Data Transparency In A Non-Transparent World

Unless you live in a cave and have never touched a smartphone or computer, you probably know that it’s impossible not to leave a personal data trail online. The invisible cookies are always watching our activities and the algorithms are always making suggestions for the benefit of the digital economy. With all of today’s connected devices, our society will soon be awash in data. Once data is produced, it rarely fades away—like a permanent marker you can’t get it off the wall, no matter how much bleach you use. Companies have been busy minting money by monetizing our personal data. In return, we get to use their app, website, or service for “free” and/or get a personalized service. As a result, we are becoming a type of product ourselves as nothing comes for free.

Sometime back I had published The Business Value of Trust report, highlighting the fact that 63% of consumers surveyed believe companies are accessing personal information that was NOT explicitly provided for their use (social network profiles, contact lists, location data, etc.). It is no wonder that consumers have a growing concern over their lack of control in how their data is mined—in fact, 53% of consumers don’t believe the claims made by companies about protecting their private data. Many companies believe they have done their job by publishing policies regarding data privacy and security, but over half the consumers we surveyed told us, “Those policies are Greek to us!” That’s why we all glaze over at the “Terms & Conditions” before pressing the “I ACCEPT” button—no matter how hard we try to protect our information, it’s almost impossible to do it.

Unfortunately, the deepening issue here is the growing lack of trust between consumers and the companies that use personal data in a way that was not expected. So, it’s not really surprising that consumers perceive very few industries as highly trustworthy when it comes to the use of their personal information. On average, only 43% of consumers have a great level of trust in institutions across industries. Considering these facts, we can’t continue to sit around and quibble about the data pigeonhole; instead, we need to address this enormous issue by flipping it on its head.

With all the fervor over data these days, we really need to start recognizing its true value and understanding that all data created by us is our personal property, not the property of the company that collected it. As consumers become more educated about how companies are using their data, they might be willing to assume more risk in exchange for more than simply a personalized experience or a free service. In fact, 72% of consumers surveyed feel that cash rewards would motivate them to share their personal data with companies. This kind of open and transparent trade-off, called the give-to-get ratio, will be the new norm of consumer trust in the future. It’s up to us to decide what we choose to disclose or not disclose about ourselves—in which contexts and with whom. I pondered over the issue of why we deserve more for our data here.

As consumers begin to demand full control of their data, there will be a need for a new role that will bring transparency upfront by ensuring consumers receive maximum value from their data, and we believe a “Personal Data Broker” role will emerge in the future. The Personal Data Broker will monitor and trade all forms of personal data that a client (consumer) creates from his/her micro data feeds; execute data trades on behalf of consumers; and track new ways of maximizing a client’s return on data. Workers in this new role will establish prices and execute trades while mastering the new global code of ethics surrounding interstate, international, and regional data trades. We have thoroughly outlined our vision about this role in our new report: 21 Jobs of the Future. In the report, you can read the exact job description for this new role, along with information about its roles and responsibilities, and the skills and qualifications the role will require in the future.

It is undeniable that we need to establish more open and honest conversations about the future of information sharing and how we want our data to be traded in the digital economy. We deserve more for our data, and while it may sound odd today, signing ‘personal data contracts’ may become a new normal in the future, so make sure you’re ready for it.

Oslo Signposts on the Future of Work

It was a real pleasure to attend Cognizant’s Norway event designed to light up the future of work and the future of Norway. The country feels that it’s at a crossroads but understands how the shift into software is changing how its firms capture value. What we learned during the day was how industrial processes are becoming infused with data. Buried in the data is meaning and that can radically shift a cost structure downwards.

First some backdrop: Norway did a smart thing with its riches from the 1970s oil boom. It has the world’s largest sovereign wealth fund set up to manage the huge profits Norway generated from the black gold lying underneath the North Sea. To say its done rather well is an understatement: it has just under €1 trillion in assets, while its net worth was recently calculated at €164,000 for every single one of its citizens alive today. Interestingly, those responsible for running the fund are beginning to make noises that perhaps the time has come to stop its global investments in oil and gas. The reason? It wants to make the government’s wealth less vulnerable to a permanent drop in oil and gas prices.

What intrigued me was hearing that Norway’s sovereign fund holds one of the largest positions on Alphabet, Amazon, and Apple etc. i.e. those companies that make meaning and an awful lot of money from our data. You would think that the large contingent of oil and gas customers present at our event would be downbeat, but not a bit of it. In fact, it was fascinating to hear how this particular sector more than any other is using super-powerful computers, data mining techniques and advanced algorithms to increase yields and drive efficiencies. One particular presentation struck a chord with me, and that was from Kvaerner and its impressive CIO, Frode Strand

By now you will know how much I like to talk about platforms, so it was fascinating to hear from a company that builds real, physical platforms and at HUGE scale (my childhood passion for Meccano reawoke). These platforms are used to drill for oil and constructed from hulking steel structures called jackets that sit out in the North Sea and endure. We learned how the designs of these huge rigs vary depending on height and geology. Of course, they cost an eye-watering amount to build. We learned how Kvaerner is beginning to use machine learning to drive the better design of these jackets because they were so darn expensive to build. Who knew that the design decisions of where to put the braces could vary quite so much with massive ramifications on cost and profitability? The placement of braces; the number and position of brace rows; the location and elevation of the legs that plug into the sea-floor; the joint optimization etc. the list goes on. A tiny miscalculation throws out the jacket and can cost millions to the bottom line.

