Much our future as it unfolds relies on data. Whether it’s the evolution of digital twins or the ability of AI to aid in gene therapy, data is the engine. As the possibility space expands, so does the challenge associated with an overwhelming amount of data. A visual via Visual Capitalist brings that scenario into focus using a connected car example. This related article highlights some of the potential obstacles. As with every scenario we envision, obstacles exist that slow or negate the scenario, while accelerants do the opposite. Envisioning possible futures requires us to understand both sides of this phenomenon – and doing so on a constant and iterative basis.
(more…)Category: Digital Foundation
The foundation of the science and technology curve
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A Conversation With Ameca – The Humanoid Robot
Ameca has already proven to be an impressive demonstration of state-of-the-art humanoid robots, with her uncanny ability to contort her face into extremely believable, human-like expressions, ranging from disbelief to disgust. Now, thanks to the power of GPT 3, Ameca is able to converse as well, in an impressive extension of what modern robots are capable of.
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Why Does Digital Transformation Fail?
Let me start by stating I dislike the overused word transformation. I like it even less when it is paired with the word digital. First, if we are not in a perpetual state of transformation in this era of uncertainty, volatility, and rapid pace, we are not likely to advance our organizations or society. Second, digital is foundational and should be part of the fabric of any business, not an optional transformation initiative. When stated as digital transformation, it feels like an event as opposed to standard operating procedure. Are you considering the use of emerging technology to create value? That’s an everyday activity given how many technological building blocks exist and how many are on the horizon. Considering a new business model? It is not the transformative event it once was, but something that happens with regularity. Extreme event rattled the status quo? Likely part of the standard operating environment going forward.
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Revisiting Digital Transformation
Many have drawn the conclusion that those organizations that invested in digital fared much better during the pandemic. When I think back to my early digital transformation content, the forcing functions that I felt would drive organizations to transform seemed clear. So why has the pandemic identified winners and losers? This question had me thinking about a discussion I had recently with colleague Hassan El Bouhali, where we reflected on the past several years in the context of what we expected and what actually happened. We specifically focused on a 2017 Video that Hassan, TCS CTO Ananth Krishnan, and I, did for an online course exploring the future. We decided to produce another video in the near term that reflects on our thoughts from four years ago. In the meantime, I started to revisit my older posts with reflection in mind, starting with my Thoughts on Automation from 2014, and then thinking about the digital discussion going on today.
In 2018, I explored what I felt was At the Heart of Digital Transformation. What strikes me from that post is how often I hear the word resilience today, and how infrequently I heard it back then. In 2015, I had a fascinating discussion with Futurist Gerd Leonhard that I captured in a post titled the Digital Transformation of Business and Society. To this day, that continues to be my most viewed post. It was a wide ranging conversation that covered topics like automation, society, digital governance, and technological unemployment. Gerd spoke of things like, instead of AI, we should refer to it as IA – or intelligent assistant. The key take away from that session was this:
(more…)The future is exponential, combinatorial, and interdependent: the sooner we can adjust our thinking (lateral) the better we will be at designing our future.
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Transformers Prioritize AI Investment
There are many examples of COVID-19 serving as an Accelerant. History and necessity tell us that automation is one of those examples. According to a Business Insider survey of 53 leaders featured in the Transforming Business series, AI and Cloud are at the top of the list of transformation that companies will invest in during 2021. It’s on the agenda of 47% of those surveyed. The connection to the pandemic can be seen in examples of where automation is applied. This recent Article describes a scenario where social distancing requirements are met through automation. Author Joe Mullich points to the kitchen of a burger joint, where a hard-working fry cook named “Flippy” is paving the way for greater use of artificial intelligence and cloud technology in the restaurant industry.
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Organizing For Disruption
Back in 2015, I was looking at emerging organization models for a societal shift to a very different era. While organizations have experimented with many of these, the truth is, most still struggle with this critical structural change. One impactful model was positioned by Geoffrey Moore in his book titled Zone to Win. Given how relevant the topic is today, I am reposting my synopsis of the book below. In addition, here are three additional posts on the topic:
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The Digital-First Enterprise
This week I attended the Annual Directions Conference held by research firm IDC. Because of the coronavirus, the conference was held online. Here are some of the key messages – a deeper analysis is provided by Michael J. Miller, chief information officer at Ziff Brothers Investments and can be found Here.
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From Automation to Hyper-Automation
In a recent Article, Gartner says that no single tool available today can replace humans in the workplace. The article goes on to say that hyper-automation is a response to this challenge – bringing together different tools, technologies and techniques to amplify every company’s ability to automate more processes, more rapidly, with better results.
It is no secret that productivity has slowed. In a Post from 2016, I described this phenomenon in detail. According to Wikipedia, productivity is an average measure of the efficiency of production. It can be express
ed as the ratio of output to inputs used in the production process. In a Citi Report I shared in that post, they describe the significant slowing of labor productivity growth, which drives a focus on next generation gains. But In spite of technological progress and innovation, measured productivity growth is low by historical comparison. -
5G is Likely to Accelerate Innovation in the 2020s
As a foundational piece of the Fourth Industrial Revolution, 5G is likely to drive the human development that many anticipate. Viewing 5G through the lens of convergence provides an organizing principle that allows us to leverage insight across domains and derive foresight as a result. 5G, the next generation of cellular mobile communications technology, is the best example of convergence – as geopolitics is getting involved in emerging technology decisions and technology discussions are influencing geopolitics.
