Visualising the procurement data pipeline
The TBFY project has undertaken a detailed benchmark study of the state-of-the-art in procurement data visualisation. This study supports the front-end work that is carried out across several of the project’s main project themes. It aims to guide project partners in their choices of visualisation schemes based on their specific business cases and customer demands. In our study, we provide an overview of the exciting work that is being done in procurement analytics with a strong focus on end-user facing aspects, in particular visualisations. We aim to provide practical support regarding common challenges of presenting a complete, yet compact guide on data visualisation design from established theories and practices. The study also provides updates on the visualisation and interaction work done in the project overall.
What is the status quo in procurement data visualisation?
We have analysed 28 different data portals by starting our search from the website of Open Contracting Partnership (https://www.open-contracting.org/) and then iterated and expanded our search based on the results we found. Portals were designed for specific purposes based on their specific data requirements. Each portal we analysed focuses primarily on relatively few analyses. Some of the approaches under investigation (for example, tenders or contracts divided by different dimensions) are more popular than others and many portals have provided data visualisations to support them. For any type of analysis, several types of data visualisation techniques are available to best support the case.
How can the TBFY guidelines help you communicate insights better?
The TBFY team produces guidelines for project partners to identify the gaps between the analyses that their products support and those supported by the existing procurement data portals. In addition, project partners can use the data visualisation and interaction guidelines to review their current work. Outside the TBFY consortium, the review and guide that we’re putting together can be used as general instructions for dashboard design and for visualisation optimisation, especially in areas with strong focus in analytics.