How Demand Sensing Can Help Businesses Thrive in the New Normal

As a customer-centric business, how often can you effectively meet demand?

You may have missed out on revenue and sales opportunities because of a lot of fluctuations in demand.

At times, you would have found it difficult to predict customer behavior and accurately forecast demand.

What has caused changes in customer behavior and buying patterns?

Customers today are well-informed and aware of the larger macroeconomic climate, because of a series of unforeseen events in recent years. On many occasions, they have had to stock more stuff at home than usual.

Not surprisingly, their buying patterns have evolved in a short span of time.

In addition to economic uncertainty, geopolitical conflicts and extreme weather events have aggravated their concerns.

But it’s not just these larger macro events that have caused fluctuations.

Even simple product reviews or conversations on social media have contributed to sudden changes in demand, as customers are influenced by how people perceive a brand or product and talk about it online.

To thrive amid such an uncertain environment as well as stay competitive, companies need to better understand changes in customer buying patterns. They also need to have a system in place to accurately forecast demand.

Additionally, they need to have speed and agility to be able to respond quickly to demand fluctuations. No longer can they rely merely on stockpiling inventory in such cases.

How can they succeed in these endeavors? What data do they need to accurately sense demand?

An accurate demand forecast is crucial not only for supply chain and inventory planning but also for stakeholders to determine budgets, capital expenditure, capacity planning and resource allocation.

How Demand Sensing Technology Works

AI-powered supply chain software has enabled businesses to engage in real-time demand sensing by processing and analyzing data aggregated from different parts of the supply chain.

As it works with real-time data, demand sensing takes place in the short term, allowing a business to make quick adjustments.

By leveraging AI and machine learning, demand signals from internal and external sources can be aggregated, cleaned and analyzed more rapidly than ever before.

Clearly, data sharing between different nodes of the supply chain is key to accurately sensing demand. This requires real-time collaboration between a business, its suppliers and customers.

Demand Forecasting Vs. Demand Sensing

Traditional demand forecasting relied heavily on historical sales data and regular purchasing cycle information.

However, with too many moving parts, it cannot provide the accuracy needed in today’s fast-changing market conditions.

As a result, many companies have replaced traditional demand forecasting methods with technology-driven and more accurate demand sensing solutions.

Estimating the demand for goods and services is a science that is becoming more precise with demand sensing, suggests a GEP and Spend Matters white paper. This is a more effective approach than traditional forecasting because it relies on more up-to-the-minute information for real-time accuracy, the paper adds.

The introduction of machine learning and algorithms in the demand prediction space is producing data that is more far-reaching, reliable and real-time than ever before.

Powerful machines can run dozens of algorithms in parallel and allow the system to choose a more accurate prediction for a particular geography, customer segment or buying channel.

Although demand sensing still needs historical data to make base assumptions, it can foresee the impact on future supply and demand more accurately from multiple variables including weather events, economic indicators, social media trends and change in public sentiment toward a product or process.

It can draw data from market events and integrate this data into the forecasting model to make accurate short- and long-term predictions.

The Need for a Cloud-Based Solution

Demand sensing technology solutions help businesses build agility to react quickly to market events. These solutions broadly collaborate on order pipelines, product lifecycle management and marketing efforts. But how do they provide accurate results?

Modern demand sensing solutions can harness the power of cloud computing to access more data and respond with more speed and accuracy.

For different market conditions, they can produce varying outlooks and levels of granularity.

For example, a forecast of up to two years may need less granularity.

But the level of granularity must increase as the timeline to the event approaches. Granularity should change from months to weeks and days based on predictions from category level to product group and down to SKU level.

Demand Sensing is Vital for Instant Gratification

For millennial and Gen Z consumers, buying a product on an ecommerce platform and having it delivered the same day has become routine.

In a digital age where products can become instantly popular (on social media channels, for example), companies must leverage advanced demand sensing technology to meet customer expectations.

Not only can this boost revenue, shorten lead times and enhance brand value, but it can also provide the much-needed edge in an increasingly uncertain yet competitive business landscape.

To learn more, download our white paper Making Sense of Demand: How to Enhance Forecasting Accuracy With Demand Sensing Technology.