Data Gathering

Arguably, a child is born without intelligence. That's similar to the basic hardware that is a raw computer, also without intelligence. Humans collect data over time as they grow; computers collect data over time by interactions with consumers and the use of the platform.

Humans have two sides to their brains: left for analytical and right for creative. Computers have two types of data—left data and right data or structured data and unstructured data.

Structured data is the organized data used in our systems. Unstructured data is all over the internet with or without our knowledge. When both types of data combine, the two become big data and can be monetized with the power of the business platform.

Rather than roll your eyes or reject the term big data, consider this: prior to computers, then-massive amounts of information—data—were stored in files and piles of paper. Back then no one ever called it big paper, says digital data expert Yuri Aguiar, author of Digital (R)evolution: Strategies to Accelerate Business Transformation.

Of course, the millions of reams of data on paper pales compared with the massive amounts of digital data that's generated today. In 2019 alone, internet-connected devices (internet of things/IoT) generated 17.3 zettabytes (ZB) of data (1 ZB is 1,000,000,000,000,000,000,000 bytes—that's 21 zeros). That number is expected to top 73 ZB by 2025.¹

Turbocharged

Aguiar, Chief Enterprise Data Officer at London-based The WPP Group, likens monetizing big data via digitally enabled data science to a car's turbocharger. Most data—80 to 90%—that companies generate is likened to exhaust that's not being used. With a car's turbocharger, exhaust is recycled to create an extra boost of power. “What we are doing is recycling this data or turbocharging it,” says Aguiar.

Digital platforms also can analyze unfathomable amounts of unstructured data to find patterns far beyond the capability of a human or even a group of humans. In tech jargon, combing through all that data translates to the capability to find cognitive elements out of dynamic data sets.

Aguiar recounts an experiment in which an AI bot—a robot equipped with artificial intelligence—and a human watched the same video. The bot came up with 63 facets or descriptors that the human couldn't even fathom. “That tells me there are patterns in things that we as humans just can't identify,” says Aguiar.

Companies that do not invest in their data capabilities constantly must adapt or react, says Aguiar. That's inefficient and sets them back in most competitive business arenas. On the other hand, dynamic and visionary organizations make this strategic decision and stick with it, which leads to greater operational efficiency. These companies also are far more likely to be innovative in their businesses.

Data versus Intuition

That's not to discount intuition in corporate decision-making. Both data and intuition are tools available to companies and their leaders to make better decisions and drive better experiences for all participants.

Plus, sometimes what some people might think is a crazy idea isn't really and is the impetus that brings about change. When cofounder and then CEO of rideshare service Uber Travis Kalanick brought in surge pricing—paying more at peak times or when driving is difficult—people railed. But the company stuck to its guns and dynamic pricing is the norm today.²

The best decisions are those that are a combination of data-driven and intuition. For example, as discussed earlier, in higher education, machine learning (ML) can identify the early warning signs of a student becoming disengaged. Then, with trend data in hand, a counselor can make an informed decision on how to move forward to best help a student.

It's much the same with ACS, the carpet installer. CEO Joe Santagata relies on digital-reliant data science to analyze real-time data so that he can manage by leading indicators, not lagging ones.

The same happens at HHS. When its people have leading data, they can make better decisions, says CEO Bobby Floyd. In healthcare settings, for example, turning over a hospital room for a new patient is labor-intensive and often occurs amid a rush of additional patients. With platform-generated data, hospitals can now predict these rush periods and increase efficiency. That avoids backlogs and can eliminate patient delays.

Human Potential

In other words, data science complements human brainpower. We all have heard the myth that humans only use 10% of their brains—in reality we use all our brains to some extent.³ Whatever amount of brainpower we as humans do use, computers and data science can fill in the shortfalls.

And, when untapped human brainpower and computer intelligence combine, they become a superpower that has the capacity to make the impossible possible. That's digital maturity and the continuation of the never-ending journey to better, faster, easier. Exponential growth follows.

But keep in mind that data is just data, says UWL's Peter John. “Data gathers; it doesn't let you do things with it, and it doesn't have impact. You have to use it to be constructive, innovative, and different,” he says.

When It Works

Information and its quality certainly work as an asset for HHS. Floyd points to a community gateway system that it has developed for an acute-care hospital. In the past, collecting the right referrals and identifying hospital vacancies as part of the patient admissions process was extremely cumbersome and usually required multiple staff telephone calls.

