All entries for Monday 11 March 2013

March 11, 2013

Measuring decision quality

Measuring the decision quality is an important part of decision knowledge. The quality is not always measured by the decision outcomes as the amount of factors are way complicated in real life business to be considered totally. Measurement cannot depend on qualitative data as interpretation can vary significantly.

The measurement of decision quality allows tthe decision makers to lean assesing decision for more robust decisions. It is also a learning curve which allows the decision maker to improve with experience when usin the appropriate theory and tools.

I can assess the quality of decisions i have to make by examining wide range of alternatives, understand all the objectives and decision requirements, understand associated positives and negatives and assess the possibility of decision implementation. This will allow me to to make an informed decision by measuring its quality before agreeing to it as the most robust decision can be out of the decision list.

RDM presentation

In our presentation we considered production location using 2 analysis tools; decision tree and AHP. We also made the most effective media channels for advertisements. In location selection my judgement urged me to select Exmouth due to higher production rate. However, The decision tree demonstrated that in year 1 Exmouth is probably more profitable and in year 2 Lymington is more profitable and has no risk associated. This taught me that judgement is poor without support. Moreover, choosing a robust decision is more effective as plans can go forward without worrying about success rate and fluctuation.

In my career, when trying to think of a solution as an engineer cutting edge solutions can be rewarding but decision analysis might differ the opinion which can allow me to make a more robust and stable decision.

Decision Verification

Robust decision making is not is not dependent on intuition or judgement. However, it is dependent on decision analysis tool. I learned that decision making either should be validated using organisation data and performance on a certain aspect or using another analysis tool for verification if both outcomes are in agreement. If not it would be useful to use the support of a third tool for determination. Nevertheless, chosen tools should be sufficient to cover most of decision aspects to avoid choosing a tool to confirm previous outcomes.

This is important to allow decision maker to assess the robustness and validity of a decision. such an action can lead to reducing decision errors and increasing the decision maker confidence.

In my future career i have to ensure that consulting more than a single analysis tool is useful. This will allow me to avoid falling in the trap of my bias by the first tool and pay my attention to further complexity of decision dimensions. I believe that it is also a useful tool to determine a career line for a change after completing my course.

March 2013

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Most recent comments

  • Good point, you dont have to consider it while using the decision tree as the available data is limi… by Ahmed Alali on this entry
  • Good point Bu Salim. However, i failed to mention that a decision objective is linked to the busines… by Ahmed Alali on this entry
  • I do agree with you Ahmed that certain modification enhance GA performance, however, even if someone… by Waddah Alharthi on this entry
  • as u said, the time scaling and sentivity need to be taken into account… i agree but do u think in… by Tzu-i Yang on this entry
  • i agree with u … choosing tools is not easy… we might fall into trap info….it was whyi decisio… by Tzu-i Yang on this entry

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