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Building the engine that drives digital transformation

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Building the engine that drives digital transformation


This is the consensus view of an MIT Technology Review Insights survey of 210 members of technology executives, conducted in March 2021. These respondents report that they need—and still often lack— the ability to develop new digital channels and services quickly, and to optimize them in real time.

Underpinning these waves of digital transformation are two fundamental drivers: the ability to serve and understand customers better, and the need to increase employees’ ability to work more effectively toward those goals.

Two-thirds of respondents indicated that more efficient customer experience delivery was the most critical objective. This was followed closely by the use of analytics and insight to improve products and services (60%). Increasing team collaboration and communication, and increasing security of digital assets and intellectual property came in joint third, with around 55% each.

All the digital objectives are integrally linked to improving customer and employee engagement, retention, and activation. Richard Jefts, vice president and general manager of HCL’s Digital Solutions, notes that increasing team collaboration and communication received additional attention over the last year.

“With covid-19, management teams needed to ensure that business could continue remotely, which has meant new levels of adoption of collaboration capabilities and the use of the low code by employees to digitize business processes to bridge the gaps,” says Jefts.

Miao Song, Brussels-based chief information officer of Mars Petcare, notes that digitalization has been steadily redefining her company’s global pet nutrition and veterinary services businesses. “Our online business has seen double-digit growth, and the resulting volume of customer data allows us to forecast demand better,” says Song.

Digital tools also allow more and better market data to be gathered and utilized quickly. Song points out that AI-enabled image recognition tools are being used by Mars’ sales reps to scan retailers’ shelves and generate insight for better inventory management.

As Mars’ reliance on AI and analytics is increasing throughout the organization, it is teaching many employees to use low-code tools to bolster their internal capabilities. Low code is a software development approach that requires little to no coding to build applications and processes, allowing users with no formal knowledge of coding or software development to create applications.

“Everybody in our company needs to become a data analyst—not just IT team members,” says Song, speaking of Mars’ efforts to increase digital literacy in a bid to enhance visibility across the company’s supply chain, refine pricing strategies, and develop new products and services.

Song notes that promoting the use of low-code development tools through hackathons and other activities has been an important part of Mars’ efforts: “we need to break the notion that only IT can access and use our data resources,” she adds.

Customer experience is (still) king

Survey respondents have indicated that they have already seen significantly increased performance in customer experience processes since undertaking digital transformation efforts. Moving into the coming year, customer experience continues to be a priority.

Respondents are seeking to improve digital channels in particular, followed by analytics and to support personalization, and AI or automated customer engagement tools. Other digital competencies are being built to accommodate changes in customer and partner expectations and requirements, streamlining customer experience processes by delivering multi-experience capabilities.

Alan Pritchard, director of ICT Services for Austin Health, a public hospital group based in Melbourne, Australia, explains that his company’s digital transformation process began to accelerate well before covid-19’s impact set in.

“A model of service review in 2019 identified home-based monitoring and home-based care as critical to our future service delivery—so even prior to the pandemic, our health strategy was focused on improving digital channels and increasing our capacity to support people outside of the hospital,” says Pritchard, noting that in order to execute on Austin Health’s outreach strategy, a common customer relationship management (CRM) platform needed to be built.

“While some future service models can be delivered with telehealth initiatives or with device integration, there’s still a lot of work to do looking at how you communicate electronically with people about their health status,” says Pritchard.

The organization’s common CRM platform needed to accommodate numerous autonomous specialty departments, “and each of them wants their own app to communicate electronically with their patients,” observes Pritchard.

Managing numerous separate app development processes is complex, although “there are common patterns in how departments engage with patients in appointment booking, preparation, and follow-up processes”, says Pritchard, “so we need a platform that’s highly reusable, rather than a series of apps built on custom code.”

This, coupled with the need to distribute some control and customization through the multiple departments, led Prichard’s team down a low-code path.

This largely correlates with the experiences of our survey cohort: over 75% of respondents indicate that they have increased their use of digital development platforms (including low code), and over 80% have increased their investment priorities in workflow management tools over the last year.

Download the full report.

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.

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The quest to show that biological sex matters in the immune system

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Sabra Klein and Janna Shapiro look at a specimen on a lightbox.


