Learned a lot lending an editorial hand here:
Finance Middle East, July 28, 2024
by Dr. Antoine Khadige, Nader Haddad, and Marwan Nadda
Banking in the GCC region is undergoing a significant transformation with the growing impact of regulatory-led open banking initiatives. The Central Bank of Bahrain is preparing to enter the second phase of its open banking plan. Saudi Arabia has announced the gradual implementation of open banking use cases. Kuwait is testing open banking products, and the Central Bank of the UAE has initiated an open finance initiative covering banks and insurers.
With open banking regulatory directives, which require the sharing of customer data (with the customer’s consent) with trusted third parties, incumbent banks are entering a new era of competition. New banking entrants such as fintechs and payment providers can access incumbents’ now-exclusive customer relationships and entice customers away with new products and services.
If they articulate the right vision, however, incumbent banks can meet this challenge head-on, adopt the regulatory dictates of open banking and go beyond them. Banks that embrace open banking—which will grow at a global annual rate of 25% to 27%, according to MarkNtel Advisors and Grand View Research—can retain their market share and transform themselves, create new revenue streams, and forge deeper customer relationships. In Saudi Arabia, for example, we project an open banking penetration rate of 20% with retail customers by 2030.
Sunday, July 28, 2024
Open banking is a rich opportunity for GCC incumbent banks
Wednesday, May 8, 2024
‘I’m Sorry, Dave.’ When AI Writes a CEO’s Apology Letter.
This Week in Leadership, May 8, 2024
by Theodore Kinni
Generative artificial-intelligence programs are already helping professionals write compelling sales presentations, convincing emails, and other difficult business communications. It was only a matter of time before someone tried using it for one of the most sensitive documents of all: an apology from the boss.
Using the widely available GPT-4, researchers at the Korea Advanced Institute of Science and Technology (KAIST) recently built a model they call “Prompt Engineering for CEO Apology.” The model incorporates a number of variables, including type of event, structure and length of previous apologies, audience, delivery method, and the communication styles of the CEO and the company. The researchers used the model to create apologies for some recent high-profile CEO gaffes, and apparently, AI did pretty well: According to the KAIST study, the notes “conveyed empathy” and “mimicked the same structure and emotional language” of CEO apologies produced by human beings. Read the rest here.
Thursday, December 8, 2022
It’s Time to Take Another Look at Blockchain
MIT Sloan Management Review, December 8, 2022
Ravi Sarathy, interviewed by Theodore Kinni
It wasn’t long after the developers of bitcoin first used a distributed ledger to record transactions in 2008 that the blockchain revolution was announced with all the fanfare that usually accompanies promising new technologies. Then, as often happens with emerging technologies, blockchain’s promise collided with developmental realities.
Now, a decade and a half down the road, that early promise is becoming manifest. In his new book, Enterprise Strategy for Blockchain: Lessons in Disruption From Fintech, Supply Chains, and Consumer Industries, Ravi Sarathy, professor of strategy and international business at the D’Amore-McKim School of Business at Northeastern University, argues that distributed ledger technology has matured to the point of enabling a host of applications that could disrupt industries as diverse as manufacturing, medicine, and media.
Sarathy spoke with Ted Kinni, senior contributing editor of MIT Sloan Management Review, about the state of blockchain, the applications that are most relevant now for large companies, and how their leaders can harness the technology before established and new competitors use it against them.
MIT Sloan Management Review: Blockchain has been slow to gain traction in many large companies. What’s holding it back?
Sarathy: Blockchain is a complex technology. It is often secured by an elaborate mathematical puzzle that is energy intensive and requires large investments in high-powered computing. This also limits the volume of transactions that can be processed easily, making it hard to use blockchain in a setting like credit card processing, which involves thousands of transactions a second. Interoperability is another technological challenge. You’ve got a lot of different protocols for running blockchains, so if you need to communicate with other blockchains, it creates points of weakness that can be hacked or otherwise fail.
Aside from the technological challenges, there is the issue of cost and benefit. Blockchain is not free, and it’s not an easy sell. It requires significant financial and human resources, and that’s a problem because it’s hard to convince CFOs and other top managers to give you a few million dollars and a few years to develop a blockchain application when they do not have clear estimates of expected returns or benefits.