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Agility
Agility is one of those buzzwords that can have many different meanings. In a recent article by Leo M. Tillman and General Charles Jacoby, they define Agility much the same way I think about it:
Agility is the capacity to detect, assess, and respond to environmental changes in ways that are purposeful, decisive, and grounded in the will to win
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Target Transforms by taking a Long Term View
A recent Article describes how Target transformed from a Retailer with stores in disrepair and leaders that struggled to adapt to changing consumer behavior, to a company that is thriving. Their first quarter results for 2019 beat analysts’ expectations, the store’s private-label lines are exploding, and the stock price is trading at an all-time high.
Target CEO Brian Cornel made a huge announcement in March of 2017 that it planned to invest over $7 billion in a turnaround strategy – Wall Street was not impressed, as Target suffered its largest stock plunge in almost a decade on the day of the announcement. But Mr. Cornel took a page out of Jeff Bezos book and pushed forward on a plan that included:
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IBM Report on Analytics
In October, IBM released a report from their Institute for Business Value titled Analytics – A Blueprint for Value. IBM releases these reports on a periodic basis, and this one is focused on the growing importance of analytics to business success. Through their analysis, they came up with nine levers that represent the sets of capabilities that most differentiated leaders exhibit:
- Culture: Availability and use of data and analytics within an organization
- Data: Structure and formality of the organization’s data governance process and the security of its data
- Expertise: Development of and access to data management and analytic skills and capabilities
- Funding: Financial rigor in the analytics funding process
- Measurement: Evaluating the impact on business outcomes
- Platform: Integrated capabilities delivered by hardware and software
- Source of value: Actions and decisions that generate results
- Sponsorship: Executive support and involvement
- Trust: Organizational confidence
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MIT Big Data Panel Discussion
In May, I participated in a Big Data panel discussion at the 2013 MIT Sloan CIO Symposium. The panel was moderated by Tom Davenport, Harvard Professor and co-founder of the International Institute for Analytics. The panel participants aside from myself were:
- Annabelle Bexiga, CIO, TIAA-CREF
- Jack Norris, CMO, MapR
- Keith Collins, SVP, CIO & CTO, SAS Institute
- Michael Chui – Senior Fellow, Mckinsey Global Institute
This was a very good discussion on the potential of Big Data and the possible direction it takes in the future. Michael Chui did a great job with his opening remarks, referencing this Mckinsey Report and using examples from it. This report, which I have mentioned previously, focuses on major disruptive technology. It is interesting to hear the perspectives (and sometimes biases) of these industry players. It’s an hour and ten minutes long, with some very good audience questions.
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Where are we on the Bring your own Device Journey?
As I prepared recently to moderate a CIO panel discussion regarding the “bring your own device” (BYOD) journey of three companies, I took a hard look at the current state of BYOD. Before I get to that, let’s set a common definition for BYOD. Wikipedia defines it as the policy of permitting employees to bring personally owned mobile devices (laptops, tablets, and smart phones) to their workplace, and use those devices to access privileged company information and applications. Gartner defines it in a recent Report this way: the ability for users and business partners to leverage personally selected and purchased devices to access business data with the option of including PCs in a BYOD strategy; and the possibility of a company subsidy for the purchase of devices.
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IBM Big Data Study
The IBM Institute for Business Value recently completed Big Data research and released a report titled Analytics: The real-world use of Big Data. As the report states, companies have been dealing with large volumes of data for years (think billions of call center records collected by Telecommunication companies). But the report also identifies the two trends that make this era of big data different:
- The digitization of virtually “everything” now creates new types of large and real-time data across a broad range of industries. Much of this is non-standard data: for example, streaming, geospatial or sensor-generated data that does not fit neatly into traditional, structured, relational warehouses.
- Today’s advanced analytics technologies and techniques enable organizations to extract insights from data with previously unachievable levels of sophistication, speed and accuracy.
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TCS Digital Mobile Consumer Study
Tata Consultancy Services recently conducted a major study to understand how large organizations in North America, Europe, Asia-Pacific and Latin America have been revamping their strategies, products and processes to win the loyalty of consumers who use mobile devices to do business with them– the so-called “Digital Mobile Consumer”. The Study focused on how companies are coping with this mobile consumer. Some key findings are summarized here.
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Big Data and the Emerging Era of Engagement
I often tell the IBM Watson story as a way of describing the future of analytics. Watson – with a large quantity of Big Data behind it – beat the two biggest Jeopardy winners of all time. Although that became the story, the bigger story for me was the business application of what I had just witnessed. Watson showed us how analytics will mature from descriptive to prescriptive. Most companies I talk to are still in the descriptive stage – reporting on that which has happened.
Inside the Next Transition 