CRITICAL FACTORS AFFECTING PERFORMANCE OF CUSTOMER SERVICE STAFF – THE CASE OF VP BANK VIETNAM

CRITICAL FACTORS AFFECTING PERFORMANCE OF CUSTOMER SERVICE STAFF – THE CASE OF VP BANK VIETNAM

Pham Thu Huong
Tran Thi Lien

Abstract:
Internationalization in society and economy has raised promptly the competition in many sectors of economy including banking. This study develops the model to access main factors affecting performance of customer service staff. The main factors include job motivation, leadership, organizational structure, organizational culture, training, technology.
The investigation on data collected from 224 customer service staffs of VPBank shows that job motivation, organizational culture, training, technology have positive relationship with the performance of customer service staffs meanwhile there is not enough evidence to prove the impact of leadership and organizational structure. The results are appropriate to the previous researches and characteristics of customer service staff (front-line staffs).
The paper propose some suggestion aiming to improvement of performance of customer service staffs in banking including creating job motivation, good working environment, appropriate training programs and advance technologies.
Key words: bank, performance, customer service staff
Date of receipt: 5th Sep.2017; Date of revision: 25th Sep.2017; Date of approval: 25th Sep.2017

1. Introduction
Banking, considered as mirror of economic growth, can contribute to economic development in at least two ways: directly, by increasing balance sheet items, and indirectly, through financing. In the global economy, the growing importance of banks is obvious, given that in a context of accelerating the development of information systems and communications (Imola Drigă, 2013).
Banking system in Viet Nam is restructured by many reforms, including opening to foreign investment, privatization…to strengthen the capitalization of Vietnamese banks. There are currently 43 commercial banks operating in Vietnam with collective assets of approximately $330 billion. The Vietnamese banking industry comprises a diverse mix of players, ranging from relatively large state-owed commercial banks down to very small privately held banks. The total collective capital of all commercial banks in Viet Nam is approximately $26 billion.
Recently, many banks in Viet Nam, especially larger joint stock banks, have started to increase their focus on with a diversified product mix being offered to the market via various channels, including mobile banking and internet banking. A number of large banks have been focusing more on enhancement the quality of their customer service, risk management, technology and talent development. By doing that, Vietnamese banks are arming to properly tap into the market opportunities and firmly establish a stronger position against more aggressive competition coming from the region in the future (Hoang, 2016).
In order to control the quality of customer service, the banks apply non-finance indicators, KPIs (Key Performance Indicators), to assess the performance of front line staffs, the first touch point to customer. This bring about many challenges and pressures to customer service staffs due to higher requirements of knowledge, skills, speed, accuracy, service attitude and plenty of other requests from both customers and managers. They not only need to provide the best service quality to customers, but they also guarantee the risk control and legal compliance in all transactions at Counters. Therefore, understanding the critical factors affecting performance of customer service staffs is sufficiently necessary in order to build up appropriate training and treatment policies which help creating the amicable and flexible working environment and thus improving the performance of each employee as well.
Vietnam Prosperity Joint-Stock Commercial Bank (formerly known as Vietnam Joint-Stock Commercial Bank for Private Enterprises) was established on August 12th 1993. In 24 years of operations, VP Bank has increased its charter capital to VND10,765 billion, expanded the number of transaction points to over 215, and grown its workforce to more than 18,000 employees. The goals of VP Bank are becoming one of the 5 leading joint-stock commercial banks and of the 3 leading retail joint-stock commercial banks in Vietnam by 2017.
In this paper, the framework to explore the critical factors affecting the performance of customer service staffs is built up and a practical investigation based on that is carried out with the sample of 224 customer service staffs of VP Bank.
2. Literature Review
2.1. Performance management
Performance management is “a continuous process of identifying, measuring and developing performance in organizations by linking each individual’s performance and objectives to organization’s overall mission and goals” (Aguinis, 2009). It is a mean of getting better results of organizations, teams and individuals by understanding and managing performance within agreed framework of goals, standards and competence requirements (Armstrong, 2006). The effective performance management can create the strong motivation for each employee not only to devote their best effort for organization, but also to improve their own skills and knowledge. Its key purpose is to focus people doing the right things by achieving goal clarity.(Armstrong, 2006).