Lastly, there are organizational challenges. A blockchain is intended to be a transparent, decentralized network in which everyone talks to each other without any intermediaries organized in a world of hierarchies. Making that transition can require a long philosophical and cultural leap for traditional companies used to a chain of command. Trust, too, becomes a huge issue, particularly when you start adding independent firms to a blockchain. Read the rest here.
Thursday, September 8, 2022
How Smart Products Create Connected Customers
Learned a lot lending an editorial hand here:
MIT Sloan Management Review, September 8, 2022
Jon Krause/theispot.com
As leaders of legacy product and service companies anchored in traditional value chains seek ways to prosper in the digital economy, one of the most important questions they can ask is, “How can we turn our existing customers into digital customers?” Digital customers don’t simply buy products and services: Their interactions with those products and services generate data that companies leverage to provide them with greater value over time. Those data insights also help companies attract new customers, create fresh revenue streams, and expand the scope of their businesses. This customer-generated data, which is often combined with other data streams, has fueled the growth engines of companies built on digital platforms, like Amazon and Google.
Legacy companies typically collect episodic data from discrete events — the sale of a product or the shipment of a component, for instance. Amazon and Google capture a continuous stream of data at every customer touch point on their platforms that is used to generate a new class of insights that play a more expansive role in their businesses. All of their customers are digital customers. Now, thanks to technologies such as sensors, the internet of things (IoT), and artificial intelligence, legacy firms, too, can transform their customers into digital customers who generate streams of data via their interactions with connected products.
Sleep Number uses sensors in its mattresses to track its customers’ sleeping heart rates and breathing patterns. This data enables the company to identify chronic sleep issues, such as sleep apnea and restless legs syndrome, and expand its business scope beyond mattresses to wellness provision. Sensors on Caterpillar heavy machinery produce data that enables the company to track wear and tear, predict component failures, and create new revenue streams from maintenance services. Chubb is installing sensors in the buildings it insures to detect water leaks before they become claims. In this way, the company is expanding beyond damage compensation to damage prevention.
For all its promise, harnessing value from digital customers also brings new challenges for legacy companies. They must develop new value propositions, build out their data infrastructures and strategies, staff for new digital and product design capabilities and competencies, and rework innovation processes to create a feedback loop using valuable customer interaction data. And they must learn to market and sell their new value proposition to create a new digital customer base — and reap the benefits of their digital transformation. Read the rest here.
Wednesday, July 20, 2022
Saudi Arabia’s dynamic television and video market
Learned a lot lending an editorial hand here:
PwC Strategy&/MBC Media Solutions, July 2022
Saudi Arabia’s vibrant and rapidly growing entertainment and media (E&M) industry is making an important contribution to the country’s culture and its economic diversification. In particular, the TV market is undergoing transformation and the over-the-top (OTT) video market is dynamic and developing as new technologies emerge. Globally, audiovisual content has become a respected cultural artefact and is experiencing record levels of demand—in which Saudi Arabia can now participate.
The Saudi market’s E&M growth potential stems from its distinct features—high rates of content consumption, including TV, streaming, video sharing, and gaming; impressive adoption of smartphones; robust social media; fast connectivity; and advertising growth opportunities. Indeed, while streaming and mobile penetration are changing how video is consumed, TV retains a majority share of viewership. Digital technology allows viewers to blend linear and streaming, curating their own content.
Thursday, June 30, 2022
Accelerating digital: A win-win-win for customer experience, the environment and business growth
Learned a lot lending an editorial hand on this report:
Economist Impact, June 2022
Digitally advanced firms are accelerating ahead of the competition. They are able to use real-time data insights to transform customer experiences and to improve their sustainability footprint. Discover how businesses can overcome data access and activation challenges to drive profitable growth.
The business landscape is constantly evolving and, with it, digital transformation. Businesses are under pressure to adapt to new competitors, increasingly from non-traditional markets, and to navigate ongoing geopolitical and economic uncertainty. At the same time, they need to become more sustainable and socially responsible, driven by government mandates and customer demands. Our new study shows that digitally driven businesses are able to embrace these rapid changes in their markets and deliver better customer experiences to drive profitable growth.
