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Travis Kalanick needs to hire Sheryl Sandberg to save Uber (FB)

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Facebook’s chief operating officer, Sheryl Sandberg, is the perfect person to help Uber through this crisis.

Uber CEO Travis Kalanick is going to try to correct his increasingly erratic management style and rescue the nearly $70 billion value of his company by hiring a COO, Business Insider’s Biz Carson reported Wednesday.

Carson says that Uber’s precedent for this move is Facebook bringing in Sheryl Sandberg, a Google veteran, to be the adult in the room and get Facebook CEO Mark Zuckerberg in shape for a billion-dollar initial public offering in 2012.

Since then, bringing in a professional COO to get things on track when a Silicon Valley tech CEO’s personality becomes a problem for investors who have sunk vast sums into a startup has been called “getting a Sheryl Sandberg.” She was that good at making Facebook the juggernaut we know today.

So Kalanick and his probably very concerned board are looking for their Sandberg. But they may not need to look very far. Sandberg might not be aiming to leave Facebook, but you could argue that if it would mean saving Uber, for the good of Silicon Valley, she should.

Uber is Silicon Valley now, much as Facebook was Silicon Valley in the early 2010s. It was imperative Facebook stage a successful IPO in 2012, and it’s increasingly important for Uber to provide investors with an exit at some point in the future. Kalanick doesn’t want to take the company public, but he won’t be able to keep it private forever — and after Snap’s IPO, the tech sector can again see, as it did with Facebook, that the good-old IPO route can be lucrative.

Beyond how Uber pays off investors, it’s important that the company simply make it through any economic turbulence ahead. Facebook survived the financial crisis, as did Tesla. (It went public in 2010.) Uber is so valuable and has upheld investment enthusiasm in Silicon Valley for so long now that it needs to remain viable.

The company’s and Kalanick’s behavior has threatened that. Sure, Uber had a spectacular rollout of its self-driving technology in Pittsburgh, but it suffered an embarrassing retreat after its lawbreaking debut of the same tech in San Francisco. What’s more, Uber has been accused of fostering a sexist, discriminatory culture, and last week it was revealed that Kalanick had lambasted a driver for complaining about price cuts.

It’s time for this to stop and for Kalanick, at 40, to grow up. Sandberg has already proved that she can guide an immature young man into a leadership role and help create a company with a market cap of nearly $400 billion. She would have her work cut out for her — Zuckerberg was 23 when Facebook went public; Kalanick may be more set in his bad ways.

But then again, Sandberg, who’s 47, wouldn’t take any guff. “Lean In,” Sandberg’s best-selling book about women and their careers, means lean in — it’s as much a philosophy of life as it is a way of advancing women’s ambition.

She’s also quite well off financially. Sandberg was rich when she joined Facebook, and she’s much richer now. This would grant her a crucial level of independence with Uber. As a member of the Disney board, she has also seen one of the most polished CEOs, Bob Iger, in action. (In fact, she was once talked about as an Iger successor.)

OK, so Sandberg joining Uber is sort of a long shot.

Sandberg tragically lost her husband, Dave Goldberg, who died in 2015. She’s among the top female leaders in tech — really, one of the top leaders, period. She has nothing to prove and certainly is entitled to live her life, having already helped to build two of the dominant companies in Silicon Valley.

Facebook and Uber are also very different operations. Google and Facebook at least had certain elements in common, which helped Sandberg maximize her contribution to creating a vibrant advertising business for Zuckerberg. And while Facebook was, early on, dorkily boyish, Uber is toxically fratty. But at a level, a business challenge is a business challenge, and both companies are undergirded by software and computer science. The core issue now for Uber is putting a responsible adult next to Kalanick — so much the better if the adult is an impressive and accomplished woman.

Besides, Uber needs her — and Silicon Valley urgently needs Uber to negotiate its latest crisis without having to take the extreme step of demanding that Kalanick, whose personality is fused with the company for better or worse, step down. It’s about time someone with powerful organizational experience and a hugely successful IPO under her belt made Kalanick get his act together.

