I tried to give a few easy examples how leading indicators can add additional information to a forecasting process.
Some clarifying examples
In Zanzibar, a power outage (blackout) resulted in 20% increase in the number of births. With a time difference of 8-10 months, this blackout event is a leading indicator for the birth rate. Therefore, blackout information can be used when forecasting baby products on a tactical level, as for example diaper sales.
Several studies found relevant effects of weather information on consumer behaviour and retail sales. When the weather is rainy, people buy fewer ice cream then when it’s sunny. But the same goes for toy sales. However, weather information is also very relevant in a Business-To-Business (B2B) context. A cold or a hot summer makes a big difference in sales…
Global economies are evolving very fast, but each market has its own dynamics. Macro-economic leading indicators can incorporate these dynamics in a forecasting model, anticipating on different national evolving markets.