Benchmarking the benefits and barriers of application integration

TLDR

Over the past three decades, heterogeneous systems have grown in organisations, creating integration challenges that ERP systems only partially addressed, leading to the emergence of Application Integration (AI) solutions aimed at reducing complexity and cost, though literature on AI benefits and barriers remains limited. The study aims to show how AI can boost organisational productivity and business processes by proposing a taxonomy of its benefits and barriers across custom, packaged, and e‑business solutions. The authors benchmark integration practices and develop a taxonomy of AI benefits and barriers. The resulting taxonomy enables researchers to better understand, analyse, and compare AI benefits and barriers, thereby improving decision making.

Abstract

During the last three decades, a number of autonomous and, in many cases, heterogeneous systems have been evolved in organisations which cause integration problems and increase the complexity and cost of maintaining these applications. Enterprise Resource Planning (ERP) systems were then introduced to overcome integration problems. However, organisations did not abandon their existing systems when adopting an ERP solution, as ERP systems focus on general processes and do not allow much customisation. As a result, ERP systems co‐exist alongside other systems, and therefore amplify the need for integration. Recently, a new generation of software solutions called Application Integration (AI) has been introduced to address integration issues. AI is a new area with limited literature and documentation and explains the integration of basic types of applications and summarises the benefits of and the barriers to the adoption of an AI solution. Uses benchmarking to search and study best practices in the integration area. Explains how AI can be used by organisations to help them increase their productivity and improve their business processes. In addition, proposes a taxonomy of AI benefits and barriers when mapped against custom, packaged and e‐business solutions. The proposed taxonomy will help researchers to better understand, analyse and compare the benefits and barriers of AI and will therefore improve decision making.