Credit Policy and Financial Performance of KTDA Factories in Kericho County, Kenya

Credit Policy and Financial Performance of KTDA Factories in Kericho County, Kenya

Rotich Simion Kiplangat¹, Joseph Theuri²

¹MBA, ²Lecturer, Department of Accounting and Finance, Kenyatta University

DOI: https://dx.doi.org/10.47772/IJRISS.2024.8100282

Received: 15 October 2024; Accepted: 26 October 2024; Published: 25 November 2024

ABSTRACT

Kenya Development Tea Agency have had problem due to produce low prices; high cost of labour and other operational expenses are general influence which impacts all the enterprise in the Country. Tea farmers are most affected through, low payment low bonuses, and delayed. The core drive of the exploration is to evaluate the effect of credit policy on the financial performance of Kenya Tea Development Agencies factories within Kericho County. The study anchored on operational cost theory. Descriptive survey research design was adopted where quarterly financial report was collected from seven Kenya Tea Development Agencies factories between the period 2010 to 2020. Where a sample of 280 records were collected from secondary records obtained from the seven factories. The root information source was the published materials which was extracted by data extraction tool. Standard deviation and mean was utilized as descriptive analysis while panel regression analysis technique was used as inferential statistics. The statistics was illustrated using table and charts. The results revealed that over the past decade receivable collection period have decline. The study revealed that the credit policy has also decline for the past ten years by half. The credit policy had positive significant influence on the financial performance (P<0.05). The study concluded that receivable management has significant influence on the financial performance of firm. The study recommended that firm should be able to increase credit policy.

Key Words: Credit Policy, Financial Performance, Operational Cost Theory, Descriptive Survey Research Design, KTDA, Kenya

INTRODUCTION

Firms should implement a strong credit strategy that assures effective debt collection process for it is vital in boosting effectiveness in receivables management and also business performance. Enterprise ought to choose a minimum receivable collection term and period because a longer period reduces cash inflows, deteriorates the enterprise’s liquidity position, and raises the likelihood of bad debt losses. Hence, the corporation was obliged to acquire debt at high interest rates in order to fund its dealings, lowering its productivity.

An efficient credit policy is required for a firm to manage appropriate debtors. Carlson, Correia and Luck (2019) acknowledges that a company’s credit policy impacts how it would give credit to consumers and enterprises. Some firms accomplish this through pulling credit records, evaluating the 5Cs of credit, and credit scoring, among other things. Enterprises chooses to sell for cash rather than crediting, but competitive constraints push the majority of firms to provide credit. Credit is taken for granted as it is now so widespread in the purchase of goods and services. When clients anticipate credit, commercial units’ credit is expected from their suppliers so as to match their consumer credit investment. To correctly manage credit sales, the following criteria must be determined: Control and Monitoring of Receivable, Credit Policy, Credit Sanction Decisions, and Credit Evaluation of Individual Buyers, Control. The production unit is made up of three components: machinery, workers, and inventory. Machines are used by men to turn raw resources into finished commodities. The efficiency with which every company unit is handled determines its success.

Adoption of a credit policy for successful receivables management is critical in a business, according to Carlson, Correia, and Luck, (2019). For a credit consumer, the conditions of sale specify how the company offered its service or product. It is critical that the company determine if a cash transaction or a credit sale is preferable. The decision is reached after conducting a credit analysis and deciding who should be given credit. If a small business chooses to extend credit to a customer, terms must be established. These conditions contained the credit time as well as any discounts provided to the consumer, as well as the discount period.

Financial performance, according to Birru (2016), is defined as the extent to which financial aims are being or have been met, or as a primary indicator of an enterprise’s entire financial health over a specified time period, and it may be applied to compare firms that are similar within the same enterprise or to perform corporation on sectors or firms in aggregate. This is the methodology of calculating the monetary value of a company’s operations and policies.

The performance on financial of Afang and Francis (2021) mostly reflects business sector outcomes and results, which represent the sector’s overall financial health through time. It shows how effectively a company uses its resources to maximize shareholder value and profitability. Financial ratios are the utmost similar performance measurement applied in the area of statistical and monetary inference. While a complete assessment of an enterprise’s financial performance takes many other types of measures into account, financial ratios are the most basic performance measurement applied in the area of statistical and monetary inference.

Financial performance, according to Maseko and Manyani (2016), primarily depicts business sector outputs and outcomes that demonstrate the sector’s whole financial health over a certain time period. It denotes how well a company uses its assets to enhance shareholder profits and wealth. Even though a comprehensive review of a business’s financial performance includes numerous other types of metrics, financial ratios are the most commonly used performance measurement in finance and statistical inference.