Boyatzi (1982) had set up “the job performance model: the competent manager” in which the effective performance occurs when all three of the critical components of the model are consistent, or “fit”. If any one or two of these components are inconsistent and do not correspond with each other, then it is expected that ineffective behavior or inaction will result.
The study of F. A. K. Raja Abdul Ghafoor Khan & Muhammad Aslam Khan (2011) showed that employees are the key elements of the firms and their success and failure based on their performance, if there is a proper planning for making the training procedures, then it will be fruitful for both employees and organization.
2.2. Factors affecting performance of employees
2.2.1. Job motivation
Motivation is an important function to encourage the talent workers performing better and doing extra for organization, is one of the most that organizations need to focus on in order to gain success and competitive advantage (Al-Rfou & Trawneh, 2009). Bartol & Martin (1998) considers that motivation is an internal drive to satisfy the unsatisfied need and to achieve the certain goals. It is also a procedure that begins through physiological or psychological need that stimulates performance set by an objective. Getting the employees to reach the full potential at work under stressful conditions is a tough challenge, but this can be achieved by motivating them (Dobre, 2013). According to (Lindner, 1998), job motivation are influenced by some main following factors including job security, supportive inspiration, employee loyalty, interesting work, good wages, promotions and growth, recognition.
2.2.2. Leadership
Leadership is a process by which a person influences others to accomplish an objective and directs the organization in a way that make it more cohesive and coherent (Jain, 2013). Schein (2010) mentioned that Leadership as a distributed function is gaining ground which lead to the possibility that anyone facilitates progress toward some desired outcomes is displaying leadership. Leadership is involved with the construction of a public self, which includes a public face. The exposure of that face to a group of people is a form on an exhibition. This public exhibition moves into performance when it is employed as a mean to persuade others of the value of the belief and/or directed toward some kind of goal (English, 2007). Leadership impacts on employees’ performance through coaching, empowerment, feedback which make people recognize their potential (Whitmore, 2010), involved in broader set of duties (Parker, 1998), less ineffective behaviours.
2.2.3. Organizational culture
The organizational culture forms a significant determinant of human behavior of organization. Its connects the objective aspect of organization, such as, technology, leadership, etc. with the motivation and trusting/distrusting, stressful or highly stressful (Dwivedi, 1995). Culture is the social glue that helps hold the organization together by providing appropriate standards for what employees should say and do. Thus, culture serves as a sense-making and control mechanism that guides and shapes the attitudes and behavior of organization members.
2.2.4. Organizational structure
Organizational structure can be defined as the arrangement and interrelationship of the component parts and positions of a company. An organization’s structure means the pattern or network of relationship between the various positions and the position holders. An organization’s structure specified its divisions and work activities and show how different functions or activities are linked. To some extend, it also shows the level of specialization. It also indicates the organization hierarchy and authority’s structure and shows the report relationship. Flexible organizational structure might result in better performance of employees. (Dwivedi, 1995)
2.2.5. Training
Training has distinct role in achievement of organizational goals. Training is the important factor in the business world because training increases the efficiency and effectiveness of both employees and organization (F. A. K. Raja Abdul Ghafoor Khan & Muhammad Aslam Khan, 2011). Effective training and development programs aim to improve the employee’s performance. Training prefers to bridge the gap between the current performance and the standard desired performance. Training could be given through different methods such as on the coaching and mentoring, peer cooperation and participation by the subordinates. This teamwork enable employees to actively participate on the job and produces better performance, hence improving organizational performance (Elnaga & Imran, 2013).
Training not only develops capabilities of employee but sharpen their thinking ability and creativity in order to take better decision in time and in more productive manner. Moreover, it also enables employees to deal with the customers in an effective way and respond to customer’s complaints timely (Hollenbeck & Hall, 2004).
2.2.6. Technology
Service managers also must recognize that the decision to adopt technology is often driven by the need not only to increase the productivity but also to improve existing performance of their organization. Often, however, with the proper technology, both performance and productivity can be improved, creating a win-win situation for the firm. Muhammad Imran (2014) figured out that the technological advancement has significant impact on employee performance.
3. Methodology
3.1. Conceptual Framework
Based on the previous study and the characteristics of front-line jobs in banking, the study develops the framework that conceptualizes the critical factors affecting the performance of customer service staffs as the following figure:

Figure 1: Conceptual Model
As mentioned above, the performance of employees is proposed to be dependent on 6 factors including job motivation, leadership, organizational culture, organizational structure, training, technology. The hypotheses are given as follows:
H1: The job motivation has positive impact to the effective employee performance
H2: The leadership has positive impact to the effective employee performance
H3: The organizational culture has positive impact to the effective employee performance.
H4: The organizational structure has positive impact to the effective employee performance.
H5: The training has positive impact to the effective employee performance.
H6: The technology has positive impact to effective employee performance.
3.2. Compiling the questionnaire and sampling selection
To carry out the measurements of the impact of factors on employees’ performance, this study develop a data collection questionnaire based on the above literature review and conceptual model. Questionnaire is presented in Vietnamese and composed of following sections:
Section 1: Job Motivation: From Question 1 to Question 7
Section 2: Leadership: From Question 8 to Question 11
Section 3: Organizational culture: Question 12 to Question 13
Section 4: Organizational structure: Question 14 to Question 15
Section 5: Training: Question 16 to Question 18
Section 6: Technology: Question 19 to Question 21
5- points Likert scale are used, in detail of agreement level: 1- Totally disagree; 2- Disagree; 3 – Normal/Neutral; 4 – Agree; 5 – Totally agree. This Likert also is used most popularly in many researches because the surveyors can get the ideas of researchers more quickly and accurately to answer.
The measures of performance are KPIs which including 5 indicators which are productivity, quality, SLA score, mistake, knowledge and skills.
The questionnaire then was delivered to pilot sample of 10 surveyors to examine the understanding about the questions. The questions are evaluated clear contents to give out the answers. In order to investigate the impacts of factors, this research aimed at 224 customer service staffs from 5 regions.
4. Findings
4.1. Characteristics of respondents
The Table 4.1 shows that almost respondents are female with 98.3 %. This also is typical characteristic of customer service staffs in banking because the frontline serves customers at branch counters daily. The first priority of customer service staffs is to provide the best service quality for customer, so this job is the more suitable to female.
The working experience in VPBank and respondent’s age has strong correlation: 66.53 % surveyed people have more than 05 experience years in VPBank. They go through the period of the biggest transform of VPBank, so their answers reflect the exact current stage of employee performance an their expectation as well.
Both customer service staffs and customer service managers are under half-yearly performance evaluation; therefore, they understand clearly all the factors impact to their performance. 45.08 % and 46.89 % are respondent rate for CSR and CSM respectively.
Table 1: Description of sample
Criteria No of response % of response
Gender
Male 4 1.8 %
Female 217 98.2 %
Total 221 100 %
Age
<= 30 70 31.67 %
>30 - <= 40 131 59.29 %
>40 - <= 50 18 8.14 %
>50 2 0.9 %
Total 221 100 %
Work experience
<= 1 year 14 6.33 %
>1 - <= 3 years 29 13.12 %
>3 - <= 5 years 29 13.12 %
>5 years 149 66.43 %
Total 221 100 %
Job title
CSR 98 44.34 %
Controller 18 8.14 %
CSM 105 47.52 %
Total 221 100 %

4.2. Exploratory Factor Analysis
Factors analysis assumes that the observed variables are linear combinations of some underlying (hypothetical or unobservable) factors. Some of these factors are assumed to be common to two or more variables and some are assumed to be unique to each variable. The unique factors are the assumed to be orthogonal to each other. Hence, the unique factors do not contribute to the covariation between variables. The linear systems in factor analysis are such that the user can identify the resulting convariance structure without error if the underlying factor loadings are known. Exploratory Factor Analysis (EFA) was used to select the proper variables for framework testing. Firstly, the KMO (Kaiser-Meyer-Olkin) testing is used to tell one whether or not enough items are predicted by each factor. The KMO measure should be greater tha 0.7 and is inadequate if less than 0.5.
In order to determine the number of variables which is the best to explain framework, the total variance explained for independent variables have been run for 3 times and the result of the third are presented in Table
Table 2: KMO and Bartlett's Test for independent variables (the 3rd time)
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .896
Bartlett's Test of Sphericity Approx. Chi-Square 2920.068
df 253
Sig. .000

