CRITICAL SUCCESS FACTORS FOR ACCOUNTING INFORMATION SYSTEMS DATA QUALITY

CHAPTER ONE
INTRODUCTION
1.1       BACKGROUND OF THE STUDY
Quality information is one of the competitive advantages for an organization. In an accounting information system, the quality of the information provided is imperative to the success of the systems. Accounting Information System (AIS) as one of the most critical systems in the organization has also changed its way of capturing, processing, storing and distributing information. Information has become a key resource of most organizations, economies, and societies. Indeed, an organization’s basis for competition has changed from tangible products to intangible information. More and more organizations believe that quality information is critical to their success (Wang, R.Y 2006).
 
However, not many of them have turned this belief into effective action. Poor quality information can have significant social and business impacts (Strong, Lee and Wang, 1997). There is strong evidence that data quality problems are becoming increasingly prevalent in practice (Redman, T.C 1998). Most organizations have experienced the adverse effects of decisions based on information of inferior quality (Huang, Lee and Wang, 1999). It is likely that some data stakeholders are not satisfied with the quality of the information delivered in their organizations. In brief, information quality issues have become important for organizations that want to perform well, obtain competitive advantage, or even just survive in the 21st century.
 
 
 
In particular, Accounting Information Systems (AIS) maintain and produce the data used by organizations to plan, evaluate, and diagnose the dynamics of operations and financial circumstances (Anthony, Reese and Herrenstein, 2005). Providing and assuring quality data is an objective of accounting. With the advent of AIS, the traditional focus on the input and recording of data needs to be offset with recognition that the systems themselves may affect the quality of data (Fedorowicz and Lee, 1998). Indeed, empirical evidence suggests that data quality is problematic in AIS (Johnson, Leith, and Neter, 1981). AIS data quality is concerned with detecting the presence or absence of target error classes in accounts (Kaplan, Krishnan, Padman and Peters, 1998).
Thus, knowledge of the critical factors that influence data quality in AIS will assist organizations to improve their accounting information systems’ data quality. While many AIS studies have looked at internal control and audit, Data Quality (DQ) studies have focused on the measurement of DQ outcomes. It appears that there have been very few attempts to identify the Critical Success Factors (CSFs) for data quality in AIS. Thus, there is a need for research to identify the critical success factors that affect organizations’ AIS DQ.
Information technology has changed the way in which traditional accounting systems work. There is more and more electronically captured information that needs to be processed, stored, and distributed through IT-based accounting systems. Advanced IT has dramatically increased the ability and capability of processing accounting information. At the same time, however, it has also introduced some issues that traditional accounting systems have not experienced. One critical issue is the data quality in AIS. IT advantages can sometimes create problems rather than benefiting an organization, if data quality issues have not been properly addressed. Information overload is a good example. Do we really need the quantity of information generated by the systems to make the right decision? Another example is e-commerce. Should the quality of data captured online always be trusted?
Data quality has become crucial for the success of AIS in today’s IT age. The need arises for quality management of data, as data processing has shifted from the role of operations support to a major operation in itself (Romney, M. and Steinbart, P. J., 2009). Therefore, knowledge of those factors impact on data quality in accounting information systems is desirable, because those factors can increase the operating efficiency of AIS and contribute to the effectiveness of management decision making.
 

• STATEMENT OF THE PROBLEM

The proliferation of computerized database with relative increase in errors of such stored data base in organizations which depend on them to support business process and decision making has been questioned by many analysts.
The number of errors in stored data and the organizational impact of these errors is likely to increase (Klein 1998).
 
Also, inaccurate and incomplete data may adversely affect the competitive success of an organization (Redman 1992). Indeed, poor quality information can have significant social and business impacts. For example, NBC News reported that “dead people still eat!” Because of outdated information in US government databases, food stamps continued to be sent to recipients long after they died. Fraud from food stamps costs US taxpayers billions of dollars.
 
Equally, losses in millions incurred by business organizations who were caught unawares by dramatic changes in interest rates is of great concern to both owners and management.
In particular, there are consequences of poor data quality in AIS. For example, errors in an inventory database may cause managers to make decisions that generate overstock or under-stock conditions (Bowen 1993). One minor data entry error, such as the unit of product/service price, could go through an organization’s AIS without appropriate data quality checks, and cause losses to an organization and / or harm its reputation.
 
More so, most of the information system research into data quality focuses on the theoretical modeling of controls and measurement while few studies have attempted to understand what causes the difference in AIS data quality outcomes, and what should be done to ensure high quality accounting information.
 
Most organizations have experienced the adverse effects of decision based on information of inferior quality. However, not many of them have turned this belief into effective action. Poor quality information can have significant social and business impacts.
 