Now, with the help of a digital platform that HHS and its partners developed, doctors and medical teams within the hospital's system of care have direct visibility to vacant beds. That's streamlined the referral and admissions process to the point that medical professionals prefer the ease of using the hospital's system over others in the area. That's boosted patient numbers and bottom lines in the process.

The digital platform works so well other area hospitals that initially weren't part of the rollout now want to be included on the platform. It's a win/win/win for everyone—including HHS—in terms of data, process, and experience as well as financial gain.

The Tesla vehicle is another business platform that disrupted the market, but not in the way many may imagine. Tesla isn't an electric car; it's a great example of an intelligent business platform—a software platform inside a moving iron box.

The car is the experience channel. Data and process control its movements. A “driver” holding the wheel is the experience.

Digital Connections

The number of digital connections we already rely on regularly can be mind-boggling—from data points to apps, to visual and voice elements, big data analytics, and beyond. Says Aguiar:

I wake up in the morning to the alarm that I've set on my phone for the entire month. My coffee already is brewed thanks to instructions input on my smartphone and conveyed over the internet to my smart coffee machine. I get in my car to drive to an appointment and my digital assistant, with its British accent, reminds me to “buckle up.”

I plug the address of the appointment into my GPS, which relies on satellite uplink and downlink connections to guide me. Driving to the appointment at 60 mph, I'm on a hands-free conversation with someone in Australia. As I drive, the call bounces off various cell towers and I'm automatically being billed for my data usage as I talk. Once at my destination, I stop to make a lunch reservation on Open Table, after checking out the app's suggestions for nearby restaurants. And, when I'm in the elevator, I check the score of last night's New York Giants game.

That is the reality of my life. By the time I get into my office, I've already consumed from about 1,500 data sources.

This is likely your life and that of most people at most companies around us.

The Numbers

Still not convinced ours is a digital world and it's time to embrace the platform? Consider just one aspect of the digital footprint: voice-activated devices. On a planet with about 8 billion people, there will be 24 billion voice-enabled devices by 2023. At the same time, the number of devices with digital voice assistants (like Siri, Alexa, Google, and so on) will top 8 billion, according to Statista. That's up from 3.25 billion in 2019.⁴

With 24 billion devices, we have to believe they're reaching all markets everywhere, says Aguiar.

Data Science Insights

Already big data seamlessly connects us to make our lives easier. Aguiar, who regularly travels from Long Island in New York to the same Florida destination, recounts his regular routine:

• A rideshare company from his Long Island, New York, home to John F. Kennedy International Airport.
• A Delta Airlines direct flight to Fort Lauderdale.
• Pick up a rental car from Hertz at the airport.
• The return to Long Island is the reverse—Hertz to the airport; Delta to JFK; and a rideshare to Long Island.

All these data points—Aguiar's experiences—connect in the background. The business platform has learned something about him and uses that to analyze his patterns and make suggestions. Aguiar is a Delta frequent flyer and belongs to Hertz's affinity club. As a result, whenever he types his membership number into Hertz or Delta online, related advertising, suggestions, or information that fits with his habits and interests pop up.

If Aguiar suddenly changes his travel routine—perhaps flying to Atlanta or stopping at a restaurant for Italian food en route to JFK—the platform analyzes the changes and modifies its deliverables to him accordingly. This is hyper-personalization in action.

Growing Market

In 2021, estimates pegged the number of IoT devices in the world at more than 31 billion, up from just 7 billion in 2018.⁵ That's nearly four times the total population of the world.

An accurate estimate of the future reach of IoT is tough. Let's just say tens of billions more devices will be in use tomorrow. Companies could invest a total of up to $15 trillion in IoT by 2025.⁶

The size of the IoT global healthcare market alone is forecast to grow from nearly $61 billion in 2019 to $260.75 billion through 2027. That market growth (a 19.8% compound annual growth rate—CAGR) is fueled by growing focus on patient engagement, patient-centric care, growth of high-speed network technologies for IoT connectivity, and the growing need to control costs in healthcare.⁷

On-Demand Services

Data logic and experience are front and center in the fitness business with two popular systems, Peloton and The Mirror. Both offer variations on IoT-powered boutique fitness classes in your home. Peloton utilizes various self-manufactured fitness equipment like treadmills and bicycles with internet-connected instructors. The Mirror provides the virtual fitness assistant literally in the mirror as you exercise.

Both are business platforms with data that deliver and gather intelligence. The more intelligence gathered, the smarter the system becomes in the form of predicting or suggesting the next “class” or fitness routine. This automated machine learning reflects the power a platform brings to data science. After all, data science predicts what does not yet exist.

