Total-productivity analysis of a Nigerian petroleum-product marketing company

APPLIED ENERGY

Applied Energy 84 (2007) 1150–1173

www.elsevier.com/locate/apenergy

Total-productivity analysis of a Nigerian petroleum-product marketing company M.T. Lilly a, U.E. Obiajulu a, S.O.T. Ogaji

b,*

, S.D. Probert

b

a

Mechanical Engineering Department, Rivers State University of Science and Technology, Port Harcourt. P.M.B. 5080, Nigeria b School of Engineering, Cranfield University, Bedfordshire Mk43 OAL, United Kingdom Available online 23 July 2007

Abstract Productivity in Nigeria is decreasing: this has adversely affected the average standard-of-living of the population and led to economic hardship. HIV/AIDS, hunger, disease and wars have lowered African productivity and the effectivenesses of public utilities have declined, while unemployment and crime are on the increase. A computer program, which considers the combined concept of partial productivity, total productivity measurement and reliability in order to analyse the effectiveness of a firm, society or nation has been developed. Its predictions have been tested with data from a Nigerian petroleum-product marketing company, namely Rock Oil and Gas Ltd., Aba, Abia State: the management of this business is representative of those of many Nigerian firms. The developed software (see Appendix) can help in identifying the causes of productivity problems, which can so adversely affect the performance of any organisation.  2007 Elsevier Ltd. All rights reserved. Keywords: Productivity; Partial productivity; Total productivity; Total productivity-index; Severity; Computer program

1. Introduction In Nigeria, there are more than 100 organisations in the downstream petroleum-sector (DPS), over 70% of which are independent marketing companies. Over 90% of these are *

Corresponding author. Tel.: +44 1235 750 111; fax: +44 1234 751 232. E-mail address: s.ogaji@cranfield.ac.uk (S.O.T. Ogaji).

0306-2619/$ - see front matter  2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.apenergy.2007.04.003

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

1151

Nomenclature and Abbreviations AGO C CAD CAM DPK DPS E ES F GP L M

automotive gasoline-oil capital investment (Naira) computer-aided design computer-aided manufacturing dual-purpose keri downstream petroleum sector energy cost (Naira) measured error feedstock cost (Naira) gross product labour cost (Naira) material cost (Naira) Nigerian currency (Naira) N OS observed severity P productivity PH Port Harcourt PMS prime motor-spirit PP partial productivity PPI partial productivity-index Q1, Q2, Q3, . . ., Q10 questionnaire’s assigned numbers S output TP total productivity TPI total-productivity index TPM total-productivity measurement TS true severity UOO name of company V variance XTotal total-productivity severity XM mean severity Z sample quantity a Cronbach’s alpha-coefficient

privately owned or registered as limited-liability firms, but still have family members as the directors and/or chairmen. Many of these firms employ no professionally-qualified managers or engineers and so are vulnerable or susceptible to closure as a result of even small government-policy or technological changes, so causing local fuel-scarcities, which adversely affect the overall manufacturing success of the nation. The Rock Oil and Gas Company Limited (see Tables 1 and 2) was incorporated as a limited liability company on 21st May 1985, being a member of the UOO group of companies. UOO now has four factories namely, Major Electrode Nig Ltd., UOO Corrugated Roofing-Sheet Plant, Aba; and UOO Feed-Mill Aba. UOO also has a chain of trading outfits around Nigeria. The Rock Company started operations with a share capital of 6 N5 · 10 in 1990, majoring in the marketing of petroleum products like prime motor-spirit

1152

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

Table 1 Total productivity analysis for Rock Oil Ltd Cost

Year

Productivity input Fixed capital Feedstock Energy Materials Labour Output for the year

2003 (Million Naira)

2004 (Million Naira)

2005 (Million Naira)

25.7 15 6 9 1.3 2.5 30.5

37.7 20 10.2 1.2 1.5 2.8 45.4

41.5 20 15 1.5 2 3 51.7

Source data: Rock Oil Ltd. During the period 2000 ! 2005, the company increased its capital investment to N20 · 106.

Table 2 Partial productivity (PP) analyses of Rock Oil Company Nigeria Ltd Year

Capital

Feedstock

Energy

Material

Labour

2003 2004 2005

2.03 2.27 2.58

5.08 4.45 3.45

33.89 37.83 34.47

23.46 3.03 25.85

12.2 16.21 1.72

(PMS), automotive gasoline oil (AGO) and dual purpose Keri (DPK). The headquarters is situated at PH – Enugu expressway Alaoji, Aba, Abia State, Nigeria. A new plant in 1990 located at PH road, Aba was built to bottle and sell cooking-gas and the share capital invested was increased to N30 · 106 with a staff of 40. The strategic location of the premier gas-station led to a tremendous growth in daily sales and hence of the company. The Cooking Gas Bottling plant provides services to customers for Aba and the surrounding towns and states. To increase its market share, the company now has numerous branches in Anambra, Abia and Lagos States in Nigeria. The cooking-gas bottling plant has also expanded. In a reliability-analysis programme, questionnaires concerning productivity factors are issued to the operators: the internal consistency of the information in the questionnaires is tested using the Cronbach alpha-coefficient, Kuder Richardson formula or a split-half reliability-coefficient analysis. A higher value for the coefficient shows a greater data consistency, which encourages the analyst to propound a recommendation based on the prediction. Software exists that applies this reliability analysis in productivity analyses [1]. The factors affecting the values of the productivity can be analysed either manually or by computer software. There is a computer-based program, using reliability analysis, which applies the Cronbach alpha-coefficient concept for productivity analysis. Productivity can also be analysed using the total-productivity index, which involves (i) considering the aggregate productivities and (ii) studying the efficiency with which each of the resources is being used to produce the required goods or services. Productivity can also be analysed using the poly-plotting approach or using a combined partial and total productivity measurement analysis [1]. A combination of reliability analysis, which applies the Cronbach alpha-coefficient concept and total productivity index, has been chosen for the present computer program