Shareholders, managers, academics, and policymakers have all had a keen interest in a company’s financial success over the years. However, there is little agreement on how such performance must therefore be measured. The tea industry’s performance is critical to Kenya’s economy. According to KTDA annual reports (2021), total payment to farmers have been declining on average from Kshs. 61.99 billion in 2015/2016 financial period with return to grower of 75% to Kshs. 51.85 billion with average percentage return to grower of 66% during the financial period 2019/2020. Tea growers were paid an average of Kshs 35.42 per kg of green leaf in the fiscal year ending June 2020, compared to Kshs 41.27 in the previous fiscal year.

Table 1: Farmers Financial return for period 2015 to 2020

KTDA Annual Report & Financial Statements 2015/2016 – 2019/2020

Percentage Return to growers is key in performance determination of KTDA industries in that it shows what goes to the farmer out of the total revenues a factory receives.

According to KTDA report (2020) there is continuous decline of profitability of the firm. There was a decline in profitability in 2020 from Ksh. 2.07 billion to 1.78 billion as resulting to 14% decline whereas return on asset reduced 6% to 5%. These were attributed to increase in production cost associated with staff rationalization and inflation, cash receivable writes backs, depression and expected credit losses. Majority of the factor are associated with receivable management which prompt for more investigation in receivable collection efficiency, credit policy and cash conversion period.

The rationale for concentrating on this area is since it constitutes for a bigger portion of Kenya’s sector of manufacturing, which provides a significant amount of production to the country’s gross domestic product. There are 7 KTDA Factories in Kericho county, referred as zone 8 KTDA factories which includes; Kapkatet, Tebesonik, Litein, Chelal, Momul, Tegat and Toror. KTDA Factories in Kericho county produces over 170 million Kgs of Green leaf annually with an average percentage return to grower of 65% (KTDA Financial Report 2020).

For several years, Kenya’s tea business has produced dismal profits. As a result, several investigations have been done to determine the causes. Various causes ascribed to this difficulty, such as low prices of product, high labor expenses, and extra operational expenditures, are universal concerns that impact all firms in the country. Furthermore, despite the fact that the KTDA companies had taken cost-cutting initiatives entailing the utilization of low-cost fuels, the returns to growers remain poor. Farmers are suffering from low profitability of the industry which have been associated with poor financial performance of KTDA as indicated by Tea Board of Kenya and KNBS from 2014 to 2021. There has been general decline of KTDA profitability from Ksh 2.07 in previous year to Ksh 1.78 resulting to 14% reduction which have been associated with cost of production, cash receivable, depression of associate and credit losses as at 2020 (KTDA, 2020). Empirical evidence in globally have shown that credit policy assist in improving the liquidity of the firm but with little evidence in Kenya. Therefore, there is need to examine credit policy in relation to returns to tea factory producers in Kericho County, Kenya.

LITERATURE REVIEW

Theoretical Review

The study was anchored on operating cycle theory, which was first proposed in the early 20th century by unknown proponent. The key assumption of the Operation Cycle theory is that a firm’s operations are influenced by the movement of cash in and out of the firm through the sales and collection of accounts receivable, the payment of accounts payable, and the purchase of inventory. The Operation Cycle theory argues that the length of the operation cycle, which is the time it takes for a firm to convert its resources into cash and back into resources, has a direct impact on the firm’s liquidity and financial performance. A shorter operation cycle is generally considered to be more favorable, as it results in less investment in working capital and higher levels of liquidity.

Collection and credit policy changes have a straightforward influence on the normal remaining accounts receivable amount upheld compared to a business’s yearly sales. Giving consumers more favorable results terms in a greater, and possibly less liquid, current investment in receivables. This likely liquidity worsening was reflected in a longer receivables period of collection and reduced receivables turnover if sales raise at least to the receivables increase proportionately. Decision that obliges a corporation to retaining greater average receivables investments for an elongated period will eventually outcome in acid-test ratios and higher current (Richards & Laughlin, 1980).

Inventory turnover measures how frequently enterprises transform their total collection of raw materials, final products into product sales, and work-in-process items. Distribution methods, adopting buying, and production scheduling that need larger inventory commitments per dollar of expected auctions results in a minimum turnover ratio. This, eventually, represents a possibly less and longer liquid inventory holding time. If businesses are unable to change either their practices of payment with trade creditors or their accessibility to temporary financing debt from creditors who are non-trade, actions that result in the less or longer liquid holding periods of time ought to be followed by a greater recent ratio indicative of creditworthiness (Weston, 2013). The operational cycle notion is inadequate as a cash flow metric because it doesn’t take into account the constraints of liquidity placed on a corporation by the temporal measurement of its present liabilities’ commitments.