Indeed, the vast majority of firms we surveyed (99%) are leveraging new digital business models to tackle these challenges and drive greater agility, a trend that has been accelerated by covid-19. Over half (55%) of businesses expect a long-term increase in their use of digital technologies as a result of the pandemic, according to research by the European Investment Bank.
Firms that are able to capture and derive value from new streams of data, and offer new products and services rooted in digital capabilities, can improve their operational efficiency, reduce their carbon footprint and boost customer satisfaction. This can translate into improvements in both revenues and profit margins, with 80% of our survey respondents stating that some form of digital transformation contributes over half of their profits today. Moreover, 95% expect some, most, or all of their revenue to be digitally enabled within five years.
However, there is often a wide gulf between the digital ambitions of firms and their ability to use data insights at scale, which would enable employees to make better real-time decisions and drive higher levels of innovation.
To better understand these trends, Economist Impact has undertaken an ambitious research programme. We have examined the state of digital transformation in businesses across five sectors in which digitalisation offers substantial opportunities for growth and competitive advantage: construction and infrastructure; manufacturing; transportation and logistics; energy; and healthcare and pharmaceuticals. Our global survey of 500 multinational firms identifies the ongoing barriers they face in executing their digital strategies. We offer cross-industry insights on how these barriers are being overcome based on economic analysis of firms that are successfully using digital business models to boost their customer satisfaction, sustainability metrics and revenues, and interviews with experts. Read and download the report here.
Monday, January 10, 2022
The Three Internal Barriers to Deep-Tech Corporate Venturing
Learned a lot lending an editorial hand here:
MIT Sloan Management Review, January 10, 2022
by Josemaria Siota and Maria Julia Prats
The flow of capital to deep-tech startups is rapidly becoming a torrent. From 2016 to 2020, annual investments in startups focused on commercializing emerging technologies such as biotechnology, robotics, and quantum computing grew in value from $15 billion to $60 billion worldwide, with the average private investment more than tripling in size. Deep-tech corporate venturing (CV) — the second-largest source of this funding — grew from $5.1 billion in 2016 to $18.3 billion in 2020.
The intent behind these deep-tech corporate investments is clear. In theory, deep-tech CV enables companies to quickly gain expertise in leading-edge technologies and pursue potentially disruptive innovations without building internal capabilities from scratch. In reality, however, such funding can come with high hurdles, such as time-to-market durations that often exceed five years, and the greater risk inherent to novel and complex technologies. The difficulties are underscored by an analysis we conducted using CV data from 46 international companies that was collected under the auspices of IESE Business School in 2018. It revealed that 68.9% of the initiatives failed to deliver their expected results.
To better understand the most significant barriers to success in deep-tech CV and the tactics that chief innovation officers (CINOs) can use to achieve more positive results, we turned to East and Southeast Asia for our new study. (In 2019, Asian companies accounted for 40% of corporate venture investments in startups, the largest percentage globally.) The study included an analysis of CV in 180 companies and interviews with 77 of their innovation executives, most of whom work in companies with CV portfolios that include a 25% or greater concentration of deep-tech startups. It revealed three internal barriers that CINOs commonly encounter with deep-tech startups and the ways in which they can be overcome. Read the rest here.
Thursday, October 28, 2021
People Analytics: A key component to your HR Technology strategy
Learned a lot lending an editorial hand here:
Deloitte Capital H Blog, October 28, 2021
by Jamaal Justice and Albert Hong
The promise of generating actionable insights in every aspect of work, the workplace, and the workforce has created fast-growing demand for people analytics (PA). A myriad of vendors are seeking to meet the demand with an ever-expanding mix of solutions (e.g., tools for Human Capital Management Systems (HCM), data ingestion, data warehouse/lake, extract/transform/load (ETL), business intelligence, and advanced analytics that are evolving as quickly as their underlying technologies.
The explosive proliferation of Human Resources (HR) technology and solutions is a challenge for HR leaders at every step along the PA maturity curve for two principal reasons. First, the ideal set of PA tools and solutions for meeting all organizational needs has not yet emerged. Second, most organizations are still in the process of developing the capabilities needed to evaluate their PA needs: Deloitte’s 2020 High-Impact People Analytics study found that 82% of organizations globally are in the earlier stages of their maturity journey.
