The electronic components industry has been struggling to cope up with dramatic fluctuations in demand, which has only been amplified by the pandemic (we tell you the consequences of the bullwhip effect on the electronic components market).
From abrupt surge in demand last year for consumer electronics, to a rebound in demand for advanced cars, no other industry has seen such fundamental shifts in its supply chain.
The global nature of the sector, and the limited information-sharing on demand spikes between suppliers and manufacturers, means that forecasting inaccuracies at one stage of the supply chain can have ripple effects along the entire chain for several months.
As a result, manufacturing has been upended while firms’ access to components from around the world has been severely disrupted. On the consumer level, this has led to price run-ups and stockouts, with the knock-on effects expected to take many months to solve.
Forecasting demand has always been a difficult undertaking, and the increasing complexity of today's global supply chains intensifies that difficulty. In a world of high expectations and evolving consumer behaviour, components manufacturers need to more accurately anticipate customers’ needs regardless of where they purchase, while maintaining a competitive edge. OEMs and EMS also need to make their supply chains more resilient to meet these needs.
It is no mean feat, but it is achievable.
Limited data-sharing capabilities along the supply chain mean that anticipating and meeting consumer demand is a major challenge. To meet the challenge, manufacturers often rely on insufficient information, such as utilizing sales data from the same month over years to predict future demand.
However, this practice feeds into two main pitfalls that many companies often fall into when making demand forecasts. The first one is about inaccurate projections. It is not a secret that many manufacturers usually conduct demand projections through a combination of historical data, experience, and pure guesswork. This is understandable since often companies simply don't have business intelligence to predict demand and market changes. But too much reliance on historical data runs the risk of producing inaccurate results and forecasting errors.
For instance, relying on historical data alone to decide the components and quantity to manufacture often leads to overproduction as companies try to put safety nets to avoid the risk of shortages or losing customers. There is also the risk of releasing a product that would fail to meet demand, which would ultimately inflict huge losses upon the manufacturer.
Not only are prediction inaccuracies expensive, but industry structures and consumer demands often change as well. For example, few people could have predicted the chronic shortage of semiconductors considering that computer chips were overabundant a year ago. Customer trends change so rapidly that projections based on historical data or guesswork simply won't be accurate beyond a few years.
The other pitfall that stems from a lack of proper demand forecasting is the bullwhip effect. Inaccurate demand signals can lead to unrealistic expectations when it comes to manufacturing and delivering electronic components to distributors. The bullwhip effect often occurs when manufacturers become highly reactive to demand, and in turn, amplify expectations around it, which causes a domino effect along the supply chain.
The phenomenon can take hold of your supply chain leading to surplus stock, a spike in inventory costs, and even waste. It is critical to have a better understanding of your customers’ demand so that planning for components manufacturing can continue without interruption due to the bullwhip effect. Companies that don’t acknowledge this may find their supply chains once again struggling to regain their footing as pandemic subsides.
Peer-to-peer transaction platforms like AIRENC can help OEMs and EMSs increase dramatically the accuracy of their demand forecasts by leveraging real-time insights from the components resell market.
AIRENC brings together the electronic components community into a common trading network, thereby enabling OEMs and EMS to detect signals from the components market and better anticipate their supply needs.
Rather than relying on historical data or guesswork, OEMs can utilize the AIRENC platform to obtain real-time market changes that can range from supply chain disruption to competition and even new product channels.
By using the right data at the right time, OEMs and EMSs can make better, flexible forecasts (6-12 months) on the electronic components, giving you a significant advantage over your competitors. For example, if an influx of orders for a specific component within the platform suggests that there’s a strong demand for that item with a potential shortage risk. Such insights allow OEMs and EMS to quickly spot and respond to changing customer trends in real-time, including the market changes expected in the post-pandemic landscape.
A full picture of the real-time data you collect will help you stay ahead, reduce waste in your manufacturing and avoid large forecasting errors.
Given the volatile nature of the electronics supply chain, manufacturers must take every factor, not just their own historical data, into consideration to align production more accurately to demand and remain competitive.
Discover how AIRENC peer-to-peer platform can help you accurate predict demand for electronic components.