The KMO results (0.896) an the Bartlett’s Test (0.000) are good for model testing
Table 3: Total Variance Explained for independent variables (the 3rd time)

Component Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %
1 9.291 40.395 40.395 9.291 40.395 40.395 4.206 18.287 18.287
2 2.639 11.474 51.868 2.639 11.474 51.868 3.314 14.408 32.695
3 1.400 6.089 57.957 1.400 6.089 57.957 3.171 13.787 46.482
4 1.236 5.373 63.330 1.236 5.373 63.330 2.875 12.501 58.984
5 1.094 4.758 68.088 1.094 4.758 68.088 2.094 9.104 68.088
6 .907 3.941 72.029
7 .829 3.603 75.632
8 .714 3.104 78.736
9 .596 2.591 81.327
10 .568 2.468 83.794
11 .484 2.104 85.898
12 .419 1.824 87.722
13 .398 1.732 89.454
14 .377 1.638 91.092
15 .344 1.497 92.589
16 .314 1.365 93.954
17 .260 1.131 95.085
18 .230 .999 96.084
19 .212 .923 97.007
20 .200 .868 97.875
21 .176 .763 98.638
22 .163 .710 99.348
23 .150 .652 100.000

Extraction Method: Principal Component Analysis.
Table 4: Rotated Component Matrix(a) for independent variables (The 3rd time)
Component
1 2 3 4 5
Mov2 -.097 .159 .527 .441 .217
Mov3 .028 .197 .598 .380 .046
Mov5 .075 .015 .093 .846 .139
Mov6 .204 -.030 .135 .861 .098
Mov7 .138 .042 .129 .885 .108
Led2 .403 .185 .693 .094 .181
Led3 .363 .198 .713 .112 .231
Led4 .402 .134 .711 .026 .230
Cul1 .586 .251 .483 .045 .104
Cul2 .537 .297 .437 .161 -.036
Cul3 .592 .142 .323 .294 .189
Cul4 .661 .134 .161 .074 .301
Struct1 .672 .314 .286 .059 -.098
Struct2 .739 .145 .247 .049 .050
Struct3 .705 .334 -.035 .141 .120
Train1 .266 .772 .192 -.012 .130
Train2 .212 .853 .164 -.018 .015
Train3 .252 .771 .160 .074 .284
Train4 .354 .700 .287 .074 .155
Tech1 .082 .008 .256 .294 .739
Tech2 .384 .343 .190 .111 .514
Tech3 .126 .252 .156 .101 .806
Tech4 .535 .382 -.054 .098 .345

Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a Rotation converged in 8 iterations.
The Table 4 presents that all the remaining variables after the 3rd testing are satisfied to run further analysis because the greatest values are greater than 0.5 and λs greater than 0.3.
The remaining independent variables belong to 05 groups as below:
Table 5: The group of independent variables after testing factor analysis

Group Code Content
Organizational Culture and Structure Cul1 The core values of organization can help achieve better employee performance
Cul2 The common norms of organization can help achieve better employees performance
Cul3 Employees in organization are happy in work to devote their best performance
Cul4 Managers in organizations focus on create good work environment for employees
Struct1 The centralization of management can help achieve better employees performance
Struct2 The changes of organizations can make the customer service officers to focus more their works
Struct3 The report lines help to resolve issues for customer service better
Tech4 Customer service officers have many effort and opportunities to raise initiatives to improve technology
Training Train1 The high quality of training contents can help customer service officers to deliver better performance
Train2 The regular frequency of training can help customer service officers to deliver better performance
Train3 The high qualified of trainers can help customer service officers to deliver better performance
Train4 The training in teamwork can help customer service officers to deliver better performance
Leadership Mov2 The supportiveness in organization make the stronger job motivation
Mov3 The employees loyalty make the stronger job motivation
Led2 Empowerment can help achieve better employee performance
Led3 Feedback of managers can help achieve better employee performance
Led4 Strategy and vision of Managers can help achieve better employee performance
Job Motivation Mov5 Good wages/ salaries make the stronger job motivation
Mov6 Promotion and growth opportunities in organization make the stronger job motivation
Mov7 Recognition make the stronger job motivation
Technology Tech1 The good technology can help customer service officers to deliver better performance
Tech2 Customer service officer is provided enough knowledge and skill to take advantages of technology
Tech3 Customer service officers is supported timely when technology have problems

