Principles of Change: How Big Data is Shifting Paradigms One Industry at a Time
Last Thursday evening, Ginni Rometty, IBM’s chief executive officer, essentially made lightning strike twice.
Standing in the exact place where IBM launched its globally recognized Smarter Planet campaign just five years prior, Ginni shared her “3 Principles of Change” at the Council on Foreign Relations in New York City.
The change that she discussed is centered on the fact that we now live in a world where industry leaders effectively analyze all available data, while laggards tend to archive it – or, worse, ignore it – without realizing its full potential. In fact, Ginni stated that “data is indeed the basis of competition in the 'smarter' era. And Big Data is indeed the next natural resource – promising to do for our era what steam, electricity and oil did for the Industrial Age.”
These Principles serve to remind us that we all do three basic things:
- We make decisions.
- We create value.
- We deliver value.
In order to “mine” that “next natural resource” for valuable knowledge and embrace the possibilities of new insights, Ginni suggests we remember the following:
- Principle 1: Decisions will be based not on “gut instinct,” but on predictive analytics.
- Principle 2: The social network is the new production line.
- Principle 3: Value will be created not for “market segments” or demographics, but for individuals.
However, she also reminded us that the real challenge is culture, and even the most significant big data discoveries can’t change an industry if the people themselves don’t want it to change. It’s the people that need to be willing to harness the power of big data for a new economy.
This isn’t just an “old dogs, new tricks” game. It’s a massive paradigm shift that opens new doors and creates new possibilities that are an order of magnitude different from what previous generations had at their fingertips… just like steam, electricity and oil. (Take a moment to ponder what your world would be like without any one or all of those resources.)
How do we embrace this paradigm shift? We can start by looking at things we see every day in ways we’ve never seen them before. For example, this week the Wall Street Journal put out a series of articles that speaks directly to this buzz-worthy subject.
In “The New Shape of Big Data,” we learn how researchers turn to esoteric mathematics to help make sense of massive sets of historical data. By aligning the right tools, technology and talent, leading organizations – from a wide variety of industries – are developing new algorithms capable of handling today's ever-changing, ever-growing and ever-demanding data sets.
In “Big Data, Big Blunders,” we learned about the five mistakes companies make—and how they can avoid them. My guess is that each one of us can relate to a few of these, if not all of them:
- Data for Data’s Sake: Don’t get “seduced by the promises of big data” without first establishing clear goals and objectives for why you want to mine the data. In other words, don’t just dig for digging’s sake…. dig for gold, dig for results.
- Talent Gap: As Jesse Harriott, chief analytics officer of Constant Contact, said, "It's an acute skill shortage out there," when it comes to using big data analytics to help companies – and specifically their customers – to be successful. This is where it becomes absolutely essential to align your big data strategy with the talent required to achieve your goals.
- Data, Data, Everywhere: There’s an evil word that fits this bill: silo. If you have the data, but you can’t access it, can’t organize it or can’t use it, you’ve got a binary mining operation that will never see one single nugget of success.
- Infighting: This one is simple: CMOs & CIOs (and their CTOs as well) need to be BFFs. Anything short of that will result in wasted opportunities as opposed to collaborative planning that’s rooted in mutual success.
- Aiming Too High: Rome wasn’t built in a day. Start small with your big data and get used to answering questions, solving problems or overcoming challenges – one step at a time. I like to define this as the “4 Phases of Big Data”: Educate, Explore, Engage and, finally, Execute.
It’s obvious now that big data really is changing the whole equation for business.
From people to products, from pitches to parcels, from automobiles to artists – big data analytics are being deployed to build out a 360o view of the customer (and beyond) in unprecedented ways that either took extended periods of time to complete in the past or… was simply impossible to do.
How has big data changed your world? Leave a comment below to tell us.