Managing inventory can be challenging for modern supply chain businesses. Buying trends change at the drop of a hat, technology is leading to a neverending surge of new products, and the market fluctuates from one hour to the next. However there are two tools that inventory-based businesses can use to best anticipate consumer demand for products and to inform inventory ordering habits: predictive analytics and demand sensing techniques.
Here’s everything you need to know about these two cutting-edge approaches to understanding customer behavior and market trends, and how you can use them to make smarter inventory decisions.
What are Predictive Analytics and Demand Sensing?
Predictive analytics and demand sensing are two distinct processes, but they work together, like two sides of the same coin, to help you best manage your inventory.
Predictive Analytics
Predictive analytics is focused on the future by looking at the past: it analyzes historical data to hypothesize what future buying demand might look like. What type of data does predictive analytics use exactly? It might incorporate historical sales data, trends and seasonality, and external factors that influence buying habits. Ultimately, predictive analytics allow you to form an educated guess about what consumer buying habits might look like for specific periods, anticipate surges in demand, and understand when slowdowns might happen.
Demand Sensing
While predictive analytics is forward-thinking, demand sensing is focused on the present. It uses real-time data and insights to provide a snapshot of current customer demand.
Essentially, demand sensing gives you a sense of what’s happening “right now” with your customers. For example, it can detect a surge in online orders for a certain product that’s happening in real time. These instant insights empower decision-makers to react quickly and adjust inventory allocation or production schedules to meet these changes in demand.
While predictive analytics is focused on long-term timelines and buying habits, demand sensing empowers you to make short-term adjustments to reflect real-time inventory needs. When used together, these two processes give you 360-degree control over your inventory, by providing you with the insights you need to order correctly.
How Can Predictive Analytics and Demand Sensing Help Your Business?
Both predictive analytics and demand sensing play critical roles in the efficiency of an inventory-based business because these processes give you essential insights into how your inventory is currently moving, and how it’s expected to move in the future. When used together, here is how these two techniques can help inventory-based businesses:
1. Understand demand patterns
Predictive analytics and demand sensing can be used to understand demand patterns and monitor them in real-time. For example, you can analyze historical sales data to identify recurring patterns and seasonal trends. This can then allow you to anticipate peak periods (like holiday shopping seasons), as well as periods of lower demand. With these insights, you can strategically stock up on popular items before the rush, and avoid overstocking during slower times.
Then, you can use demand sensing to monitor the accuracy of your ordering, and adjust it as needed. For example, if real-time demand is surpassing what you anticipated, you can adjust your ordering accordingly.
2. Identify shifts due to external factors
Inventory fluctuations are often fueled by external factors, which predictive analytics can take into account. These factors might include upcoming marketing campaigns, economic trends, and even weather forecasts. Then, as you use demand sensing to monitor your inventory in real-time, you can identify if your forecasts are aligned with your buying.
3. Improve customer satisfaction
When you better anticipate customer shopping habits, you can provide your customers with the best experience possible, by avoiding stock outs and long delivery times. Keep in mind that if an item is out of stock or has a longer delivery time than expected, a customer might choose to shop with your competitor. Research shows that nearly 60% of online shoppers in the US say that “out-of-stock issues” impact their shopping behavior.
4. Reduce excessive inventory costs
When you order too much inventory, you end up tying up valuable capital, and can incur unnecessary storage expenses. Predictive analytics and demand sensing can help you minimize excessive stock by giving you the data and insights you need to order the right amount of inventory.
5. Increase resilience
Today’s market is unpredictable, and businesses need to be prepared for challenging economic times. When used together, predictive analytics and demand sensing allow you to react quickly to market shifts and unexpected demand fluctuations. You can monitor your predictions against real-time insights, adapting your inventory strategies as you go, to make your business more resilient to disruptions, fluctuations, and delays. While supply chain operations normalized in 2023, outlooks show that there is still significant risk to the global supply chain in 2024 and beyond (due to things like policy and labor), and that resilience is still essential.
6. Better decision-making
While we’ve touched on this topic a few times, better decision-making is a powerful benefit in its own right. When you have the insights of both predictive analytics and demand sensing, you can make the best decisions possible for your company. By leveraging clear data into demand patterns and trends, decision-makers can make informed choices about purchasing, production, and resource allocation.
Implementing Predictive Analytics and Demand Sensing
While predictive analytics and demand sensing work together to give you a complete picture of your inventory, they are two distinct processes. Here are some tips to get you started with both processes in your organization:
1. Make sure you have the right data
Both predictive analytics and demand sensing rely on data, albeit different types of data. For predictive analytics, you need historical sales data and external market data, for example, while you need real-time insights for demand sensing. Ensure that your historical data is accurate and complete for your predictive analytics, and that you have the right systems in place to monitor your real-time inventory movements for demand sensing.
2. Choose the right tools and software
As you can likely surmise, tools and software are at the heart of predictive analytics and demand sensing. Today’s inventory and supply chain planning tools provide you with advanced forecasting models, data dashboards, and real-time insights, to give you instant access to the insights you’re looking for. They also integrate seamlessly with your existing systems (such as your ERP and CRM). With that in mind, look for tools that will support both your forecasting and real-time needs.
3. Set clear goals and KPIs
When implementing these techniques, set clear goals and key performance indicators (KPIs) to help you monitor your progress. For example, do you want to reduce stockouts by 10%? Improve forecasts by 5%? Having clear goals allows you to track progress, measure the success of your initiatives, and see how these processes are impacting your operations.
Both predictive analytics and demand sensing are essential for optimizing your inventory. By mastering both of these processes, you can make smarter inventory decisions, and ensure you’re providing your customers with the best service possible.
StockIQ: Supporting Your Inventory Management Needs
If you’re looking for a comprehensive solution to your inventory needs, StockIQ is here to help. StockIQ is an advanced supply chain planning suite that allows you to control inventory, simplify ordering, and improve forecasting. StockIQ’s user-friendly supply chain management software covers everything from demand planning to supplier performance.
Find out how StockIQ can overhaul the way you manage your inventory by contacting us today, or requesting a StockIQ demo.
