For most businesses that rely on demand forecasts for supply and capacity planning, improving demand forecast accuracy is critical. There are many methods to measure forecast bias and the accuracy of supply chain forecasts including using statistical methods like the Mean Absolute Percent Error or MAPE that we’ve discussed in our previous blogs.

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.

The Supply chain is driven by demand, supply, and inventory planning. Under demand planning, the importance of sales forecasting is undeniable. It provides a basis for the production process regulating quantities, inventory and maximizes the efficiency of the resources available.

In our whitepaper on the 8 essentials of an S&OP Software, we outlined creating a consistent data basis for supply chain planning as an essential S&OP software requirement. In this week’s ‘Supply Chain Talk,’ Arkieva CEO Harpal Singh discusses the key aspects of creating a consistent data basis that supports supply chain planning.

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.

Statistical forecasts are often used as the baseline forecast for demand planning. Due to this reason, statistical forecast accuracy is critical to improving the entire demand planning process. Use this easy step by step statistical forecast technique guide to help you get started with improving your forecasts.

“It is said that the present is pregnant with the future” – Voltaire Forecasting, therefore, is an attempt to deduce the future from the present. It is both, art and science. We will explore the practice of forecasting demand in the short to medium term. Within the constraints of economic and technology trends, demand forecasting drives the planning process in most businesses.

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.

What demand planning lessons can we learn from the recent United Airlines Overbooking Issue?

We all love spreadsheets. But when do you know when you’ve pushed your Excel spreadsheet to the limits? In this week’s, Supply Chain Talk, Arkieva CEO Harpal Singh discusses the telltale signs that show when you are pushing the limits of Excel.

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.

How do you get the sense of what works for demand planning? Market volatilities including changes in the weather can affect any business at any given time. As such, businesses cannot rely on their history alone without considering the full picture of possible market changes. When these changes occur, businesses should be ready to adapt without causing a disruption in existing business processes. So how to do you get to the point where you get a sense of what works when it comes to demand planning?