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In the data decade, data can be both an advantage and a burden



In the data decade, data can be both an advantage and a burden

In 2016, Dell Technologies commissioned our first Digital Transformation Index (DT Index) study to assess the digital maturity of businesses around the globe. We have since commissioned the study every two years to track businesses’ digital maturity.

Sam Grocott is Senior Vice President of Business Unit Marketing at Dell Technologies.

Our third installment of the DT Index, launched in 2020 (the year of the pandemic), revealed that “data overload/unable to extract insights from data” was the third highest-ranking barrier to transformation, up from 11th place in 2016. That is a huge jump from the bottom to close to the top of the ranking of barriers to digital transformation.

These findings point to a curious paradox—data has the potential to become businesses’ number one barrier to transformation while also being their greatest asset. To learn more about why this paradox exists and where businesses need the most help, we commissioned a study with Forrester Consulting to dig deeper.

The resulting study, based on a survey with 4,036 senior decision-makers with responsibility for their companies’ data strategy, titled: Unveiling Data Challenges Afflicting Businesses Around the World, is available to read now.

Candidly, the study confirms our concerns: in this data decade, data has become both a burden and an advantage for many businesses—which one depends on how data-ready the business might be.

While Forrester identifies several data paradoxes hindering businesses today, three major contradictions stood out for me.

1. The perception paradox

Two-thirds of respondents would say their business is data-driven and state “data is the lifeblood of their organization.” But only 21% say they treat data as capital and prioritize its use across the business today.

Clearly, there’s a disconnect here. To provide some clarity, Forrester created an objective measure of businesses’ data readiness (see figure).

The results showed that 88% of businesses are yet to progress either their data technology and processes and/or their data culture and skills. In fact, only 12% of businesses are defined as Data Champions: companies that are actively engaged in both areas (technology/process and culture/skills).

2. The “want more than they can handle” paradox

The research also shows that businesses need more data, but they have too much data to handle right now: 70% say they are gathering data faster than they can analyze and use, yet 67% say they constantly need more data than their current capabilities provide.

While this is a paradox, it’s not all that surprising when you consider the research holistically, such as the proportion of companies that are yet to secure data advocacy at a Boardroom level and fall back to an IT strategy that can’t scale (i.e., bolting on more data lakes).

The implications of this paradox are profound and far-reaching. Six in 10 businesses are battling with data silos; 64% of respondents complain they have such a glut of data they can’t meet security and compliance requirements, and 61% say their teams are already overwhelmed by the data they have.

3. The “seeing without doing” paradox

While economies have suffered during the pandemic, the on-demand sector has expanded rapidly, igniting a new wave of data-first, data-anywhere businesses that pay for what they use and only use what they need—determined by the data that they generate and analyze.

Although these businesses are emerging, and doing very well, they’re still relatively small in number. Only 20% of businesses have moved the majority of their applications and infrastructure to an as-a-service model—even though more than 6 in 10 believe an as-a-service model would enable firms to be more agile, scale, and provision applications without complexity.

Achieving breakthrough together

The research is sobering,but there is hope on the horizon. Businesses are looking to revise their data strategies with a multi-cloud environment, by moving to a data-as-a-service model and automating data processes with machine learning.

Granted, they have a lot to do to prime the pumps for a proliferation of data. Still, there is a path forward, by firstly modernizing their IT infrastructure so they can meet data where it lives, at the edge. This incorporates bringing businesses’ infrastructure and applications closer to where data needs to be captured, analyzed and acted on–while avoiding data sprawl, by maintaining a consistent multi-cloud operating model.

Secondly, by optimizing data pipelines, so data can flow freely and securely while being augmented by AI/ML; and thirdly, by developing software to deliver the personalized, integrated experiences customers crave.

The staggering volume, variety and velocity of data may seem overpowering but with the right technology, processes and culture, businesses can tame the data beast, innovate with it, and create new value.

To learn more about the study, visit

This content was produced by Dell Technologies. It was not written by MIT Technology Review’s editorial staff.


The hunter-gatherer groups at the heart of a microbiome gold rush



The hunter-gatherer groups at the heart of a microbiome gold rush

The first step to finding out is to catalogue what microbes we might have lost. To get as close to ancient microbiomes as possible, microbiologists have begun studying multiple Indigenous groups. Two have received the most attention: the Yanomami of the Amazon rainforest and the Hadza, in northern Tanzania. 

Researchers have made some startling discoveries already. A study by Sonnenburg and his colleagues, published in July, found that the gut microbiomes of the Hadza appear to include bugs that aren’t seen elsewhere—around 20% of the microbe genomes identified had not been recorded in a global catalogue of over 200,000 such genomes. The researchers found 8.4 million protein families in the guts of the 167 Hadza people they studied. Over half of them had not previously been identified in the human gut.

Plenty of other studies published in the last decade or so have helped build a picture of how the diets and lifestyles of hunter-gatherer societies influence the microbiome, and scientists have speculated on what this means for those living in more industrialized societies. But these revelations have come at a price.

A changing way of life

The Hadza people hunt wild animals and forage for fruit and honey. “We still live the ancient way of life, with arrows and old knives,” says Mangola, who works with the Olanakwe Community Fund to support education and economic projects for the Hadza. Hunters seek out food in the bush, which might include baboons, vervet monkeys, guinea fowl, kudu, porcupines, or dik-dik. Gatherers collect fruits, vegetables, and honey.

Mangola, who has met with multiple scientists over the years and participated in many research projects, has witnessed firsthand the impact of such research on his community. Much of it has been positive. But not all researchers act thoughtfully and ethically, he says, and some have exploited or harmed the community.