That same logic applies in the medical field to smart or intelligent hospital beds from makers like Hillrom, recently acquired by Baxter Technologies. With internet connectivity these beds enhance patient care by connecting patient needs and actions remotely with caregivers.

Enabling Consistency

Joe Santagata, the company's CEO, wants growth for ACS, not only in size as in numbers—his personal goal is to double his business—but also in consistency with technology as a driver. He points to fast-food giant McDonald's. The chain is deliberate and even maniacal in its operations. Even the simplest things are done the same every time and in every location. It's a culture and a replicable model, says Santagata.

If with the help of AI that consistency can be replicated at ACS, then, he says, he can spend his time working on the business and growing it as opposed to working in the business, constantly problem solving on day-to-day issues. For example, on the customer service side, AI can provide valuable analytical insights.

Traditionally, if ACS has an issue with a customer, they pull phone call records and data from the system. But with the help of AI, the company can extract data before it becomes a problem, Santagata says, and do more to help people more consistently.

Innovative thinking and use of platform-generated data can end up a value add for companies. Perhaps in the future a company like ACS could develop an innovative technology or use of a technology and end up supplying value-added goods or services to other companies. After all, smaller companies are much more agile than the large behemoths and can pivot more quickly with market demands. Those companies can more easily take the lead with the help of digital operating models.

Transparency and Control

Said Hathout of Bahrain-based Al Hilal Life sees on-demand self-service and transparency as big value-adds that his industry can deliver to its customers with the help of business platform technology. That means potentially a policyholder could have full access to their policies and the ability to make changes without the need to go through a very long process to change even one small thing, says Hathout.

The concept of renting life insurance during specific activities or for a certain period of time—like travel insurance, for example—versus owning the policy is another potential option, says Hathout. “I'm not talking 10 years in the future, but maybe next year.”

Though life insurance is usually a difficult product to sell because of its complexities, technology—as in the business platform—can make these various options possible.

Gary McGeddy of insurance giant C&F also sees an on-demand, digitally enabled future in his industry. Perhaps like instant payment platforms deliver fast cash, there could be an instant travel insurance payout system that delivers on the promise of money back to consumers in their time of need.

Let's say someone's plane has been delayed three hours. If that person bought a travel insurance policy with a travel-delay benefit, at three hours and one second their benefit would appear in their checking account. That's the utopia of travel insurance, says McGeddy. But that also will become table stakes as consumers demand it.

“We owe the consumer the promise (of payout), so why do we make them fill out the form? That's the legacy process in place,” says McGeddy. “(Right now) to go to that type of purely virtual environment is wildly expensive and a huge investment of time.”

But, he says, “We have to pay attention to what it is people demand as consumers.” That includes ease and access.

An Ecosystem

A simplistic way to look at blockchain is it's a software platform, a community, and an ecosystem that is made up of a chain of records stored in the form of blocks that link together chronologically and aren't controlled by a single entity. The blockchain creates a trust based on cryptography, decentralized databases, and consensus mechanisms.

Blockchain is the next step toward disruption, says Cesar Castro, Founder and Managing Partner of Escalate Group, and a digital transformation and disruption expert. After Internet 2.0 comes blockchain, and it is allowing innovators to capture economic value in open ecosystems, he says.

When the internet happened decades ago, it was about making information and communication available anywhere without the use or need for paper. Now with blockchain, we're enabling the Web 3.0, adding trust to the mix so anyone can send digital property and digital value to anyone, anywhere. Web 3.0 is creating the incentive structures required to solve the world's biggest problems, says Castro.

The blockchain has enhanced smart contracts—contracts written in code that are executed automatically without human intervention. It's secure, and because it's immutable, the records can't be changed or tampered with, says Castro. It's a decentralized community with protocols behind it and centered around absolute trust.

Ultimate in Security

Blockchain is a public wall that provides the ultimate accountability and transparency, says Rohan Sharan, a recent graduate of Indian Institute of Technology (Kharagpuru, India) and a digital entrepreneur. Sharan is an advocate to bring innovation and disruption into the marketplace with blockchain and through cryptocurrencies like Bitcoin (bit is the monetary value and coin is the money).

In finance, for example, there are certain recording requirements that traditionally involved paper. Blockchain replicates the nature of the paper trail but brings it into the digital world with a permanent, unalterable record, says Sharan. Block history cannot be deleted so there's traceable ownership. Theoretically it also removes the middleman from transactions, removing extra fees in the process.

