From time to time people have asked me how to implement Holt Winters (trend-seasonal exponential smoothing) in Excel. Let me start by saying that although Excel is probably the most common forecasting tool in business, it is also not a good one. It does not provide many useful options and tools and there is plenty of space for mistakes.
I have produced a small example of Holt Winters that you can download. It comes with two options, depending on how the initial values are calculated. The first option is using a simple heuristic, while the second requires finding optimal initial values with solver.
Two words of caution: i) Excel’s optimiser can easily get stuck to local minima, so try to start with reasonable starting values; ii) Do not use Holt-Winters method when you do not have trend-seasonal data. Instead prefer the simpler Holt or Single Exponential Smoothing methods.
You can download the example spreadsheet here.
My personal view is that organisations should invest in expertise in forecasting and appropriate systems. There are multiple benefits to be gained by accurate and robust forecasts. A relatively inexpensive solution is using R. Several forecasting related packages exist. Prof. Rob Hyndman maintains the excellent forecast package that includes a state-of-the art exponential smoothing implementation. Alternatively you can consider the TStools package that includes a very flexible exponential smoothing implementation by Ivan Svetunkov, amongst other useful forecasting tools and methods (like the Theta method) or try the MAPA package, which implements the Multiple Aggregation Prediction Algorithm that has demonstrated very good performance relatively to exponential smoothing.