Whether HR leaders are in the early stages of building PA capabilities or trying to stay on the cutting edge of what is possible, they need a North Star — a guiding light and a path that will lead them to a strategy and HR technology architecture capable of delivering on the promise of PA across their organizations over time. Read the rest here.
Tuesday, September 28, 2021
The Digital Superpowers You Need to Thrive
Learned a lot lending an editorial hand here:
MIT Sloan Management Review, September 28, 2021
by Gerald C. Kane, Rich Nanda, Anh Nguyen Phillips, and Jonathan Copulsky
On Jan. 8, 2020, when Chinese researchers announced that they had identified a new virus that had infected dozens of people across Asia, few business leaders realized that their companies were on the brink of an economic, medical, political, and cultural disruption of global magnitude. In short order, they were called upon to respond to potential illness among employees and customers, supply chain interruptions, dramatic fluctuations in demand, and extraordinarily high levels of uncertainty.
Yet, for all its grim — and ongoing — consequences, the COVID-19 pandemic is just one of many fundamental breaks in the business environment that have challenged leaders over the past 30 years or so. These disruptions come in two forms.
The COVID-19 pandemic is an acute disruption. As with an acute medical condition, the onset of such a disruption is sudden and severe, and its symptoms are obvious. Its treatment calls for a rapid and dramatic response, and its duration is relatively short. The Sept. 11, 2001, terrorist attacks in the U.S., the 2004 tsunami in the Indian Ocean, the 2008 housing and financial crisis, and the 2010 volcanic eruptions in Iceland are examples of acute disruptions.
The second form of disruption is more like a chronic medical condition. Chronic disruptions build slowly. Their immediate symptoms can be subtle and easily overlooked. They require sustained treatment that must be tolerable over time. Chronic disruptions, such as China’s economic rise, climate change, and the evolutionary emergence of digital technology, tend to be persistent and long lasting.
While the two phenomena present differently, they both represent a departure from business as usual to which companies must respond. In studying corporate responses to the pandemic from March through December 2020, we found that companies with existing playbooks for responding to chronic digital disruptions were also responding more quickly and effectively to the acute pandemic disruption. The economic payoffs from digital technologies that allow for enterprise virtualization — such as remote work, e-commerce, and telehealth — increased significantly in the context of COVID-19. Moreover, in responding to the pandemic, many of these companies wound up accelerating their digital transformation efforts and their returns on those efforts.
These companies’ ability to manage the pandemic offers a dramatic illustration of what we’ve come to call the transformation myth. The myth is the idea that transformation is an event with a start and an end during which organizations migrate from one steady state to another, as opposed to a continuous process of adapting to a highly volatile, ambiguous, and uncertain environment shaped by multiple, overlapping disruptions. Read the rest here.
Tuesday, March 2, 2021
Why So Many Data Science Projects Fail to Deliver
Learned a lot lending an editorial hand here:
MIT Sloan Management Review, March 2, 2021
by Mayur P. Joshi, Ning Su, Robert D. Austin, and Anand K. Sundaram
Image courtesy of Jean Francois Podevin/theispot.com
To better understand the mistakes that companies make when implementing profitable data science projects, and discover how to avoid them, we conducted in-depth studies of the data science activities in three of India’s top 10 private-sector banks with well-established analytics departments. We identified five common mistakes, as exemplified by the following cases we encountered, and below we suggest corresponding solutions to address them. Read the rest here...
Thursday, December 17, 2020
Is the gig up?
strategy+business, December 17, 2020
by Theodore Kinni
Photograph by Brothers91
A decade ago, advocates touted the sharing economy as an alternative to corporate capitalism. Digital technology was opening vast, new peer-to-peer marketplaces: TaskRabbit and Airbnb were founded in 2008, Uber in 2009, RelayRides (now Turo) in 2010, Postmates in 2011, Lyft in 2012. These platforms promised that people would be able to make a good living while working when and how they wanted — selling their time and skills, and renting out their cars, spare bedrooms, and that dusty camping gear in the attic.
