Benefit dependency network explained

A benefit dependency network (BDN) is a diagram of cause and effect relationships. It is drawn according to a specific structure that visualizes multiple cause-effect relationships organized into capabilities, changes and benefits. It can be considered a business-oriented method of what engineers would call goal modeling and is usually read from right to left to provide a one-page overview of how a business generates value, starting with the high level drivers for change, such as found with Digital Initiatives[1] or cross-organizational ERP management.[2] First proposed by Cranfield School of Management as part of a Benefits Management approach [3] the original model has developed to encompass all the domains required for Benefits Management [4] namely Why, What, Who and How. Recent development has added weights to the connections to create a weighted graph so that causal analysis, sometimes referred to as causality, is possible on the represented value chains so different strategies can be compared according to value and outcome. These chains provide a way to construct a compelling story or message that shows how the benefits proposed can be realized from the changes being considered. In software engineering, Jabbari et al.[5] report the use of BDN for the purpose of software process improvement. They use BDN to structure the results of a systematic review on DevOps.

Notes and References

  1. Joe Peppard Harvard Business Review https://hbr.org/2016/06/a-tool-to-map-your-next-digital-initiative
  2. Eckartz Daneva Wieringa van Hillegersberg SAC 09 http://dl.acm.org/citation.cfm?id=1529641
  3. Benefits Management Best Practice Guidelines by John Ward, Peter Murray and Elizabeth Daniel, Cranfield School of Management, 2004
  4. A look at existing methods by Torsten Langner, LinkedIn https://www.linkedin.com/pulse/look-existing-methods-torsten-langner
  5. Jabbari . Ramtin . bin Ali . Nauman . Petersen . Kai . Tanveer . Binish . Towards a benefits dependency network for DevOps based on a systematic literature review . Journal of Software: Evolution and Process . November 2018 . 30 . 11 . e1957 . 10.1002/smr.1957. 53951886 .