Cash outflow integration time pattern needs realized by a company’s current obligations is equally crucial for analysis of liquidity as analyzing the pattern of time of currency inflows created by current asset investments transformation (Richards, 1980). This likely in liquidity worsening may be reflected in a longer period of receivables gathering and reduced receivables turnover proportionally to the rise in receivables.

In relation to accounts receivable, the Operation Cycle theory supports the idea that a firm’s management of its accounts receivable can have a significant impact on the length of the operation cycle and thus on the firm’s liquidity and financial performance. Therefore, a firm that effectively manages its accounts receivable by improving the efficiency of its credit and collection processes and reducing the risk of bad debts can shorten its operation cycle and improve its financial performance.

Empirical Review

Credit policy was examined by Byusa and Nkusi (2012) on bank performance from Commercial Banks in Rwandan. The research triangulated  results collected from questionnaires and secondary review of document in the banking sector. Findings revealed that commercial banks in Rwanda were vibrant. Profits maximization was achieved through the increase in accounts and customer in the commercial bank. Increased interest rate margins and average interest rate spreads affected the Rwanda’s commercial banks which leads inefficiency and competition. The banks have improved the growth of financial systems.

Credit management and credit policy were examined Mafumbo (2020) on financial performance. Key intention of the investigation was to found the association between credit policy, capital adequacy and credit risk on performance. Causal research design was used based on secondary facts obtained on yearly supervision reports and financial statement of Uganda’s commercial banks. The outcomes obtained using multiple regression analysis designated that credit management had confident important influence of commercial banks’ financial performance. Capital adequacy and credit risk control had negative noteworthy influence on the financial performance in that increasing order. However, credit policy had no significant outcome on financial performance.

Credit policy was examined by Mwaura and Jagongo (2017) on financial performance. Credit information, loan terms and conditions were examined on financial performance. Descriptive research design was used where forty-three commercial banks in Nairobi. Close-ended questionnaire were used in collecting primary data. The findings indicated that loan terms and condition affect performance of commercial bank. Credit policy had positive noteworthy outcome on commercial banks’ performance.

Chikamai and Mutua (2018) investigated credit policy linking to SACCOs on financial performance in Kakamega County. The investigation used descriptive design. Collection of data was completed using structured questionnaires based on a sample 99. The outcomes revealed that credit policy had positive noteworthy outcome on financial performance. The SACCOs was recommended to develop analytic capabilities, credit policies and procedures.

RESEARCH METHODOLOGY

The study utilized a longitudinal design because it is most suited for collecting records for a given period on financial performance and accounts receivable of KTDA industries in Kericho County. A target 7 KTDA factories in Kericho County was used where data was extracted from quarterly reports from the period of 2010 to 2020 from KTDA factories in Kericho County. Census of all the seven factories were used to extract quarterly financial report data between the period of 2010 to 2020. This made a sample size of 280 records. The survey form was employed in the study to collect raw facts from KTDA workers. Experts were involved in ensuring statistical measures operationalized and conceptualized achieve criterion, content and face validity.

The researcher conducted pilot testing using the test-retest approach, distributing 18 questionnaires to KTDA factory respondents in Kericho County. The Cronbach’s alpha of the questions or items in the surveys was calculated using SPSS after piloting. Cronbach’s alpha was employed in which a coefficient of 0.801 was obtained above the recommended threshold of 0.7. Data was analysed using mean and standard deviation as descriptive statistical and simple regression as inferential analysis. The results were presented in tables and figures.

RESEARCH FINDINGS AND DISCUSSION

Credit Policy Results

The credit policy was computed using debt management (Average payable / Cost of goods sold × 365 days). This relate to the duration in days that the company takes to pay their debts to creditors. The credit policy which is the number of day it takes to clear the cost of goods sold during the planning period was tabulated in terms of mean and standard deviation in Table 2.

Table 2: Credit Policy

Source: Field Data (2024)

The results in Table 2 revealed a declining debt payment duration from 860.8 days in 2013 to 388.83 days in 2022. This indicated that that account payable period had improved from 2.5 years in 2013 to one year in 2022. The KTDA companies had improve the credit policy through reducing the time of payment of debts and loans.

Similarly, there is an improvement of credit policy variation across the firms during the years. The results revealed that in 2013 the variation stands at the highest with 307.18 days, however, by 2022 the variation was 149.20 days revealing a decline in variability across the firms. This implies during the period of ten years the variation in debt repayment had reduced by half from 10 months to 5 months. Notably, the KTDA companies had significantly improved debt management as well as variability of credit policies across the industry.

