An investment in this book will have immediate payoff for those that believe that knowledge and intelligence are power.
This is an indispensable guide to better managing your knowledge assets. The executive moments throughout the book provide an excellent and concise guide for the issues addressed in each chapter. A must read for any executive who works for an organization that has to compete! Rothberg and Erickson have done an outstanding job in providing a clear pathway to understanding and developing an organisation's knowledge assets within a competitive. Change challenges competitiveness - and Rothberg and Erickson provide a unique and innovative approach to understanding today's sustainable competitive advantage and to strategically managing change.
A must read.
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So what is your company's SPF? They impress upon us the reality that in today's business world with increasing pressure to find and hold a real positioning advantage, Knowledge Management is as important an asset for success as your company's brand name. And maybe moreso! Peigh, Senior Vice President, Interpublic Group of Companies "This book will reduce ignorance and add insights onto the evolution of knowledge leadership, especially on how to develop capacity for intelligence.cumredelbestgym.ga/giz-le-jour-ou.php
Reshaping Business With Artificial Intelligence
By comb She is also a full-spectrum business consultant with expertise in both micro and macro managerial and organizational functions. She does business consultation and seminar development in the areas of competitive intelligence, competitive analysis, strategic planning, shadow and cross-functional teams, and organization development and design.
He has written over 50 scholarly papers and over 80 presentations and has received the Outstanding Reviewer Award from the American Society for Competitiveness Conference. Du kanske gillar. AI is swiftly becoming the foundational technology in areas as diverse as self-driving cars and financial trading.
Self- learning algorithms are now routinely embedded in mobile and online services. Researchers have leveraged massive gains in processing power and the data streaming from digital devices and connected sensors to improve AI performance. And machines have essentially cracked speech and vision specifically and human communication generally. The implications are profound:.
A field that once disappointed its proponents is now striking remarkably close to home as it expands into activities commonly performed by humans. See Exhibit 1 and the sidebar. AI programs, for example, have diagnosed specific cancers more accurately than radiologists. No wonder that traditional companies in finance, retail, health care, and other industries have started to pour billions of dollars into the field.
Because AI systems think and interact, they are invariably compared to people. But while humans are fast at parallel processing pattern recognition and slow at sequential processing logical reasoning , computers have mastered the former in narrow fields and are superfast in the latter. Without further quantum leaps in processing power, machines will not reach artificial general intelligence AGI : the combination of vastly different types of problem-solving capabilities—the hallmark of human intelligence.
But when properly applied, AI excels at performing many business tasks quickly, intelligently, and thoroughly. Artificial intelligence is no longer an elective. AI is different. The naked algorithms themselves are unlikely to provide an edge. And many prominent AI researchers have insisted on retaining the right to publish their results when joining companies such as Baidu, Facebook, and Google.
- Knowledge management as a competitive asset: a review | Emerald Insight.
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Rather than scrap traditional sources of competitive advantage, such as position and capability, AI reframes them. See Exhibit 2. Companies, then, need a fluid and dynamic view of their strengths. Positional advantage, for example, generally focuses on relatively static aspects that allow a company to win market share: proprietary assets, distribution networks, access to customers, and scale. These articles of faith have to be reimagined in the AI world. AI and agile are inherently iterative.
In both, offerings and processes become continuous cycles.
Competitive intelligence overview
Algorithms learn from experience, allowing companies to merge the broad and fast exploration of new opportunities with the exploitation of known ones. This helps companies thrive under conditions of high uncertainty and rapid change. In addition to reframing specific sources of competitive advantage, AI helps increase the rate and quality of decision making. For specific tasks, the number of inputs and the speed of processing for machines can be millions of times higher than they are for humans. Predictive analytics and objective data replace gut feel and experience as a central driver of many decisions.
Stock trading, online advertising, and supply chain management and pricing in retail have all moved sharply in this direction. To be clear, humans will not become obsolete, even if there will be dislocations similar to but arguably more rapid than those during the Industrial Revolution.
Development and evaluation of a framework to explain causes of competitive intelligence failures
First, you need people to build the systems. And AI experts are the most in-demand hires on Wall Street. Second, humans can provide the common sense, social skills, and intuition that machines currently lack. Even if routine tasks are delegated to computers, people will stay in the loop for a long time to ensure quality. In this new AI-inspired world, where the sources of advantage have been transformed, strategic issues morph into organizational, technological, and knowledge issues, and vice versa.
Structural flexibility and agility—for both man and machine—become imperative to address the rate and degree of change. Scalable hardware and adaptive software provide the foundation for AI systems to take advantage of scale and flexibility. One common approach is to build a central intelligence engine and decentralized semiautonomous agents. Winning strategies put a premium on agility, flexible employment, and continual training and education.
AI-focused companies rarely have an army of traditional employees on their payroll. Open innovation and contracting agreements proliferate. As the chief operating officer of an innovative mobile bank admitted, his biggest struggle was to transform members of his leadership team into skilled managers of both people and robots. Companies looking to achieve a competitive edge through AI need to work through the implications of machines that can learn, conduct human interactions, and engage in other high-level functions—at unmatched scale and speed.
They need to identify what machines do better than humans and vice versa, develop complementary roles and responsibilities for each, and redesign processes accordingly.
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AI often requires, for example, a new structure, of both centralized and decentralized activities, that can be challenging to implement. Finally, companies need to embrace the adaptive and agile ways of working and setting strategy that are common at startups and AI pioneers. All companies might benefit from this approach, but it is mandatory for AI-enabled processes, which undergo constant learning and adaptation for both man and machine.
Executives need to identify where AI can create the most significant and durable advantage. At the highest level, AI is well suited to areas with huge amounts of data, such as retail, and to routine tasks, such as pricing. But that heuristic oversimplifies the playing field. Increasingly, all corporate activities are awash in data and capable of being broken down into simple tasks.
See Exhibit 3. We advocate looking at AI through four lenses:. First, define the needs of your customers. AI may be a sexy field, but it always makes sense to return to the basics in building a business.
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Where do your current or potential customers have explicit or implicit unmet needs?
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