A leading manufacturing company has struggled with the problem of evaluating the timing and supply quality of their suppliers. Deliveries often arrived late or in a different quantity than what was requested. Reports and metrics were used but their creation and calculation were manual and slow. Detection of the true root cause of the problem may not always occur because of the large fragmentation of data in ten different systems / sources.

We designed a solution, in the form of a set of automated reports, which eliminates the need for lengthy manual creation. Big Data IT infrastructure is used, since the amount of data to be processed is huge. Reports now provide the logistics managers with an up-to-date overview of each supplier, so they can quickly decide about (dis)continuing cooperation with them. At the same time, it is possible to predict whether the delivery will occur on time, which allows our client to act in advance. This forecasting is enriched by integration of several other external sources, such as weather input (For instance - the weather today in Poland determines the probability of a truck from Poland that will arrive on time tomorrow).