Data quality issues in implementing an ERP

Data quality is a critical issue during the implementation of an enterprise resource planning (ERP) system. Data quality problems can have a significant impact on an organisation’s information system. Therefore, it is essential to understand data quality issues to ensure success in implementing ERP systems. This paper uses SAP as an example of an ERP system and describes a study, which explores data quality problems with existing systems, and identifies critical success factors that impact data quality. The study resulted in the development of a framework for understanding data quality issues in implementing an ERP, and application of this framework in a case study in two large Australian organisations. The findings of the study suggest that the importance of data quality needs to be widely understood in implementing an ERP, as well as providing recommendations that may be useful to practitioners. Computerised databases continue to proliferate and as organisations become increasingly dependent upon their databases to support business process and decision making, the number of errors in stored data and the organisational impact of these errors are likely to increase (Klein, 1998). Information research has demonstrated that inaccurate and incomplete data may adversely affect the competitive success of an organisation (Redman, 1992). Poor quality information can have significant social and business impacts (Strong et al., 1997). For example, NBC News reported, `̀ dead people still eat!’’ It was found that, because of outdated information in government databases, food stamps continued to be sent to recipients long after they died. Fraud from food stamps cost US taxpayers billions of dollars. Business and industry often have similar DQ problems. For example, a financial company absorbed a net loss totalling more than $250 million when interest rates changed dramatically, all because the company database was lacking in quality and simple updates (Huang et al., 1999). In order to ensure DQ in information systems, it is important to understand the underlying factors that influence DQ. There have been some studies of critical success factors in information systems and quality management, such as total quality management (TQM) and just-in-time (JIT). Some of the DQ literature has also addressed the critical points and steps for DQ. Table I shows the related research efforts and reflects issues or elements of critical success factors for DQ. ERP-SAP ERP systems use relational database technology to integrate the various elements of an organisation’s information systems. They provide a number of separate, but integrated modules. The use of an ERP avoids the costs of maintaining many separate `̀ legacy’’ systems and overcomes the problems associated with interfacing different systems. It is quite expensive to implement an ERP system, requiring multimillion-dollar budgets and large project teams. Despite the expense, such systems are becoming very widely used in the world’s largest companies (Scapens et al., 1998). SAP is one of the well-known ERP packages on the market, with strengths in finance and accounting. SAP is an integrated business system, which evolved from a concept first developed by five former IBM systems engineers in 1972. It is a software package designed to enable businesses to effectively and efficiently run a variety of business processes within a single integrated system. SAP stands for systems, applications and products in data processing. It is produced by SAP AG, based in Walldorf, Germany, which employs more than 22,000 people in more than 50 countries. SAP AG is the third-largest software company in the world. SAP software is deployed at more than 22,000 business installations in more than 100 countries and is currently used by companies of all sizes, including more than half of the world’s 500 top companies (SAP AG Corporate Overview, 2000). Therefore, SAP is an excellent system to study in an effort to evaluate ERP environments. Table I Summary of literature review identifying factors influencing (data) quality Fa ctor Sa raph et a l. (19 89) E ng lish (1999) Firth (19 96) W ang (1 998) H uang e t a l. (1 999) Segev (1996 ) Z hu and M eredith (19 95) O rr (1998) Cu sh ing (1974) Yu and N eter (19 73) Fie lds et a l. (19 86) N ich ols (19 87) Bo w en (199 3) Tra in in g * * * * * To p m anage m ent supp ort * * * * * * O rganisation al stru cture (com m unicatio n) * * M anag e chang e * E m ployee/p erson nel re la tions * * * D Q contro l Interna l contro l * Input cont ro l * So urce: From Xu, 200 0 [ 48 ] Hongjiang Xu, Jeretta Horn Nord, Noel Brown and G. Daryl Nord Data quality issues in implementing an ERP Industrial Management & Data Systems 102/1 [2002] 47±58