- Circana
- 21 minutes ago
- 8 min read
For manufacturers, one of the most common blind spots in their supply chain management is consumer behavior. Even if your retail partners share sales and performance data, it can be difficult to predict how a sudden change in consumer demand could impact the efficiency of your supply chain. Understanding demand fluctuations is key to optimizing your supply chain and making the right decisions at the right time. With the right data partner and platform, it is possible to both predict potential demand fluctuations and have the infrastructure in place to effectively navigate them when they crop up.
What Causes Demand Volatility for Supply Chain Management?
Seasonality
The time of year can significantly influence consumer demand, particularly for seasonal products. Changing temperatures, upcoming holidays, and special occasions can all contribute to fluctuations in demand. While some elements of seasonality can be predicted, it can be difficult to predict demand down to the product level. For example, you can expect an increase in consumer purchases around the holidays, but it might be unclear how much extra product needs to be provided to retailers without clear data on both existing trends and predictions for this season.
Product Life Cycle
Products go through a life cycle that includes introduction, growth, maturity, and decline stages. Each stage has its unique challenges and opportunities for your supply chain management. As it goes through each stage, the demand for a product can change and impact supply chain activities. By getting data from your retailers, manufacturers can better understand volume changes at each stage of a product’s life cycle and plan accordingly.
Price Sensitivity
Many factors can contribute to price sensitivity. Price sensitivity often shakes up existing patterns, as many shoppers who may have been loyal customers regarding certain brands or products change their shopping behavior as prices rise or, rarely, fall. As a supply chain manager, you must be aware of these price trends and adjust your strategies based on consumer behavior data.
Economic Concerns
Tariffs play a significant role in shaping the market, as they directly impact the cost of goods and materials. Recent changes in tariff policies have led to increased costs for imported raw materials. Of course, these increases have a ripple effect throughout supply chains and cause increases in pricing that are shared between suppliers, manufacturers, retailers, and consumers. You need flexible planning and real-time data to ensure you are making the correct decisions for your supply chain.
How Can Manufacturers Use Supply Chain Data Effectively?
Measuring performance across retailers and manufacturers can help provide both groups with the data they need to make the right decisions regarding consumer demand. For example, with the right data partner, you can understand your on-shelf availability and gain insights into out-of-stocks and their impact on your revenue. When it comes to supply chain data, the most important elements are granularity, expediency, and visibility.
Through work with a supply chain data platform, retailers and manufacturers can share the same data, ensuring they speak the same language. And with those shared tools, both groups have access to granular data so that they can improve on-shelf availability and optimize the rundown of discontinued items. These tools can help you prevent out-of-stocks, reduce waste, and align with retail partners on timely replenishment.
With visibility across the entire supply chain from distribution centers to shelves, you can see the complete picture and respond to shifts in consumer demand effectively. For example, if you know that holiday gift-giving increases demand on your supply chain, you can use tools like these to accurately forecast the specific timing of your seasonal sales through your retailers and optimize your product staging locations and delivery scheduling. Working in partnership with your retail customers drives further efficiencies as they can be prepared for your adjusted plan.
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What Are the Challenges for Manufacturers/Retailers Regarding Supply Chain Data?
Data Access — Getting Cross-Retailer/Distributor Data
In the world of supply chain management, data is crucial for informed strategic planning and decision-making. However, it can be a challenge to get accurate and comprehensive data, especially as a manufacturer. When you work with a large network of retailers, you need to rely on them to provide store-level data, and you have to work on organizing data from a variety of disparate sources. Missing and incongruent data from different retailers can make it difficult for manufacturers to see the full picture when managing their supply chains.
Data Amount — Too Much Data Leads to Slow Decision Making
With the rise of e-commerce and omnichannel strategies, the amount of data available to retailers and distributors has significantly increased. And while more data can mean more opportunities, it can also cause issues if you do not have a reliable way to pull in all the data, organize it, and clearly see valuable data trends. With the right supply chain data analysis tools, you can make informed decisions about product management, inventory restocks, future marketing promotions, and other crucial business operations. However, without the right data environment, it can be easy to get overloaded with too many data sources. This can often lead to manufacturers being unable to sift through data fast enough to get the insights they need when they would be most effective.
Data Analysis — How to Draw Insights from Data
Data analysis involves the process of collecting, organizing, and interpreting data to uncover trends, patterns, and other valuable information. By understanding the potential insights hidden within data, you can make strategic and informed decisions that can significantly impact your bottom line. This is essential from the first stage of product development to logistics and sales operations. Investing in a modern supply chain data platform can transform your ability to efficiently transform data into actionable insights.
How Can Modern Supply Chain Data Platforms Help Manufacturers and Retailers?
