To Lead Across Cultures, Focus on Hierarchy and Decision Making
Summary. When misunderstandings arise among members of global teams, it’s often because managers conflate attitudes toward authority and attitudes toward decision-making. However, the two are different dimensions of leadership culture, says the author, who has extensive research and consulting experience with global companies. Attitudes toward authority range from strongly hierarchical to strongly
Andrew Ng: How to Choose Your First AI Project
Summary. Tapping the power of AI technologies requires customizing them to your business context. The purpose of your first 1-2 pilot projects is only partly to create value; more importantly, the success of these projects will help convince stakeholders to invest in building up your company’s AI capabilities. When you’re considering a pilot AI project, ask yourself the following questions: Does t
Curiosity-Driven Data Science
Summary. Data science can produce immense value and go well beyond providing merely incremental efficiencies. It can also enable wholly new and innovative capabilities that can completely differentiate a company. But those innovative capabilities aren’t so much designed or envisioned as they are discovered and revealed through curiosity-driven tinkering by the data scientists. So, before you jump
Why Data Science Teams Need Generalists, Not Specialists
Summary. Most businesses organize for efficient productivity. They do this through specialization. Workers that are highly skilled at narrow tasks can perfect their skill and, when put in an assembly line, produce goods with high efficiency. Data science teams have been built this way, too, with highly specialized tasks assigned to individuals that work together to create new business capabilities
The 2 Types of Data Strategies Every Company Needs
Summary. Although the ability to manage torrents of data has become crucial to companies’ success, most organizations remain badly behind the curve. More than 70% of employees have access to data they should not. Data breaches are common, rogue data sets propagate in silos, and companies’ data technology often isn’t up to the demands put on it. In this article, the authors describe a framework for
The Surprising Power of Online Experiments
Getting the most out of A/B and other controlled tests by Ron Kohavi and Stefan Thomke Summary. In the fast-moving digital world, even experts have a hard time assessing new ideas. Case in point: At Bing a small headline change an employee proposed was deemed a low priority and shelved for months until one engineer decided to do a quick online controlled experiment—an A/B test—to try it out. The
The New New Product Development Game
In today’s fast-paced, fiercely competitive world of commercial new product development, speed and flexibility are essential. Companies are increasingly realizing that the old, sequential approach to developing new products simply won’t get the job done. Instead, companies in Japan and the United States are using a holistic method—as in rugby, the ball gets passed within […]
What’s Driving the Machine Learning Explosion?
Machine learning systems have been around since the 1950s, so why are we suddenly seeing breakthroughs in so many diverse areas? Three factors are at play: enormously increased data, significantly improved algorithms, and substantially more-powerful computer hardware. Over the past two decades (depending on the application) data availability has increased as much as 1,000-fold, key algorithms have
The Business of Artificial Intelligence
What does it mean to be human? What do we recognize as artificial? The art for this series was generated from a series of photographs of humans, but because of an application of distortion, you may not recognize the features they portray. Or you may. HBR Design Staff
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What Does “Stakeholder Capitalism” Mean to You?
How to Scale AI in Your Organization
Is Data Scientist Still the Sexiest Job of the 21st Century?
True Leaders Believe Dissent Is an Obligation
An Agile Approach to Budgeting for Uncertain Times
Only 3% of Companies’ Data Meets Basic Quality Standards
Reengineering Work: Don’t Automate, Obliterate
Scaling Your Team’s Data Skills
Building the AI-Powered Organization
Noise: How to Overcome the High, Hidden Cost of Inconsistent Decision Making
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