Analytics & Organizational Culture

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A Noble Purpose Alone Won’t Transform Your Company

A noble purpose isn’t enough to create employee engagement within a company. The primary determinant of engagement is the level and quality of interpersonal collaboration. Leaders play a key role in these interactions. Their behaviors can create an environment of trust, imbue work with purpose, and generate positive energy — three conditions that nurture interpersonal collaboration and, in turn, bolster engagement.

Demystifying the Intelligence of AI

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Three common trouble points impede companies moving toward using AI: Leaders are unclear what it means to adopt AI; systems are drawing from too much junky data; and there isn’t a careful balance between customer loss of privacy and the value returned. These problems can be resolved only when leaders pay close attention to the strategic challenges of bringing AI on and approach AI as an integrated element of their processes.

How Algorithms Can Diversify the Startup Pool

Biases related to gender and other demographic factors creep into decisions about which projects to fund with venture capital. Data-driven approaches can help tease out those biases and limit their impact. Algorithmic methods identify potential instances of discrimination and increase transparency, making it easier to find and fix problems. Aversion to algorithms can be tempered by letting decision makers retain some subjective control over the data-driven process.

The Regulation of AI — Should Organizations Be Worried?

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As companies pour resources into designing the next generation of tools and products powered by AI, many are failing to simultaneously examine the question of who is ethically and legally responsible for the societal backlash if these systems go awry. Over 80% of Americans now believe that robots and/or AI should be carefully managed. Because there are no clear-cut answers or solutions, the talk of regulations — and, more lightly, standards — is getting louder.

Measuring Culture in Leading Companies

To survive and thrive in today’s market, a healthy corporate culture is more important than ever. The MIT SMR/Glassdoor Culture 500 uses machine learning and human expertise to analyze culture using a data set of 1.2 million employee reviews on Glassdoor. This interactive tool offers previously untapped insights about the organizational culture of over 500 of the world’s leading companies and provides leaders with new tools for benchmarking culture in their own organizations.

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What Does an AI Ethicist Do?

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Microsoft has been active in advocating for an ethical perspective on artificial intelligence, and in 2018 it appointed its first general manager for AI policy and ethics. Tim O’Brien, who had been with the company for 15 years, says his activities as “AI ethics advocate” include extending the community of people who are focused on the ethics topic, meeting with Microsoft customers, and leading a research effort to develop a global perspective on tech ethics.

Train Your People to Think in Code

The future of work will entail thinking not just analytically, but also algorithmically — so companies need to retrain workers for writing code, not formulas. Organizations that manage to make code the natural language for diffusing analysis across their organizations can often grow and innovate faster than their peers.

How You Can Have More Impact as a People Analyst

In the messy real world of ambiguous evidence and contentious objectives, organizational decisions — especially those about the people you’re hiring, developing, managing, and trying to retain — usually hinge on relationships and trust. So if you work in people analytics, you must learn to traffic in that currency to make an impact. It’s not enough to be right. You also have to sell your model or idea. These tactics can help.

Getting Your Employees Ready for Work in the Age of AI

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How can companies and employees find common ground when it comes to skill development and investment in AI capabilities? To start, senior executives should seek clarity around capability gaps and determine which skills their people need. From there, leaders should take an approach that advances those skills for human-AI collaboration.

Using Digital Tools to Assess Talent

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The workforce is changing, with more and more skilled workers electing to work for themselves or become entrepreneurs. As the competition for talent heightens, intuition is no longer adequate to identify and attract — not to mention keep — the best potential employees. In this webinar, ManpowerGroup’s chief talent scientist Tomas Chamorro-Premuzic discusses the current workplace dynamic and the innovative methods to solve the talent problem, including digital tools for talent assessment.

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Every Leader’s Guide to the Ethics of AI

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As artificial intelligence-enabled products and services enter our everyday lives, there’s a big gap between how AI can be used and how it should be used. A 2018 Deloitte survey of AI-aware executives found that 32% ranked ethical issues as one of the top three risks of AI, but most companies don’t yet have specific approaches to grapple with the challenges. Here, we list the seven actions that leaders of AI-oriented companies — regardless of their industry — should consider taking.

AI-Driven Leadership

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Not many companies are there yet, but there’s a developing framework for what it takes to lead an AI-driven company. Leaders at the forefront of AI have seven key attributes: They learn the technologies; establish clear business objectives; set an appropriate level of ambition; look beyond pilots and proofs of concept; prepare people for the journey; get the necessary data; and orchestrate collaborative organizations.

From Winning Games to Winning Customers: How Data Is Changing the Business Side of Sports

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Sports analytics first proved its case on the field and in the front office, but as the practice spreads into business operations, the industry is addressing adoption challenges found in many sectors. At the MIT Sloan Sports Analytics Conference, speakers from teams and leagues discussed how they are using analytics to boost revenue, and how they’re managing transitions in culture and strategy.

Why APIs Should Be Regulated

Digital titans with access to large quantities of data are a challenge to competition. To maintain a competitive business environment, regulation focusing on both market and data dominance needs to be developed. Among the best tools for limiting companies’ influence: data audits.

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AI in the Boardroom: The Next Realm of Corporate Governance

Business has become too complex for boards and CEOs to make good decisions without intelligent systems. Just as artificial intelligence helps doctors use patient data to make better diagnoses and create individualized medical solutions, AI can help business leaders know more precisely which strategy and investments will provide exponential growth and value in an increasingly competitive marketplace.

Leading Analytics Teams in Changing Times

Analytics teams are often underfunded, misunderstood, and starved for talent. Extracting business value from data depends on nurturing the development and effectiveness of these teams — not just in terms of finding talent, but also in terms of getting leaders up to speed on how to use the insights analytics teams produce.

Five Management Strategies for Getting the Most From AI

A global survey by the McKinsey Global Institute finds that AI is delivering real value to companies that use it across operations. C-level executives report that when they adopt AI at scale — meaning they deploy AI across technology groups, use AI in the most core parts of their value chains, and have the full support of their executive leadership — they are finding not just cost-cutting opportunities, but new potential for business growth, too.

Accelerate Access to Data and Analytics With AI

Detailed and data-rich insights won’t help your company if your employees don’t know where to find them — but that’s a problem AI can solve. Machine learning can enable faster organizational learning by helping each employee quickly understand what others in the organization understand — forming a knowledge distribution network.

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