Sandberg, who at one time worked for former Treasury Secretary Larry Summers, was once rumored to be interested in entering politics. But that was before Donald Trump won the presidential election and the GOP took over Washington. So Sandberg, whose politics are aligned with Hillary Clinton, has far less of an incentive to do that these days.

The obvious question is: Would she even consider leaving Facebook to rescue some of Silicon Valley’s biggest investors? That would be a tough one for Sandberg to answer. And Zuckerberg would, I’m sure, be dead-set against losing her. But then again, she could also spend a year or so shaping up Uber and then return to Facebook.

Maybe she’s looking for another challenge; maybe she isn’t. But it shouldn’t be hard for Uber to figure out who Kalanick’s Sandberg, in a perfect world, would be.

source;http://pulse.ng/bi/tech/tech-travis-kalanick-needs-to-hire-sheryl-sandberg-to-save-uber-fb-id6339845.html

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THE 7 MOST IN-DEMAND TECH JOBS FOR 2018

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The 7 most in-demand tech jobs for 2018

CIO | Jun 6, 2018

From data scientists to data security pros, the battle for the best in IT talent will wage on next year. Here’s what to look for when you’re hiring for the 7 most in-demand jobs for 2018 — and how much you should offer based on experience.

 

 

 

 

Source: Computer World

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Industry

AUTOMATION WILL MAKE LIFELONG LEARNING A NECESSARY PART OF WORK

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As more companies adopt and learn through digital solutions, and as new forms of employment and investment opportunities strengthen the demand recovery, we expect productivity growth to recover, write James Manyika and Myron Scholes in Project Syndicate.

For years, one of the big puzzles in economics has been accounting for declining productivity growth in the United States and other advanced economies. Economists have proposed a wide variety of explanations, ranging from inaccurate measurement to “secular stagnation” to questioning whether recent technological innovations are productive.

But the solution to the puzzle seems to lie in understanding economic interactions, rather than identifying a single culprit. And on that score, we may be getting to the bottom of why productivity growth has slowed.

Examining the decade since the 2008 financial crisis – a period remarkable for the sharp deterioration in productivity growth across many advanced economies – we identify three outstanding features: historically low growth in capital intensity, digitization, and a weak demand recovery. Together these features help explain why annual productivity growth dropped 80%, on average, between 2010 and 2014, to 0.5%, from 2.4% a decade earlier.

Start with historically weak capital-intensity growth, an indication of the access labor has to machinery, tools, and equipment. Growth in this average toolkit for workers has slowed – and has even turned negative in the US.

In the 2000-2004 period, capital intensity in the US grew at a compound annual rate of 3.6%. In the 2010-2014 period, it declined at a compound annual rate of 0.4%, the weakest performance in the postwar period. A breakdown of the components of labor productivity shows that slowing capital-intensity growth contributed about half or more of the decline in productivity growth in many countries, including the US.

Growth in capital intensity has been weakened by a substantial slowdown in investment in equipment and structures. Making matters worse, public investment has also been in decline. For example, the US, Germany, France, and the United Kingdom experienced a long-term decline of 0.5-1 percentage point in public investment between the 1980s and early 2000s, and the figure has been roughly flat or decreasing since then, creating significant infrastructure gaps.

Intangible investment, in areas such as software and research and development, recovered far more quickly from a brief and smaller post-crisis dip in 2009. Continued growth in such investment reflects the wave of digitization – the second outstanding feature of this period of anemic productivity growth – that is now sweeping across industries.

By digitization, we mean digital technology – such as cloud computing, e-commerce, mobile Internet, artificial intelligence, machine learning, and the Internet of Things (IoT) – that is moving beyond process optimization and transforming business models, altering value chains, and blurring lines across industries. What differentiates this latest wave from the 1990s boom in information and communications technology (ICT) is the breadth and diversity of innovations: new products and features (for example, digital books and live location tracking), new ways to deliver them (for example, streaming video), and new business models (for example, Uber and TaskRabbit).

