The Digital and AI Transformation KPI project
Digital transformation is important but extremely challenging. Organizations invest funds, involve people, and spend significant amount of time and energy on digital transformation projects, but due to inadequate key performance indicators (KPIs), they often have only a vague sense of how their initiatives are going. Thus, it is no wonder that more than 80% of digital transformation projects fail to meet objectives.
We have been studying the problem of insufficient digital transformation KPIs for a few years. Building on our own work with organizations, and supported by academic research, we have collected a portfolio of ‘tried and tested’ digital transformation measures, metrics, and KPIs.
This site presents these KPIs in an intuitive and dynamic format.
We have organized the KPIs by business objective into four categories: Operational Efficiency, Workforce Engagement, Customer Engagement, and New Sources of Value Creation.
How to use this tool
Each of the four digital transformation KPI categories is represented by a “bubble” which is surrounded by a “constellation” of KPIs. By clicking on each KPI, you can visualize specific information such as a description of the KPI, case study examples, and specific usable measures.
The bar on top of the screen allows you to filter by category, owner, company size and other factors: in this way, you can identify the KPIs that are relevant to your specific transformation initiative. By clicking on the reset button, you can remove all the filters applied.
Please be aware that this is a living project, hence the filters can undergo various updates, based on further research, feedback received etc.
If you wish to save or download data, you need to register – the usage remains free of charge, but registration is needed for us to verify reliable sources and keep a high-quality standard.
If you want to provide feedback without registering, you can click on the feedback button on the bottom right of the page.
Disclaimers
The case studies are public and we share the sources where possible. The measurement framework is updated as new information emerges. Feel free to provide us with your feedback.
Credits
We would like to thank Jialu Shan, Delia Fischer, and Alex Beck for assistance in building and visualizing this tool.