When one thinks of a forecast, the local meteorologist’s weather report likely comes to mind. These meteorologists monitor several data sources, such as barometric pressure and historical conditions, to forecast what the coming week’s weather might be like. In some cases, they are almost exactly right. In other cases, their call for a cold, rainy day might result in a warm, cloud-free one. Indeed, these weather models and simulations used to forecast the weather are dynamic, and misreading just one input parameter can result in great miscalculations. However, one might argue that the ability to predict the weather has improved over the years, as have technologies and the understanding of the science behind the weather.
Everything described above can be said for forecasting in operations. There is a reliance on a variety of data sources to construct a best guess of what production needs might be. Data sources might include things like past customer behavior and sales levels, seasonal variations in the demand for products or services, competitive factors, market conditions, and a wide variety of other variables that largely depend upon the kind of product or service that is offered. Sometimes it is adequate to use a simple forecasting model, where projections are based solely on the last period. Other times, a more quantitative technique to derive a forecast is required. Regardless, just like how technology and the science behind weather forecasting has improved, the ability to forecast production requirements has improved over the years for the same reasons. There are better models and more data about consumers (such as the data they provide every time they use the internet or a cell phone). In this module, the importance of forecasting will be discussed. Basic qualitative and quantitative techniques will also be addressed. It is important to remember the saying, “All models are wrong, but some are useful.” There will never be an ability to perfectly predict the future, but an educated, data-based forecast can provide a good starting point.
Just as it is important to forecast future needs, operations managers need to plan and execute projects related to their operations so that they remain on time and within budget. The role of project management and the use of smart project management tools and techniques are thus inextricably linked to operations management. This module introduces two frameworks used to manage projects: the program evaluation and review technique (PERT) and the critical path method (CPM). These frameworks provide the foundation upon which we can understand additional project management tools, like activity mapping via the creation of network diagrams. Understanding how to properly use these tools is an essential skill for operations managers.