“You will know by now that things haven’t turned out exactly as expected,” Juliet Schor wryly notes in her new book, After the Gig. Schor, a sociology professor at Boston College, and her team at the Connected Consumption project, funded by the MacArthur Foundation, studied gig workers and platforms of the sharing economy from 2011 to 2017. The result is a more nuanced view than has been offered by previous books on this topic, which typically focus on either how companies can build their own platforms or how platform companies prosper by evading regulation and exploiting workers.
This finding partly contradicts the headlines of worker abuse that have generated a lot of political Sturm und Drang lately. At the same time, it is clear that the gig economy can’t really substitute for a full-time job. As Schor concludes: “With some exceptions, our data suggest that being dependent on a platform is not a viable way to make a living.” Read the rest here.
Thursday, November 19, 2020
The New Elements of Digital Transformation
Learned a lot lending an editorial hand here:
MIT Sloan Management Review, November 19, 2020
by Didier Bonnet and George Westerman
Image courtesy of Michael Glenwood Gibbs/theispot.com
Since 2014, when our article “The Nine Elements of Digital Transformation” appeared in these pages, executive awareness of the powerful and ever-evolving ways in which digital technology can create competitive advantage has become pervasive. But acting on that awareness remains a challenging prospect.
It requires that companies become what we call digital masters. Digital masters cultivate two capabilities: digital capability, which enables them to use innovative technologies to improve elements of the business, and leadership capability, which enables them to envision and drive organizational change in systematic and profitable ways. Together, these two capabilities allow a company to transform digital technology into business advantage.
Digital mastery is more important than ever because the risks of falling behind are increasing. In 10 years of research, we have seen digital transformation grow increasingly complex, with a new wave of technological and competitive possibilities arriving before many companies mastered the first. When we began our research, most large traditional enterprises were using digital technologies to incrementally improve parts of their businesses. Since then, this first phase of activity has given way to a new one. Advances in a host of technologies, such as the internet of things, artificial intelligence, virtual and augmented reality, and 5G, have opened new avenues for value creation. More important, leaders now recognize the need for — and the possibility of — truly transforming the fundamentals of how they do business. They understand that they have to move from disconnected technology experiments to a more systematic approach to strategy and execution.
Some companies have successfully graduated from the first phase of digital transformation and are diving into the second. But many are still floundering: In 2018, when we surveyed 1,300 executives in more than 750 global organizations, only 38% of them told us that their companies had the digital capability needed to become digital masters, and only 35% said they had the leadership capability to do so. This has become more worrisome than ever: As COVID-19 accelerates the shift to digital activity, digital masters are widening the gap between their capabilities and those of their competitors.
These conditions prompted us to reexamine the elements of digital transformation that we proposed in 2014. While strong leadership capability is even more essential than ever, its core elements — vision, engagement, and governance — are not fundamentally changed, though they are informed by recent innovations. The elements of digital capability, on the other hand, have been more profoundly altered by the rapid technological advances of recent years. Read the rest here.
Wednesday, November 11, 2020
What people like you like
strategy+business, November 11, 2020
by Theodore Kinni
Photograph by Paper Boat Creative
I don’t set much store in the endless stream of recommendations offered by Amazon, Netflix, Spotify, and most other online businesses. Occasionally, a book, flick, or song pops up that delights me, but most of the suggestions I get either miss the mark or appear suspiciously advantageous to recommendation engine operators and their advertisers.
Michael Schrage, visiting fellow at the MIT Sloan School of Management’s Initiative on the Digital Economy and s+b contributor, awakens us to the potential of delightful discovery in his latest book, Recommendation Engines. “Recommendation inspires innovation: that serendipitous suggestion—that surprise—not only changes how you see the world, it transforms how you see—and understand—yourself. Successful recommenders promote discovery of the world and one’s self,” Schrage writes in its introduction. “Recommenders aren’t just about what we might want to buy; they’re about who we might want to become.”
If this smacks of techno-utopianism, well, there is a strong strain of that ideology running through Recommendation Engines. For the most part, however, Schrage grounds this rosy view in the powerful effects that recommenders are already producing and balances it with acknowledgment of these systems’ potential for abuse. He also provides a short history of recommendations and a suitably technical description of how recommendation engines work and are built.
