William (Bill) Schmarzo, known as the Dean of Big Data, has the secret to making money from the Internet of Things (IoT): Transform from connected to smart.
"Of course, then the question becomes, how do you create smart?" says Schmarzo, whose official title is Chief Technology Officer (CTO) of the Big Data practice at Dell EMC Services. He's also the author of Big Data: Understanding How Data Powers Big Business and Big Data MBA: Driving Business Strategies with Data Science.
Schmarzo will provide some useful hints to attendees of the premier Ayla Connect user conference, being held April 10 to 11, 2018, at the Omni Hotel San Francisco. At 9:00 am on Wednesday, April 11, Schmarzo will present "How to Monetize Your IoT."
We spoke recently to Schmarzo about big data, IoT, and Ayla Connect.
Can you give us a sneak preview of what you'll be presenting in your 'How to Monetize Your IoT' talk at Ayla Connect?
My talk will help attendees explore some fundamental questions that include:
- How can you become effective at your organization at driving business value from data? I'll introduce my Big Data Model Maturity Index, which is useful for knowing where you stand and how you can progress in your data monetization goals.
- What is 'smart,' and how do you create it?
- What are the basics of data science? I believe that any business person can learn to "think like a data scientist"-to become what I call "citizens of data science.
- How can you monetize data-and specifically, the big data generated by IoT?
Which of these questions is the most difficult for people to grapple with?
In my experience, the whole idea of monetizing data is the hardest. The problem is that the basic ways that organizations and analysts approach data is wrong.
The business accounting systems of today's organizations can be traced way back to 1776, when Adam Smith first published The Wealth of Nations. He laid out the argument for 'value in exchange'-that things are worth what people are willing to pay for them.
But that model doesn't hold up with today's data technologies. Instead, we need to pursue a 'value in use' model. It's an economics rather than an accounting conversation.
What the biggest challenge for organizations trying to make that shift?
Fear of failure. But failure is the fundamental way we learn. As businesses try to make predictions about the future, they are going to need to get comfortable with failure as a way to learn. Too few executives are willing to fail because they think it's uncool. Failure is the new cool.
Today, most companies use data and analytics to monitor their businesses. Organizations need to move beyond this approach for leveraging their data and analytics. In the transformation world, data needs to be used to predict, prescribe, and prevent actions. It requires looking to the future, not to the past.
Many chief information officers (CIOs) have risen to fame riding the "mega big bang" ERP implementations. They have a lot of personal investment in that achievement, and they sometimes hang onto it for dear life. They're not likely to leave that security blanket to do something new.
But in a data-driven world, it's necessary to change our thinking quickly, to be willing to throw out the old gospel. It's necessary to think about investing in IT not as a source of parity, but as a source of differentiation. Because if everyone has the same ERP system, where's the differentiation? No one ever gained market dominance by having the best HR system.
But as you say, it's hard to give up on what's worked in the past.
That's true. CIOs today are scared to death because they need to change their frame of reference and realize that their old ways of working are not setting them up for success in the future.
I'm part of that baby boomer technology generation, but I've nearly given up on my generation of CIOs. Honestly, how many current CIOs do you think have-and use-an Amazon Echo in their homes? By the way, I do (heck, how do you think I order my Cap'N Crunch!).
I have much higher hopes for the Gen X and Millennials, who have grown up in a much different world. They have a fundamentally different way of interacting with apps. I'm hoping that generations of CIOs will be able to use data and analytics in ways that help them and their organizations to be more effective at powering their business models.
What are some particular big data-related issues that pertain to the IoT?
The IoT is about capturing lots more granular data across a huge range of sources. In the IoT space, organizations need to move beyond thinking about making discrete smart IoT products. Instead, companies need to think about how to harness the big data generated through IoT to create smart experiences.
Take airports for example. Think about all the ways you could use data to improve the experience at airports.
Here's one simple example. Let's say a huge 787 Dreamliner jet is going to land after a 10-hour flight, disgorging its 300+ passengers into the terminal. That's not the time to schedule the maintenance crews to clean the bathrooms. Instead, knowing that the plane is due to land soon could be a signal to clean the bathrooms ahead of time, so the passengers entering the terminal have a clean, well-stocked bathroom to use.
In other areas of the airport, you could use video cameras and sensors to tell how long people are standing in TSA lines, to trigger that the opening of a new line or the addition of more TSA agents. And imagine how 'smart itineraries' could work, knowing when a flight is delayed by 2 hours and providing passengers with options for entertainment such as visiting an in-airport museum or art display. Maybe the airport shows a movie for those delayed passengers, or suggests which restaurants are open and reserves seats.
That same approach-how can we improve the guest experience, the operational experience, the customer experience? -can be put in motion to drive new sources of customer value, and ultimately new sources of revenue.
And that's what the monetization of IoT is all about.