The CIO saw this as an “optimization challenge” and wanted to build a model and use data and algorithms to generate and analyse various designs to arrive at a viable solution quickly. Do that, and he surmised, he reduces the cost of steel needed to build the rigs and the overall build time. Do it right, and Kvaerner would save millions in raw material and manufacturing costs. He set out to design an algorithm and deploy the massive computing power needed (a mix from the cloud and onsite from what I could gather) to generate and analyse the various designs and to arrive at a viable solution quickly. This design would then be optimised for weight and/or cost and/or build time. And he did according to his slides. His model has several thousand parameters with constraints and rules programmed in. The resulting algorithm works and looks set to be monetized. Go and see him speak to hear the story – like I say it was fascinating to hear and a very unexpected and enthralling 40 minutes.

There was something very real about what Kvaerner are doing. In this accelerated world of digital where we obsess over customer experience and their “next best actions”, it is worth remembering how our physical world still matters. These wise words from our very own analytics and AI lead at Cognizant James Jeude who also presented at the event really brought it home:

"Everything we touch, own, or use ultimately comes from mining, fishing, or farming."

I couldn’t agree more. It is a profound thought when you think about it. James gave a very illuminating presentation on the definitions of AI and explained his three M model (machinery, material and model). I would recommend reading his work on Storytelling and AI because it teaches the art of fact-based storytelling that not only informs but inspires meaningful decision-making and keeps key stakeholders aligned and engaged. Something we saw from Mr Strand in spades.

At the end of the event, we heard from the incredible, gutsy Karina Hollekim who was one of the world’s best extreme sports athletes until her parachute failed to open after doing a base-jump (she had it live on camera too, so it was painful to watch that jump unfold). She was predicted a life in a wheelchair but came back a winner. She is fully mobile and skis and hikes again. Talk about grit; she is indomitable. It was a story to remember.

P.S. You know you are onto a winner when the host for the event nonchalantly explained how he had hot-footed it from Windsor Castle after performing for the British Queen and Prince Philip to celebrate their 70th wedding anniversary the night before! His flying table trick left both them and us questioning our senses...

Every click, swipe, "like," buy, comment, deposit, jog and search produces information that creates a unique virtual identity - something we call

Code Halo

Code Halo TM
Learn more »

Humans, Machines And The Future Of Collaboration

The meaning of collaboration has evolved over time. The first email was sent in 1971 and after that, the Internet age completely changed the way we connect and collaborate with each other. Fast forward to today, and we are on the verge of re-defining collaboration between humans and machines. So, what do we do when machines do everything? Ultimately, the answer depends on whether you are a pessimist or an optimist. While it’s true that many types of repetitive jobs will disappear due to automation, a world without work will always be a fantasy. As a result of our fear of losing jobs to automation, we are overlooking the possibility of the human + machine collaboration that has the potential to transform our industries, businesses, workplaces, and jobs. We need to stop looking at humans and machines in contrast to each other and imagine a world of human-machine collaborations, which would be more engaging, fun, and challenging.

We are in an incredible time, when technology is significantly extending the envelope of human capability. While humans are good at the art of the job (judgment, visual cues, emotion/ empathy, ethics, and social context), machines are good at the science of the job (computational capabilities, data analysis, pattern recognition, and next action determination based on all statistical facts). When we combine the strengths of humans with the strengths of machines in a joint environment, magic happens. This human-robot duet perfectly weaves together the art of dance and the science of mechanical engineering. The future of work will be based on how well companies blend and extend the abilities of humans and machines by making them collaborative. Human-machine collaboration is the new hybrid workforce.

So, how can we ensure the transparent communication between humans and machines? How can we translate consumer and employee needs, and business strategies into machine experiences? Who will define roles and responsibilities, and set the rules for how machines and workers should coordinate to accomplish a task? These questions demonstrate the need for a new role that will create augmented hybrid teams to generate better business outcomes through human-machine collaboration. This new role of “Man-Machine Teaming Manager” is highlighted in our new report, 21 Jobs of the Future. The key tasks for this role are to develop an interaction system through which humans and machines mutually communicate their capabilities, goals and intentions, and to devise a task-planning system for human-machine collaboration.

The Man-Machine Teaming Manager will shape the future of work and its various workplaces within companies by turning machines and workers into collaborative “colleagues” in order to reach entirely new performance thresholds. As a teaming manager, you will identify tasks, processes, systems, and experiences that can be upgraded by newly available technologies and you will imagine new approaches, skills, interactions, and constructs. You will design flexible experiences that meet workers’ expectations, while providing a simple and intuitive interaction with machines (translating consumer behavior to business users, as well as to machines, for instance). We have developed an exact job description your HR department will need to fill this new role and advance human-robot cooperation strategies in a dynamic business environment.

In the future workplace, your career potential will no longer be based on your last job title, but instead on your ability to collaborate with machines for the work ahead. At the heart of human-machine collaboration is the simple idea that nearly every person and job, can and must be improved through technology. Whether management likes it or not, leaders who recognize that collaboration is the key to business success will be more desired in the digital workplace. Fostering collaboration is a work skill that will be in great demand in the near future, and your organization must be ready.