As organisational information systems increase in complexity and their use become more pervasive, the quality of the data in these systems becomes progressively more critical. Management uses stored data as inputs to their decision making processes to the organisation. Erroneous data may lead to decisions and actions that are costly and sometimes disastrous. This paper investigates the types of errors that exist in operational databases and develops an explanatory model of the data quality of a business information system. In particular, the research investigates the influence of (1) difficulty in recognising real-world events, (2) difficulty in measuring errors, and users' perception on factors that contribute to improving data quality. These factors are (1) intuitiveness of screen design, (2) intuitiveness of data values, (3) preciseness of controls, (4) importance of data accuracy to job duty, and (5) importance of organisational ties.
Findings indicate a negative association of data quality in relation to difficulty in recognising real-world events and difficulty in measuring errors. The results also show that users who perceive controls as being more precise will perceive the database as containing higher quality data. Similarly, users who perceive organisational ties as being important will also perceive higher data quality. Surprisingly, users who perceived data values as being more intuitive and view data accuracy as being important to job duty will perceive the database as containing lower quality data. The research failed to find any significant relationship between users' perception on screen design and data quality.