A business analytics approach to augment six sigma problem solving: A biopharmaceutical manufacturing case study Abstract   Biopharmaceutical manufacturers are required to collect extensive observational data sets in order to meet regulatory and process quality monitoring requirements. These datasets contain information that may improve the performance of the production process. Analytics provides a means of extracting this information while Six Sigma provides a means for the insights to be incorporated into production practices.  We present a novel framework which combines Six Sigma and Business Analytics. This approach mines large volumes of inline and offline biopharmaceutical production data, allowing the entire production process to be analysed and modelled. The recommendations of the model are represented as manufacturing rules which give actionable insights to improve the performance of the process.  The integrated approach delivers promising results from synthetic experiments as well as being applied in practice to a cell culture process.

The declarative approach to business process execution : an empirical test Declarative approaches have been proposed to counter the limited flexibility of the traditional imperative modeling paradigm, but little empirical insights are available into their actual strengths and usage. In particular, it is unclear whether endusers are really capable of adjusting a particular plan to execute a business process when using a declarative approach. Our paper addresses this knowledge gap by describing the design, execution, and results of a controlled experiment in which varying levels of constraints are imposed on the way a group of subjects can execute a process. The results suggest that our subjects can effectively deal with increased levels of constraints when relying on a declarative approach. This outcome supports the viability of this approach, justifying its further development and application.