Performance of insurance firms has largely been influenced by operational factors. Insurance firms have

continually performed poorly in the Kenyan market since 1985. So far, there is still limited information as regards

this trend. The objective of the study was to establish the extent to which operational factors affect the

performance of insurance firms. The study adopted a descriptive census survey design. The study location was in

Nairobi and the population consisted of 40 registered insurance companies as at August 2010. Reliability of the

results was determined by the test-retest approach. Validity of the research instrument was established by using

two firms outside the target population. Data was analyzed using descriptive statistics and inferential statistics.

The hypothesis was tested using simple regression coefficient at 95% confidence level. The study revealed that

operational factors have no relationship with organizational performance

Mudaki, Abisay Lumosi

Ochieng, Isaac

Odera, Odhiambo

Wanjere, Dishon

English

University of Southern Queensland ePrints

International Journal of Business and Social Science                                                Vol. 3 No. 17; September 2012 237   Effects of Operational Factors on Organizational Performance in Kenyan Insurance Industry   Abisay Lumosi Mudaki  Department of Business Management Masinde Muliro University of Science and Technology Kakamega, Kenya.  Dishon Wanjere Department of Business Management Masinde Muliro University of Science and Technology Kakamega, Kenya.  Dr. Isaac Ochieng Department of Mathematics and Business Studies Egerton University, Kenya.  Odhiambo Odera  University of Southern Queensland, Australia and Masinde Muliro  University of Science and Technology, Kenya.     Abstract  Performance of insurance firms has largely been influenced by operational factors. Insurance firms have continually performed poorly in the Kenyan market since 1985. So far, there is still limited information as regards this trend.  The objective of the study was to establish the extent to which operational factors affect the performance of insurance firms. The study adopted a descriptive census survey design. The study location was in Nairobi and the population consisted of 40 registered insurance companies as at August 2010. Reliability of the results was determined by the test-retest approach. Validity of the research instrument was established by using two firms outside the target population. Data was analyzed using descriptive statistics and inferential statistics. The hypothesis was tested using simple regression coefficient at 95% confidence level. The study revealed that operational factors have no relationship with organizational performance.   Keywords:  Agents, claims and insurance  Background  Kenya’s insurance sector comprises of 41 registered companies, 200 brokers and 500 active agents. The supervision and regulation of this sector is the responsibility of Insurance Regulatory Authority (IRA). According to IRA a general insurance company must have a minimum capital of Kshs.300 million whereas a life insurance company must have a minimum capital base of Kshs.150 million (Turana, 2010). These regulations and laws contribute immensely to the growth of business and hence organizational performance. The lack of a supervisory body thirty years ago may have contributed to poor performance by the insurance industry. Some insurance firms may have been in insurance business without the required minimum capital base. On average, the experience has been that one insurance firm goes under or is placed under receivership after every four years since 1985.   The contribution of insurance at 2.63% of the Gross Domestic Product in Kenya is very low compared to other countries like South Africa which has a contribution of 9.94%. In Malaysia, it is estimated that 41% of the population have some form of life insurance in comparison to Kenya that has less than 1% of the population insured.   © Centre for Promoting Ideas, USA                                                                                                www.ijbssnet.com 238  A stable and vibrant insurance industry of any country among other things provides the population with peace of mind in performance of their daily economic activities and boosts investor confidence. It is from these investments that governments are able to generate revenues to finance their operations that may lead to alleviation of hunger, poverty, achieve universal primary education and generally raise the standard of living of its population. In the Kenyan market, insurance firms have continually performed poorly since 1985.   