Barriers: Overcoming Hurdles and Reaching a New Performance Trajectory in Visual Studio .NET

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Barriers: Overcoming Hurdles and Reaching a New Performance Trajectory
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31 BARRIERS Identifying hurdles toward reaching a new performance trajectory is most direct To defeat inhibiting behavior, we must make clear what is getting in the way A characteristic of smart data strategy is to leap beyond legacy problems to achieve a new performance trajectory We don t want to level off at a new plane; instead, we want to push the performance trend upward with momentum To accomplish this, consider two elements: (1) executive and organizational inhibitors and (2) technical inhibitors The following list contains the principal executive and organizational inhibitors that we encounter as barriers to implementing effective smart data strategy:
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Don t understand it Executives aren t on board Reluctance to change Limited discretion and bandwidth to change Threat from and to stovepipe behavior Lack of awareness of ability to improve anticipation and prediction
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Smart Data: Enterprise Performance Optimization Strategy, by James A George and James A Rodger Copyright 2010 John Wiley & Sons, Inc
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BARRIERS: OVERCOMING HURDLES AND REACHING A NEW PERFORMANCE TRAJECTORY
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Second, there are technical inhibitors:
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Legacy infrastructure based on outmoded ideas De cient skill, knowledge, and experience needed to leap beyond the legacy Lacking a strategy such as smart data to escape from legacy performance
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32 OVERCOMING BARRIERS Understand the Strategy Smart data strategy begins when executives declare that they need and want total enterprise performance represented as fully attributed process models featuring data inputs and outputs, controls, and mechanisms They must want the models activated in a real-time executive support system Knowledgeable executives need, want, and expect their enterprise data to be presented as an operational model that aggregates to a top line view and decomposes into details that explain every enterprise function within the domain of responsibility, and extending to supply chain and community of participant dependencies, including customers and sources of capital Knowledgeable executives will articulate and share an inventory of routine questions for which actionable data must be available at all times; and executives will share dynamic scenarios enabling what-if calculations and measurable effect of alternative decisions and choices Smart data strategy requires data engineering such that data is open and interoperable Smart data strategy is dependent on state-of-the-art smart grid and smart services as depicted in the service-oriented enterprise (SOE) paradigm and as part of cloud computing services and World Wide Web progression Smart data is a product of current technologies, and superiority is gained from progress in applying emerging technologies as suggested in the draft concept of operations and operational architecture described herein Smart data strategy is implemented with the introduction of the executive enterprise performance optimization system (EPOS) and associated management interface Become Aware of the Possibilities and Get on Board To remove or mitigate these barriers, the executive needs convincing Our approach is to demonstrate that data is on the critical path to enterprise performance optimization, and the CEO can achieve this best with a smart data strategy The principal idea is to focus executives attention on data that is essential to enterprise performance and executives ability to execute their primary responsibilities
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Executives should expect more from IT services than infrastructure alone They need analytical capability to model and simulate conditions in response to a dynamic environment They need the ability to anticipate and predict performance with high certainty in the near term and with increased visibility over the longer term Executives taking ownership for data that is needed to optimize enterprise performance may be considered invasive because it disturbs the status quo in information technology management where the data is buried Ask for answers to such requests as:
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Let s see the enterprise process model Let s see the data inputs Let s see how processes transform data inputs into higher yield outputs Let s see the system in real-time performance reporting mode Show the value of data outputs compared with associated costs Show how much is spent on enterprise application interface maintenance Show how much is spent on data exchange and business transactions Show what will happen when certain variables are changed such as changing the employment mix, adding or changing equipment, tools, or systems Show the material effect of changes in business rules, policies, laws, and regulations Show the enterprise data model
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Smart data is intended to make enterprise performance visible and observable, and to enable executives to try what-if scenarios and conditions to evaluate possible decisions and alternatives
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Reluctance to Change Technically, risk to change is minimal because smart data implementation is intended to leap beyond the IT legacy into a new world of open data exchange and transactions Changing IT from old culture to smart data culture requires managing, executive leadership, and collaboration with enabling technologists who possess contemporary knowledge, skill, and pro ciency The data engineering discipline has progressed in that regard, and only those with current credentials are quali ed to advance the idea Therefore current staff must advance in professional development and may require augmentation to stimulate fresh thinking The cost to change expressed as capital and executive and organizational mindshare must be estimated based on having a clear picture of what it will take to move from the present situation to an improved state In addition, the enterprise must estimate its own bandwidth given all of the priorities and activities demanding attention However, if data is not made a top priority, there can be no meaningful change
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