She ultimately found a postdoctoral position in the lab of one of her thesis committee members. And in the years since, as she has established a lab of her own at the university’s Bloomberg School of Public Health, she has painstakingly made the case that sex—defined by biological attributes such as our sex chromosomes, sex hormones, and reproductive tissues—really does influence immune responses. 

Through research in animal models and humans, Klein and others have shown how and why male and female immune systems respond differently to the flu virus, HIV, and certain cancer therapies, and why most women receive greater protection from vaccines but are also more likely to get severe asthma and autoimmune disorders (something that had been known but not attributed specifically to immune differences). “Work from her laboratory has been instrumental in advancing our understanding of vaccine responses and immune function on males and females,” says immunologist Dawn Newcomb of the Vanderbilt University Medical Center in Nashville, Tennessee. (When referring to people in this article, “male” is used as a shorthand for people with XY chromosomes, a penis, and testicles, and who go through a testosterone-dominated puberty, and “female” is used as a shorthand for people with XX chromosomes and a vulva, and who go through an estrogen-dominated puberty.)

Through her research, as well as the unglamorous labor of arranging symposia and meetings, Klein has helped spearhead a shift in immunology, a field that long thought sex differences didn’t matter. Historically, most trials enrolled only males, resulting in uncounted—and likely uncountable—consequences for public health and medicine. The practice has, for example, caused women to be denied a potentially lifesaving HIV therapy and left them likely to endure worse side effects from drugs and vaccines when given the same dose as men.


Men and women don’t experience infectious or autoimmune diseases in the same way. Women are nine times more likely to get lupus than men, and they have been hospitalized at higher rates for some flu strains. Meanwhile, men are significantly more likely to get tuberculosis and to die of covid-19 than women. 

In the 1990s, scientists often attributed such differences to gender rather than sex—to norms, roles, relationships, behaviors, and other sociocultural factors as opposed to biological differences in the immune system.

For example, even though three times as many women have multiple sclerosis as men, immunologists in the 1990s ignored the idea that this difference could have a biological basis, says Rhonda Voskuhl, a neuroimmunologist at the University of California, Los Angeles. “People would say, ‘Oh, the women just complain more—they’re kind of hysterical,’” Voskuhl says. “You had to convince people that it wasn’t just all subjective or environmental, that it was basic biology. So it was an uphill battle.” 

Sabra Klein (left) and Janna Shapiro in Klein’s laboratory at Johns Hopkins University in Baltimore, Maryland.

ROSEM MORTON

Despite a historical practice of “bikini medicine”—the notion that there are no major differences between the sexes outside the parts that fit under a bikini—we now know that whether you’re looking at your metabolism, heart, or immune system, both biological sex differences and sociocultural gender differences exist. And they both play a role in susceptibility to diseases. For instance, men’s greater propensity to tuberculosis—they are almost twice as likely to get it as women—may be attributed partly to differences in their immune responses and partly to the fact that men are more likely to smoke and to work in mining or construction jobs that expose them to toxic substances, which can impair the lungs’ immune defenses. 

How to tease apart the effects of sex and gender? That’s where animal models come in. “Gender is a social construct that we associate with humans, so animals do not have a gender,” says Chyren Hunter, associate director for basic and translational research at the US National Institutes of Health Office of Research on Women’s Health. Seeing the same effect in both animal models and humans is a good starting point for finding out whether an immune response is modulated by sex. 

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Why can’t tech fix its gender problem?

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From left to right: Gordon MOORE, C. Sheldon ROBERTS, Eugene KLEINER, Robert NOYCE, Victor GRINICH, Julius BLANK, Jean HOERNI and Jay LAST.


Not competing in this Olympics, but still contributing to the industry’s success, were the thousands of women who worked in the Valley’s microchip fabrication plants and other manufacturing facilities from the 1960s to the early 1980s. Some were working-class Asian- and Mexican-Americans whose mothers and grandmothers had worked in the orchards and fruit can­neries of the prewar Valley. Others were recent migrants from the East and Midwest, white and often college educated, needing income and interested in technical work. 

With few other technical jobs available to them in the Valley, women would work for less. The preponderance of women on the lines helped keep the region’s factory wages among the lowest in the country. Women continue to dominate high-tech assembly lines, though now most of the factories are located thousands of miles away. In 1970, one early American-owned Mexican production line employed 600 workers, nearly 90% of whom were female. Half a century later the pattern continued: in 2019, women made up 90% of the workforce in one enormous iPhone assembly plant in India. Female production workers make up 80% of the entire tech workforce of Vietnam. 