To date, the powerful effects of recommenders have manifested themselves mostly in commerce. Schrage cites a variety of facts in this regard: a survey that found recommendations account for approximately 30 percent of global e-commerce revenues; another that found online shoppers are 4.5 times more likely to buy after clicking on a recommendation; and research that “strongly suggests” recommendations drive roughly a third of Amazon’s sales. Read the rest here.
Tuesday, August 18, 2020
Driving Growth in Digital Ecosystems
Learned a lot lending an editorial hand here:
MIT Sloan Management Review, August 18, 2020
by Ina M. Sebastian, Peter Weill, and Stephanie L. Woerner
High-growth companies don’t go it alone. Increasingly, they are achieving results by creating and orchestrating digitally connected ecosystems — coordinated networks of enterprises, devices, and customers — that create value for all of their participants.
Companies whose dominant business model is ecosystem driver — in both B2B and B2C domains, such as energy management, home ownership, and financial services — experienced revenue growth approximately 27 percentage points higher than the average for their industries, and had profit margins 20 percentage points above the average for their industries, according to our research. That 2019 global survey of 1,311 executives also found that successful drivers achieve outsized results by attracting the partners needed to provide complementary — and competing — products and services that make their ecosystems seamless “one-stop shopping” destinations for customers.
Complementary offerings make it easier for customers to obtain comprehensive solutions to their problems. For example, when China’s largest insurer, Ping An, realized that its customers wanted not only insurance but also a means of addressing their medical and well-being needs, it created Good Doctor. The Good Doctor platform offers 24-7 one-stop health care services that are provided by pharmacies, hospitals, and about 10,000 doctors. In September 2019, Good Doctor reported serving more than 62 million customers monthly. Moreover, nearly 37% of Ping An customers used more than one of its services in 2019 — an important measure of ecosystem success.
As all of this suggests, a strong partnering capability is required to successfully grow digital ecosystems. This capability must be designed to support digital partnering, which is not the same as the traditional handshake and bespoke partnering of the physical world. Traditional partnering often includes exclusive relationships, long-term contracts, and deep integrations, all of which take time to establish and require strategic commitment. Digital partnering creates growth by adding more products and customers via digital connections with other companies that enable fast response to customer needs. It requires the ability to determine and agree with partners about who will create value, how revenue will be apportioned, and what data will be shared; it also requires the capacity to quickly add partners’ products and services via plug-and-play connections that offer immediate order and payment processing, and sometimes delivery as well.Successful ecosystem drivers also offer their customers greater choice, even when that entails featuring competing offers. In Australia, real estate platform driver Domain partners with about 35 mortgage lenders to offer homebuyers more loan choices. In the second half of 2019, the company’s Consumer Solutions segment, which consists of its loans, insurance, and utilities connections businesses, grew revenue by 72%...read the rest here
Monday, July 6, 2020
Fit-for-context leadership
strategy+business, July 6, 2020
by Theodore Kinni
Illustration by wildpixel
From Herodotus and Machiavelli to Peter Drucker and Warren Bennis, most leadership writers have followed the same basic approach: They study successful leaders and try to derive practices from their lives and careers that aspiring leaders can adopt. Amit Mukherjee, a professor of leadership and strategy at Hult International Business School, rejects this approach in his intriguing new book, Leading in the Digital World.
As Mukherjee tells it, the technologies that gave rise to the industrial era — mass manufacturing, electric power, and scientific management, among others — created the context for authoritarian leadership. Then, in the mid-20th century, new technologies, starting with statistical process control, which was pioneered by Walter Shewhart at Bell Telephone Laboratories in the 1920s, gave rise to the quality movement and spawned empowered leadership. Today, new technologies with a long arc of impact are giving rise to the “digital epoch” and creating the need for a new set of leadership practices.
In a variation on the theme of contextual leadership championed by Harvard Business School’s Anthony Mayo and Nitin Nohria, Mukherjee contends that the practices of business leaders must evolve with and from the technological context of their times. “Periodically, technologies appear that have long arcs of impact into the future,” he writes. “When introduced, they require dramatic changes in the nature of work, which, in turn, require profound changes in how people are organized. That changes how people must be led. Companies — and executives — who fail to adapt are cast aside by those who do.”