Therefore, there is lack of knowledge of the CSF for data quality in AIS that can assist organizations to ensure and improve accounting information quality.
These has necessitated the conduct of this research.
1.3       OBJECTIVES OF THE STUDY
The main objective of this study is to examine the critical success factors for accounting information systems data quality. The subsidiary objectives include the following:

• To determine the factors that affects the variation of data quality in accounting information systems.
• To ascertain the variations with regard to the perceptions of importance of those factors that affect data quality in accounting information systems.
• To examine the stakeholder perceptions on importance of critical factors for accounting information systems.
• To investigate the factors that are critical success factors to ensure a high quality of data in accounting information systems
• To examine the organizations perspective in the importance and performance of critical success factors for accounting information system data quality.

 
1.4       RESEARCH QUESTIONS
In order to explore the research problem, the focus of this project is on five research questions which reflect on the objectives of the study are fielded.

• What factors affect the variation of data quality in accounting information systems?
• Are there any variations with regard to the perceptions of importance of those factors that affect data quality in accounting information systems?
• What are the perceptions of stakeholder groups in importance of critical factors for accounting information systems?
• Which of these factors are critical success factors to ensure a high quality of data in accounting information systems data quality?
• What are organizations perspective in the importance and performance of critical success factors for accounting information system data quality?

 
1.5       RESEARCH HYPOTHESES
In analyzing the critical success factors for accounting information systems’ data quality, some tentative statements were formed to help answer the research questions hence the following hypotheses that have to be tested were put forward for this study.
 
Hypothesis One
H_o:      There are no significant factors that affect the variation of data quality in   accounting information system.
H₁:      There are significant factors that affect the variation of data quality in         accounting information system.
 
Hypothesis Two
H₀:      There are no significant differences between the perceptions of importance           of critical factors for accounting information systems’ data quality, and             actual             performance of those factors.
H₁:      There are significant differences between the perceptions of importance of            critical factors for accounting information systems’ data quality, and actual performance of those factors.
Hypothesis Three
H₀:      There are no significant differences between different stakeholder groups in their perceptions of importance of critical factors for accounting information systems’ data quality.
H₁:      There are a significant difference between different stakeholder groups in their perceptions of importance of critical factors for accounting information systems’ data quality.
 
Hypothesis Four
H₀:      There are no significant critical success factors to ensure a high quality of data in accounting information systems.
H₁:      There are significant critical success factors to ensure a high quality of data in accounting information systems.
 
Hypothesis Five
H₀:      Different organizations have the same perspective in the importance and performance of critical success factors for accounting information systems data quality.
H₁:      Different organizations have different perspective in the importance and performance of critical success factors for accounting information systems data quality.
 
1.6       SIGNIFICANCE OF THE STUDY
Identifying the critical success factors for AIS could enhance the ability of AIS’s to gather data, process information and prepare reports. Outcomes of this research will contribute to the body of knowledge both in AIS and data quality field, and it may benefit other research into these areas. For example, it can help arouse the awareness of data quality issues in AIS field, and to make it possible to establish the linkage of the identified CSFs with the existing data quality dimensions for outcomes assessment.
Thus, understanding how these factors affect organizations’ AIS performance may be useful to practitioners. Focusing on those factors that are more critical than others will lead to efficiency and effectiveness AIS’s procedures. In brief, the results from this research are likely to help the academic community for future researchers, organizations’ top management, accountants, and IT managers obtain better understanding of AIS DQ issues.
 
1.7       SCOPE OF THE STUDY
This study is limited to four Nigerian companies selected for the case study in this research. Two of them were chosen from banking industry, and two from manufacturing industry. As there is no one set of criteria to distinguish banking industry and manufacturing industry for the purpose of the case study analysis of this research, employee number was use to define the size of the organizations. Although criteria defining organizations as bank, manufacturing vary, in this research organizations with more than 1000 employees were categorized as manufacturing companies while those organizations with fewer than 1000 employees were categorized as banking industries. In order to respect the privacy of the participating organizations and individual interviewees they were not identified by their real names or actual position titles.
 
 
1.8       LIMITATIONS OF THE STUDY
As part of the research experience by researchers all over the globe; certain limitations hindered the effective and smooth collection of data for the work. These in specific terms include: inadequate working fund, lack of time and difficulties (minimal) in obtaining needed data relevant to the subject matter of critical success factors for accounting information systems data quality.
 
Financial Constraint: The finance needed to carry out this work is too much and cannot be afforded by the student. This to an extent hampered the success of this work.
Time Constraint: Time was really a big constraint in carrying out this research study. The researcher had to combine the collection of materials for the study with other academic activities. The study was not easy to carryout due to distant part of the organizations and the huge financial burden involved.
Non-Challant Attitude of Respondents: Another limitation in the course of carrying this study was the non-chalet attitude of the respondents in supplying the necessary information. This was probably due to their ignorance of the main purpose of the study. Also many refused to grant interviews or answer question bordering on the activities of the organizations.
Scope of the Research: The study was constrained to Nigerian organizations; therefore, the conclusions drawn from this study may have a potential problem on generalization.
 
