Analytics & Organizational Culture

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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

  • Frontiers

  • Research Highlight
  • Read Time: 7 min 

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

  • Video | Runtime: 0:59:36

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.

Every Leader’s Guide to the Ethics of AI

  • Blog
  • Read Time: 9 min 

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.

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AI-Driven Leadership

  • Column

  • Column
  • Read Time: 7 min 

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

  • Blog
  • Read Time: 5 min 

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.

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.

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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.

When Jobs Become Commodities

Most of us view our jobs as specialized or somehow differentiated, but the world of business and management increasingly feels otherwise. For many organizations today, the next big driver of job commoditization is automation driven by smart machines. Simply put, if a job is viewed as a commodity, it won’t be long before it’s automated. The key for workers whose jobs have traditionally seemed safe: Highlight the tasks that require a human touch.

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Ethics Should Precede Action in Machine Intelligence

As analytics and big data continue to be integrated into organizational ways and means from the C-suite to the front lines, authors Josh Sullivan and Angela Zutavern believe that a new kind of company will emerge. They call it the “mathematical corporation” — a mashup of technology and human ingenuity in which machines delve into every aspect of a business in previously impossible ways.

A Data-Driven Approach to Identifying Future Leaders

Many executives believe they are good at identifying leadership talent. However, when asked how they make their decisions, they often cite intuition or “gut” instincts. Social science research, on the other hand, suggests that individuals are often prone to cognitive biases in such decisions. Rather than just relying on the subjective opinions of executives, some companies are using assessment tools to identify high-potential talent.

Participant Questions From the Recent Data and Analytics Webinar: Round 2

On March 15, 2017, MIT SMR held a webinar to share insights from our report, “Analytics as a Source of Business Innovation.” Many participants asked questions during the webinar that we didn’t have time for, so we decided to answer them in blog format instead. This post is the second set of responses.

Questions and Answers About Analytics as a Source of Business Innovation

On March 15, 2017, MIT SMR held a webinar to share insights from our report, “Analytics as a Source of Business Innovation,” which summarizes our findings about the increased ability to innovate with analytics and its benefits across industries. Many participants asked questions during the webinar that we didn’t have time for, so we’ll answer some of them in blog format instead.

Why Your Company Needs Data Translators

When it comes to putting data to use, communication — or rather, lack of it — between the data scientists and the executive decision makers can cause problems. The two sides often don’t speak the same language and may differ in their approach to and respect for data-based decisions. Given these challenges, organizations may need to call upon a “data translator” to improve how data is incorporated into decision making processes.

Showing 1-20 of 79