W3_HYCIENTH_AFE values vs. As-built values Cause & Effect Analysis

1.  Problem Recognition, Definition and Evaluation

What Cause and Effect analysis type would be best suited to capture AFE value variance from As-built values for O&G projects executed in the past 10 years in the Niger Delta region of Nigeria

2.  Development of Feasible Alternatives

Cause and Effect/Fishbone Diagram is a tool that allows graphical display of all possible causes related to a problem or condition to discover its root causes (s). There are three (3) major cause and effect formats:

1. The Dispersion Analysis Type – constructed by placing individual causes within each “major” cause, category.

2. The Process Classification Type – uses the major steps of the process in place of the major cause categories.

3. Cause Enumeration Type - Instead of building up a chart gradually (starting with the 'backbone', deciding broad areas, then adding more and more branches), you postpone drawing the chart and simply list all the possible causes first. Then draw the chart in order to relate the causes to each other. The disadvantage is that it is more difficult to draw the diagram from this list rather than from scratch.

Two methods are used to generate the causes needed to build a Cause & Effect Diagram:

1. Brainstorming – requires no prior preparation

2. Check Sheets – based on data collected by team members.

3.  Develop the outcomes for each Cause & Effect Type

Three important factors or attributes that will best determine the Cause and Effect type to analyse AFE value variance against As-built value over a 10 year period are:

 (1) Reduce multiple categorizations of causes

 (2) Flexibility in categorisation

(3) Easy to use with a list of historic data.

 4.  Selection of a criteria

A good CE diagram is one which explores all possibilities so it is likely to be large and complex-looking as twig after twig sprouts for each new related idea noted down. CE Diagrams with few factors are suspect and may reflect a lack of knowledge of the situation, or show that the effort to draw the diagram was not creative and exhaustive enough.

5.  Analysis and Comparison

Attributes	Cause & Effect Formats
	Dispersion Analysis Type	Process Classification Type	Cause Enumeration Type
Avoid multiple cause categorization	Good	Poor	Good
Categorisation Flexibility	Good	Good	Good
Work from listed/ historical  causes	Poor	Poor	Good

6.  Selection of the preferred alternative

From the Table above, Cause Enumeration Type would be best to categorise AFE value variance against As-built values as it will reduce, if not completely eliminate, duplication of causes under various category. It will allow use if unstructured historical data gathered over time from teams.

7.  Performance Monitoring & Post Evaluation of Results

The CE below shows the various causes of AFE value variance from As-built values for O&G projects executed in the Niger Delta Region of Nigeria within the last 10 years.

8.  Reference:

1.     HCi Services, Cause & Effect Diagram. Retrieved from: http://www.hci.com.au/hcisite3/toolkit/causeand.htm#Cause enumeration

2.     Brassard, M., & Ritter, D. (2010).The Memory Jogger 2: Tools for Continuous Improvement and Effective Planning.

3.     Sullivan, W. G., Wicks, E.M., & Koelling, C.P. (2012). Engineering Economy (15th ed.), Chapter 14, New Jersey, NJ. Pearson Higher Education, Inc.