 
 
1.9       OPERATIONAL DEFINITIONS OF KEY TERMS
This section develops the definition of core terms for this research because precise definitions of core terms are the foundation of any research project.
 
Accounting Information System: Accounting information system (AIS) is a system of records, usually computer based, which combines accounting principles and concepts with the benefits of an information system and which is used to analyze and record business transactions for the purpose to prepare financial statements and provide accounting data to the organizations studied.
 
Critical Success Factor: Critical success factor (CSF) is the term for an element that is necessary for an organization or project to achieve its mission.
 
Data Quality: Data Quality (DQ) is the state of completeness, validity, consistency, timeliness and accuracy that makes data appropriate for a specific use.
Data Suppliers: Data suppliers are those who provide raw, un-organized data to the accounting systems which include both internal and external such as, other departments within the organization (internal), and trading partners (external).
 
Information Users: Information users are the users of the accounting information which include both internal and external users. Such as: top management and general users within the organization (internal), banks and government (external).
 
Middle Management: is responsible for implementing the strategic decisions of top management. Middle managers make tactical/short-range decisions.
 
Non-management Employees: who include production, clerical, and staff personnel.
 
Stakeholder: Stakeholder is a person, group, organization, or system who affects or can be affected by the organization’s actions
 
Small to Medium Organizations: Small to medium organizations (SMEs) are companies whose headcount or turnover falls below certain limits.
Top Management: Executive or senior management includes the highest management positions in an organization.
 
1.10    PROFILE OF THE ORGANIZATION USED FOR THE STUDY
1.10.1 First Bank Plc
First Bank Plc is one of the oldest financial institutions in Nigeria and was the first bank to be established in West Africa. The bank was incorporated as a limited
liability company in March 1894 and was listed on The Nigerian Stock Exchange in March 1971. Following the Central Bank of Nigeria’s (“CBN”) induced industry-wide consolidation in 2005, the bank acquired its merchant banking subsidiary, FBN (Merchant Bankers) Limited and MBC International Bank Plc. The bank offers a wide array of financial services to a diverse customer base through its local and offshore offices, including 465 branch offices country wide and 532 ATM’s. In addition to growing organically through new products and branch development, other viable domestic acquisitions are being explored as the Bank marked its 110 years of existence during which it pioneered the art and science of modern banking in the country.
 
First Bank of Nigeria maintains a subsidiary in the United Kingdom, FBN Bank (UK), which has a branch in Paris. The bank also has representative offices in South Africa and China. In October 2011, the bank acquired Banque International de Credit (BIC), a leading bank in the Democratic Republic of Congo (DRC).  (http://www.firstbanknigeria.com/Portals/2/pdf/Rating_rep/FirstBank%20-%20GCRFinal%20%20rpt%2008.pdf)
 
1.10.2     Zenith Bank Plc
Zenith Bank was established in May 1990. It became a public limited company in July 2004, and had an initial public offering on the Nigerian Stock Exchange (NSE) on October 21 of that year. Also in 2004, credit rating agency Fitch Ratings identified its credit as AA- on their long-term scale.
Zenith Bank Plc is a Nigeria-based commercial bank engaged in the provision of universal banking services to corporate, commercial and individual customers. The Bank provides services as savings and current accounts, treasury and financing services, investment banking, mortgage loans, trade financing, fund management and investment banking, import and export finance, and cash and liquidity management services to the wholesale and retail market, among others. In addition, various types of credit and debit cards, Internet and telephone banking, as well as money transfer services. The Company operates a number of subsidiaries include, among others, Zenith Realtors Ltd, Zenith Registrars, Zenith General Insurance, Zenith Pension Custodian, Zenith Securities, Zenith Life Assurance, Zenith Capital, Zenith Medicare and Zenith Trustees Limited.
 
1.10.3   Nigeria Breweries Plc
Nigerian Breweries Plc (NB), incorporated in 1946, is the pioneer and largest brewing company in Nigeria with current annual production capacity estimated at 10 mn hectolitres. The company is engaged in brewing, marketing and selling of alcoholic and non-alcoholic products such as lagers, stouts, non-alcohol malt drinks and soft drinks. Nigerian Breweries Plc (NB) is a subsidiary of Dutch brewer, Heineken N.V. and distributes its products across Nigeria. NB offers beer under the Star and Gulder brands, lager under the Heineken brand, malt drinks under the Maltina and Amstel Malta brands, premium stout under the Legend brand, and sparkling soft drinks under the Fayrouz brand. The company operates five breweries in Lagos, Aba, Kaduna, Ibadan and Ama regions in Nigeria, as well as a malting plant in Aba region providing a geographical spread across the country, albeit bias for cities in the southern part of Nigeria. It classifies its sales regions into six units namely, Lagos, Central, East, West, North, and South. The company is headquartered in Lagos, Nigeria. Listed on the Nigerian Stock Exchange in 1990, NB is one of the most capitalized and actively traded companies outside the banking and insurance sectors.