Venture: “The Boys Club”

Chipmaking’s fiercely competitive and unusually demanding managerial culture proved to be highly influential, filtering down through the millionaires of the first semiconductor generation as they deployed their wealth and managerial experience in other companies. But venture capital was where semiconductor culture cast its longest shadow. 

The Valley’s original venture capitalists were a tight-knit bunch, mostly young men managing older, much richer men’s money. At first there were so few of them that they’d book a table at a San Francisco restaurant, summoning founders to pitch everyone at once. So many opportunities were flowing it didn’t much matter if a deal went to someone else. Charter members like Silicon Valley venture capitalist Reid Dennis called it “The Group.” Other observers, like journalist John W. Wilson, called it “The Boys Club.”

The men who left the Valley’s first silicon chipmaker, Shockley Semiconductor, to start Fairchild Semiconductor in 1957 were called “the Traitorous Eight.”

WAYNE MILLER/MAGNUM PHOTOS

The venture business was expanding by the early 1970s, even though down markets made it a terrible time to raise money. But the firms founded and led by semiconductor veterans during this period became industry-defining ones. Gene Kleiner left Fairchild Semiconductor to cofound Kleiner Perkins, whose long list of hits included Genentech, Sun Microsystems, AOL, Google, and Amazon. Master intimidator Don Valentine founded Sequoia Capital, making early-stage investments in Atari and Apple, and later in Cisco, Google, Instagram, Airbnb, and many others.

Generations: “Pattern recognition”

Silicon Valley venture capitalists left their mark not only by choosing whom to invest in, but by advising and shaping the business sensibility of those they funded. They were more than bankers. They were mentors, professors, and father figures to young, inexperienced men who often knew a lot about technology and nothing about how to start and grow a business. 

“This model of one generation succeeding and then turning around to offer the next generation of entrepreneurs financial support and managerial expertise,” Silicon Valley historian Leslie Berlin writes, “is one of the most important and under-recognized secrets to Silicon Valley’s ongoing success.” Tech leaders agree with Berlin’s assessment. Apple cofounder Steve Jobs—who learned most of what he knew about business from the men of the semiconductor industry—likened it to passing a baton in a relay race.

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Predicting the climate bill’s effects is harder than you might think

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Predicting the climate bill’s effects is harder than you might think


Human decision-making can also cause models and reality to misalign. “People don’t necessarily always do what is, on paper, the most economic,” says Robbie Orvis, who leads the energy policy solutions program at Energy Innovation.

This is a common issue for consumer tax credits, like those for electric vehicles or home energy efficiency upgrades. Often people don’t have the information or funds needed to take advantage of tax credits.

Likewise, there are no assurances that credits in the power sectors will have the impact that modelers expect. Finding sites for new power projects and getting permits for them can be challenging, potentially derailing progress. Some of this friction is factored into the models, Orvis says. But there’s still potential for more challenges than modelers expect.

Not enough

Putting too much stock in results from models can be problematic, says James Bushnell, an economist at the University of California, Davis. For one thing, models could overestimate how much behavior change is because of tax credits. Some of the projects that are claiming tax credits would probably have been built anyway, Bushnell says, especially solar and wind installations, which are already becoming more widespread and cheaper to build.

Still, whether or not the bill meets the expectations of the modelers, it’s a step forward in providing climate-friendly incentives, since it replaces solar- and wind-specific credits with broader clean-energy credits that will be more flexible for developers in choosing which technologies to deploy.

Another positive of the legislation is all its long-term investments, whose potential impacts aren’t fully captured in the economic models. The bill includes money for research and development of new technologies like direct air capture and clean hydrogen, which are still unproven but could have major impacts on emissions in the coming decades if they prove to be efficient and practical. 

Whatever the effectiveness of the Inflation Reduction Act, however, it’s clear that more climate action is still needed to meet emissions goals in 2030 and beyond. Indeed, even if the predictions of the modelers are correct, the bill is still not sufficient for the US to meet its stated goals under the Paris agreement of cutting emissions to half of 2005 levels by 2030.

The path ahead for US climate action isn’t as certain as some might wish it were. But with the Inflation Reduction Act, the country has taken a big step. Exactly how big is still an open question. 

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