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

1153

because it applies the data from the partial-productivity questionnaire and tests the internal consistency of the data as well as considers the total output/input activities in the organisation during the period under consideration. This approach gives a more accurate overall account of the organisation’s problems at a glance. 2. Literature review Productivity has been defined as the ratio of output to input. It is a measure of how well inputs (i.e., manpower, machines, materials, money, time, space, energy, information and other resources) are transformed into the required useful outputs (i.e., finished goods or services) [2]. However, a quantified value for productivity tends to vary according to the proposed use of the productivity predictions as well as the subjective perception of the definer in the economy under analysis, as well as and the skill of the definer in interpreting the statistics [3]. The majority of people are selfish even though they may not acknowledge this themselves. At the first American Conference on productivity held in 1947, it was agreed that almost any comparison of output with input provided an indication of productivity [4]. Most people tend to underestimate the planning, cost, time taken and effort required to undertake a major project. Accurate and perceptive management is required to maintain a high productivity [5]. Good work-practices improve an establishment’s productivity [6], which should be checked at regular intervals: if this is not done, standards of performance tend to decline. Even though the deterioration is gradual, the company may soon become uneconomic [7]. Management applications and work practices affect the productivity of every organisation: one measure of productivity (and efficiency) is the output per dollar spent on labour [8]. A low productivity usually arises from poor leadership, resulting in goals not being set or achieved, high staff-turnover and excessive workers’ absenteeism [9]. A study [10] concludes that automation boosts productivity as a result of less maintenance being required. Logistics, automation, technology, power per unit optimisation, material and equipment provision, cost control, antecedents (e.g., rules) and consequences (e.g., punishments) in the organisation, lack of standardisation and egocentric culture of the management oligarchy also affect personnel morale and so influence the productivity of the organisation [11]. The presence of a manufacturing company affects its local community [12]. So the company needs to develop a good relationship with its host community. There are at least 27 factors that affect productivity (see Table 3) and these can be grouped into 9 super-factors [13]. These and many other findings have been applied directly or indirectly to analyse, predict and enhance productivity in organisations. For some of these influences, computer programs have been devised to assess productivity and suggest how improvements may be achieved. Pertinent computer programs: the PMBOK tool was developed by the Project Management Institute (PMI) of America. It involves an assessment of the capability of the project manager [14]. This program (i) collates answers to a questionnaire issued to the manager and provides a numerical indication of his or her relevant knowledge, language, undertaking of pertinent concepts and professionalism and (ii) supplies a measure of the quality of the human-resource input required to achieve the resource quality of product or service. Calliper International, Inc and Professional Development Solutions Inc developed computer-based programs such as the supervisor’s self-rating software, KRA #1, PDS, that some organisations are currently using for project-management

1154

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

Table 3 Rock Oil Ltd. productivity – problem items severity data and recommendations (obtained from questionnaires) Factor No. 1 2 3 4 5 6 7 8 9 10

11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

Problem description (i.e., Factor)

Q1

Q2

Q3

Q4

Q5

Q6

Q7

Q8

Q9

Q10

Mean

Insufficient manpower and support Lack of (i) multi-skilled training, (ii) flexibility and (iii) commitment Insufficient personal recognition for each individual’s effort Lack of goal orientation and awareness of mission Lack of equity, mutual respect, trust and valued partnerships Lack of autonomy, self-management and attitude of continual improvement Workers dislike their positions and taking responsibilities Lack of financial control: corruption and misappropriation ensues Inadequate funding of project Purchase of wrong raw and operational materials; ineffective stocking and delivery leading to undue delays Insufficient or unreliable tools and machinery Obsolete or scarce relevant technology Lack of high-tech or pertinent automation processes Information technology and communication problems Workers believe that the working environment is inherently dangerous Benchmarking, strategic, alignment and procedural problems Staying within customers’ desirable specifications Climate problems (too hot, cold ,dry and/ or humid) Host-community demands Host community wants good personnel replaced with their choices Inadequate maintenance planning, execution and/or records Government bureaucracy (excessive controls, licensing delays, etc.) Trade-union practices: unreasonable times for meetings, negotiations, etc. Workers’ strikes and industrial disputes Workers do not feel they belong in the business Casual staff feel that permanent staff are favoured Workers believe that inadequate commission is giving to their dependants’ needs

14 10

14 6

10 8

10 9

12 9

12 6

15 8

9 8

12 8

12 8

12 8

25

25

25

25

25

25

25

25

25

25

25

8

8

12

12

10

12

8

10

10

10

10

25

25

25

25

25

25

25

25

25

25

25

8

10

2

2

6

6

10

2

6

6

5.4

5

2

8

5

5

5

5

5

5

5

5

15

14

16

10

20

15

18

12

15

15

15

25 25

24 25

25 22

25 25

24 25

22 25

25 24

25 25

25 25

25 25

24.5 24.6

25

24

25

25

25

25

25

24

25

25

24.8

25 25

25 24

25 25

24 25

25 25

24 24

25 25

25 25

24 25

25 25

24.7 24.8

24

22

25

25

25

25

25

25

24

25

24.5

20

10

12

18

15

15

16

14

15

15

15

20

25

15

22

18

20

18

22

20

20

20

16

18

14

16

10

22

16

20

12

16

16

10

10

12

14

8

6

10

10

10

10

10

5 10

5 10

5 12

5 8

5 6

6 6

4 14

2 16

8 8

5 10

5 10

10

10

10

14

13

6

8

10

10

10

10.1

15

15

20

12

12

16

12

18

15

15

15

4

2

4

6

4

4

4

4

2

6

4

5 25

5 25

4 24

4 25

6 25

5 24

5 25

4 24

6 25

6 25

5 24.1

25

25

24

24

25

25

25

25

25

25

24.8

15

20

10

18

12

15

15

15

16

14

15

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

1155

predictions [15]. These programs again assess the quality of the human resource input just like the PMI tool that considers the ratings of the leader by also questioning by his seniors, peers and the subordinates – i.e., a 360 assessment. There are also productivity computer-programs available that were developed by a group of organisations including NASA and the USA navy, e.g., HPCS, which is being used for defining and measuring performance, programmability, portability, robustness and productivity in an organisation: it is labour-input based [16]. The software Productivity Research Centre in the USA developed project-estimation software called SPR Knowledge PLAN, which reduces the time required for estimating and coordinating project spending and correlating it with the preordained budget [17]. This productivity-enhancing program reduces the required logistics, labour and maintenance requirements in the production of goods and services. There is also a reliability program, developed for testing and analysing productivity by applying the Cronbach alpha-coefficient concept [1]. This has been applied to test productivities in several Nigerian organisations. It was developed by applying the formula of the Cronbach coefficient, defines a measure of the squared correlation between the true and observed severities used in measuring the reliability of the product [18]. The Cronbach alpha-coefficient reliability concept has been applied successfully to analyse reliability using the Stroke Rehabilitation Assessment of Movement (STREAM) measure, which developed an instrument to measure the recovery of human movement following a human stroke [19]. This is a productivity-measuring as well as an analysing program: it measures the reliabilities of the values of the input productivityfactors and also indicates if the data are true and interrelated. It can give a factor for total productivity for a critical productivity measurement. There are diverse programs that offer quick methods for procuring available materials like One World Xe developed by J.D. Edwards World Source Company USA. It has been employed by many organisations to carry out inventory management, including material ordering, tracking, approvals and auditing, as well as for electronic-service ordering. Maintenance management system (MMS) is used for work-order management of an organisation’s logistics, as well as material and machine control. It is a productivity-enhancing program [20]. There are computer-aided work enforcers, e.g., the Thomer work-enforcer that improves working aptitude through automatic directional prompting and the Microsoft-work place enforcer that applies ergonomic computer operations at a workstation [21]. There are also many personnel card-clocking programs that help minimise personnel compensation fraud and some complicated productivity-enhancing software like robotics programs that empower robots to undertake jobs better and faster than man. Such complicated programs include CAD and CAM and their compilers. Checklist Productivity Software recently developed a user-friendly task-management and productivity-enhancing software called checklist Productivity [22]. This program assigns tasks and schedules events. Another software item, produced by 4th Software Inc called Pforth [23], arranges tasks into groups and then organises the associated decision trees. It marks items as ‘‘due today’’ and ‘‘set well-qualified today’’. It also estimates completion dates. With this, you can often eliminate the labour cost of two planning engineers in a project. It is a productivity-enhancing program. There is software that enhances productivity called Web timesheet 5.8: this calculates and sorts out the timesheets of workers [24]. Pace productivity Inc developed a program called Tabular that reduces time and effort expenditure for such tasks [25]. This productivity-measurement software compares time input with that for the previous nominally-similar job. Win Planet is the

