- Forecast accuracy often appears under control to C-suite executives, since they see only aggregated quarterly or annual accuracy reports, but supply chain managers dealing with forecasts on a weekly basis often witness less accurate forecasts, according to a recent report by E2open.
- Improving forecast accuracy can help create leaner supply chains by cutting capital and operating costs, ensuring the right amount of inventory is located at the most needed locations. However, these benefits are often lost to superiors since the final savings figures are clouded by other, more technical metrics.
- The white paper makes an argument for demand sensing technologies to improve accuracy. Demand sensing technology uses current data, as opposed to historical data, to create forecasts and can reportedly reduce margins of error by 40%.
Estimating supply and demand is a complex process, but as consumers increasingly drive production companies are looking for ways to adapt their supply chain to best suit demands.
These "demand-driven" supply chains require a massive amount of properly parsed and continually updated data, so while few have perfected the science, various companies are looking to incorporate more real-time data. That's why visibility, transparency, and integrated software matters.
Yet forecasts are but predictions and the supply chain manager's job is not to be a fortune teller, but also a risk manager. Lean supply chains may help optimize costs, but they may also decrease agility. In addition to raising accuracy and efficiency, then, supply chain managers must also look to increase agility and resilience in order to make sure one mistaken forecast does not erode heavily at the profit margins gained from the new methods.