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Enterprise transformation: An analytics-based approach to strategic planning

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9 Author(s)
Kapoor, S. ; IBM Research Division, Thomas J. Watson Research Center, Yorktown Heights, NY, USA ; Ray, B. K. ; Toft-Nielsen, C. ; Dobrindt, K.
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The importance of strategic planning is universally recognized in the business world as an effective approach to enable achievement of enterprise business objectives over long time periods. However, despite the criticality of the task, the strategic planning process often does not take advantage of analytics to support the process in a consistent way. This paper describes a transformation of the strategic planning process for a globally integrated enterprise through development of a planning system that provides a planning framework as well as a set of analytic capabilities to improve both efficiency and effectiveness. The system consists of a hierarchically structured data store, rules that govern relationships among data elements, and an enterprise dashboard with reports and insights supported by analytic capabilities. The hierarchical nature of the planning model can account for the needs and opportunities of individual lines of business while yielding a coherent, executable strategy at the enterprise level. Integrated scenario and sensitivity analysis, enterprise simulation, and other analytic capabilities enable optimal planning in the face of volatile and uncertain market conditions characteristic of a long planning horizon. In addition, the system fosters collaboration among planners and exemplifies the key attributes of a Smarter Planet™: instrumentation, interconnectedness, and intelligence.

Note: The Institute of Electrical and Electronics Engineers, Incorporated is distributing this Article with permission of the International Business Machines Corporation (IBM) who is the exclusive owner. The recipient of this Article may not assign, sublicense, lease, rent or otherwise transfer, reproduce, prepare derivative works, publicly display or perform, or distribute the Article.  

Published in:

IBM Journal of Research and Development  (Volume:56 ,  Issue: 6 )