The domino effect describes how one seemingly insignificant event, like a domino tipping over, can lead to a larger, unforeseen outcome. As one event concludes, it sets off another, and another, and another, until a larger outcome comes into view. And while it may have been difficult to predict the result, it’s easy to see how the chain of factors led to that conclusion.
This idea should be kept in mind when trying to forecast product demand. Due to the massive amount of potential influences, it’s nearly impossible to account for every factor and how they will impact product demand. Traditionally, business leaders have not had visibility into the nuances of how some non-obvious factors affect demand, and had to guess which external factors to use in demand forecasting. However, newer technologies enable businesses to learn which factors have the greatest impact on demand. Manufacturers that find and prioritize these can efficiently forecast demand and stay ahead of their competitors, resulting in elevated performance and increased profitability in their supply chain. Let’s look at three examples of some hidden dominos that fell and caused changes in specific product demand.
On the surface, architects don’t appear to be directly connected to beer, no more than any other trade. However, there is a direct correlation between the Architectural Billings Index and beer sales.1 The Architectural Billings Index measures the month-over-month changes in the hours architects are billed for construction design. An increase in billing activity means an increase in construction projects, which in turn means that more jobs are available, leading to increased discretionary spending. So even though this relationship seems random on the surface, it makes more sense when taking a closer look. With more disposable income on hand, people are more likely to make purchases for non-essential products, like beer. Understanding the correlation between the Index and beer sales, companies can use store activity, shipping volume, and other indicators to accurately predict these swells and capitalize on the opportunity.
Whereas some correlations are applicable everywhere, others are region-specific—making them more challenging to identify. A notable example of this is the relationship between oil and wine in Texas. From 2002 to 2010, the health of the oil and gas industry showed a 90% correlation with wine consumption.2 Oil and gas comprise a healthy portion of the Texas economy, so when the industry as a whole thrives, the region’s community reactively prospers. More disposable income results in increased potential wine sales in Texas, which isn’t true in other regions where oil doesn’t make up a large part of the economy. Business leaders must realize that there are scenarios that influence demand in different geographies in varying ways—one size doesn’t fit all.
Lotion sales and morning sickness
While many effects on demand can be tied to a specific industry or region, there are a few trends that are present regardless of business or location. For example, there is a correlated relationship between hand and body lotion sales and the amount of times people search for “morning sickness” on Bing. Morning sickness is one of the most consistent early signs of pregnancy, and the biological changes during pregnancy cause dry skin. Unlike the Architectural Billings Index or oil prices, pregnancy exists purely on a person-to-person level. These types of trends are powerful because they exist anywhere. When businesses can understand and identify them, they can forecast demand for their products accurately to fully capitalize on the market they serve and gain an advantage over their competitors.
Finding hidden insights about certain effects on product demand is key for businesses to gain optimized supply-chain performance and profitability. Like a single domino falling, these insights seem insignificant, but can massively affect demand. Manufacturers who can drive real-time and actionable insights from small, nuanced, and non-obvious external factors stand to gain a competitive advantage over those who still practice traditional demand forecasting methods.
Prevedere’s Demand Forecasting solution, Built on Microsoft Cloud technology, is instrumental for companies to uncover those hidden external factors, the dominos that influence their business, and forecasting the most. Learn more about Demand Forecasting by visiting its page on Microsoft AppSource.