The operating factors include; claims, agents and brokers, infrastructure, customer needs, capital and finance, marketing and legislation. Claims and loss handling is the materialized utility of insurance; it is the actual product paid for. Vaughan and Vaughan (1995) state that it is important for the insurance company pay its claims fairly and promptly. It is equally important for the company to resist unjust claims and avoid overpayment of them. A fair claim service is one of the most effective competitive tools available to an insurance company. Vaughan and Vaughan (1995) note that in order to determine the ability of an insurance firm to settle a claim, the most critical information is contained in the solvency ratio which is equivalent to total assets of a company divided by total liabilities. The larger the ratio, the healthier an insurance company is financially.   The marketing and distribution channels of insurance in Kenya involve among others, agents and brokers. These are professionals trained in sales, marketing and finance and are engaged by insurance companies and agencies to sell these insurance products (Mudaki, 2011). In Kenya, almost all the premium income generated is through intermediaries like agents and brokers. This is in contrast to other countries that have a variety of distribution channels. The sales made by these professionals impact positively on the organizational performance. On the other hand, the delay by these groups in remitting proceeds from sales made to the parent insurance company impact negatively on the organizational performance. Feedbacks from these groups serve as a basis for innovation in product, business portfolio balance and formulation of organizational policies (Hayes, 2010). Agents and brokers are responsible for direct selling which in turn translates to income for the organization (Mudaki, 2011). The higher the sales, the higher the organizational performance especially when sales are used as a measure. According to Siciliano (1996), the impact of computers and information technology (IT) is being felt in every kind of organization in every industry. For example, information on the sales of an insurance product made per branch and in the entire firm is shared by all employees and therefore promotes understanding by all on the status of the firm. This implies that the agents and brokers have to travel far and wide in search of prospective buyers (Mudaki, 2011). The road network and technology have a direct impact on organizational performance.   Customers are actually the end users of the firms’ products and services (Ivancevich, 1999). An organization should aim at meeting customers’ needs for it to remain relevant (Mudaki, 2011). By tailoring its products to meet these needs, the sales will improve and hence the overall organizational performance. Insurance availability and affordability are both policy concerns, as evidenced by government’s many regulations of the insurance market. Legislation of any country creates an enabling environment and business opportunities for all entrepreneurs. For example, in Kenya it is a legal requirement for all motor vehicles to be insured (Insurance Act Chapter 405, 1989). This requirement has in itself created an opportunity for insurance companies to design suitable products to address this need.  Government licensing of insurance companies in Kenya is a major issue due to bureaucracy. For instance, a life insurance company requires a starting capital of Ksh.150 million to be given a license whereas a general insurance requires Ksh.300 million to acquire a license. These amounts of license fee are quite high and therefore discourage new investors in the insurance industry (Mudaki, 2011). Although there are laws in Kenya, the biggest challenge continues to be how to convince a struggling population that they need an insurance product for which they have no money, no education and certainly no trust at all.  All these issues affect the overall organizational performance and hence the industry as a whole.  Organizational performance as a variable is made up of dimensions as profitability, corporate image and number of products.  Bell et al. (1997) contend that high performance and commitment are possible outcomes in organizations that are designed for high involvement but may not occur if environmental conditions are unfavorable. Torrington et al. (2008) argue that the performance effects of human resource policies and practices are multiplicative rather than additive. In other words, a particular set of mutually reinforcing practices is likely to have more impact on performance than applying one or just some of these in isolation. Torrington et al. (2008) suggest that there is an assumption that before it is able to plan and manage individual performance, the organization will have made significant steps in identifying the performance required of the organization as a whole.  