1156

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

software that performs stock taking, net stocking, quote barcode and stock monitoring [26]. It also indicates trends in productivity, because any drop in the company stock price sends a productivity message to managers as well as the company shareholders. Current research focuses upon specific cases of low productivity in a system. Most of the pertinent software is to help organise, design, manufacture, transport, keep records and process data, so encouraging investment in aspects that will lead productivity rises. Nevertheless there is a general belief that the consultant knows how to do it, so why bother to use such programs. However, a pertinent program allows the manager to learn and apply the program to suggest time to time what to do to stop any downward drift of his/her company’s productivity. But most of the programs have been developed in western nations and do not account sufficiently for the problems peculiar to third-world nations like Nigeria. The available analyses consider only one or two approaches to productivity analysis. This present research has developed a tool that anybody can use, including those in the third world. The model has been tested and compared with existing ones and has advantages compared with them. It employs a multi-dimensional approach to procuring and analysing data on productivity, and calculates the partial, total and index of productivity, test data reliability, the Cronbach alpha-coefficient for the data and advises the individual whether to use it or not. It will also indicate any critical factors and calculate the productivity index. It then analyses the factors influencing the productivity. It is fast and simple to apply and the manager/engineer requires little or no coaching to learn how to apply it by himself in his organisation. 2.1. Theoretical framework for this new program Total productivity is expressed as the ratio of output to input. Partial productivity (PP) deals with specific individual components of the input that produce the output. The total-productivity index (TPI) is a ratio of total productivity measurement (TPM) for the considered year to the total productivity measurement for first year of the considered period. Analytically it can be represented as follows [1] and [6]: S S S S S PP ¼ ; ; ; ; :::or L C F E M S  100 TPM ¼ L þ C þ F þ E þ       M 3. Reliability component This involves (i) the calculation of the severity of the productivity factor, (ii) testing the internal consistency of the whole data and (iii) evaluating the index. The Cronbach alpha-coefficient approach is adopted for the calculation of the productivity reliability. It is a measure of the squared correlation between observed severity and true severity of the data collected. The observed severity (OS) is equal to the true severity (TS) plus the measured error (ES), i.e., OS ¼ TS þ ES

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

1157

The measured items (i.e., variable-value parameters) used to form scales need to have internal consistency (i.e., be measured in the same units). A useful coefficient for assessing internal consistency is Cronbach’s alpha-coefficient.  X V i  Z 1 a¼ Z1 Vt Total productivity severity = XTotal = X1 + X2 + X3 + X4, . . . . . . , . . . ,X27 (Note: In this study, 27 factors have been identified as affecting the productivity). The Cronbach alpha-coefficient, which is the level of interrelationship of the factors affecting the productivity, becomes the coefficient for the Nigerian situation-factor. From previous [2,12] research, the Nigerian factor will be 0.9991792. So in the software, any pertinent data-set sourced from Nigeria will involve this parameter. But, in the course of feeding the information into the program, if you click on ‘‘No’’ for the question ‘‘Are the data from Nigeria?’’, the program will ask for the productivity-factor severity for the chosen organisation or country for which the final TPM and TPI are calculated. In such a case, you will need to issue an appropriate questionnaire corresponding to that used in the program presented in the Appendix. Because the Cronbach alpha-coefficient is a measure of the internal consistency of all the data and their reliabilities, it can as well be a measure of true orderliness of the information available about the organization. It measures the interrelationship between all the personnel’s feedback in the questionnaire: a lack of proper communication is a productivity-inhibiting factor in itself. So the program multiplies the productivity measurement with ‘‘a’’ to get the true value. The program predicts the a value, the TPM and the TPI values without a, so that you can use the productivity without it if you so which. 4. Program-operation manual Do not input zero into any value space in the software. Put the base date for the analysis as instructed in the first dialog that comes on. Click on next. Input the partial-productivity values for capital, feedstock, labour, energy and materials for the first physical year. This can represent any input resource to you, e.g., amounts of utilities used can be noted and used as feedstock for the computer. Click on next. Input the second physical year. Click on next. Input the third year. Click on next. Click on the location (i.e., Nigeria or other country). Click on next. If you click on ‘‘No’’, a table in the software for productivity severity will come up. Input the data from the returned questionnaires. You may get the value of a of any organisation in Nigeria: click ‘‘NO’’ if you already have the data. Input the quantities as filled in the returned questionnaires, for the 27 productivity factors if you have clicked on ‘‘NO’’. Input the number of questionnaires returned. Type in 27 for the column box (it’s a default number).

1158

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

Type in the value of the severity (i.e., calculated frequency of occurrence multiplied by the effect) for each factor in one row, before inputting the second factor severities, until the last factor is considered. The result will be printed out giving the Cronbach alpha-coefficient, the PPIs for the respective years and the PPs for the subsequent years: the TPM and the questionnaire analysis will identify the problem factors in the organisation. Click on the download button. Download the result into Excel if you want to print or save it. Save it into any file or folder in your program and expand the expert recommendation from the program. IF you have clicked ‘‘NO’’ to location, the program identifies the problems with respect to the 27 productivity factors. 5. Research methodology A candid opinion of the managers and staff of Rock Oil Ltd. was collated from answers to 10 productivity questionnaires issued to a random sample of personnel to fill out. The managing director was asked to complete, with the help of his management staff, the source data form and an interactive approach was adopted by the researcher visiting the firm’s head office and branches for interactive interviews. The two-source data from the company was plugged into the developed computer-program and the computer’s report was analysed using, in addition, the information from oral interviews carried out within the company, the analyses are shown in Tables 1 and 2. The total productivity measurement (TPM), total productivity index (TPI) and alpha (a) were calculated by the developed computer program and a results print-out is obtained. 5.1. General analysis of results The productivity results shown in Fig. 1 indicate that a serious productivity decline has occurred. The company will become bankrupt if urgent attention is not given to rectify this problem. Productivity fell more rapidly between AD 2003 and 2004, i.e., before the bank loan given to the company to boost its capital base to try to give it temporary stability. However, the business is still in dire straits: and either the productivity problem is solved or liquidation will occur within 3 years. The fall of partial productivities of labour and energy in 2004 over the base year is because of the reduction of capital investment due to the increase in the use of alternative power-sources and subsequent equipment breakdowns and shutdowns. 6. Partial productivity  The capital invested in the company shows an increase of 12.8% during the considered 3 years. However, the resources are not well utilised because of low equipment reliability and misplaced priorities. The capital invested should have been targeted to raise the output of the firm. The plant at Unubi in Anambra State was shut down during the 3-year period.

