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Descubre un mundo infinito de historias

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MIT Technology Review Insights

The Business Lab is a sponsored podcast produced by Insights, the custom content division of MIT Technology Review. The Business Lab podcast features a 30-minute conversation with either an executive from the sponsor partner or a technologist with expertise in a relevant technology area. The discussion focuses on technology topics that matter to today’s enterprise decision makers. Laurel Ruma, MIT Technology Review’s custom content director for the United States, is the host.

Business Lab

The World Bank Group has a massive mission to “help developing countries escape poverty and share prosperity,” says Vijay Yellai, program manager for enterprise resource planning transformation at the World Bank Group. For example, it provides an wide array of financial products and technical know-how in a complex and ever-changing global setting.
 
Therefore, for an institution like the World Bank Group, which provides funding and resources to countries with low bandwidth and infrastructure, IT modernization is no small feat.
 
“So in an ever-changing environment–complexity, risk, and security threats with a global workforce–the World Bank is under pressure to do more with less,” says Yellai. He explains that the challenge is to increase real-time business, as well as quickly respond to changing needs of customers and employees. But also, Yellai continues, “security, risk, and data are key elements. Not to mention the continuous need for business intelligence and quick decision making.” The ultimate goal is to “capitalize on technology to meet our mission and goals.”
 
And although data collection and processing is key to IT systems, an agile and adaptive approach is needed to keep operational and financial systems current in each business. “Data is very fundamental to that. And data and research help us understand how we are addressing the needs, helps us set up priorities, helps us share knowledge, and helps us measure progress.” Yellai says.
 
With a modernized IT system, Yellai says, there are a number of innovations that become possible. Predictive analytics, natural language processing, blockchain, and process automation are a few of the technologies emerging to allow for quicker decision-making and efficiency.
 
“Anything we can do to reduce the work we need to do in technology, but let the technology do more for us, so we can focus our time on the strategic priorities, will be the most exciting thing for us,” says Yellai.
 
This episode of Business Lab is produced in association with Infosys Cobalt.

Modernizing IT Helps Enterprises Do More with Less

Although the world population has continued to steadily increase, farming practices have largely remained the same. Amid this growth, climate change poses great challenges to the agricultural industry and its capacity to feed the world sustainably. According to the World Bank, 70% of the world’s fresh water is used in agriculture and droughts and heat waves continue to threaten crops. And that is where the challenge arises to feed the world while mitigating the environmental effects of agricultural practices.
 
The answer to this challenge, according to Thomas Jung, head of IT Research and Development at Syngenta, is regenerative agriculture. Just as important as clean water and clean air, soil is the critical foundation of agriculture. The crux of regenerative agriculture is to grow more food with less environmental impact by enhancing the health of soil.
 
“So not much has changed, but we need to feed more and more people,” he continues “How do we address this challenge of feeding the world in a sustainable fashion without exploiting our soils more?”
 
Regenerative agriculture efforts look to find solutions to help plants stay healthy, find solutions to make crops more resistant to climate change-induced droughts and heatwaves, and use less water in farming.
 
Therefore, what’s necessary is, “moving beyond the traditional agriculture and the way we've been doing this for probably 100 years or more. I mean, this is a leap,” says Jung. “This is an agricultural revolution that is ongoing, and artificial intelligence will play the decisive role in it.”
 
Although farmers have invaluable knowledge of their own crops and fields, says Jung, AI and machine learning tools can be instrumental in cataloging greater detail, refining algorithms, and creating recommendations for solutions. As more data is collected and algorithms continue to improve to create new innovations, we’ll be even closer to understanding our planetary ecosystem, says Jung. Breakthroughs like soil regeneration, really living with sustainable agriculture across disciplines are achievable within the next three years.
 
“There's a lot of advocacy for open source, for democratized data, for fair data, and we need to bring that to the industry,” says Jung. “This can't just be an NGO or a volunteering thing, that this is how I believe our industry needs to work. So we really want to share, we want to lead by example, we want to nurture the community, and through that, win altogether.”

