W4_Doyin_Contracting Incentives

1.       Problem Recognition, Definition and Evaluation:

Incentive contracts are designed to achieve specific acquisition objectives such as:

Establishing reasonable and attainable targets that are clearly communicated to the contractor

      Discourage contractor inefficiency and waste.

In view of the various types of incentive contracts available,  Multi-attribute decision making process is employed to make decision .

2.       Development of Feasible Alternatives.

In Project Management, Incentive Contracting methods include:

·         Cost-plus-incentive-fee contracts (C+I)

·         Cost-plus-award-fee contracts (C+A)

·         Cost/Time plus Incentive/Disincentive(A+B)

·         Fixed-price incentive (firm target) contracts (FPI)

·         Fixed-price incentive (successive targets) contracts.( FPI(ST))

·         Fixed-price contracts with award fee(FPI(AF)

3.       Development of the outcomes and cash flows for each alternative

These alternatives will be considered based on the following attributes

·         Scope Definition:  

·         Risk

·         Cost

·         Time

·         Technical Performance

·         Contract Improvement

·         Gains

·         Loss

4.       Selection of Criteria

Table 1. Alternatives

Attribute	C+I	C+A	A+B	FPI(FT)	FPI(ST)	FPI(AF)
Scope Definition	Very Good	Poor	Excellent	Good	Poor	Good
Risk Exposure	Significant	Minimal	Minimal	High Risk	Average	Average
Cost	Satisfactory Reduction	Increment	Stable	Satisfactory Reduction	Satisfactory Reduction	Satisfactory Reduction
Time	20% reduction	10% reduction	32% reduction	5% reduction	5% increment	2% increment
Technical Performance	High	Low	Very  High	Meaningful Impact	Low	Cannot be measured objectively
Contract Improvement	Significant	Insignificant	Significant	Significant	Low	Insignificant
Gains	5%	5%	50%	10%	0%	0%
Losses	2%	3%	0%	2%	5%	5%

The most important attribute is time and cost reduction which is the bane of Project Management.

5.       Analysis and comparison of the alternatives.

This is done by using the non-compensatory model called Disjunctive Resolution method evaluates each alternative on the best value achieved for any attribute.

Table 2- Feasible Range.

Attribute	Minimum	Maximum
Scope Definition	50%	100%
Risk Exposure	1%	5%
Cost	10%Reduction	20% Reduction
Time	10% Reduction	40% Reduction
Gains	10%	Unlimited
Losses	0	10% 0f Profit
Technical Performance	5%	10%
Contract Improvement	2%	7%

Comparing table 1 with the acceptable Standard, Cost-plus-incentive-fee contracts and Cost/Time plus Incentive/Disincentive (A+B) are the two most feasible alternatives.

The Additive Weighty Technique of Compensatory model is also being used for this analysis in

Table 3 - Additive Weighty Technique

Attributes	Step 1 Relative Ranking	Step2: Normalized Weight (A)	(B)	C+I	C+A	A+B	FPI(FT)	FPI(ST)	FPI(A)
Scope Definition	6	6/36=0.17	0.17	0.034	0.003	0.156	0.001	0.035	0.002
Risk Exposure	1	1/36=0.03	0.03	0.024	0.033	0.030	0.014	0.016	0.012
Cost	7	7/36=0.19	0.19	0.095	0.100	-3.80	0.032	0.011	0.023
Time	8	8/36=0.22	0.22	1.070	1.022	6.100	1.000	1.200	1.078
Technical Performance	5	5/36=0.14	0.14	0.084	0.056	0.112	0.020	0.036	0.024
Contract Improvement	4	4/36=0.11	0.11	0.066	0.043	0.066	0.011	0.022	0.011
Gains	3	3/36=0.08	0.08	0.004	0.001	0.016	0.022	0.015	0.016
Losses	2	2/36=0.06	0.06	0.012	0.011	-0.01	0.009	0.005	0.028
Sum	36	1.00		1.390	1.734	2.600 Best Choice	1.109	1.340	1.194

                                                                                                                               

6.       Selection of the preferred alternative

The best Choice is Cost /Time Method (A+B)

7.       Performance Monitoring.

·          Time of Completion against the Scheduled time

·         Actual Project cost against the Budgeted Project Cost.

8.       References

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

2. Giammalvo, P.D (2012, October 22). Integrated portfolio (asset), program (operations) and project management methodology course (Power Point slides) (An AACE methodology course). Day 5 (pp 73-91) Lagos.  Nigeria.

3. Randall, C.B & Lynn, W. (Sept 2007) Contract Management □ 21. I N C E N T I V E C O N T R A C T S(Pp 18-22)  Retrieved from: www.ncmahq.org/files/Articles/F5720_CM0907.pdf.

4. Ashley .M (Dec 2010), Incentive Contracts for Sub part 16.4. Retrieved from: code210.gsfc.nasa.gov/education/Incentive Contracts.ppt

5. Fadaunsi.F. (Nov 2012) Folakemi_ Filling_Vacant Roles . AACE Preparatory Class of Oct 2012. Retrieved from:bistro12.blogspot.com/2012/11/w4

 

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.