1.4 1.2 1 0.8 0.6 0.4 0.2 0

Total Productivity Measurement

1159

Absolute TPM

120 TPM*(ALPHA)

TPM

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

100 80 60 40 20 0

2003

2004 Year

2005

2003

2004 Year

2005

TPI or TPI*(ALPHA)

Total Productivity Index 100 TPI 90

TPI*(ALPHA)

80 70 60 2003

2004

2005

Year

Fig. 1. Productivity plots for Rock Oil Ltd.

 Feedstock (e.g., the fuel for the generators and lube oil for the gas plants) has been reduced during the 3-year period.  The cost of energy went up by 11.6% and later came down by 8.90% having a gross upward shift of 2.7%, i.e., the energy input has not increased significantly. But it is also due to lack of rapid expansion and fuel-stations rapid shut-down in the company.  During the 3 years, the cost of materials in the business has risen 10.2% but the partial productivity shows that the cost of materials’ increase is small relative to that of the output. Materials are important in the business, but some irrelevant materials were purchased in this case.  Labour productivity fell by 84.2% in 2005 relative to that for the base year, showing that there was an action that increased labour cost in 2004, but the productivity in 2005 could not carry the equivalent labour burden because of non-diversification in the business of the company. Old machines and not investing in new technologies led to the low growth-rate. This also arose because of the improper actions of the directors and dependants’ roles in the business. This has made it difficult for the management to increase workers’ compensation to improve productivity because of the profit target, but this affects the morale of the workers. This adversely affects the productivity of the business. Table 3 shows the productivity severity data of the company used as the case study, while Table 4 shows the recommended actions based on calculated partial and severity productivities of the company.

1160

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

Table 4 Recommendation based on partial productivity and productivity severity questionnaire Factor No. (from Table 3) 1

3

4

5

8 9

10

11

12 13

14

15 16

Remarks Rock Oil management needs to consider out-sourcing some professional jobs and retain reliability jobs like preventive maintenance. A consultant is required to inform the company of recent international trends in the oil business. Diversification of the business is needed. Should explore more opportunities in the wholesale delivery of cooking gas. Need to explore opportunities for providing N2 and O2 gas supplies. Appoint pertinent experts on the bases of commission payments There is currently no effective compensation process in place. A performance measurement process should be developed. Within one month after developing a performance-measurement process, a performance rewarding process should be implemented to reward personnel for excellent performance. Within the same month after developing a performancemeasurement process, the company needs to implement some penalties for non performance amongst its personnel The organisation runs a planning system, but it is still based on end measures. A board of directors should be appointed and their functions defined. The company should introduce daily work-planning meetings (of 15 min duration) starting every 7.30am. A weekly review meeting should be established to review target achievements and the lessons learnt. A 360degree communication system should be introduced. Every worker should know (i) the aims of the company and (ii) how well they are being achieved. Introduce email for everybody in the company The company needs to depart immediately from a family and friends oligarchy in the management of the organisation; but should establish a management board which consists of highly-competent members to run the organisation. An effective financial-control system needs to be introduced. The company should hire a reputable accountant to review and restructure the current financial-control process The company needs to be recapitalised by investing at least 100 million Naira in order to facilitate restructuring and expansion. External loans should be considered, but can the resulting debt be serviced relatively easily? Lead-time stocking of petroleum products should be considered. Big lease tanks should be built in one part of Nigeria to hold petroleum products especially when nearing the festive period. Import licenses should be sought from the government. Government recently liberalised the importation of petroleum products and now is a good opportunity to expand the business Modern tools need to be deployed in the gas plant and the fuel stations all over Nigeria. Preventive maintenance should be implemented. Hire a highly capable maintenance engineer (Q4) to create a maintenance department and take over the plant-reliability jobs including keeping records. Work with DPR (Government) regulations to comply with all legal requirements Set up an engineering department to identify and adopt best technologies available The gas-filling plants need some (process and weighing) automation. The fuel pumps must be changed to digital automated versions in all the branches where manual pumps are still in the use Create an effective communication system. Create software to improve plant reliability, pay salaries, and calculate workers’ and management performances and compensation processes for land acquisition. Install a network server and introduce an e-mail system within each branch Engage a security consultant to advise the company on the appropriate protection system that needs to be adopted Engage a professional to devise adequate procedures for all operations in the company. There should be a written procedure for each operation including those for pumps and generators as well as cooking-gas handling (continued on next page)

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

1161

Table 4 (continued) Factor No. (from Table 3)

Remarks

17

Project inspectors should be employed. Initially the company should use temporary but qualified labour until it finishes the restructuring and expansion process Install air conditioners and fans in the offices and blowers in the plants. Install ergonomic furniture in the offices Though not a big problem in this case, but consider using qualified labour for casual lowskilled jobs. Must not replace a winning team Use a large network computer with a large memory Draw up procedures for working with the government and find out who does what in the government offices that are relevant to the business. Use a consultant to deal with government bureaucracy Set up morale-boosting procedures in the company like long-service awards, best-seller awards, etc. Explain clearly that this is not a core-family business and promotion is based on competence. Workers should see that they are justly rewarded for their efforts. No discrimination (as a result of religion, sex, ethnicity, etc) in the business. No harassment or molestation in the work place Engage casual staff through a sub-contractor. Compensate them reasonably well and conduct performance appraisals for them just like those for regular staff and reward them appropriately Functions that should bring families together occasionally should be initiated. Awardees could come with their spouses to long-service award ceremonies. Involve families in the endof-the-year celebrations

