What Does Your Data Tell You? How Transfusion Chain Data Can Support Managerial Decision‐making

Background/IntroductionIn recent years, the expanding digitization of information has resulted in an abundance of data being collected. As a consequence, more and more data are available to support decision‐making. Despite the numerous examples where data have provided valuable insights, data can only contribute to solving those problems for which the right information is captured within the data.Methods/ResultsConceptually, the way in which data creates value is by providing new insights through revealing or highlighting existing patterns or associations. This knowledge can be used for example to develop a reference for interpretation of new (or alternative) data, or to identify clusters with (dis)similar characteristics. The increasing availability of data opens up new opportunities to enhance decision‐making. However, there are various pitfalls when analysing data, in particular when it involves data that is collected routinely. In most cases, additional modelling is also required in order to apply the data for decision‐making support.Three examples of utilizing routinely collected data to enhance managerial decision‐making within the blood supply are discussed: predicting donor population size and demographics, predicting future red blood cell demand and identifying test‐seeking behaviour among repeat donors. For each example, we will show how data analysis and (when applicable) subsequent modelling was transformed to relevant management information.ConclusionAnalyses of routinely collected data may provide invaluable information to support decision‐making. The information obtained may not only support decisions made, but may in addition allow quantification of the impact of the decision and provide guidance on how potential improvements are best achieved.