Rough order of magnitude

Rough order of magnitude
See also

Rough order of magnitude (also called ROM) is top-down estimation of costs used at the beginning of projects, often to estimate first rough budget for the project . It is said if should be accurate within 35 percent (plus or minus)[1]. Is used in risk cost evaluation and conceptual cost evaluation[2]. This method is especially advised when there is[3]:

  • limited data so only a few details are available,
  • short time but there is need to estimate costs quickly,
  • there is no possibility of detailed analysis,
  • possibility to use similar models, systems, expertises are subjects,
  • historical data and ratios that could be used,
  • analysis answering question what if,
  • need to estimate some specific part of the project,
  • need to make decision out of many high-level alternatives to assess which one is the most feasible,
  • there is no need to develop budget-quality cost estimate yet.

Benefits of rough order of magnitude for cost evaluation[edit]

There are several reasons why using rough order of magnitude is beneficial[4]:

  • uses fundamental assumptions,
  • meets basic requirements,
  • users may build knowledge of type of (future) costs,
  • users have better awareness of costs in the project,
  • cover costs in total life cycle,
  • enables visibility on suitable material solutions,
  • reduces costs, efforts and time on alternatives that were nonviable from the beginning.

Process of rough order of magnitude for cost evaluation[edit]

When company or project manager decides to evaluate costs with use of rough order of magnitude, below five steps should be taken [5]:

  1. Definition of goal and requirements: statutory mission requirements, gap analysis, combining requirements, developing capabilities,
  2. Collection of data and analytical review: researching government and industry standards, data from stakeholders, reviewing Life Cycle Cost Estimates (LCCE), evaluation of techniques and methodologies,
  3. Transferring requirements to capabilities: connecting requirements and costs, define the best cost dimensions, developing rules,
  4. Analyzing and developments of model: deeper cost estimation, identification of cost drivers,
  5. Delivering results and documentation: delivering final cost evaluation, documentation, informing board about results to enable making of decision and gaining feedback

Additionally, to be estimate if there is possibility of improvements, so that at little cost or effort, analysis could be at better quality, below questions might be answered[6]:

  • How quality of rough order of magnitude can be improved?
  • Were any complex assumptions avoided due to capacities?

Footnotes[edit]

  1. Rowe S. R., (2015)
  2. Black J., Lane J., Lane R., (2017)
  3. PWC, (2015)
  4. PWC, (2015)
  5. PWC, (2015)
  6. PWC, (2015)

References[edit]

Author: Weronika Burzawa