W1_Thuraiya_Leadership Styles analysis Using Tuckman model

W4__Hamda__PARETO Analysis__

1-     Problem Recognition

During the life of the project and under some phases, there are some problems may the project will face and they will affect on the life cycle of the project or the process under each stage. The majority of these problems is different from one to another depends on the causes of the problem, the effect of the problem, and the size of its impact on the specific phase and the whole project. In order to look at the issues and causes of this problem, the decision maker shall use a perfect and creative tool and technique. One main tool that can be used in identifying the main causes and issues of any problem is the PARETO Analysis. In this blog, I will use the PARETO Analysis tool in order to analyze one main problem that the department face some months while processing the monthly invoice which is the accuracy of the plant model- Fuel Demand Model (FDM) while running it- which it is used in calculating the Fuel charge.

1-     Feasible alternative

The Pareto Analysis, also known as the Pareto principle or 80/20 rule, assumes that the large majority of problems (80%) are determined by a few important causes 20%).The founder of this analysis, Italian economist Vilfredo Pareto, discovered this when he was carrying out a study at the end of the 18th century in which he ascertained that 20% of the Italian population owned 80% of the property.

In order to use the PARETO analysis in the above mentioned problem, it is important to know the frequency of occurrence of each cause (the number of time that the department face this cause), and the impact of such cause on the result of the FDM Run (increase in the figure-technical element (X figure) - technical element used in calculating the FC- ), which may cause huge deduction on the charge. 

Picture from: https://pmstudycircle.com/2015/06/pareto-chart/

1-     Development of the outcome of Alternative

In the above the case that I mentioned above, in order to solve the problem and get accurate results from the plant model and then get accurate calculations in the monthly invoice without facing any difficulties and to avoid may be any deduction because of the non-accurate results from the model, it is important to identifying and determining the main causes and issues that develop this problem. Because identifying and solving the small causes will help in mitigation or avoiding the occurrence of the large problem. The main causes of the mentioned problem are: 

-        Problem A: Non-accurate  additional data- Gross data for each GTs, and STs of the whole plant- that is used as inputs data to the model. (Input data). 

-        Problem B: Non-accurate -Net data for each GTs, and STs of the whole plant- provided in the invoice that used as input data and ambient conditions data.

-        Problem C: Non-accurate of equations developed in the Model. 

-        Problem D: Design of the model. 

2-     Selection Criteria

There are number of issues that cause the main problem which is the Non-Accurate Results from the FDM as I mentioned above. The major issues that cause 90% of all the non-accurate FDM result will be listed in tables and Pareto Chart. The rest of the issues are minor and affecting the performance by 10%.

3-     Analysis and comparison of the Alternative

Table 1 shows the main issues that cause the non-accurate FDM results which affects on the calculation of on specific charge in the invoice.

Problem	Frequency	Increase deduction (Cost)
Problem A	200	30,000
Problem B	130	14,000
Problem C	50	5,000
Problem D	10	2,000
Total	390	51000

Note: the data used in table is RANDOM data (for the purpose of explanation only)

PARETO Chart 1: represent the data mentioned in table 1

Table 2 shows the main issues that cause the non-accurate FDM results which affects on the calculation of one specific charge in the invoice. It shows more calculations on the percentage of occurrence of each issue and the percentage of cumulative of issues. 

Problem	Frequency	% of total	Frequency (cumulative)	% of total (cumulative)
Problem A	200	51%	200	51%
Problem B	130	33%	330	85%
Problem C	50	13%	380	97%
Problem D	10	3%	390	100%
Total	390	100%	390	100%

Note: the data used in table is RANDOM data (for the purpose of explanation only)

PARETO Chart 2: represent the data mentioned in table 2

1-     Selection of the preferred Alternative 

From the above chart, it clear that the first 2 issues which they are ( non- accurate Gross Data of the units in the plant (GTS, STs), and the non-accurate NET data of the units and ambient conditions), have the highest percentage, which indicate that they are the main causes of the occurrence of the problem. So the one way that can be used in order to mitigate or avoid the huge deduction which is because of the non-accurate FDM results is to provide the accurate data of Gross and Net Production of each unit, and accurate data of the ambient conditions. That mean these data shall be checked and reviewed before submitted to the FDM. 

2-     Performance Monitoring and the Post Evaluation of result

PARETO analysis tool is very helpful technique which helps the projects manager or the team member (who is responsible of doing such small projects) to identify the causes of most of the problems the process is facing. By identifying the causes of the problem, this will help in reducing the occurrence of the problem or avoiding the occurrence at all.

Reference: 

1-     Fahad Usmani (2017), What is a Pareto Chart?, Retrieved 26 November 2017, from https://pmstudycircle.com/2015/06/pareto-chart/

2-     Pareto Analysis Diagram including an example and template | ToolsHero. (2017). ToolsHero. Retrieved 26 November 2017, from https://www.toolshero.com/problem-solving/pareto-analysis/

3-     GUILD OF PROJECT CONTROLS COMPENDIUM and REFERENCE (CaR) | Project Controls - planning, scheduling, cost management and forensic analysis (Planning Planet). (2017). Planningplanet.com. Retrieved 20 November 2017, from http://www.planningplanet.com/guild/gpccar/risk-opportunity-monitoring-and-control