Best Practice Demand Planning Meets Unprecedented Demand Volatility

Research shows how best practice demand planning contributes to the challenge of accurate forecasting in an era of global demand uncertainty


In the past few years, demand volatility has become a major focus area for supply chain managers at large process manufacturers. The economic uncertainty that followed the credit crisis in 2008 has led to unreliable purchasing patterns among consumers of finished goods, particularly in developed economies. This has had inevitable consequences on demand for raw materials further up the supply chain.  

However, the post-crisis spike in volatility is really the latest development in a long-term global trend, in which the economic power of emerging markets has pulled manufacturing eastwards to Asia. The partial transfer of manufacturing plants to the Far East has been driven, in large part, by the need to better manage changing demand with shorter supply chains and reduced logistics costs for customers in those regions. Even as the growth trajectory in consumption centers like China slows down, new markets in the Association of Southeast Asian Nations (ASEAN) continue to emerge and drive an even faster pace of change.

While businesses have been experiencing significant shifts in demand patterns, the supply of feedstock and other key materials has become notoriously volatile in the same period. Volatile demand and volatile supply are intimately linked in a circular causal relationship. But geo-politics, globalization and depressed economic trajectories in developed markets have all contributed to the problem.

The traditional model of comparatively stable supply and demand, with tolerable amounts of unpredictability, has been overturned with greater variability on both sides of the supply chain. Securing profitability has become more challenging and addressing the lack of clarity in the demand picture is now more challenging than ever.

Demand Planning and the Bottom Line

In this climate, constructing a feasible, constrained and profitable demand plan is essential. Without accurate demand forecasting, manufacturers can only be confident in their ability to meet demand if they rely on inefficient stockpiling of inventory: The emphasis is on “just in case” processes, rather than “just in time.”

Inefficient inventory management directly increases costs by using up capacity in production and storage facilities, and tying up capital in carrying non-productive stockpiles. Accurate inventory enables optimal production processes that minimize transitions and setups. It also empowers more efficient transportation and logistics operations in which choices are driven by cost rather than expedience.

The effects of inaccurate demand forecasting on the bottom line has now been demonstrated in research from Triple Point Technology. It shows that there is a dramatic correlation between investing time in developing effective demand management processes and improving forecasting accuracy. It also shows that demand accuracy can, in turn, have a major impact on business profitability.

The headline figures from the research show that:

  • Businesses can experience a 17-point average improvement in forecasting accuracy when adopting best practices and new technologies.
  • For every 1 percent improvement in forecast accuracy, businesses experience a drop in inventory levels between 1 and 2 percent.
  • As a result, firms can benefit from a 17 to 34 percent reduction in stored inventory.

When these numbers are applied to real-world examples with real-world budgets, the results are even more stark: A company with a turnover of $1 billion can expect savings between $5 and $10 million, and a company with a turnover of $20 billion can experience savings between $100 and $200 million.

These numbers translate to obvious benefits to most readers. Yet there are still other, secondary benefits that accrue from improved production processes and logistics. In reality, firms of all sizes can expect savings to exceed even these impressive results.

Defining Best Practice for Demand Planning

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