How Three Companies are Incorporating Demand Modeling for a Better Supply Chain Design
Have you ever said something along the lines of, ‘well, I thought I had seen it all, but this year was really the craziest yet!’ With the unprecedented pace of change in regulations, political and socioeconomic shifts, and rapidly evolving customer preferences, it’s absolutely critical for supply chains to be able to rapidly respond, or risk reduced profit and market share. Designing better, more responsive supply chains is more than just calculating optimal cost and service levels. You also need a good understanding of the key drivers of your demand and the ability to accurately predict and test future demand scenarios for more confidence in critical supply chain decisions.
Demand modeling has emerged as a critical consideration in supply chain design. Standard forecasting tools can fall short if they can’t take into consideration external causal factors that drive demand like weather and economic indicators, or help predict demand 5-10 years out when making long-term strategic decisions.
The marriage of demand modeling and supply chain modeling technology results in a better demand signal that drives a better supply chain design for the future. Let’s take a look at three case studies of how businesses are reaping the benefits:
Manufacturer leverages demand modeling to better understand key demand drivers of engine demand
Previously, long-term demand modeling for engine sales in the oil and gas sector was done using simple time series algorithms in spreadsheets. Since business and external factors were not considered, there was a lack of understanding of key demand drivers, and very little confidence in the long-term business decision-making.
The manufacturer utilizes demand modeling with built-in causal data to identify 13 potential macroeconomic factors that influences demand, including GDP construction/mining and gas prices. This insight not only improved the accuracy of the model, but also provided more statistical evidence to the business on what is driving the demand to support long-term strategy, potentially freeing up significant additional working capital.
Chemical company uses demand modeling to improve long-term capacity planning
This company had been applying simple growth factors of 5, 10, 15 percent to historical demand across its primary product lines to understand capacity needs in the network to meet future demand for the five years. This solution lacked true visibility into product life cycle and key drivers of demand.
Using demand modeling, the company can now build demand models to determine the optimal growth strategies for each product line considering business factors and external causal factors. They can understand key drivers of your demand for each product line and quickly perform what-if analysis on demand drivers. This means it’s much simpler to create alternate growth strategies to test potential supply chain changes and capacity requirements.
Home appliance company applies demand modeling to enable holistic inventory optimization
This major home appliance manufacturer had no good way to de-seasonalize and de-trend data to remove known sources of variability and isolate true demand variability. It lacked full understanding of product life cycle (which products are growing and which are declining compared to mature products) and the impact to inventory. The company also needed to better understand the various types of inventory such as prebuild, safety stock, and promotional inventory.
Today, the company is incorporating demand modeling as part of its supply chain design process, allowing analysts to explore demand and extract out demand patterns such as seasonality, trend, lifecycle, and promotions. Forecast error is used as a better signal to drive optimal safety stock targets, and the company has been able to develop a holistic inventory strategy by more accurately modeling the various components of demand as part of inventory optimization.
Take the Next Step towards Demand Modeling
Thinking about demand modeling often raises lots of questions. This ebook answers six central questions to help you understand if your organization needs demand modeling and how to best approach it.