4.3. Reliability Analysis
Cronbach’s alpha  of all measures are greater than 0.7 which is close to one and Corrected Item-Total Correlation is greater than 0.3, which means that all are reliable (Field, 2011).
Item-Total Statistics
Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted
Cronbach's Alpha = .882 for “Organizational Culture and Structure”
Cul1 27.75 10.727 .688 .865
Cul2 27.75 10.679 .656 .867
Cul3 27.68 10.459 .656 .867
Cul4 27.81 10.237 .631 .870
Struct1 27.87 9.780 .677 .865
Struct2 27.74 10.211 .691 .863
Struct3 27.89 10.386 .664 .866
Tech4 27.96 10.660 .556 .877
Cronbach's Alpha = .884 for “Training”
Train1 11.71 2.978 .717 .862
Train2 11.93 2.664 .743 .856
Train3 11.72 2.862 .780 .838
Train4 11.74 2.946 .759 .847
Cronbach's Alpha = .823 for “Leadership”
Mov2 16.61 4.182 .494 .820
Mov3 16.74 3.933 .482 .829
Led2 16.89 3.502 .729 .753
Led3 16.84 3.701 .749 .752
Led4 16.88 3.673 .656 .775
Cronbach's Alpha = .876 for “Job Motivation”
Mov5 9.12 1.221 .724 .866
Mov6 9.14 1.355 .772 .816
Mov7 9.12 1.319 .797 .794
Cronbach's Alpha = .777 for “Technology”
Tech1 8.09 1.352 .591 .723
Tech2 8.42 1.477 .544 .771
Tech3 8.28 1.153 .715 .579
Cronbach's Alpha = .817 for “Performance”
Per1 16.14 3.644 .551 .798
Per2 16.00 3.511 .614 .780
Per3 16.18 3.603 .604 .783
Per4 16.26 3.242 .647 .770
Per5 16.23 3.495 .627 .776

4.5. Regression analysis
Based on EFA, the framework had been adjusted as follows:
H1: The Organizational Culture and Structure has positive impact to effective employee performance
H2: The Training has positive impact to effective employee performance
H3: The Leadership has positive impact to effective employee performance
H4: The Job Motivation has positive impact to effective employee performance
H5: The Technology has positive impact to effective employee performance

Figure 2: The adjusted framework
Regression Analysis to have some following results:

Table 7: Model Summary(b) for Regression

Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics
R Square Change F Change df1 df2 Sig. F Change
1 .526(a) .277 .259 .33630 .277 15.177 5 198 .000
a Predictors: (Constant), TECH, MOV, TRAIN, LEAD, CULandSTRUCT
b Dependent Variable: PER
The Table 7 shows some main indicators of this model: The R value is 0.526 greater than 0.5 and R Square is 0.277 which means that the independent variables explain 27,7% the dependent variable. Moreover, the Sig F change is 0.000 < 0.05, so the variables in this model is significant difference to explain the framework.
Table 8: ANOVA(b) for Regression analysis

Model Sum of Squares df Mean Square F Sig.
1 Regression 8.582 5 1.716 15.177 .000(a)
Residual 22.394 198 .113
Total 30.976 203
a Predictors: (Constant), TECH, MOV, TRAIN, LEAD, CULandSTRUCT
b Dependent Variable: PER
The Table 8 show the Sig. value is 0.000 (a) < 0.05, it means the variables are significant difference to explain the dependent variable. Furthermore, this result also shows the collected data has meaning in homogeneous statistic and suitable with this research method.
Table 9: Coefficients(a) for Regression analysis
Model Unstandardized Coefficients Standardized Coefficients t Sig. 95% Confidence Interval for B
B Std. Error Beta Lower Bound Upper Bound
1 (Constant) 1.919 .263 7.307 .000 1.401 2.437
CULandSTRUCT .077 .080 .090 .966 .335 -.080 .234
TRAIN .186 .059 .265 3.172 .002 .071 .302
LEAD .055 .073 .067 .755 .451 -.089 .199
MOV .102 .049 .145 2.098 .037 .006 .198
TECH .102 .060 .132 1.684 .094 -.017 .221
a Dependent Variable: PER
The regression results show that there are enough evidence to conclude about the positive relationship between employee’s performance and job motivation, training (the value of t-test is significant at 95% confidence level respectively – .002, .037 < .05. The positive beta values means that there are positive relationship between dependent variable and independent variables.

