Jorn Bettin

Jorn Bettin

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Conclusion: Risk management and quality are two sides of the same coin. Building quality into organisational decision-making processes and systems is only possible if operational risks are well understood. The results of risk analysis should be a key input for the design of enterprise architectures and systems. It all sounds obvious, but risks associated with the decision-making processes in an organisation are only rarely quantified in terms of likelihood, impact on external parties, and potential costs.


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Conclusion: Software products are marketed with long feature lists, and data export/import features in industry standard formats are commonly advertised – and perceived as the pinnacle of product maturity. Similarly application integration is often equated with the need for data exchange mechanisms between systems. Yet interoperability is a much wider topic, and data exchange only represents the most rudimentary form of interoperability. Failing to understand more advanced forms of interoperability leads to overly complex and brittle systems that are extremely costly to maintain and operate.


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Conclusion: Operational data is the heart of a business in the information age. Without operational data the organisation would cease to function, irrespective of the software and hardware infrastructure that is in place. Hence the quality of data is a logical starting point for identifying opportunities to improve business operations. When used in combination with top-down value chain analysis, a quality assessment and categorisation of data can be used to identify essential system functionality, to identify pockets of obsolete functionality, and to discover sets of unreliable or redundant data.


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Conclusion: Neither written languages nor formal programming languages are capable of representing organisational knowledge in a human-friendly format. Even though Semantic Web technologies attempt to offer assistance in this area, their scope of applicability is limited to the role of establishing crude links between elements of knowledge in the public domain. Making organisational knowledge tangible and easily accessible requires new techniques, and dedicated technologies.


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It all really started with the hype and the launch around Apple’s iPad earlier this year. Until then, tablet devices were perceived as a fringe phenomenon, of little interest to the mainstream consumer or business user. I have had an eye on the tablet space since the first release of the Amazon Kindle in 2007, and always wondered when devices with a tablet form factor would finally take off. To some degree the introduction and promotion of netbooks in the last two years had confused the market, but the range of tablet devices that are now available is reassuring. Still, the dust is far from settled, and there is a whole pipeline of tablet devices that have yet to hit the shelves. So, apart from the geek-factor, what value can a business user get out of a tablet?


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Conclusion: The perceived relevance of information technology varies greatly, depending on who is being asked. In software intensive industries, the overall IT budget consumes between 10–20% of the overall operating expenses. In software product development organisations the number is close to 100%. When defining the business strategy, it is easy to focus on costs and to underestimate lost opportunity costs and business risks. The biggest impact of IT budget cuts is on the resulting increase in operational risks, and conversely, the biggest potential for gaining value out of IT investments lies in the area of operational risk reduction.


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Conclusion: Large-scale Enterprise Data Warehouse implementations and operations often lead to multi-million dollar items in annual IT budgets. It is paramount that investments of this magnitude are put to good use, and are translated into tangible value for the organisation. Complexity of the underlying information structures can become a major issue, especially once complexity impacts the ability to formulate data warehouse queries in a timely manner. With a bit of foresight, or even retrospectively, it is possible to equip data warehouse designs with simple orientation and navigation aids that significantly reduce the time that users need to locate relevant information.


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Conclusion:Value chain analysis is one of the fastest ways to understand the essence of a business or an organisation, provided appropriate techniques are used in the analysis. The only concepts needed for recording value chains are roles, systems, artefacts, the links between these concepts, and a distinction between artefacts that are exchanged with other organisations and artefacts that are only relevant within the organisation. One of the biggest pitfalls in value chain analysis is to lose track of the big picture, and to get lost in the details - which can easily be avoided by following a small set of best practices to avoid work that does not add value.


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Conclusion:Last year Richard Soley, Ivar Jacobson, and Bertrand Meyer called for action to re-found software engineering on principles and practices that are backed by robust scientific theories. Achieving big gains in software quality and productivity by introducing off-the-shelf methodologies has proved to be elusive. The evidence suggests that looking for much smaller (and scientifically validated) building blocks that can be composed into an organisation-specific methodology is much more likely to deliver results than the quest for the ultimate methodology. Alignment between business and IT requires constant vigilance of staying on the narrow ridge that separates over-simplification of an organisation’s activities from spurious complexity in software implementations.


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Conclusion:Knowledge workers – and people in general – commonly overestimate their ability to convey information in documents, diagrams, and in discussions. To make matters worse, they typically have too much faith in the validity of their personal mental models to frame the problems that need to be solved. As a result, misinterpretations often remain undetected for months, milestones are missed, and deliverables don’t meet expectations. There is no antidote against project failure in terms of a universally applicable methodology, but many failures are avoidable by recognising that communication and collaboration is fraught with difficulties.


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Conclusion:When it comes to evaluating software products to address a particular business need, the first activity after determining a list of candidate products often consists of sourcing product selection criteria from independent subject matter experts. But qualified product selection is only possible if extensive information about the specific organisational context is taken into consideration, otherwise boilerplate product selection criteria only have the effect of a security blanket.


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Conclusion:It is tempting to seek out easy solutions for hard problems. Many others must have had similar problems, and a large part of the solution development effort can be short-circuited by selecting an appropriate productised solution – that’s hope. But similarities between problems in different organisations are easily over-estimated – that’s uncertainty. Business cases are strengthened by highlighting key differences to other organisations, and by proposing a path that incrementally removes uncertainty.


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Software development was still a very esoteric discipline in the days when Lisp was born. In the meantime the software industry went through a whole series of major paradigm shifts:

  • From structured programming (Pascal and related languages)

  • To relational databases (the SQL standard and implementations from IBM, Oracle and others)

  • To Computer Aided Software Engineering (a very large range of competing tools)

  • To object-oriented languages (such as Smalltalk, C++ and Java)

  • To components (such as the CORBA standard and Java Enterprise Edition)

  • To web based applications (HTML, XML, JavaScript, and other scripting languages)


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Conclusion: A decade ago Knowledge Management was the next big thing, and according to the analysts responsible for the Knowledge Management hype, it has evolved into a well-understood concept that is firmly established in the majority of organisations. Nothing could be further from the truth. Only very few organisations have a practically useful definition of knowledge, and even fewer realise that knowledge is not something that needs to managed, but something that needs to be nurtured - by committing to capture knowledge in its purest form, neither diluted by implementation technologies, nor distorted by organisational politics.


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