18 20 21 22

25

26

27

7. Conclusion An analysis has been undertaken of the profitability of an independent downstream petroleum marketing company, namely Rock Oil, Nigeria. The case study is useful tool for analysing and solving productivity problems in any firm, government or society. The presented computer program is versatile and user friendly. It enables one to allocate more time to think about how to improve productivity. It does a large part of the management tasks normally undertaking by a production engineer. You simply input the data and it uses formulae and concepts to give you the desired information quickly. The program is written in Visual Basic, which is interactive and has an executable form ready to go. It can be exported to an Excel file, which you can use to plot a graph, devise a table, save, as well as send the output to someone else. Appendix SOURCE CODE Public year(2) As Integer Public capital(2), feedstock(2), energy(2), material(2), labour(2), output(2) As Double Public ppcapital(2), ppfeedstock(2), ppenergy(2), ppmaterial(2), pplabour(2) As Double Public tpm(2), tpi(2), alphatpm(2), alphatpi(2) As Double Public Rep(27) As String

1162

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

Public stage As Integer Public datsource As Boolean Sub Main() Rep(1) = ‘‘Manpower, and support role insufficient’’ Rep(2) = ‘‘Lack of (i) multi-skilled cross training, (ii) flexibility and (iii) commitment.’’ Rep(3) = ‘‘Insufficient recognition and rewards for each individual’s effort’’ Rep(4) = ‘‘Lack of goal orientation and awareness of mission’’ Rep(5) = ‘‘Lack of equity, mutual respect, trust, valued partnerships’’ Rep(6) = ‘‘Lack of autonomy, self-management and continual-improvement endeavour’’ Rep(7) = ‘‘Workers dislike their positions and taking responsibility’’ Rep(8) = ‘‘Lack of financial controls, corruption and misappropriation ensues’’ Rep(9) = ‘‘Inadequate funding of project or operation by stakeholders’’ Rep(10) = ‘‘Purchase of wrong raw and operational materials, ineffective delivery and stocking’’ Rep(11) = ‘‘Insufficient or unreliable tools, and machinery’’ Rep(12) = ‘‘Obsolete or scarce relevant technology’’ Rep(13) = ‘‘Lack of high-tech or pertinent automation of processes’’ Rep(14) = ‘‘Information technology and communication problems’’ Rep(15) = ‘‘Workers believe that work environment is inherently dangerous’’ Rep(16) = ‘‘Benchmarking, strategic alignment, procedural problems’’ Rep(17) = ‘‘Staying within project parameters’’ Rep(18) = ‘‘Climate problem (too hot, cold, dry or humid)’’ Rep(19) = ‘‘Host community demands’’ Rep(20) = ‘‘Host community wants good personnel replaced with their choice’’ Rep(21) = ‘‘Inadequate maintenance planning, execution and/or records’’ Rep(22) = ‘‘Government bureaucracy(excessive controls, licensing delays, etc.)’’ Rep(23) = ‘‘Trade-union practices – unreasonable time for meetings, negotiations, etc.’’ Rep(24) = ‘‘Workers’ strikes and industrial disputes’’ Rep(25) = ‘‘Workers do not feel they belong in the business’’ Rep(26) = ‘‘Casual staff feel that permanent staff are favoured’’ Rep(27) = ‘‘Workers believe that inadequate consideration is given to their dependents’’ frmMain.Show End Sub ***************** End Module Global ************************************* ***************** Main Code ************************************* Option Explicit Private Sub cmdBack_Click() Dim msg As String Dim i As Integer If Frame1.Visible = True Then If Not IsNumeric(txtyear.Text) Or (txtyear.Text = ‘‘’’) Then msg = MsgBox(‘‘You have entered an invalid year’’, vbInformation + vbOKOnly, ‘‘Error’’) Else For i = 0 To 2

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

1163

year(i) = CInt(txtyear.Text) + i Next lblInfo.Visible = True lblInfo.Caption = ‘‘The Application will process model for year’’ & year(0) & ‘‘, ’’ & year(1) & ‘‘, ’’ & year(2) End If controlButton End If End Sub Private Sub controlButton() If Frame1.Visible = True Then If lblInfo.Visible = True Then cmdNext.Enabled = True cmdBack.Enabled = False Else cmdNext.Enabled = False cmdBack.Enabled = True End If End If End Sub Private Sub cmdNext_Click() If Frame2.Visible = True Then If Not Validated = True Then Exit Sub End If stage = stage + 1 If Frame1.Visible = True Then Frame1.Visible = False Frame2.Visible = True End If If stage = 2 Then lblyear = year(0) End If If stage = 3 Then SaveValue (0) lblyear = year(1) End If If stage = 4 Then SaveValue (1) lblyear = year(2) End If If stage = 5 Then SaveValue (2) Frame2.Visible = False Frame3.Visible = True ‘lblyear = year(2) End If If stage = 6 Then

1164

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

Frame3.Visible = False If Optyes.Value = True Then datsource = True frmMain.Hide frmFinal.Show End If If Optno.Value = True Then ‘Frame4.Visible = True datsource = False frmMain.Hide frmFinal.Show End If ‘lblyear = year(2) End If ‘End If End Sub Private Sub SaveValue(ByVal i As Integer) Dim box As Integer capital(i) = ppinput(0) feedstock(i) = ppinput(1) energy(i) = ppinput(2) material(i) = ppinput(3) labour(i) = ppinput(4) output(i) = ppinput(5) ‘clear textbox For box = 0 To 5 ppinput(box) = ‘‘’’ Next End Sub Private Sub-Form_Load() stage = 1 controlButton Frame2.Visible = False Frame3.Visible = False End Sub Function Validate() As Boolean Validate = True If ppinput(0) = ‘‘’’ Then Validate = False If ppinput(1) = ‘‘’’ Then Validate = False If ppinput(2) = ‘‘’’ Then Validate = False If ppinput(3) = ‘‘’’ Then Validate = False If ppinput(4) = ‘‘’’ Then Validate = False End Function ***************** Final Code ************************************* Dim alphaCoef As Variant ‘Alpha variables Dim no_item As Integer

