Sodas lift McDonald’s

Some interesting trend in fast food business:

  • introducing in-store ordering kiosks,
  • expanding delivery through UberEats, and
  • launching a mobile order-and-pay option.

Reference: Sodas lift McDonald’s

McDonald’s optimizes drive-thru with analytics

McDonald’s optimizes drive-thru with analytics

These days, it has become less clear between “data analytics” and “optimization.” There are many stories about Big Data that are talking about reducing cost, increasing revenue, or enhancing marketing. On the other hand, optimization is more about how to model your system or process of interest with mathematical or statistical models with an objective function; the function can be a revenue, profile, or number of consumers. By minimizing or maximizing the objective function over the (solution) space of the models, Operations Research professionals seek the best solution (among the feasible ones) to achieve the optimal value of the objective function. So, data analytics is different from optimization. Data analytics is more about control or monitoring. Data analytics gives you insight of a system/process of interest but is seldom associated with an objective function. It usually has many indicators or benchmarks of a few dashboards. It gives you “intelligence” so you know your system/process better in order to have a better control of where you would like it to go to. Optimization, on the other hand, tells people the best way to achieve the specified objective with the least effort. When the objective changes or the solution space changes, the optimal solution changes.

The referred article at the top of this blog has both keywords in its heading, “optimizes” and “analytics”. If you read the article, you would realize that it is an optimization problem, less about data analytics. Such confusion will become more common, as Big Data people want to bring more value to improve its acceptance and Operations Research professionals want to be part of the Big Data wave. No matter where the trend will take us, it is quite important for us to understand the differences of these two disciplines so we would be able to focus on what problems we are solving and what techniques we should use.