It’s been clear for several decades that digital technologies are driving the transformation of entire industries. As an example, Mukherjee points to the pharmaceutical industry, in which technologies such as genomic medicine and radio-frequency identification (RFID) tracking have driven a fundamental revamping of R&D and distribution models.
Instead of focusing on digital technologies themselves, however, Mukherjee examines their ramifications for work and organizational structures, which he categorizes as seven principles...read the rest here
Tuesday, June 2, 2020
Making experiments pay
strategy+business, June 2, 2020
by Theodore Kinni
Illustration by AndSim
The current pandemic is a dramatic case study in why experiments matter. How else are we to know which tests accurately identify COVID-19 infections and their telltale antibodies, whether and how well drugs already at our disposal mitigate the suffering inflicted by the coronavirus, or whether the vaccines currently in development will actually protect us from it? Randomized controlled trials are the only way to answer these questions short of playing Russian roulette with the lives of large numbers of people.
Experiments have been around for a long time. In The Power of Experiments, an introductory paean to the benefits of experimentation for corporate and government decision making, Harvard Business School professors Michael Luca and Max Bazerman peg the first recorded experiment to the reign of King Nebuchadnezzar in Babylonia circa 600 BC.
As the Old Testament story goes, Nebuchadnezzar attacked Jerusalem and took a group of young Israelites, including one named Daniel, as servants. He ordered that they be acculturated for three years, in part by being fed the same food as the royal court, which the Israelites considered “ritually unclean.” But Daniel proposed that he and three other prisoners be fed only vegetables and water for 10 days, at which point a guard would compare their health to that of the rest of the prisoners, who would have been fed the local fare. At the end of the experiment, the guard judged the vegetarians healthier, and Daniel and his three comrades were able to continue eating the less objectionable diet.
About 2,600 years later, Luca and Bazerman write, “We are in the early days of the age of experiments.” By this, they mean that experiments have spread far beyond the boundaries of science labs and medical trials. In 2018, Google ran more than 10,000 experiments. Amazon, Facebook, Uber, Yelp, and TripAdvisor run thousands of experiments per year. As these names indicate, technology companies, especially those with digital platforms, are at the forefront of corporate experimentation. That’s because it is relatively easy to run experiments on their large, captive audiences. Read the rest here.
Tuesday, February 11, 2020
The Future of Platforms
Learned a lot lending an editorial hand here:
MIT Sloan Management Review, February 11, 2020
by Michael A. Cusumano, David B. Yoffie, and Annabelle Gawer
The world’s most valuable public companies and its first trillion-dollar businesses are built on digital platforms that bring together two or more market actors and grow through network effects. The top-ranked companies by market capitalization are Apple, Microsoft, Alphabet (Google’s parent company), and Amazon. Facebook, Alibaba, and Tencent are not far behind. As of January 2020, these seven companies represented more than $6.3 trillion in market value, and all of them are platform businesses.
Platforms are also remarkably popular among entrepreneurs and investors in private ventures. When we examined a 2017 list of more than 200 unicorns (startups with valuations of $1 billion or more), we estimated that 60% to 70% were platform businesses. At the time, these included companies such as Ant Financial (an affiliate of Alibaba), Uber, Didi Chuxing, Xiaomi, and Airbnb.But the path to success for a platform venture is by no means easy or guaranteed, nor is it completely different from that of companies with more-conventional business models. Why? Because, like all companies, platforms must ultimately perform better than their competitors. In addition, to survive long-term, platforms must also be politically and socially viable, or they risk being crushed by government regulation or social opposition, as well as potentially massive debt obligations. These observations are common sense, but amid all the hype over digital platforms — a phenomenon we sometimes call platformania — common sense hasn’t always been so common.
We have been studying and working with platform businesses for more than 30 years. In 2015, we undertook a new round of research aimed at analyzing the evolution of platforms and their long-term performance versus that of conventional businesses. Our research confirmed that successful platforms yield a powerful competitive advantage with financial results to match. It also revealed that the nature of platforms is changing, as are the ecosystems and technologies that drive them, and the challenges and rules associated with managing a platform business.
