Measuring and improving information systems agility through the balanced scorecard approach
Authors: Yassine Rdiouat, Samir Bahsani, Mouhsine Lakhdissi, Alami Semma
Abstract: Facing an environment increasingly complex, uncertain and changing, even in crisis, organizations are driven to be agile in order to survive. Agility, at the core heart of business strategy, represents the ability to grow in a competitive environment of continuous and unpredictable changes with information systems perceived as one of its main enablers. In other words, to be agile, organizations must be able to rely on agile enterprise information systems/information technology (IT/IS). Since, the agility needs are not the same among stakeholders, the objective of this research is to develop a conceptual model for the achievement and assessment of IT/IS agility from balanced perspectives to support agile organizations. Several researches have indicated that the IT balanced scorecard (BSC) approach is an appropriate technique for evaluating IT performance. This paper provides a balanced-scorecard based framework to evaluate the IS agility through four perspectives: business contribution, user orientation, operation excellence and innovation and competitiveness. The proposed framework, called IS Agility BSC, propose a three layer structure for each of the four perspectives: mission, key success factors, and agility evaluation criteria. According to this conceptual model, enterprise information systems agility is measured according to 14 agility key success factors, over the four BSC Perspectives, using 42 agility evaluation criteria that are identified based on literature survey methodology. This paper explores agility in the broader context of the enterprise information systems. The findings will provide, for both researchers and practitioners, a practical approach for achieving and measuring IS agility performance to support organizations in attempt to become agile as a new condition of surviving in the new business world.
Explore the paper tree
Click on the tree nodes to be redirected to a given paper and access their summaries and virtual assistant
Look for similar papers (in beta version)
By clicking on the button above, our algorithm will scan all papers in our database to find the closest based on the contents of the full papers and not just on metadata. Please note that it only works for papers that we have generated summaries for and you can rerun it from time to time to get a more accurate result while our database grows.