During the pandemic outbreak, global supply chains experienced several disruptions due to which demand and supply oscillations were a major problem over the past year. These disruptions prompted demand planners and supply chain leaders to adapt to a new normal, and consumers have had to face severe shortages of essential products. Businesses can stay future-ready and navigate these uncertainties by leveraging real-time data to predict demand spikes and take necessary actions. Hence, demand sensing is turning out to be imperative for businesses to thrive in the post-COVID-19 era. But the key lies in accurate data sharing between various supply chain nodes, failing which businesses cannot fulfill demand in real-time.
Machine learning and natural language processing enable businesses to analyze demand signals and analyze data much more rapidly than manual spreadsheet-based methods. Speak to an analytics expert to find out how you can benefit from ML and NLP.
What is Demand Sensing?
Demand sensing is a short-term demand forecasting approach that leverages real-time supply chain data and NLP to help businesses forecast demand based on the current scenario and existing realities of the global supply chain.
How Does Demand Sensing Differ from Demand Planning and Forecasting?
Demand sensing enables businesses to anticipate and plan for short-term changes in demand, whereas demand forecasting is more long-term. In short, it is a methodology that focuses on reducing supply chain lag by persistently reducing the time between the occurrence and response to events, i.e., demand fluctuations. As such, supply chain demand sensing aims to reduce the time between the emergence of a statistically meaningful mix of demand signals to the demand planner’s ability to respond intelligently to those demand signals.
How Demand Sensing Can Help Tackle Supply Chain Disruptions
Businesses can no longer rely on stockpiling methods to cope with unforeseen demand-supply fluctuations and inventory stock-outs. Quantzig lists the top three ways business leaders can tackle supply chain disruptions amid market turbulence by using supply chain demand sensing solutions:
Gaining insights into buyer behavior and responding to demand spikes in real-time
Customers today have various choices and expect products and services to be tailor-made to suit their needs. In such a scenario, working in real-time defines the ability of a business to satisfy the needs of its customers. Demand sensing empowers businesses to analyze demand fluctuations in real-time and reduce the latency of signals transmitted through the supply chain.
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Visualizing market trends and risks
Demand sensing enables businesses to analyze both internal and external factors that can impact demand drivers. Using these insights, business leaders can adjust forecasting and their product portfolios in accordance with market trends.
Utilizing data from diverse sources to respond on a granular level
Analyzing data stored in silos enables organizations to gain granular insights into factors impacting demand-supply fluctuations. By aiding this process, demand sensing opens a whole new realm of opportunities for fulfilling demand.
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With businesses gaining access to new data sources, the ability to aggregate, decode, and interpret data using analytics-backed solutions can drive supply chain demand forecasting accuracy. Adopting practical approaches to do so, enhances the agility to respond to supply chain disruptions efficiently, which is crucial for businesses to stay competitive in today’s digital age. However, businesses must understand that supply chain demand sensing is a short-term process that must be backed with a long-term demand planning and forecasting strategy.