One enduring problem, says Mangola, is that scientists have tended to come and study the Hadza without properly explaining their research or their results. They arrive from Europe or the US, accompanied by guides, and collect feces, blood, hair, and other biological samples. Often, the people giving up these samples don’t know what they will be used for, says Mangola. Scientists get their results and publish them without returning to share them. “You tell the world [what you’ve discovered]—why can’t you come back to Tanzania to tell the Hadza?” asks Mangola. “It would bring meaning and excitement to the community,” he says.

Some scientists have talked about the Hadza as if they were living fossils, says Alyssa Crittenden, a nutritional anthropologist and biologist at the University of Nevada in Las Vegas, who has been studying and working with the Hadza for the last two decades.

The Hadza have been described as being “locked in time,” she adds, but characterizations like that don’t reflect reality. She has made many trips to Tanzania and seen for herself how life has changed. Tourists flock to the region. Roads have been built. Charities have helped the Hadza secure land rights. Mangola went abroad for his education: he has a law degree and a master’s from the Indigenous Peoples Law and Policy program at the University of Arizona.

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The Download: a microbiome gold rush, and Eric Schmidt’s election misinformation plan



The Download: a microbiome gold rush, and Eric Schmidt’s election misinformation plan

Over the last couple of decades, scientists have come to realize just how important the microbes that crawl all over us are to our health. But some believe our microbiomes are in crisis—casualties of an increasingly sanitized way of life. Disturbances in the collections of microbes we host have been associated with a whole host of diseases, ranging from arthritis to Alzheimer’s.

Some might not be completely gone, though. Scientists believe many might still be hiding inside the intestines of people who don’t live in the polluted, processed environment that most of the rest of us share. They’ve been studying the feces of people like the Yanomami, an Indigenous group in the Amazon, who appear to still have some of the microbes that other people have lost. 

But there is a major catch: we don’t know whether those in hunter-gatherer societies really do have “healthier” microbiomes—and if they do, whether the benefits could be shared with others. At the same time, members of the communities being studied are concerned about the risk of what’s called biopiracy—taking natural resources from poorer countries for the benefit of wealthier ones. Read the full story.

—Jessica Hamzelou

Eric Schmidt has a 6-point plan for fighting election misinformation

—by Eric Schmidt, formerly the CEO of Google, and current cofounder of philanthropic initiative Schmidt Futures

The coming year will be one of seismic political shifts. Over 4 billion people will head to the polls in countries including the United States, Taiwan, India, and Indonesia, making 2024 the biggest election year in history.

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Navigating a shifting customer-engagement landscape with generative AI



Navigating a shifting customer-engagement landscape with generative AI

A strategic imperative

Generative AI’s ability to harness customer data in a highly sophisticated manner means enterprises are accelerating plans to invest in and leverage the technology’s capabilities. In a study titled “The Future of Enterprise Data & AI,” Corinium Intelligence and WNS Triange surveyed 100 global C-suite leaders and decision-makers specializing in AI, analytics, and data. Seventy-six percent of the respondents said that their organizations are already using or planning to use generative AI.

According to McKinsey, while generative AI will affect most business functions, “four of them will likely account for 75% of the total annual value it can deliver.” Among these are marketing and sales and customer operations. Yet, despite the technology’s benefits, many leaders are unsure about the right approach to take and mindful of the risks associated with large investments.

Mapping out a generative AI pathway

One of the first challenges organizations need to overcome is senior leadership alignment. “You need the necessary strategy; you need the ability to have the necessary buy-in of people,” says Ayer. “You need to make sure that you’ve got the right use case and business case for each one of them.” In other words, a clearly defined roadmap and precise business objectives are as crucial as understanding whether a process is amenable to the use of generative AI.

The implementation of a generative AI strategy can take time. According to Ayer, business leaders should maintain a realistic perspective on the duration required for formulating a strategy, conduct necessary training across various teams and functions, and identify the areas of value addition. And for any generative AI deployment to work seamlessly, the right data ecosystems must be in place.

Ayer cites WNS Triange’s collaboration with an insurer to create a claims process by leveraging generative AI. Thanks to the new technology, the insurer can immediately assess the severity of a vehicle’s damage from an accident and make a claims recommendation based on the unstructured data provided by the client. “Because this can be immediately assessed by a surveyor and they can reach a recommendation quickly, this instantly improves the insurer’s ability to satisfy their policyholders and reduce the claims processing time,” Ayer explains.

All that, however, would not be possible without data on past claims history, repair costs, transaction data, and other necessary data sets to extract clear value from generative AI analysis. “Be very clear about data sufficiency. Don’t jump into a program where eventually you realize you don’t have the necessary data,” Ayer says.

The benefits of third-party experience

Enterprises are increasingly aware that they must embrace generative AI, but knowing where to begin is another thing. “You start off wanting to make sure you don’t repeat mistakes other people have made,” says Ayer. An external provider can help organizations avoid those mistakes and leverage best practices and frameworks for testing and defining explainability and benchmarks for return on investment (ROI).

Using pre-built solutions by external partners can expedite time to market and increase a generative AI program’s value. These solutions can harness pre-built industry-specific generative AI platforms to accelerate deployment. “Generative AI programs can be extremely complicated,” Ayer points out. “There are a lot of infrastructure requirements, touch points with customers, and internal regulations. Organizations will also have to consider using pre-built solutions to accelerate speed to value. Third-party service providers bring the expertise of having an integrated approach to all these elements.”

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