Forecasting Demand Accurately in the Age of Uncertainty

The impact of poor forecasting has been keenly felt by many companies in recent months. A prime example lies within the automotive industry. Anticipating a drop in consumer interest in automobiles during the pandemic, carmakers ceased ordering supplies of critical materials like semiconductors. This decision left them scrambling to produce new vehicles amidst a global semiconductor shortage when demand recovered faster than anticipated.

This is an extreme example, but it should serve as a warning to other companies: inaccurate forecasting can have enormous and long-lasting ramifications, from lengthy backlogs to dissatisfied customers. But what can shippers do to improve the accuracy of their forecasting at a time of constant disruptions, uncertainty, and change? Here are a few key steps every shipper can take.

Eliminate blind spots

Historically, some companies have experienced issues with certain regional teams being less on the ball than others when it comes to providing up-to-date supply chain data. This can make it harder for companies to evaluate big-picture trends or understand regional differences. Suppose the New York facility is experiencing a sudden uptick, for example, but the California branch hasn’t shared any data in some time. In that case, leaders at HQ may struggle to determine with any degree of certainty whether this is a trend they need to prepare for across the U.S. or if it’s confined to the East Coast.

Having a single hub through which all supply chain data flows can help companies avoid this problem and achieve total visibility. When data is automatically centralized, supply chain leaders are no longer dependent on the whims of individual managers. Ideally, the system used should also normalize data from disparate teams and regions to ensure that slight variations (like spelling and currency differences) don’t skew the results and muddy the accuracy of the forecasting.

Prioritize speed

While rushing can lead to mistakes, taking too long to aggregate and analyze data during the demand-planning process can lead to companies making decisions based on outdated information. This is especially risky at a time when the market is moving fast and staying agile and responsive is critical.

Having analytics and business intelligence tools in place that enable them to monitor data and trends and pass learnings on to business leaders in real-time will allow supply chain managers to improve the accuracy of both short- and long-term forecasting. With fresh data in hand, shippers can feel confident in their ability to pinpoint emerging trends and act proactively—rather than reactively—in the face of new challenges and opportunities.

Increase frequency

During calmer, more stable periods, supply chain managers might have felt comfortable running demand forecasts monthly or even quarterly. To navigate uncertainty and disruption, however, more frequent forecasting is a must.

Shippers can learn a lot from fast-fashion retailers and other manufacturers that have incredibly short market cycles. These companies typically commit to forecasting demand and updating their supply plan accordingly as often as twice a week. That way, if a trend proves to be a flash in the pan rather than a prolonged shift (or vice versa), they can rapidly pivot to avoid wasting time and resources.

Improve your forecasting capabilities today

When the only certainty is uncertainty, accurate forecasting may seem unattainable. But by using the right tools, sticking to a few tried-and-tested best practices, and taking steps to improve your agility, you can stay on top of a shifting business landscape—minimizing waste and ensuring you can continue to meet customers’ needs.

Discover the best in supply chain analytics and business intelligence tools. Contact CTSI-Global today to learn more.

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