Peer-to-Peer Payments

Cryptocurrency, specifically Bitcoin, originated as a way to deliver peer-to-peer micropayments—electronic cash—via the internet. Blockchain is the neutral ledger for Bitcoin (and other cryptocurrencies) to be issued. Every 10 minutes the chain is extended with a new block added, says Sharan.

Cryptocurrencies are traded via decentralized digital transactions on online coin exchanges utilizing blockchain technology. That compares with the more traditional trading of financial assets on highly regulated financial exchanges like stock markets. There are literally hundreds of cryptocurrencies that are traded or mined (in the jargon) today.

New Reality

“What we have is a marketplace for computer transactions to happen worldwide,” says Sharan. “All data, all transactions happen on the public blockchain, so instead of private databases like Facebook and Twitter, connectivity happens by default and at minimal or no cost. Users own and control their own data that's all stored on the public blockchain.”

Already, blockchain technology's accuracy and broad accessibility is such that it can enable confirmation of transactions without a centralized clearing authority. That can expedite and lower the costs on currency transfers, corporate transactions, even voting.

Castro predicts that soon this decentralized protocols approach will move to social networks—it already has but remains niche. With the power of blockchain, individuals will maintain ownership of their information and the value they create.

This will happen in most industries, says Castro. And very fast, too. Already it's happening in the finance sector, though it remains somewhat complicated for the average user. “All this will become simpler and only grow,” he adds.

Wrong Conclusions

With basic machine learning, a bot can learn to return better information incrementally with limitations. But it still can draw wrong conclusions that require human interface to correct. For example, someone makes the statement, “It's raining cats and dogs.” A bot with ordinary machine learning capabilities assumes the literal translation—cats and dogs are falling out of the sky.

However, when deep learning capabilities are added to machine learning, the algorithm can figure out the real meaning—it's raining hard outside. It's this deep learning that has the ability to totally disrupt.

Power of Disruption

A mainstream use of deep learning is language and dialect recognition and some advanced chatbots. For example, if we ask a smart phone or smart speaker, “Show me restaurants with spicy food in my neighborhood,” that's the voice-enabled experience model at work. Or, if we call for an airline reservation, the moment we select one option, we get more and related options.

Though the computer learns as it progresses, today it's only the beginning. This is deep learning in the toddler stage. There's not the ability yet to generate enough data to guide consistently accurate direct interaction without human intervention.

Timesaver

HHS, the hospitality organization, capitalized on RPA with its business platform and slashed its data error rates, freed a number of employees for more creative work, and saved money in the process.

Bots also are used widely in interactive chats as part of customer service, bank reconciliation, generating reports, and in hiring. With the latter, these automated systems initially sift through and weed out unqualified candidates. Then with new hires, the bots can enhance training and cut down on the tedious filling out of lots of different forms.

As more companies embrace the digital operating model, more will look to RPA to solve data accuracy and other business challenges. That includes inventory distortion—out of stock and overstocked merchandise that amounts to $1.8 trillion worldwide annually. That's more than the gross domestic product of Canada! Potentially bots, with more accurate inventory counts, could dramatically curtail some of those losses.⁸

Limitations

But robotic process automation today still has limitations. In insurance, for example, RPA can bring speed and accuracy to analyzing risk for a basic pet healthcare policy or travel insurance.

But, to assess and write a $25 million umbrella policy is more nuanced and requires a more complex and personalized approach. Perhaps tomorrow intelligent RPA will change those limitations.

Better Experience

The labor shortage is very real, says HHS CEO Bobby Floyd. “And, I'm not 100% sure it's a function of the COVID-19 pandemic. I think there is a portion of the workforce that is not going to return.”

That realization has prompted Floyd, along with other chief executives, to explore what tasks can be successfully completed with robotics. Robotics makes sense, Floyd says, because labor is not available, or if it is, it's very expensive. Plus, as the costs of labor go up, the costs of robotics are coming down.

That presents a great option with one big caveat. “What we have learned the hard way is that the technology isn't really there yet,” Floyd adds. “It's come a long way … but we have found in some cases when we purchase robotics and we hear feedback, our people spend more time managing the robots than themselves. Using the goofs, though, as learning experiences, it will get there. It's come light-years from just five years ago.”

Remember the network effect? That's the proven concept that as more people turn to the business platform, recognize its value, and begin to demand that value, the use of the platform grows. It's all about tapping the potential of technology to make our lives better. And the network effect will only grow into the future.

The cryptocurrency phenomenon is a great example of the power of the platform and the network, and how as its advantages spread more people demand and expect the value it offers.