Platforms are here to stay, but to build a successful, sustainable company around them, executives, entrepreneurs, and investors need to know the different types of platforms and their business models. They need to understand why some platforms generate sales growth and profits relatively easily, while others lose extraordinary sums of money. They need to anticipate the trends that will determine platform success versus failure in the coming years and the technologies that will spawn tomorrow’s disruptive platform battlegrounds. We seek to address these needs in this article. Read the rest here.
Thursday, January 16, 2020
Pessimism dematerialized: Four reasons to be hopeful about the future
strategy+business, January 16, 2020
by Theodore Kinni
Photograph by Klaus Vedfelt
The principle support upon which McAfee constructs this thesis, which he admits will be hard for more skeptical readers to swallow, is an ongoing process of dematerialization that he finds occurring in mature economies. Building on research by environmental scientist Jesse Ausubel and writer Chris Goodall, McAfee charts resource consumption in the United States. For instance, he uses U.S. Geological Survey data to show that as of 2015, the consumption of the five “most important” manufacturing metals in the U.S. — aluminum, copper, steel, nickel, and gold — are all off their peaks since 2000. Steel consumption is down 15 percent; aluminum is down 32 percent; copper is down 40 percent. The same is true for energy consumption, as well as a variety of farming and construction inputs. Since the first Earth Day in 1970, U.S. consumption of resources has been falling, yet the nation’s economy has continued growing. Simply put, McAfee is arguing that it takes a lot less stuff to produce a dollar of GDP today than it did 50 years ago.
McAfee declares that the data shows “a great reversal of our Industrial Age habits is taking place. The American economy is now experiencing broad and often deep absolute dematerialization.” And the rest of world? Well, the data is incomplete. McAfee finds some evidence that Europe’s industrialized nations are “past peak” resource consumption, but developing countries, such as China and India, that are still in the process of industrializing, “probably are not yet dematerializing.”
Four forces drive the engine of dematerialization, according to McAfee. Read the rest here.
Friday, July 5, 2019
Cloud-based HCM systems should come without surprises
Lent an editorial hand preparing this guide to preparing a reality-based business case for HCM:
by Marty Marchetti
The business case for cloud-based human capital management (HCM) systems can sound pretty compelling. What CHRO wouldn’t want fast access to the latest advances in HCM technology at a lower overall cost? But my colleagues and I help companies make the move to cloud HCM, and we often get a firsthand view of the mismatch between expectations and reality that was revealed in Deloitte’s 2019 Global Human Capital Trends study.
“No surprises” should describe your move to the cloud, and the following 5 questions can help you reduce them. Read the rest here.
Friday, June 14, 2019
Conversational computing
strategy+business, June 13, 2019
by Theodore KinniSteve Jobs could be relentless when he wanted something. In early 2010, he wanted a small startup in San Jose, Calif. CEO Dag Kittlaus and his cofounders had just raised a second round of funding and didn’t want to sell. Jobs called Kittlaus for 37 days straight, until he wrangled and wheedled a deal to buy the two-year-old venture for Apple at a price reportedly between US$150 million and $200 million. The company was Siri Inc.
Wired contributor James Vlahos tells the story of how Siri took up permanent residence in the iPhone in his new book, Talk to Me. It’s the first nontechnical book on voice computing that I’ve seen and a must-read if you have any interest in the topic.
Vlahos spends the first third of Talk to Me describing the platform war currently raging in voice computing. It details the race among the big players, including Amazon, Google, and Apple, to embed AI-driven voices in as many different devices as possible, as they seek to dominate the emerging ecosystem. The fact that Amazon now has more than 10,000 employees working on Alexa provides a good sense of the dimensions of that race.
But voice computing is more than a platform play. It is likely to have ramifications and applications for every company, especially if Vlahos’s contention that “the advent of voice computing is a watershed moment in human history” turns out to be right.
“Voice is becoming the universal remote to reality, a means to control any and every piece of technology,” he writes. “Voice allows us to command an army of digital helpers — administrative assistants, concierges, housekeepers, butlers, advisors, babysitters, librarians, and entertainers.” Voice will disrupt the business models of powerful companies — and create new opportunities for upstarts — in part because it will put AI directly in the control of consumers, Vlahos argues. “And voice introduces the world to relationships long prophesied by science fiction — ones in which personified AIs become our helpers, watchdogs, oracles, and friends.” Read the rest here.