Harmonize Data
Managing data in categories and priorities can help supply chain managers make informed decisions. With cross-retailer insights enabled through data harmonization, you can gain a complete view of your entire supply chain operations. By combining the data from different retailers with your own data, you can clearly see trends in what is causing out-of-stocks and the shelf-level impact of those out-of-stocks. By comparing retailers with standardized metrics and product hierarchies, you can make supply decisions that consider in-stock conditions across your entire customer base, along with the unique requirements of each retailer. Communicating current conditions ensures that you are on the same page with your retailers regarding replenishment rates. Having all your information in one place makes it possible for you to quickly identify incoming changes in consumer behavior and make necessary adjustments to streamline operations.
Leverage Consumer Data
Consumers are the leading force in today’s market, and their purchasing behaviors, demands, future trends, and preferences are crucial for supply chain management. Gathering this data in real-time gives your company the advantage of reacting quickly to market changes and staying ahead of its competitors. With the help of advanced analytics tools, manufacturers and retailers can leverage consumer insights to make informed decisions regarding inventory management, demand forecasting, and distribution strategies. This enables companies to meet customer demands effectively while minimizing costs and maximizing profits.
Understand your customer
Manufacturers supply many different types of retailers, from traditional brick-and-mortar grocers to pure-play e-commerce retailers and convenience store chains. To further complicate things, most retailers today have a hand in more than one of those channels. It is critical for data analytics partners to have experience working with supply chain data for retailers. Understanding the unique needs of each channel, or the impact of different order fulfillment methods on the data, results in data structures and reporting capabilities that serve those needs most effectively. What works best for a distribution center fulfilling thousands of orders for a large region will differ from a regional grocery chain with in-store fulfillment or using dark stores to fill local orders. Broad-based supply chain analytics intended to cover every industry possible usually don’t have the expertise to deliver efficient analyses for retail partners.
Benefits of Supply Chain Data Platforms
Fast Access to Actionable Insights
With these platforms, you can get real-time updates and future forecasts on inventory levels, consumer behavior, and market trends that help you identify potential risks and opportunities. Having visibility to spikes and drops in sales, down to the individual SKU level, while also being able to see regional trends in audience preferences, can help you make the right decisions at the right time for your supply chain.
Complete Visibility
With the right tools, you can gain a comprehensive understanding of your entire supply chain with a harmonized, omnichannel approach. By integrating all data sources and systems, manufacturers and retailers can track every step of the supply chain and identify any potential bottlenecks or inefficiencies. This level of visibility enables proactive planning and decision-making, enhancing the overall performance of your supply chain. Adjust inventory levels, shipments, and production schedules daily to keep pace with changing demand and ensure your network operates at maximum efficiency.
Improved Collaboration Between Retailers and Manufacturers
With the latest advancements in supply chain data analysis, collaboration between retailers and manufacturers has become easier and more efficient. Real-time communication systems and reporting enable retailers and manufacturers to easily collaborate. This leads to better planning, forecasting, and decision-making. As a retailer, you can now easily communicate your inventory levels, sales data, and industry-wide contributions to your manufacturers every day, which allows them to adjust replenishment schedules accordingly. Goals and custom metrics can be shared so that everyone is on the same page. When challenges arise, partnerships incorporating shared data visibility generate faster resolutions as the information necessary is already available to both sides and pathways exist to implement changes quickly.
How Can Circana’s Supply Chain Data Platform Help Your Business Address Demand Volatility?
Our platform delivers complete supply chain visibility by harmonizing data across retailers, categories, and channels in one flexible, collaborative environment. Your team can create custom reports, visualize current trends, and automate insights for faster, smarter decisions. Circana’s complete data provides retailers and manufacturers with a holistic view of consumer behavior. Beyond our supply chain data platform, Circana can help your team understand the driving forces that impact demand fluctuations. As experts in consumer behavior, our solutions can be paired together to help brands create demand forecasting models, identify key market drivers, and compare forecasts to actual results, so that you can optimize inventory, improve availability, and respond quickly to market changes.
Frequently Asked Questions
What Is Demand Volatility?
Demand volatility is a major challenge for supply chain management. It refers to the unpredictable fluctuations in customer demand for products or services, which can have a significant impact on the entire supply chain. Demand volatility can be caused by various factors that depend on the industry, market trends, and consumer behavior.
How Does Demand Forecasting Work?
Demand forecasting works by combining historical weekly sales data with other market drivers, such as promotions, media spend, pricing, and seasonality, to generate automated, best-fit models. Demand forecast platforms quantify the impact of each variable, enabling users to adjust inputs, run scenarios, and observe how different drivers affect demand. Forecasts can be customized or automated, aggregated across categories, and compared to actual sales. This enables your team to proactively align production, inventory, and promotional planning with anticipated consumer behavior.
What Is a Coefficient of Variation in Supply Chain Data?
The coefficient of variation (CV) is a statistical measure that is commonly used in supply chain data analysis. During the forecasting process, it is crucial to understand the variability of data to make accurate predictions. In supply chain data analysis, the coefficient of variation can be used to assess demand patterns and identify potential risks. A high CV indicates that there is a significant variability in demand, while a low CV suggests stability in demand.