This episode of Business Lab is produced in association with Infosys Cobalt.

Feeding the World by AI, Machine Learning, and the Cloud

The last five years have seen large innovations throughout drug development and clinical trial life cycles—from finding a target and designing the trial, to getting a drug approved and launching the drug itself. The recent use of mRNA vaccines to combat covid-19 is just one of many advances in biotech and drug development.

Whether in preclinical stages or in the commercialization of a drug, AI-enabled drug development is now used by an estimated 400 companies and has reached a $50 billion market, placing AI more firmly in the life sciences mainstream.

“Now, if you look at the parallel movements that are happening in technology, everyone’s in consensus that the utility of what AI can do in drug development is becoming more evident,” says senior vice president at Medidata AI, Arnaub Chatterjee.

The pandemic has shown how critical and fraught the race can be to provide new treatments to patients, positioning the pharmaceutical industry at an inflection point, says Chatterjee.

And that’s because drug development usually takes years. Evidence generation is the industry-standard process of collecting and analyzing data to demonstrate a drug’s safety and efficacy to stakeholders, including regulators, providers, and patients.

The challenge, says Chatterjee, becomes, “How do we keep the rigor of the clinical trial and tell the entire story, and then how do we bring in the real-world data to kind of complete that picture?”
 
To build more effective treatments faster, drug and vaccine companies are using data iteratively to improve understanding of diseases that can be used for future drug design. Bridging gaps between clinical trial and real-world data creates longitudinal records. AI models and analytics can then be used to enable feedback loops that are key for ensuring safety, efficacy, and value, says Chatterjee.

“We want to create safe and expeditious access to therapy,” says Chatterjee. “So we really have to meet this moment with innovation. With all the new advances happening in drug development, there’s no reason why technology and data can’t be there.”
 
This episode of Business Lab is produced in association with Medidata.
 
Related resources
● Integrated evidence, Medidata
● Why artificial intelligence could speed drug discovery, Morgan Stanley

AI and Data Fuel Innovation in Clinical Trials and Beyond

Memory and storage solutions for technology are built into our everyday life, from mobile applications, cars, health-care systems, and more. To meet that need and help propel innovation, Micron Technology said it would invest $150 billion into research and development to build factories for its semiconductor memory chips. This investment looks to expand not only the reach of memory chips but also to innovate new solutions to common problems, says Naga Chandrasekaran, senior vice president of technology development at Micron.

“The day we stop innovating, not just in memory, but as a human race, the day we stop innovating, we stop progressing and that's not where we want to be. We want to continue to drive innovation,” says Chandrasekaran.

With each iteration of new technology, from phones to cars, consumers are looking for improved performance, lower latency, more storage, and lower costs. Meeting these expectations means finding solutions at an atomic scale and making micro changes to push the boundaries of what’s possible.

Since its inception 44 years ago, Micron has developed over 50,000 patents. While Chandrasekaran emphasizes that patents are just one part of fostering innovation, they do represent the strides toward greater innovations and the company culture that Micron has worked to establish.

While having strong team members is important, the culture that a company fosters is just as crucial when it comes to seeing positive results. Chandrasekaran says that building successful teams that can create so many patents and build technologies with an eye on innovation requires a certain company mindset that doesn’t shy away from mistakes or failure.

“So we are taking risks on a regular basis, but the key is to make sure we can fail fast and not see those failures as a mistake, but actually learn from them.” Chandrasekaran continues, “That's why failing fast is important, but not being afraid of failing.”

In addition to taking risks, diversity has become a significant contributor to driving new solutions. Between 2017 and 2021, the number of women listed as inventors on Micron patent applications quadrupled. Chandrasekaran says that for any sustained success and innovation to be possible, diversity is necessary.

