Despite the importance of post‑merger IS integration to the success of the whole merger, post‑merger IS inte‑ gration literature remains scarce. This paper attempts to synthesise the often implicit or vague definitions of post‑merger IS integration success with those provided in the vast body of literature on IS evaluation. As a result, four categories of success issues for post‑merger IS integration are proposed: User satisfaction with the integrated software's system and information quality as well as its use; Efficient and effective IS integration management; Efficient IS staff integration; and IS ability to support the underlying motives of the merger.

Beale and Cole is a company that was experiencing significant levels of growth in its business. However, its existing operational practices and ICT infrastructure were incapable of efficiently sustaining their level of growth. A thorough analysis of the operational systems was carried out covering both the manual systems and those supported by its computerised accounting system. A number of beneficial changes were made, including the implementation of a major new business system replacing the old accounting system. In all these developments, the work of a teaching company associate, now known as knowledge transfer partnerships associate supported the analysis, but the full participation and support of all key personnel within the company was essential. Although there were problems during the implementation, these have being resolved and Beale and Cole now has a fully supported and integrated IT system which will maintain their competitive advantage and facilitate their continued growth and profitability.

Partnering companies can share data via various configurations. Typically problems become evident as partnering companies seek to exchange data. These problems take a different form for different data integration configurations and are thus of great relevance when evaluating different configurations. This paper identifies issues to be taken into account when evaluating inter‑organizational data integration configurations. Eight problems are discussed: difficulties to identify which information flows to automate; to relate different viewpoints on boundary objects; to agree on data formats; to distribute investments among the parties; to deliver appropriate service levels; to preserve the value of the data sharing; to clarify data ownership and to do all of this in the frame of changing relationships. For several problems it is illustrated how they surface in a completely centralized and in a completely decentralized inter‑ organizational data‑integration scenario.

The question of integration of information systems (IS) into the planning and execution of operational activities has been the focus for researchers from different constituencies. Organisational theorists recognise the need for integrating mechanisms for co‑ordinating the actions of sub‑units within an organisation. Centralisation has been seen as a defensive reaction by organisations when placed under increasing external control , and also as a way to improve the efficiency of information processing, at least for routine tasks. In the meantime, researchers have been sceptical about the ability for structured information systems to deal with the complexity of the information flows within the organisation. Frameworks have also been identifying characteristics of the tasks themselves that have a bearing on the amount of information processing required. The real world is complex and moving, thus managers require flexibility in their interpretation of the mixed signals arising from this complexity. However, managers are working in environments where highly integrated information systems blur the distinction between what is real and what is virtual. There is a need for an integration approach allowing organisations to question which areas of activity are worth integrating, and conversely which areas are better left under local control. Where integrated, managers require processes for the maintenance of data integrity (people, tools, procedures). Based on field work involving two multi‑national manufacturing companies, this paper proposes a framework for ERP integration, which describes the evolution of functionality gaps as an ongoing and inevitable process that requires management.

The Global Commerce Initiative (GCI) established the Global Upstream Supply Initiative (GUSI) in order to provide a standard framework for consumer goods manufacturers and their suppliers of ingredients, raw materials and packaging to better integrate across a number of supply chain processes. Without Internal Data Alignment, for example, Global Data Synchronization (GDS) will definitely not improve business performance and will, in fact, magnify the negative impact of poor quality data. What’s more, collaborative initiatives such as those included in Efficient Consumer Response (ECR) and Collaborative Planning, Forecasting and Replenishment (CPFR) will not be economically deployable on a wide scale without the consistently accurate and available information that will result from an Internal Data Alignment program. GDS is based on a global network of data pools, or electronic catalogues, which are all inter‑operable and compliant with the same business requirements and standards. Interoperability means that a manufacturer can publish a product and partner data on one single Data Pool without having to worry about the fact that customers may select different Data Pools to access the data. Integrated Suppliers is a concept for improving the part of supply chain between manufacturers and the tiers of suppliers of ingredients, raw materials and packaging. By sharing information both parties are able to exercise judgment on costs, quantities and timing of deliveries and productions in order to stream line the production flow and to move to a collaborative relationship. GUSI underlined the long term policy on the use of Standards as a key success factor to achieve upstream e‑supply integration. Before exchanging information, partners must agree on product identification. This is a part of the data alignment step defined by GUSI. The UIM (Upstream Integration Model) offers common business processes and data interchanges to support interoperability between manufacturers and suppliers.