Data$-$driven decision making: Use the data provided to determine two cities should consider for its next set of stores.

Sampling and Probability: From the sales data, pick random samples to estimate sales for the new stores. Use probability techniques to predict the range of sales figures.

Predictive Modeling:

$$ Use single and multiple regressions to predict sales for new products.

$$ Build a predictive model to estimate the monthly sales for the new stores for the first year.

Simulation: Use Monte Carlo simulation or Event Logic and Entity Life$-$Cycle Logic Models to forecast sales and stock demands for different seasons.

Linear Programming:

$$ Use Solver to determine the optimal product assortment for the new stores, given constraints like shelf space, supplier agreements, and predicted demand.

$$ Factor in simultaneous decision problems, ensuring every decision complements the other.

Visualization and Presentation: In Excel, create dashboards and charts that showcase your findings in a clear, visually appealing manner. Your final presentation should tell a compelling story about how Superstore should approach its expansion.