“No matter what we say, we are all limited in our thought process in how we approach problems, in how we approach solutions. And even with a growth mindset, we have limitations, because we are who we are based on the experiences and the exposures that we have gained,” says Chandrasekaran. “So diversity brings in not just from a gender diversity or ethnic diversity, but if we look at diversity from a broader scale, it's diversity of thought process.”
 
 
This episode of Business Lab is produced in association with Micron Technology.

Building a Culture of Innovation in Research and Development

In any enterprise, digital transformation is not only a technology transformation but enables business transformation itself, driving new products, solutions and innovations. Having an efficient data strategy is critical to any successful digital transformation but requires careful investment into both people and systems.
 
“To achieve that goal, availability of good data, of the right data, and availability of that to the right people and systems is very, very critical. So that forms the data strategy for any enterprise today,” says chief architect for data and AI services at Kyndryl, Sundar Shanmugam.
 
Getting the most out of digital transformation investments means evaluating and optimizing agility throughout an enterprise to drive actionable insights, says Shanmugam. A strong data governance framework also goes a long way in keeping data high-quality. Often data governance primarily serves regulatory requirements. But truly effective data governance is holistic, he adds. Data usage, regulations, and the data itself are constantly evolving within an enterprise, effectively making data governance a continuous process.
 
Although tech teams are often dictating how data should be managed and used, Shanmugam says everyone across the enterprise, including leaders and decision makers, should be data literate.
 
“End of the day, the people are the ones who design the systems and who develop the systems that consume the data, so the right investment on literacy is paramount in that aspect,” says Shanmugam.
 
Another key component to digital transformation lies in maximizing investments across business units. The combination of software development and operations to form devOps, AI and machine learning to form MLOps, and finance and operations to form finOps all fall under the broader umbrella of XOps that categorize these merging of IT disciplines with business operations. XOps all come together to deliver value in the most efficient way with each combination focused on maximizing automation, reusability, and agility, says Shanmugam.
 
“As we say, necessity is the mother of innovation, so that necessity can continuously change,” says Shanmugam. “At the core of that, if we keep that data proper [condition], then it can expand the horizons, not just internally, but even for the other external requirements and use cases.”
 
This episode of Business Lab is produced in association with Kyndryl.
 
Related reading
Top Trends in Data and Analytics for 2021, Gartner, February 16, 2021

Maximize Data Outcomes by Investing in People and Systems

As more business, shopping, and banking is done online and from, well, anywhere, customers increasingly expect high-quality digital-first services that remove the need to go into a physical store or bank.
“People were working from home, shopping from home, banking from home, and are more tech and digital savvy than ever,” says Mike Dargan, group chief digital and information officer for UBS. “And if you look at the financial services industry, the ecosystem is constantly evolving, so it becomes more competitive, open, connected, and location-independent every day.”
Banks like UBS are experiencing a cultural transformation that makes technology itself integral to the business offering. Because technology is often the first—or only—medium via which customers encounter a business, the quality of that digital customer experience is key to the value it provides. To make that digital-first experience a differentiator for a business, Dargan explains, requires strategically and substantially investing in tech throughout the enterprise.
Investing in technology means a targeted focus on the people and platforms behind the customer-facing experiences, not just building out the feature of the month. Dargan’s roadmap begins with engineering excellence—attracting and retaining engineers who want to shape the direction of the industry.
In addition to offering an inclusive culture and opportunities to solve important real-world problems, companies seeking the best engineers must provide cutting-edge platforms and tools to create an industry-leading developer experience. To enable this—as well as to reimagine what they can offer to clients—UBS has made years-long investments in updating legacy systems to new technology, focusing on infrastructure allowing the launch of cloud-native applications on a cloud-native platform.
Internal company processes, though invisible to customers, drive the speed and quality of digital innovation. At UBS, process focus has included training on agile methodologies—teaching employees from all business areas how to get from emerging requirements to high-quality outcomes as quickly and iteratively as possible.
Less obvious longer-term investments in the technology future may also pay dividends both in business terms and in customer experience. In the sustainability space, UBS has partnered with the Green Software Foundation to build software standards and best practices for reducing carbon emissions, and has set a goal of net zero greenhouse gas emissions across its operations by 2050.
Says Dargan, “the world is faster, more digital, and more data-driven than ever before, so clients really do demand services that are digital-first, anytime, anywhere, and are underpinned by first-class technologies. In fact, I'd say tech is really how our clients experience us every day.”
 