International Journal of Business and Social Science                                                Vol. 3 No. 17; September 2012 239  In most cases, this will involve a mission statement so that performance is seen within the context of an overriding theme. Organizational objectives are particularly important, as it is common for such objectives to be cascaded down the organization in order to ensure that individual objectives contribute to their achievement. Beardwell et al. (2004) observe that firms using a commitment model of human resource management saw a higher productivity, lower labour turnover and lower rates of rejected production. This may in turn lead to a good corporate image and concur with Bag (2008), that the ideal corporate image should be managed to become congruent. This implies that what the public see is what the organization is. The objective of the study was to establish the extent to which operational factors affect the performance of insurance firms in Kenya.   Methodology   The study covered all the registered and licensed insurance firms in Kenya as at August, 2010 and as such sampling of the population was not necessary. It is therefore a census survey design. The results of this method are accurate due to the fact that each unit to be measured was included in the survey. This implies that there was no sampling variability attributed to the statistic because it is calculated using data from the entire population. The study was carried out in Nairobi which is the capital city of Kenya. The population of the study comprised of all 40 registered insurance companies in Kenya. The researcher targeted to get information from the 40 underwriting managers of these firms. These were chosen because they have the information required for the purposes of the study. Sekaran (2003) states that population refers to the entire group of people, events, or things of interest that the researcher wishes to investigate.   All the 40 registered insurance firms have their head offices in Nairobi. Some of the offices are in the central business district whereas others are in its peripheries. Branch offices in insurance firms, just like other financial institutions, are not authorized to divulge company information without express authority from their headquarters. This is the main reason why the researchers had to involve the various headquarters of the firms. In this study, the results were subjected to statistical tests to determine the magnitude and strength of the relationships in the dimensions and variables.  The cross-sectional method of data collection was employed in this study. The key informant method of getting information from these firms was used. The questionnaires were distributed in a non-contrived study setting since it involved studying events as they normally occur. Data was analyzed using descriptive statistics and inferential statistics. The hypothesis was tested using simple regression coefficient at 95% confidence level.   Results   Table 1: Percentage Frequencies of responses on Operational Factors  Dimensions 1 2 3 4 5 Total % Claims are settled with minimal disputes 0 16.7 6.7 50 26.7 100 Company infrastructure 3.3 23.3 0 50 23.3 100 Products meet IRA conditions 3.3 6.7 3.3 20 66.7 100 Information through seminars 13.3 13.3 50 20 3.3 100 Information through agents and brokers 0 0 6.7 46.7 46.7 100 Sales are through referrals 0 10 33.3 33.3 23.3 100 Product meets customer needs 0 3.3 10 63.3 23.3 100   1=Strongly Disagree, 2= Disagree, 3= Not Sure, 4= Agree, 5= Strongly Agree. Source: Research data (2011)  76.7% of respondents agreed that claims are settled with minimal disputes. 93.4% of respondents agreed that company information is passed to the insuring public through agents and brokers. This means that insurance agents are very important within the industry in as far as the dissemination of information is concerned. The highest percentage of respondents who strongly disagreed with the dimensions of operating factors was 23.3 %( company infrastructure).     © Centre for Promoting Ideas, USA                                                                                                www.ijbssnet.com 240  Table 2: Mean Score Summary of Operational Factors  Dimensions N DF Mean Std. Dev. Claims are settled with minimal disputes 30 29 3.9 1.0 Company infrastructure 30 29 4.4 1.1 Products meet IRA conditions 30 29 3.7 1.1 Information through seminars 30 29 2.9 1.0 Information through agents and brokers 30 29 4.4 0.6 Sales are through referrals 30 29 3.7 0.95 Product meets customer needs 30 29 4.1 0.69  1=Strongly Disagree, 2= Disagree, 3= Not Sure, 4= Agree, 5= Strongly Agree.  Source: Research data (2011)  The mean score of operational factors is 4 which imply that all respondents agree with the operational factors.  Table 3: Percentage Frequencies of responses for Organizational Performance  Dimensions 1 2 3 4 5 Total % Emphasis on rate of return on investments 0 0 6.7 50 43.3 100 Keen on market trends 0 3.3 10 53.3 33.3 100 Participation in community projects 6.7 3.3 10 40 40 100 Efficiency claim settlement service  0 3.3 6.7 46.7 43.3 100 Company known for qualified personnel 0 3.3 6.7 40 50 100   1=Strongly Disagree, 2= Disagree, 3= Not Sure, 4= Agree, 5= Strongly Agree.  