14th August 2018
Written by Annie Hou (Senior Data Scientist, Sandtable)
We were tasked with building a model of consumer behaviour in the automotive industry. The model was complex with many parameters, so to better understand the model dynamics we wanted to conduct a sensitivity analysis of a number of the parameters over a wide range of values. Furthermore, because the model was stochastic, it required us to run a number of independent simulations in order to understand model behaviour per parameterisation.
Using Sandman, we were able to easily setup and run the sensitivity analysis. It allowed us to efficiently and reliably run thousands of parameter combinations across large amounts of cloud resources on-demand.
The parameter sweeps allowed us understand the model behaviour better and to continue to develop and improve it quickly. We were able to run further sensitivity analyses as the model developed. In the end, we were able to deliver a better model and insights to the client.