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

1165

Dim no_prob As Integer Dim t_value() As Integer Dim col_item() As Integer Dim xmean() As Double Dim sd() As Double Dim variance() As Double Dim var_t As Double Dim var_i As Double Dim xpos, ypos As Integer Dim x As Integer Private Sub CmdAuth_Click() frmAbout.Show 1 End Sub Private Sub cmdCR_Click() PicAlpha.Visible = True Picfinal.Visible = False PicReport.Visible = False End Sub Private Sub CmdExcel_Click() On Error Resume Next Dim i, y, m, celpos Dim ctot(1 To 4) Dim objExcl As Excel.Application Set objExcl = New Excel.Application objExcl.Visible = True objExcl.SheetsInNewWorkbook = 1 objExcl.Workbooks.Add objExcl.ActiveSheet.Cells(1, 2).Value = ‘‘PARTIAL PRODUCTIVITY’’ objExcl.ActiveSheet.Cells(3, 2).Value = ‘‘YEAR’’ objExcl.ActiveSheet.Cells(3, 3).Value = ‘‘CAPITAL’’ objExcl.ActiveSheet.Cells(3, 4).Value = ‘‘FEEDSTOCK’’ objExcl.ActiveSheet.Cells(3, 5).Value = ‘‘ENERGY’’ objExcl.ActiveSheet.Cells(3, 6).Value = ‘‘MATERIAL’’ objExcl.ActiveSheet.Cells(3, 7).Value = ‘‘LABOUR’’ Dim J, q As Integer q=0 For J = 4 To 6 objExcl.ActiveSheet.Cells(J, 2).Value = year(q) objExcl.ActiveSheet.Cells(J, 3).Value = ppcapital(q) objExcl.ActiveSheet.Cells(J, 4).Value = ppfeedstock(q) objExcl.ActiveSheet.Cells(J, 5).Value = ppenergy(q) objExcl.ActiveSheet.Cells(J, 6).Value = ppmaterial(q) objExcl.ActiveSheet.Cells(J, 7).Value = pplabour(q) q=q+1 Next objExcl.ActiveSheet.Cells(8, 2).Value = ‘‘Total-Productivity Measurement (TPM); Total-Productivity Index ( TPI ) and Alpha ( IX )’’

1166

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

objExcl.ActiveSheet.Cells(10, 2).Value = ‘‘YEAR’’ objExcl.ActiveSheet.Cells(10, 3).Value = ‘‘TPM’’ objExcl.ActiveSheet.Cells(10, 4).Value = ‘‘TPI’’ objExcl.ActiveSheet.Cells(10, 5).Value = ‘‘TPM x ALPHA’’ objExcl.ActiveSheet.Cells(10, 6).Value = ‘‘TPI x ALPHA’’ q=0 For J = 11 To 13 objExcl.ActiveSheet.Cells(J, 2).Value = year(q) objExcl.ActiveSheet.Cells(J, 3).Value = Round(tpm(q), 7) objExcl.ActiveSheet.Cells(J, 4).Value = Round(tpi(q), 2) objExcl.ActiveSheet.Cells(J, 5).Value = Round(alphatpm(q), 7) objExcl.ActiveSheet.Cells(J, 6).Value = Round(alphatpi(q), 2) q=q+1 Next If datsource = False Then objExcl.ActiveSheet.Cells(15, 2).Value = ‘‘CRONBACH ALPHA COEFFICIENT ANALYSIS’’ objExcl.ActiveSheet.Cells(17, 2).Value = ‘‘X(i)’’ For i = 1 To no_item objExcl.ActiveSheet.Cells(17, 2 + i).Value = ‘‘X’’ & i Next objExcl.ActiveSheet.Cells(17, no_item + 3).Value = ‘‘TOTAL’’ objExcl.ActiveSheet.Cells(17, no_item + 4).Value = ‘‘MEAN’’ objExcl.ActiveSheet.Cells(17, no_item + 5).Value = ‘‘S.D’’ objExcl.ActiveSheet.Cells(17, no_item + 6).Value = ‘‘VARIANCE’’ celpos = 17 For m = 0 To x  1 y=m+1 celpos = celpos + 1 objExcl.ActiveSheet.Cells(celpos, 2).Value = y For i = 1 To no_item objExcl.ActiveSheet.Cells(celpos, 2 + i).Value = col_item(i, y) Next objExcl.ActiveSheet.Cells(celpos, no_item + 3).Value = t_value(m) objExcl.ActiveSheet.Cells(celpos, no_item + 4).Value = xmean(m) objExcl.ActiveSheet.Cells(celpos, no_item + 5).Value = sd(m) objExcl.ActiveSheet.Cells(celpos, no_item + 6).Value = variance(m) Next End If objExcl.ActiveSheet.Cells(celpos + 1, no_item + 5).Value = var_t objExcl.ActiveSheet.Cells(celpos + 1, no_item + 6).Value = var_i celpos = celpos + 2 objExcl.ActiveSheet.Cells(celpos, 2).Value = ‘‘PRODUCTIVITY PROBLEMS (PROBLEMS DESCRIPTION) REPORT’’ celpos = celpos + 2 objExcl.ActiveSheet.Cells(celpos, 2).Value = ‘‘PROBLEM NO’’ objExcl.ActiveSheet.Cells(celpos, 3).Value = ‘‘MEAN’’

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

objExcl.ActiveSheet.Cells(celpos, 4).Value = ‘‘PRODUCTIVITY (PROBLEMS DESCRIPTION)’’ For m = 0 To x  1 If CDbl(xmean(i)) < 10 Then celpos = celpos + 1 objExcl.ActiveSheet.Cells(celpos, 2).Value = m + 1 objExcl.ActiveSheet.Cells(celpos, 3).Value = xmean(m) objExcl.ActiveSheet.Cells(celpos, 4).Value = Rep(m + 1) End If Next End Sub Private Sub cmdFR_Click() PicAlpha.Visible = False PicReport.Visible = False Picfinal.Visible = True End Sub Private Sub cmdOk_Click() If txtsampling.Enabled = True Then x = CInt(txtsampling.Text) no_item = CInt(txtitem.Text) no_prob = CInt(txtsampling.Text) ReDim t_value(x) As Integer ReDim col_item(no_item, x) As Integer ReDim xmean(x) As Double ReDim sd(x) As Double ReDim variance(x) As Double MSHFlexGrid2.Rows = x + 3 MSHFlexGrid2.Cols = no_item + 5 GetAlpha txtsampling.Enabled = False xpos = 0 ypos = 1 End If If ypos > no_item Then Exit Sub col_item(ypos, xpos + 1) = CInt(txtvalue.Text) MSHFlexGrid2.row = xpos + 2 MSHFlexGrid2.Col = 0 MSHFlexGrid2.Text = xpos + 1 MSHFlexGrid2.Col = ypos MSHFlexGrid2.Text = col_item(ypos, xpos + 1) MsgBox ypos & ‘‘ ’’ & xpos + 1 ypos = ypos + 1 txtvalue.Text = ‘‘’’ txtvalue.SetFocus ‘ If ypos > no_item Then DoProcess (xpos)