The aggregate mean of 658.4 days’ account payable period which implied that it took about one year nine months for KTDA companies to clear their debts. A variation of 275.64 days in account payable period was achieve by the KTDA companies. This implies that KTDA had variation of 8 months in the credit policies. The firms need to improve the variation in credit policies to establish a more robust and stable debt management in Kericho County.

Figure 1: Credit Policy

Further, results from the box plot figure 1 revealed that continuous improvement of credit policy over the period 2013 to 2022. During 2013, 2015 and 2019 reveal high variation in debt management policies which can be attributed to external and internal factors. There was a general decline in the variation from 2013 to 2018 which might be associated with external factor. In 2019 the variation might be associated to COVID 19 pandemic, however, the subsequent years revealed decline in variation.

Financial Performance Results

Financial performance was examined using return on asset which is a ratio of net profit to total assets of the firm. The mean and standard deviation was obtained for the ten years from seven KTDA factories in Kericho County, Kenya.

Table 3: Return on Assets

The results indicated that the performance of the KTDA companies over the ten year have been fluctuating with a maximum of 98.48% in 2013 and the lowest of 78.30% in 2019. The fluctuation is associated with socio-economic environment in international market. The lowest performance concedes with COVID-19 pandemic in 2019.

The variation in return on asset tend to decline from 2013 to 2015, another phase of decline between 2016 and 2017, 2018 and 2019 as well as between 2020 to 2022. However, there is general decline in fluctuation in return on asset from 2013 at 24.92% to 14.15% in 2022 which are mainly due to internal as well as external environment.

The financial performance of KTDA in Kericho County shows 86.56% return on assets with a standard deviation of 21.22%. This implies the firms has continuously varied financial performance.

Figure 2: Return on Asset

In figure 2, the return on asset have continuously fluctuated during the entire period with constant trend from 2013 to 2022. Similarly, the variation is high in the period of 2019 and 2020 which demark the period of COVID-19 pandemic. However, the variation in not related with financial performance but socio-economic factors.

Regression Analysis Results

Simple linear regression analysis was adopted to examine the relationship credit policy and cash conversion period with financial performance. The linear regression was used to test hypothesis of the study using a significant level of 5%.

Table 4: Regression Analysis

The results in Table 4 showed that there existed significant relationship between credit policy and financial performance (Prob>F= 0.0005<0.05). The results also revealed that credit policy contributed 24.52% variation of financial performance (R Square overall =0.2452), however, 99.56% in variation in financial performance come from between the KTDA factories (R square between =0.9956) while 3.45% come within the KTDA factory (R Square within = 0.0345). This indicates that the difference KTDA had varied credit policy resulting to different in financial performance. The final regression model was therefore given by;

Yt = 0.97276 + 0.0006076X1t

Where, Yt = Financial Performance at time t and X1t = Credit Policy at time t. This implies that a unit increase in number of days in account payable period would lead to an increase in 0.06076% increase in return on assets.

H02: Credit policy has no important outcome on the financial performance of KTDA factories in Kericho County.

The null hypothesis was rejected and alternative accepted which implies that credit policy had positive relationship with financial performance of factories in Kericho County (β2=0.0006076, P<0.05). This implies with an increase in account payable period there is positive increase in financial performance.

CONCLUSION AND RECOMMENDATIONS

Summary

The analysis of debt payment duration across KTDA firms from one decade highlights a significant improvement in credit policy and debt management practices within the industry. The results demonstrate a notable decline in the average number of days required for debt repayment. Moreover, there has been a marked reduction in variation across firms, indicating a halving of variability in debt repayment duration from 10 months to 5 months over the ten-year period. This improvement signifies a significant enhancement in debt management and credit policy standardization across the KTDA industry. The account payable period takes approximately one year and nine months for KTDA firms to clear their debt. Despite these challenges, the overall trend showcases a positive trajectory towards more robust and stable debt management practices in Kericho County. The study found that the credit policy had positive significant relationship with financial performance of KTDA factories.

Conclusions

Credit policy in KTDA has significantly improve the debt management practices over the last one decade. There have been decline of credit payment half during the ten years’ period. Similarly, the variation in KTDA debt management practices have also reduced by half during the same period.

Recommendations

The study suggests a promising outlook for the industry, with continued efforts needed to further refine credit
policies and navigate external challenges to sustain this positive momentum in debt management efficiency. There is need to balance the account receivable with account payable within the same planning period.

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