5. Discussion and Conclusion
Regarding to our study aim, it was confirmed that the adjusted framework to explore critical factors affecting the performance of employees is appropriate. The investigation presents the positive relationship between performance of customer service staffs and job motivation, culture, training and technology. The results reflects the previous studies including Boyatzi (1982), F. A. K. Raja Abdul Ghafoor Khan & Muhammad Aslam Khan (2011), Muhammad Imran (2014), Hollenbeck & Hall (2004), Dwivedi (1995), Dobre (2013), Lindner (1998).
The relationships between leadership and organizational structure and performance of customer service employees are not significant in this study. It might be reason that the customer service staffs (front-line staffs) are those who do not feel directly being affected by leadership and organizational structure. Therefore, the data collected do not reflect these relationships. In VPBank situation, the processes and systems in counter service are stable through many years, thus the customer service staffs do not feel being affected by technology.
The results suggest that the bank should consider more about the job motivations including high security, supportiveness, salaries, promotion and regognition. Strategy and vision of manager, core values and common norms can help achieving better performance of customer service staffs’ performance. The bank should remain training frequently and emphasis on qualification of trainers as well as contents of training, which help customer service staffs delivering better performance.
The limitation of the study is that the framework had been investigated basing on data collected from customer service staffs of VPBank. This might be better if the framework are tested in the broader data community.

References
1. Aguinis, H. (2009). Performance management: Pearson Prentice Hall Upper Saddle River, NJ.
2. Al-Rfou, A., & Trawneh, K. (2009). Achieve Competitive Advantage through Job Motivation. J Soc Sci, 20(2), 105-107.
3. Armstrong, M., & Baron, A. (2000). Performance management. Human resource management, 69.
4. Bartol, K. M., & Martin, D. (1998). Management. Int. Edition: Irwin, New York. McGraw-Hill.
5. Dobre, O.-I. (2013). Employee Motivation and orgaizational performance.
6. Dwivedi, R. (1995). Organizational culture and performance: MD Publications Pvt. Ltd.
7. Elnaga, A., & Imran, A. (2013). The effect of training on employee performance. European Journal of Business and Management, 5(4), 137-147.
8. English, F. W. (2007). The art of educational leadership: Balancing performance and accountability: Sage
9. Field, A. (2011). Discovering Statistics Using SPSS. London SAGE Pulication Ltd.
10. Hoang, N. N. (2016). Putting Vietnam’s banks on the map. Vietnam Investment Review,, 1.
11. Hollenbeck, G. P., & Hall, D. T. (2004). Self-confidence and leader performance. Organizational dynamics, 33(3), 254-269.
12. Imola Drigă, C. D. (2013). The financial sector and the role of banks in economic development. Financial Stability Report, 1-6.
13. Jain, M. K. S. a. S. (2013). Leadership Management: Principles, Models and Theories. Global Journal of Management and Business Studies., 3, 309-318.
14. Lindner, J. R. (1998). Understanding employee motivation. Journal of extension, 36(3), 1-8.
15. Muhammad Imran (2014) Impact of Technological Advancement on Employee performance in banking sector, International Journal of Human Resource Studies, Vol. 4, No.1.
16. Parker, S. (1998). Role breadth self-efficacy: Relationship with work enrichment and other organizational practices. Journal of Applied Psychology, 83(6), 835-852.
17. Raja Abdul Ghafoor Khan, F. A. K., Dr. Muhammad Aslam Khan (July 2011). Impact of Training and Development on Organizational Performance. Global Journal of Management and Business Research, 11(7 Version 1.0).
18. Schein, E. H. (2010). Organizational culture and leadership (Vol. 2): John Wiley & Sons.
19. Whitmore, J. (2010). Coaching for performance: growing human potential and purpose: the principles and practice of coaching and leadership: Nicholas brealey publishing.