The Human Impact of Rapid Tech Change

Lead Change Blog

These companies find themselves managing complex organizational change, with challenges that will vary depending on the professional levels and geographic diversity of their human resources. The leadership team managing the change should be able to articulate the why, what, and how of the change so that everyone can understand and equally communicate in the same manner. Individuals may fall into three categories: early adopters, late adopters, and resistors.

What Google “Glassholes” Reveal About Managing Innovation

Harvard Business Review

But a larger global innovation insight here demands top management attention. Innovation increasingly blurs technical and marketing distinctions between “ lead users ” and “early adopters.” That challenges how organizations need to manage, learn from and even brand their first-generation customer communities. Your lead users or early adopters may be technically brilliant. Your lead users/early adopters are becoming your most important innovation asset.

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Like It or Not, You Are Always Leading by Example

Harvard Business

How talent management is changing. Here are a few examples from my work with executives: A Silicon Valley start-up CEO attended his company’s diversity/inclusivity training workshop for the entire day. A senior project manager cited the highly public immediate dismissal of a direct report who had fudged a quality control audit and then lied about it. Do employees take enterprise diversity/inclusion initiatives more seriously?

Personal Needs vs. Customer Relationships

Strategy Driven

Some compile complex Customer Relationship Management algorithms to develop and maintain these relationships. People are commonly referred to as ‘buyers,’ ‘shoppers,’ ‘payers,’ ‘non-responders,’ ‘early adopters,’ and ‘eyeballs.’ He has worked with a diverse range of companies across numerous industries, with a special focus on consumer packaged goods, healthcare, and advertising.

Aaker 59

Advanced Analytics Are Crucial to Digital Transformation - SPONSOR CONTENT FROM DXC TECHNOLOGY

Harvard Business

IT has long played a critical role in helping organizations deliver better products and services, improve operations, better manage risks, and develop new business models to stay relevant. For example: As an early adopter of advanced analytics, the securities industry is now defined by automated, algorithm-centric trading and artificial intelligence-based advisors that outperform professional money managers.

A Survey of 3,000 Executives Reveals How Businesses Succeed with AI

Harvard Business

And AI success stories are becoming more numerous and diverse, from Amazon reaping operational efficiencies using its AI-powered Kiva warehouse robots, to GE keeping its industrial equipment running by leveraging AI for predictive maintenance. While investment in AI is heating up, corporate adoption of AI technologies is still lagging. However, we are likely at a key inflection point of AI adoption. Furthermore, early AI adopters are 3.5 Photo by Aaron Burson.

How Netflix Expanded to 190 Countries in 7 Years

Harvard Business

It also must face a diverse set of national regulatory restrictions, such as those that limit what content can be made available in local markets. and Netflix has managed to make inroads into even those markets where Prime arrived first. But from the experience and learning it gained in that process, Netflix developed the capabilities to expand into a diverse set of markets within a few years — the second phase of the process.

How AIG Moved Toward Evidence-Based Decision Making

Harvard Business

Machine learning, pattern recognition, and other predictive analytics tools can constitute a source of competitive advantage for those companies that adopt them early on; but like any new capability, there is an enormous gulf between awareness, intent and early engagement, and achieving significant business impact. How can companies better manage the process of converting the potential of data science to real business outcomes?

How AIG Moved Toward Evidence-Based Decision Making

Harvard Business Review

Machine learning, pattern recognition, and other predictive analytics tools can constitute a source of competitive advantage for those companies that adopt them early on; but like any new capability, there is an enormous gulf between awareness, intent and early engagement, and achieving significant business impact. How can companies better manage the process of converting the potential of data science to real business outcomes?