This episode of Business Lab is produced in association with UBS.

Building great digital customer experiences with agile infrastructure

A heritage financial services institution isn’t necessarily the first place a technologist looks to grow their career. But that hasn’t been a problem for JPMorgan Chase, which has made itself an appealing career destination for technologists. “Technology is not an afterthought,” says Gill Haus, chief information officer of consumer and community banking at JPMorgan Chase. “It is in everything we do, from our offices to our branches to our contact centers to our web and mobile applications.”
Haus explains that there’s more to being a technology company than using technology to solve problems. “What really makes a technology company is how you think about the way you hire teams, the way you groom teams, the way you build software, the way you deploy that software,” says Haus. “It's how you organize around products, not around your business units.”
Like a technology startup, the technical teams at JPMorgan Chase solve real-world problems. “Every single day, we are launching new features and products that make it easier for everyone. It's incredibly exciting,” says Haus.
However, unlike a startup, JPMorgan Chase has scale. The financial services institution supports 44 million mobile active customers and 59 million digitally active customers in general. The company spends $12 billion on technology annually. “When we launch a solution or bring a new product to market, we don't bring it to market for 1,000 people. We don't bring it to market for a 100,000 people. We bring it to market for millions of customers immediately, and that is incredible,” says Haus. “There's incredible talent here, as you can imagine, because we have such a technical need. Talent begets talent. It's exciting to go to a place where you know you're going to be challenged.”

Using Technology to Power the Future of Banking

The current 5G evolution in network connectivity is expected to drive unprecedented demands for bandwidth, reliability, and security. However, a network of this magnitude and robustness doesn’t pop up overnight and enterprises and consumers are just beginning to realize the myriad use cases a 5G network can support.
For example, consider the increased number of connected devices in a house like smart thermostats, security cameras, tablets, smartwatches, and mobile phones, of course. Raj Savoor, the vice president of network analytics and automation at AT&T Labs explains, “Currently we estimate the average consumer home footprint has about 13 connected devices, including mobile and other devices.” And although that sounds like a large number, he continues to explain the real scale, “That's going to increase to 30 to 40 devices over the next five years, so a really big increase.” And the real challenge he continues to explain is that, “This growth needs advanced network architectures to support, manage and provide fast, secure, and reliable services.”
Bandwidth will also increase five times in the next five years, according to Savoor, as consumers adopt immersive interactive applications. Immersive experiences also require lower latency and jitter, and a lot more security and reliability. For a company like AT&T that supports a large existing network, building the next generation network requires an incremental approach. In fact, AT&T’s 5G network has been years in the making. “We look at it as a journey. There are a lot of steps that we've taken over the past few years to build on it, and we have prepared for the next step,” says Savoor.
And as businesses and consumers transition to a 5G world, AT&T keeps looking ahead. “We are thinking about the next 20 and 50 years. Network investments take a long time, and we want to make those investments with economics in mind, but also very much ensuring the most reliable network offering,” says Savoor.

