5% of all data is actually analyzed. This means that less than 1ZB of the 33ZB generated in 2018 was analyzed. These numbers may help explain why, according to a study from NewVantage Partners, the “percentage of firms identifying themselves as being data-driven has declined in each of the past 3 years – from 37.1% in 2017 to 32.4% in 2018 to 31.0% this year.”
The big takeaway here is that success in the data age takes more than hard, sweat equity work. It requires a commitment to innovation across the company. This is how businesses bring value and monetize their data.
As I wrote last August, CIOs are now in the bull’s-eye of company’s success. Those of us who are embracing this new role are more engaged with the business. We’re also more committed to activating our data to ensure that colleagues from IT and marketing to HR, product development, sales, finance and more have the right elements of data, at the right place and at precisely the right time.
By the way, I’m not talking about the tiny 2.5% of data I touched on earlier. Companies looking to become an industry disruptor demand that CIOs unlock ALL of the data their business needs and do so with proper context.
For Hitachi Vantara, this required three key elements.
The first was a powerful Hitachi Virtual Storage Platform. Specifically, something I like to call #YourDataCenterAdvantage. A platform capable of transforming our data center and fueling new life into existing assets while charting our data-driven path and future-proofing our organization to avoid the need for any surprise investments.
All of us can remember at least one situation where a “surprise” purchase was needed in our data center, one that was not inexpensive or quick to install. For example, data volumes were growing rapidly and the CIO needed a hardware solution with the highest level performance, maximum dedupe and compression capabilities, resiliency, security, along with the other expected features.
Next step, we began using Hitachi’s Lumada. At this point we realized that a third and final element was required—we had the ability to store all of the business’s structured and unstructured data (which included both IT and sensor data) and we could store them both in the cloud and on the premises. The issues were this—the analytics, machine learning, AI and advanced reporting demand and insights that we thought would naturally or magically follow were slow to arrive, and in some cases never did.
The missing ingredient was DataOps, the framework we needed to replace the “build it and they will come” context. In recent months, DataOps has generated huge buzz. In fact, it’s been declared the answer for those enterprises looking to harness their data for value.
It is so simple, but we know simplicity is hard—the ability to get the right pieces of data to the right person when they need it most, all with the appropriate business context. And, as our CMO Jonathan Martin mentioned in his blog, “Cheers. It’s Time To Drink Our Own DataOps Champagne,” another challenge is sifting through the many potential use cases to pinpoint which one the business should focus on first. Gone are the days of Big Bang Data Oceans!
At Hitachi Vantara, we employed a methodical approach, with a dash of design thinking that connected the different stakeholders and functions. First off, we needed to begin with a discrete business challenge. After some discussion, the decision was made—we would begin our DataOps journey with marketing. That was progress of course, but we still needed to sharpen our focus and pinpoint a single specific area within marketing, and do so with urgency.
To do so we recognized our Digital Value Envisioning (DVE) methodology was the missing element that would be key to ensuring we maximized our investments in data. The DVE methodology is a collaborative development framework that Hitachi Vantara’s DVE team uses to efficiently and effectively bring value to our customers. As you know, Hitachi Vantara eats its own cooking and that extends beyond just our solutions, to include methodologies and frameworks.
Jonathan and I took part in an exercise and found it to be ideal because it provided a way to help teams collectively hone-in on a specific area that could benefit from DataOps. There are many options, which Jonathan outlined in his blog, and through this exercise we came together and successfully made our decision to leverage the power of DataOps to better predict our customer needs.
Using DataOps, the marketing team will be able to have more relevant conversations with customers WE KNOW need a DataOps Advantage—or more data center performance, simplicity, flexibility and cost-efficiency. With this insight, we can produce better bottom-line results for ourselves, while simultaneously providing customers the beneficial conversations and solutions they need, at exactly the right time. This is a true win-win and this is how we kill what I like to call the marketing spam to our customers.
As a CIO, it is imperative that we do whatever is needed to usher our business into this new DataOps era and put one of our two most valuable assets to work: Data (by the way, employees are our other most valuable asset; without them none of what I just described happens). However, we must resist the urge to open the floodgates and wholesale ingest zettabytes of data into a large container. Instead, chose a more disciplined and methodical approach that ultimately ensures repeatable success. This is how you begin a successful DataOps journey.