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Being an Agile software development team isn t about speci c practices such as pair programming, or employing a certi ed Scrum master It means being a learning organization The true hallmark of an Agile team is that it learns and it changes You can t achieve true Agility without learning You might be able to jump-start a team by adopting speci c practices, but if you don t build in learning your agility will be fragile; most likely, it will depend on one or two individuals The team may go through the motions of Agile development without understanding why, and will never develop its own Agile method to match your business needs True Agile software development is Lean development done by learning teams It is unimportant whether it is done under the name of Crystal, XP, Feature-driven Development (FDD) or any other methodology The rest of this book is aimed at helping make teams Agile through learning, and through sustaining that learning so that teams can continue to improve
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Knowledge
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Error 1: Not Developing a Working De nition of Knowledge If knowledge is not something that is different from data or information, then there is nothing new or interesting in knowledge management Liam Fahey and Larry Prusak (1998)
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We don t know how many knowledge workers there are in the world today, but in 2003 Bill Gates claimed there were over 95 million such workers in America alone So we know that there are a lot of knowledge workers However, while we talk about knowledge a lot, it isn t always clear just what we re talking about Software engineers are accustomed to shunting bits and bytes about We call this data, and we may even accept that this represents information, but is it knowledge In fact, are there any real and important differences between data, information and knowledge And are these differences of any importance to us when we develop software Unless we develop an understanding of what knowledge is, how can we even attempt to understand software development as a knowledge industry
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31 The Difference between Knowledge and Information
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In everyday language data, information and knowledge tend to be interchangeable terms Many dictionaries de ne each one in terms of the others However,
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Changing Software Development: Learning to Become Agile 2008 John Wiley & Sons, Ltd Allan Kelly 35
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if there s no difference between these terms, what s the point of having three different words In fact, there are many more words that we could consider: wisdom, skills, intelligence, pro ciency and facts, just to name a few We could subdivide the whole concept of knowledge and information into even smaller chunks and ever increasing subtlety It is possible to de ne a three-way division data, information and knowledge that s both useful and succinct, but we still need to distinguish between these three terms We start with the working de nitions provided by two of the leading writers on the subject of knowledge, Davenport and Prusak:1
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Data claims to be some objective facts about events Information is a message intended to change the receiver s perception of something: it is the receiver rather than the sender who decides what the message means Knowledge is a uid concept, incorporating experience, values and the context that exists inside an individual s mind or in the processes and norms of an organization
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Another leading writer on the subject of knowledge is Ikujiro Nonaka; he assigns three attributes to knowledge:2
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Knowledge is about beliefs and commitment: it is a function of perspective and intention Knowledge is about action: creating knowledge requires action and knowledge is embedded in our actions Knowledge and information are about meaning and are context speci c
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Later, Nonaka3 extended these ideas to place knowledge within a concept called ba Ba is a Japanese term used to describe the space in which knowledge exists A single piece of information doesn t exist in isolation but, instead, within a space that contains experience, re ections and ideas, about events and people While you can write down a simple fact, it is harder to capture the space it resides in, which is intangible If you separate the fact from the ba, what you re left with is mere information For example, computer languages have their own ba There s more to knowing a computer language than simply knowing the keywords and syntax Each language has its own idioms and norms, which are more dif cult to articulate than the keywords and syntax Communities of people form around languages to share experience, practice and advance the understanding of the language These communities have values, ethics and beliefs that in uence the way in which the language is used Knowledge can be a delicate thing: if we don t use it, we forget it So, we need to consider the environment in which we keep and grow our knowledge some
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See Davenport and Prusak (2000) See Nonaka and Takeuchi (1995) See Nonaka (1998)
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