Building Tomorrow’s Telecommunications Network Today

The skills and capabilities needed to undergo digital transformation are in high demand as every company jockeys to gain a competitive advantage. To address the skills gap, some companies are prioritizing upskilling and reskilling. But to be effective, learning and development itself must undergo a transformation.
According to Daniela Proust, global vice president and head of global people enablement and growth at Siemens, learning and development is at the core of digital transformation. “In light of a major transformation that businesses are facing, either by new business models arising or new innovation and technologies driving a certain business area forward, you see that you need to accompany that structural change, that structural workforce transformation in order to drive business transformation,” she says.
Traditional training methods need to also transform. Given the speed of technological change and need for business agility, multi-day offsite training (some of which may not even apply to the employee’s role) is no longer viable. Fortunately, the same technologies that are driving digital transformation in other areas of the business can also be leveraged to transform learning and development.
“Now people learn more often, for shorter periods of time, but training is much more tailored to what they need in that moment, and that is enabled by technology,” explains Proust.
In addition to delivering just-in-time training, a modern learning and development platform can provide valuable insights. “A platform-based learning ecosystem with a learning experience platform at the core enables you to gain insights that we never had in the past.” says Proust.
This new approach to learning delivers benefits to both the business and its employees as they acquire the skills that help accelerate the company’s digital transformation and fuel their own career growth.
 
This episode of Business Lab is produced in association with Infosys Cobalt.

Building the Necessary Skills for Digital Transformation

Like many banks, National Australia Bank (NAB) decided to outsource a large part of its operations in the 1990s. “We pushed all our operations and a large part of our development capability out to third parties with the intent of lowering costs and making our operations far more process driven,” says Steve Day, the chief technology officer of enterprise technology at National Australia Bank.
Unfortunately, achieving these goals had an unintended consequence. “We froze our operations in time,” says Day. “If you roll forward to 2018, we realized that we were still operating like we're in the 1990s. We were very waterfall driven. Our systems were highly processed driven, but in a very manual way, and it took us a very long time to roll out new products and services that our customers really needed.”
Meanwhile, young financial services companies were coming to market with innovative products and services and NAB was finding it difficult to compete. “Many customers today are expecting an Amazon experience, a Google experience, a Meta experience, but we were still operating in the 1990s,” says Day. “We stood back, and we looked at it, and we decided that our entire culture needed to change.”
What ensued was nothing less than an internal transformation. “Our original teams didn't have a lot of tech skills, so to tell them that they were going to have to take on all of this technical accountability, an operational task that had previously been handed to our outsourcers, was daunting,” says Day.
Day and his team rolled out a number of initiatives to instill confidence across the organization and train people in the necessary technical skills. “We built confidence through education, through a lot of cultural work, a lot of explaining the strategy, a lot of explaining to people what good looked like in 2020, and how we were going to get to that place,” says Day.
This episode of Business Lab is produced in association with Infosys Cobalt.

Embracing Culture Change on the Path to Digital Transformation

There’s nothing new about conspiracy theories, disinformation, and untruths in politics. What is new is how quickly malicious actors can spread disinformation when the world is tightly connected across social networks and internet news sites. We can give up on the problem and rely on the platforms themselves to fact-check stories or posts and screen out disinformation—or we can build new tools to help people identify disinformation as soon as it crosses their screens.
Preslav Nakov is a computer scientist at the Qatar Computing Research Institute in Doha specializing in speech and language processing. He leads a project using machine learning to assess the reliability of media sources. That allows his team to gather news articles alongside signals about their trustworthiness and political biases, all in a Google News-like format.
“You cannot possibly fact-check every single claim in the world,” Nakov explains. Instead, focus on the source. “I like to say that you can fact-check the fake news before it was even written.” His team’s tool, called the Tanbih News Aggregator, is available in Arabic and English and gathers articles in areas such as business, politics, sports, science and technology, and covid-19.
Business Lab is hosted by Laurel Ruma, editorial director of Insights, the custom publishing division of MIT Technology Review. The show is a production of MIT Technology Review, with production help from Collective Next.
This podcast was produced in partnership with the Qatar Foundation.
Show notes and links
Tanbih News Aggregator
Qatar Computing Research Institute
“Even the best AI for spotting fake news is still terrible,” MIT Technology Review, October 3, 2018

Machine Learning Project Takes Aim at Disinformation

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