However, there are also similarities, particularly regarding the effect on productivity growth. The ICT revolution was visible everywhere, the economist Robert Solow famously noted, except in the productivity statistics. The Solow Paradox, as it was known (after the economist), was eventually resolved when a few sectors – technology, retail, and wholesale – ignited a productivity boom in the US. Today, we may be in round two of the Solow Paradox: while digital technologies can be seen everywhere, they have yet to fuel productivity growth.

MGI research has shown that sectors that are highly digitized in terms of assets, usage, and worker enablement – such as the tech sector, media, and financial services – have high productivity. But these sectors are relatively small in terms of share of GDP and employment, whereas large sectors such as health care and retail are much less digitized and also tend to have low productivity.

MGI research also suggests that while digitization promises significant productivity-boosting opportunities, the benefits have not yet materialized at scale. In a recent McKinsey survey, global firms reported that less than a third of their core operations, products, and services were automated or digitized.

This may reflect adoption barriers and lag effects, as well as transition costs. For example, in the same survey, companies with digital transformations under way said that 17% of their market share in core products or services was cannibalized by their own digital products or services. Moreover, less than 10% of the information generated and that flows through corporations is digitized and available for analysis. As these data become more readily available through blockchains, cloud computing, or IoT connections, new models and artificial intelligence will enable corporations to innovate and add value through previously unseen investment opportunities.

The last feature that stands out in this period of historically slow productivity growth is weak demand. We know from corporate decision-makers that demand is crucial for investment. For example, an MGI survey conducted last year found that 47% of companies increasing their investment budgets were doing so because of an increase in demand or demand expectations.

Across industries, the slow recovery in demand following the financial crisis was a key factor holding back investment. The crisis increased uncertainty about the future direction in consumer and investment demand. The decision to invest and boost productivity was correctly deferred. When demand started to recover, many industries had excess capacity and room to expand and hire without needing to invest in new equipment or structures. That led to historically low capital-intensity growth – the single biggest factor behind anemic productivity growth – in the 2010-2014 period.

But, as more companies adopt and learn through digital solutions, and as new forms of employment and investment opportunities strengthen the demand recovery, we expect productivity growth to recover. Myriad factors contribute to productivity gains, but it is the twenty-first century’s steam engine – digitization, data, and its analysis – that will power and transform economic activity, add value, and enable income-boosting and welfare-enhancing productivity gains.

 

 

 

 

Source: Project Syndicate

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Business

WHY AI ISN’T THE DEATH OF JOBS

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Companies using AI to innovate are more likely to increase employment, writes Jacques Bughin in MIT Sloan Management Review.

When pundits talk about the impact that artificial intelligence (AI) will have on the labor market, the outlook is usually bleak, with the loss of many jobs to machines as the dominant theme. But that’s just part of the story — a probable outcome for companies that use AI only to increase efficiency. As it turns out, companies using AI to also drive innovation are more likely to increase head count than reduce it.

That’s what my colleagues and I recently learned through the McKinsey Global Institute’s broad-based research initiative aimed at understanding the spread of AI in economies, sectors, and companies.1 We polled 20,000 AI-aware C-level executives in 10 countries to compile a sample of more than 3,000 companies (mostly large), identified distinct clusters within that pool, and ran a variety of scenarios on those clusters to project the effects of AI on employment, revenue, and profitability.

This research and analysis suggest that although AI will probably lead to less overall full-time-equivalent employment by 2030, it won’t inevitably lead to massive unemployment. One major reason for this prediction is because early, innovation-focused adopters are positioning themselves for growth, which tends to stimulate employment. (See “How AI-Based Innovations Drive Employment.”)

Here’s how we expect things to play out in the five clusters of companies we examined.

Enthusiastic innovators, or pioneering companies that make early investments in AI and embrace the disruption it can create in the quest for advantage, adopt a full range of AI technologies and use them to bolster innovation and efficiency. These companies are analogous to what sociologist and communication theorist Everett Rogers called “early adopters” back when he coined the term — they’re intrinsically motivated to use new technology to shape and open markets.2 While this approach is potentially complex in the short term, our analysis shows that by 2030, the profitability of enthusiastic innovators will grow 8% faster than that of the average company on an annual basis, their revenue will grow 4% faster, and their head count will rise 2.2% faster.

Source: MIT Sloan Management

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