1167

PROBLEMS

1168

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

ypos = 1 xpos = xpos + 1 End If If xpos > (x  1) Then MSHFlexGrid2.row = xpos + 2 MSHFlexGrid2.Col = no_item + 3 MSHFlexGrid2.Text = var_t MSHFlexGrid2.Col = no_item + 4 MSHFlexGrid2.Text = var_i GetCronAlpha txtvalue.Enabled = False cmdOk.Enabled = False Exit Sub End If End Sub Private Sub DoProcess(ByVal xpos As Integer) Dim i, y As Integer ‘******************* Cal total value/Mean************************************* y = xpos + 1 For i = 1 To no_item t_value(xpos) = t_value(xpos) + col_item(i, y) Next ‘t_value(xpos) = CInt(txtvalue.Text) xmean(xpos) = Round(t_value(xpos) / no_item, 2) ‘***************************************************************************** ‘ ******************Get Variance******************************************* For i = 1 To no_item variance(xpos) = variance(xpos) + ((col_item(i, y)  xmean(xpos))ˆ2) Next variance(xpos) = Round(variance(xpos) / no_item, 4) ‘************************************************************************** ‘***********************Get Standard Deviation***************************** sd(xpos) = Round(Sqr(variance(xpos)), 4) ‘************************************************************************** MSHFlexGrid2.row = xpos + 2 ‘ For j = 1 To 5 MSHFlexGrid2.Col = no_item + 1 MSHFlexGrid2.Text = t_value(xpos) MSHFlexGrid2.Col = no_item + 2 MSHFlexGrid2.Text = xmean(xpos) MSHFlexGrid2.Col = no_item + 3 MSHFlexGrid2.Text = sd(xpos) MSHFlexGrid2.Col = no_item + 4 MSHFlexGrid2.Text = variance(xpos) ‘ ‘ Next ‘***********************Summation of var./sd*******************************

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

1169

var_t = var_t + sd(xpos) var_i = var_i + variance(xpos) ‘************************************************************************** End Sub Private Sub GetCronAlpha() alphaCoef = Round((no_item/(no_item  1))*(1  (var_t/var_i)), 4) Label11.Caption = ‘‘ CRONBACH ALPHA = ’’ & alphaCoef GetResult PicAlpha.Visible = False End Sub Private Sub cmdReport_Click() loadReport End Sub Private Sub Form_KeyPress(KeyAscii As Integer) If KeyAscii = 13 Then cmdOk_Click End Sub Private Sub Form_Load() ‘datsource = False If datsource = True Then alphaCoef = 0.99 cmdCR.Enabled = False cmdReport.Enabled = False GetResult Else PicAlpha.Visible = True PicReport.Visible = False Picfinal.Visible = True End If End Sub Private Sub loadpp() ‘Load partial productivity. Dim i, J, q As Integer q=0 For i = 2 To 4 For J = 1 To 6 MSHFlexGrid.row = i MSHFlexGrid.Col = J Select Case J Case 1: MSHFlexGrid.Text = year(q) Case 2: MSHFlexGrid.Text = ppcapital(q) Case 3: MSHFlexGrid.Text = ppfeedstock(q) Case 4: MSHFlexGrid.Text = ppenergy(q) Case 5: MSHFlexGrid.Text = ppmaterial(q) Case 6: MSHFlexGrid.Text = pplabour(q) End Select Next q=q+1

1170

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

Next End Sub Private Sub pp() ‘Cal partial productivity. Dim i As Integer For i = 0 To 2 ppcapital(i) = Round(output(i) / capital(i), 2) ppfeedstock(i) = Round(output(i) / feedstock(i), 2) ppenergy(i) = Round(output(i) / energy(i), 2) ppmaterial(i) = Round(output(i) / material(i), 2) pplabour(i) = Round(output(i) / labour(i), 2) Next End Sub Private Sub tp_final() ‘Cal partial productivity. Dim i, J, q As Integer Dim ans As Variant For i = 0 To 2 tpm(i) = CDbl(output(i))/(CDbl(capital(i)) + CDbl(feedstock(i)) + CDbl(energy(i)) + CDbl(material (i)) + CDbl(labour(i))) tpi(i) = (tpm(i) * 100) / tpm(0) alphatpm(i) = alphaCoef * tpm(i) alphatpi(i) = alphaCoef * tpi(i) Next ‘Load tp_final q=0 For i = 2 To 4 For J = 1 To 5 MSHFlexGrid1.row = i MSHFlexGrid1.Col = J Select Case J Case 1: MSHFlexGrid1.Text = year(q) Case 2: MSHFlexGrid1.Text = Round(tpm(q), 7) Case 3: MSHFlexGrid1.Text = Round(tpi(q), 2) Case 4: MSHFlexGrid1.Text = Round(alphatpm(q), 7) Case 5: MSHFlexGrid1.Text = Round(alphatpi(q), 2) End Select Next q=q+1 Next End Sub Private Sub GetResult() Picfinal.Visible = True PicReport.Visible = False PicAlpha.Visible = False MSHFlexGrid.ColHeaderCaption(0, 1) = ‘‘YEAR’’ MSHFlexGrid.ColHeaderCaption(0, 2) = ‘‘CAPITAL’’

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

MSHFlexGrid.ColWidth(2, 0) = 2000 MSHFlexGrid.ColHeaderCaption(0, 3) = ‘‘FEEDSTOCK’’ MSHFlexGrid.ColWidth(3, 0) = 2000 MSHFlexGrid.ColHeaderCaption(0, 4) = ‘‘ENERGY’’ MSHFlexGrid.ColWidth(4, 0) = 2000 MSHFlexGrid.ColHeaderCaption(0, 5) = ‘‘MATERIAL’’ MSHFlexGrid.ColWidth(5, 0) = 2000 MSHFlexGrid.ColHeaderCaption(0, 6) = ‘‘LABOUR’’ MSHFlexGrid.ColWidth(6, 0) = 2000 ‘2 MSHFlexGrid1.ColHeaderCaption(0, 1) = ‘‘YEAR’’ MSHFlexGrid1.ColHeaderCaption(0, 2) = ‘‘TPM’’ MSHFlexGrid1.ColWidth(2, 0) = 2000 MSHFlexGrid1.ColHeaderCaption(0, 3) = ‘‘TPI’’ MSHFlexGrid1.ColWidth(3, 0) = 2000 MSHFlexGrid1.ColHeaderCaption(0, 4) = ‘‘Alpha x TPM’’ MSHFlexGrid1.ColWidth(4, 0) = 2000 MSHFlexGrid1.ColHeaderCaption(0, 5) = ‘‘Alpha x TPI’’ MSHFlexGrid1.ColWidth(5, 0) = 2000 pp loadpp tp_final Label11.Caption = ‘‘ CRONBACH ALPHA = ’’ & alphaCoef End Sub Private Sub GetAlpha() Dim i As Integer MSHFlexGrid2.ColHeaderCaption(0, 0) = ‘‘X(i)’’ For i = 1 To no_item MSHFlexGrid2.ColHeaderCaption(0, i) = ‘‘X’’ & i MSHFlexGrid2.ColWidth(i, 0) = 500 Next ‘MSHFlexGrid2.ColWidth(1, 0) = 500 MSHFlexGrid2.ColHeaderCaption(0, no_item + 1) = ‘‘TOTAL’’ ‘MSHFlexGrid2.ColWidth(2, 0) = 1500 MSHFlexGrid2.ColHeaderCaption(0, no_item + 2) = ‘‘MEAN’’ MSHFlexGrid2.ColWidth(no_item + 2, 0) = 1350 MSHFlexGrid2.ColHeaderCaption(0, no_item + 3) = ‘‘S.D’’ MSHFlexGrid2.ColWidth(no_item + 3, 0) = 1500 MSHFlexGrid2.ColHeaderCaption(0, no_item + 4) = ‘‘VARIANCE’’ MSHFlexGrid2.ColWidth(no_item + 4, 0) = 1500 End Sub Private Sub loadReport() On Error Resume Next Dim i, J, row As Integer PicReport.Visible = True PicAlpha.Visible = False Picfinal.Visible = False

