Modern supply chain management requires dynamic, data-backed strategies. Here’s why.
The boom in AI data center construction caused semiconductor demand and prices to soar. Semiconductor executives forecast a prolonged market shortage of memory chips, possibly lasting through 2027.
This extended demand cycle is unusual. Normally, the periods of short supply and oversupply happen quickly. The longer demand period creates unique revenue and forecasting scenarios.
Traditionally, orders are a strong demand indicator. But during product shortages, many customers increase their inventory buffers, over-purchase or order from multiple suppliers to protect themselves against disruptions. At the same time, customer needs change during the years it takes to produce and deliver products.
As a result, not all current orders will materialize as expected, distorting financial projections and forecasting calculations, not to mention exacerbating the problem of phantom inventory and revenue leakage. The longer cycle means the miscalculations compound.
Additionally, today’s demand environment is also more complex and volatile due to geopolitical conditions, regulatory uncertainty and long-horizon AI investment decisions. Modern supply chain management requires dynamic, data-backed strategies.
The extended demand cycle creates more revenue management challenges
Established demand planning strategies assume a stable market and typical supply and demand cycles. The extended volatility breaks those assumptions, widening the gap between forecasted and realized revenue and increasing opportunities for leakage.
Manufacturers create pricing rubrics and contracts to align with current demand, then commit resources to ramping up production to match contracted orders. Companies can’t just stop production when the shortage ends. As supply eventually outpaces real consumption, product prices plummet, and manufacturers are left with phantom inventory.
When chips are scarce, distributors and channel partners often purchase the commodity at peak distributor costs. For example, buying a component at $100 when demand is at its highest. That stock sits on the books looking like realized sales for months, and manufacturers forecast revenue, plan production and make pricing decisions based on an overstated view of demand and inventory value.
When the channel partner eventually sells the chips for just $60, it will claim the $40 difference through price protection, credits, rebates or debit claims. This scenario results in delayed margin erosion. With the high number of contract transactions happening right now, the cost of phantom inventory adds up quickly.
This financial strain is worsened by the industry’s reliance on multi-year, fixed-price contracts that are too rigid for today’s volatility. These agreements lack the flexibility to adapt to rising production costs, shifting trade tariffs or demand shifts. Manufacturers often find themselves locked into selling at outdated prices — either high or low — or even delivering obsolete products. Companies may take a loss on the chips, or customers may break their contracts, leading to lost sales.
Some revenue leakage comes from an even more basic problem: manual revenue management processes. Manual workflows for contracts, pricing, billing and rebate management are prone to mistakes. The explosive volume of sales makes these processes more expensive to run and compounds the cost of errors. Without automated management, salespeople may apply outdated promotional pricing or unauthorized discounts, or the finance department could bill for the wrong amount.
Manufacturers must modernize their practices to close these leaks.
Modern market dynamics require new strategies
With the unpredictable shift of customer behavior, manufacturers cannot plan demand based on current contracts and historical sales patterns. Companies must incorporate leading indicators and analytics into their forecasting.
Leading indicators include variables like:
- Product lead times
- Channel inventory and sell-through
- Competitor sales and product development
- Claims activity
- Contract changes
- Regulatory and economic changes
Manually collecting and analyzing all of these factors is nearly impossible. Conditions shift too rapidly, and patterns can be hidden in the data. Adopting automation and analytics increases data accuracy, timeliness and trend recognition. With high order volume, even small forecasting variances make a significant revenue impact, so improved insight can reduce lost revenue at a large scale.
Beyond automation, manufacturers need new contract structures. When manufacturers employ short-term or contingency-based contracts, they protect themselves from cost volatility, demand instability and supply fluctuations. For example, performance-based incentives reward or adjust terms based on actual customer order performance, reducing the impact of cancellations or order changes. Shorter contracts prevent both parties from being stuck in an unfavorable deal.
Data analytics enable better contracts. Negotiations can be informed by real-time information and optimized for maximum value.
Supply chain visibility helps manufacturers separate actual market consumption from distorted demand signals. Distributor inventory and point-of-sale data allow manufacturers to see if products are actually being sold or simply sitting on shelves. Companies can then prioritize distribution, adjust forecasting and production, and reduce phantom inventory.
The chip shortage also incentivizes gray market sales, as desperate buyers seek chips from wherever they can get them. Comprehensive channel data highlights suspicious sales spikes in unexpected and restricted markets. Manufacturers can shut down the illicit activity to avoid regulatory violations and lost revenue.
Adjusting to the new normal
The manufacturing industry has always dealt with disruptions. Once this extreme demand passes, another challenge will come along. We must throw old assumptions out the window.
While semiconductor manufacturers navigate the current situation, they can also build systems that will support them through other unexpected conditions. Situational control is not the goal; adaptability is. Supply chain visibility, automation and data analytics enable agility and informed strategies, regardless of what comes next.
This article was originally published in Supply & Demand Chain Executive.
