Though social media could drive up the brand of a company, it can also cause big disruptions in the supply chain operations of a company. A great example that happened recently is where Popeyes Louisiana Kitchen chain ran completely out of chicken sandwiches.
Over the past few months, we’ve been running simulation tests on different demand forecasting methods: Winter’s additive & multiplicative, seasonal and robust seasonal. Then, we used MAPE to determine the forecast accuracy for each method. Here’s what we found.
Seasonal method is a regression method that fits a linear trend along with sine and cosine curves. These sine and cosine portions of the regression can fit any seasonal deviations from the linear trend. Robust seasonal method also fits a trend along with sine and cosine curves, however this method uses linear programming to fit a seasonal series in a way that compared to the regular seasonal method is less likely to be thrown off by noisy values that depart from the trend or seasonality.
In the previous What-if Wednesday posts, we experimented with the three parameters of the Holt-Winters Multiplicative method, namely; alpha, beta, and gamma. This time we are going to run similar tests by adjusting damping factor for the Winters Multiplicative method.
In this week’s What-if Wednesday post, Arkieva Supply Chain Optimization Consultant – Abhishek Shah – shares the results of a what-if demand forecast simulation using the gamma multiplicative forecast parameter of the Winters forecasting method.
In this week’s What-if Wednesday post, Arkieva Supply Chain Optimization Consultant – Abhishek Shah – shares the results of a what-if demand forecast simulation using the Winters multiplicative beta parameter.
In this week's What-if Wednesday post, Arkieva Supply Chain Optimization Consultant - Abhishek Shah - shares the results of a what-if demand forecast simulation using the Winters multiplicative alpha parameter.
In the previous What-if Wednesday previous posts, we experimented with the three parameters of Holt-Winters method, namely; alpha, beta, and gamma. This week we are going to run some tests with the damping factor.
Seasonality forecast simulation: what is the effect of changing the gamma parameter in Holt-Winters forecasting method?
In our previous blog, we experimented with Alpha - the intercept parameter of the Holt-Winters method - to see how the forecast gets affected as the weight changes. This week we are going to run similar tests with Beta, the trend parameter. Learn how you can use your recent sales trends to improve future forecasts.