1171

1172

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

MSHFlexReport.ColHeaderCaption(0, 1) = ‘‘PROBLEM NO’’ MSHFlexReport.ColWidth(2, 0) = 1000 MSHFlexReport.ColHeaderCaption(0, 2) = ‘‘MEAN’’ MSHFlexReport.ColWidth(2, 0) = 2000 MSHFlexReport.ColHeaderCaption(0, 3) = ‘‘PRODUCTIVITY PROBLEMS (PROBLEMS DESCRIPTION)’’ MSHFlexReport.ColWidth(3, 0) = 8000 MSHFlexReport.Rows = x + 2 J=x1 row = 2 For i = 0 To J If CDbl(xmean(i)) < 10 Then ‘MsgBox xmean(i) & ‘‘ ’’ & Rep(i + 1) MSHFlexReport.row = row MSHFlexReport.Col = 1 MSHFlexReport.Text = i + 1 MSHFlexReport.Col = 2 MSHFlexReport.Text = xmean(i) MSHFlexReport.Col = 3 MSHFlexReport.Text = Rep(i + 1) row = row + 1 End If Next End Sub ***************** End Final Code ************************************* References [1] Obiajulu U. Solving productivity problems using reliability analysis, RSUST, Nigeria M.Tech. thesis unpublished; 2002. [2] Okechukwu TM. Productivity-improvement techniques in non-factory situations. Management in Nigeria. Heineman; 1983. Educational books. p. 43–50. [3] American Management Association. Report 40; 2000. p. 1–5. [4] American conference on productivity (1946) in Washington, DC, USA, Communique´ released under American economic review (March 1947) vol. 37, No. 1. p. 1–3. [5] Colo B. Artemis solves top-10 project-management problems. NL: Business Wire; 2001. p. 1–2. [6] Adel Aladwani. Reliability of information services project performance in Kuwait. J Global Inform Manage 2001;8:50. [7] Besser T, Miller M. Is the good corporation dead? The community social responsibility of small businessoperators. J Eng 2001;11(2):1–2. [8] Neumark D, Capelli P. Does high-performance work practice improve established level outcomes? Ind Labour Relat Rev 2001;54(4):737–75. [9] Haller E. Manager’s handbook, vol. 1. Cambridge: Cambridge University Press; 2000. [10] Richard W. How to contribute to the bottom line? Emerson Process Management Company, profile, 2004. . [11] Kerridge AE. It takes experience to be a construction contractor. Hydrocarbon Processing PP1-3; 2000. . [12] Eti M, Jombo PP, Yousuo NA. Productivity analysis: a case study of the Nigerian petrochemical industry. J Eng 2001;11(2):1–2. [13] Lilly MT, Obiajulu U. Computer software for productivity analysis. J African Contemp Res 2005;1:101–11.

M.T. Lilly et al. / Applied Energy 84 (2007) 1150–1173

1173

[14] Bigelow D, West J. Putting the right PM on the right job. What competency assessment is all about. In: Proceedings of the Project-Management Institute Global Congress North America, Baltimore, September 18–25, 2003, Maryland, USA; 2003. [15] PMBOK Guide, A guide to the project management body of knowledge, Project Management Institute PMI, USA; 2003. [16] SPC project plan templates and checklist – project planning solutions, Software Productivity Center Inc USA, 2004 ed. [17] SPR KnowledgePLAN Profile, – project estimation practice, Software Productivity Research Centre, USA 2004 edition. [18] Cronbach LJ. Coefficient alpha and the internal structure of test. Psychometrika 1951;16:297–333. [19] Kathy D, Nancy M, Wood-Dauline S. Reliability of scores for stroke-rehabilitation assessment of movement measures ICHHC; 1999. p. 1–10. . [20] One World Xe user guide 1996–2002 model, J.D. Edward World Source Company, USA. [21] Lockout: The self-imposed, computer-aided work enforcer guide: also . [22] Checklist Productivity software (2005), Task management and productivity software profile. [23] Web site 5.8 timesheet user guide (2005 ed.). [24] Checklist 4th Software, Pforth task management-profile. A handbook that followed the machine. [25] Pace Productivity, Tabulator time-profile creator user-handbook. A manual that accompanies the timing tool. [26] Win Planet Stock management software, personal stock monitor tool-guide. .

Glossary Average severity mean (XM): XMi is the average severity mean for the ith factor affecting the productivity of an organisation. When several researchers award different scores as to how a particular factor affects productivity, the average of the scores for that particular factor is called the average severity. If the severity score for a particular severity factor is X1 to XN for the N issued and returned questionnaires, then the severity mean for that particular factor is ðX 1 þ X 2 þ . . . ::X N Þ=N : Partial productivity: This concept, for an input resource, is the effect on total productivity of the resource, all other factors remaining invariant.The most commonly-used partial-productivity ratios (i.e., those published by the Bureau of Labour Statistics in the USA) are output per employee (or input) per employee-hour.Where labour, feedstock, energy and materials are the input resources, the individual partial productivities can be OUTPUT OUTPUT OUTPUT OUTPUT represented by the following ratios:-LABOUREMPLOYED ; CAPITAL ; FEEDSTOCK ; ENERGY EMPLOYED CONSUMED OUTPUT and MATERIAL : CONSUMED Total productivity (TP): This is the integrated effect, over a stipulated period, of all the inputs upon the achieved Output output.The total productivity (TP) can be represented as follows: TP ¼ LabourþCapitalþ FeedstockþEnergyþMaterial , where the values of all the factors are measured in the same financial unit.In carrying out a total-productivity analysis for an organisation, it is often beneficial to analyse the present productivity relative to those that occurred in the past, so that you can detect when any change in behaviour started.Then you are better able to identify the factor that varied and so led to a decline or an improvement in performance. Present TPM100 Total productivity index: TPI ¼ Base The Present TPM is the total productivity now. The base period period TPM TPM usually means the total productivity for the first year of the period under consideration. The AD 2004 productivity may be the base period, but one has to check the values of TPs for at least AD 2005 and 2006 for any trend to become apparent. This will enable the production engineer to study the production processes and the way input resources were utilised during the period in order to make remedial recommendations to the managers.