AJ Visualizations: Operations Analytics


Trends and Seasonality Analysis

We use regression analysis to capture data trends, and the moving averages model for non-stationary data series. For more complex datasets that, for instance, includes seasonality trends, we use the SARIMA model to forecast the data. The SARIMAX model can also be implmented if there are highly correlated exogenous variables involved in the dataset.


High & Low Uncertainty Optimization

We provide analysis for various types of optimization in both low and high uncertainty situations. Low uncertainty situations corresponds to, for example, a highly certain level of demand for the coming period, whereas, in high uncertainty situations the level of demand may deviate from the forecast. We use probability distributions to account for high and low uncertainty.


Decision Trees with Simulation

In the case where a company has several decisions it can make, we help construct a decision tree to determine the expected payouts. We then use simulation and optimization techniques to determine the best course of action for the company based on those decisions.