Source: Research data (2011)  Most respondents agreed with the dimensions in organizational performance.  The corresponding hypothesis of this study was stated as follows: - H01: There is no relationship between operating factors and organizational performance. In order to test this hypothesis, the scores of the operating factors were regressed with those of the organizational performance. The table 4.5 here below shows the regression results between these two variables.  Table 5: Regression Summary of Results of each Indicator of Operating Factors on Organizational Performance   Indicator Regression Coefficient (β) Significance Level or p-value Claims -0.010 0.983 Agents and Brokers 0.223 0.631 Infrastructure 0.385 0.393 Customer Needs -0.071 0.880 Marketing -0.230 0.620  Source: Research data (2011)  Some indicators of operating variables had a negative relationship with organizational performance (claims, customer needs and marketing) whereas others had a positive relationship. All the significance levels (p-values) of these indicators were statistically insignificant and therefore failed to reject the null hypothesis.   Table 6: Regression Summary of Results of Operating Factors on Organization Performance  Regression Coefficient, Beta(β) Significance Level, p-value 0.06 0.895  Source: Research data (2011)     International Journal of Business and Social Science                                                Vol. 3 No. 17; September 2012 241  The regression results indicate that there was a positive relationship between these two variables although weak (β = 0.06) and that p-value = 0.895 which was not statistically significant. This implies that the test failed to reject the null hypothesis H01: There is no relationship between operating factors and organizational performance.  Conclusion  The operating factors, that is, claims, agents and brokers company infrastructure customer needs among others do not affect the performance of an insurance firm significantly. The results of the study may not be in agreement with the normal practice in the insurance industry. It is true that a healthy life span leads to a better life insurance rate and therefore a lower premium. This may allow a longer period for the insurer to invest the premiums collected in readiness for future claims. The greatest challenge for insurers in Kenya is that the insuring public lacks information about the insurance products or if they have any, it has been distorted by those charged with the responsibility of disseminating the information. In Kenya, there are issues concerning fraudulent companies, non-payment of claims and total mismanagement of insurance companies. These and many other issues have hampered the growth of insurance companies in Kenya.   The insurance industry is the main umbrella or driving force in all other industries. Insurance industry boosts investor confidence apart from providing financial compensation in case of losses due to risks insured against. There are many third world countries where poverty, hunger, diseases and poor living conditions directly affect the mortality rates and as a result insurance business in these countries is not profitable. For instance, half of the population here in Kenya is below the poverty line and cannot afford premiums for insurance even if they have information about it. All these issues impact negatively on the overall performance of the insurance industry in Kenya and in other third world countries.   References    Bag, A.(2008). Improve Your Corporate Image. Corporate Image, Inc. http://www.corporate.images.com/fckeditor.  Bell, Jr. C.O.and French, W. L. (1997). Organization Development. Sixth Edition. Behavioral Science Interventions for Organization Improvement. New Jersey. Prentice Hall. Beardwell, I., Holden, L.and Claydon, T. (2004). Human Resource Management: A Contemporary Approach. London. Pitman Publishing. Hayes, D. (2010). Brand Technology Brokers International. New York. 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Human Resource Management: A Contemporary Approach.

Improve Your Corporate Image.

Management : Responsibility For Performance .

New Regulations Seen Hurting Micro-Finance. Nairobi. Business Daily Africa. At http://microfinanceafrica.net/tag

Organization Development. Sixth Edition. Behavioral Science Interventions for Organization Improvement.

Resource Management, seventh edition.

The Effect of Risk Underwriting Decisions on the Performance of Insurance Firms in Kenya. Unpublished MSc (HRM) thesis.

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Effects of operational factors on organizational performance in Kenyan insurance industry

http://eprints.usq.edu.au/22083/1/Mudaki_Wanjere_Ochieng_Odera_PV.pdf

Effects of operational factors on organizational performance in Kenyan insurance industry

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