Demand sensing has fast become critical to a company’s demand strategy. Customers have become more and more accustomed to near-instantaneous order fulfillment. And companies are under increasing pressure to have their products ready to ship as soon as an order is placed — or better yet, to have already started the fulfillment process.
Demand sensing is the use of big data and machine learning to “sense” when customers will make a purchase prior to the actual sale. That way, you can get your products in the hands of customers right away. Big data and artificial intelligence (AI) made demand sensing possible, so it makes sense that investing in technology that incorporates the latest developments is key to successfully engaging in this practice.
It’s also important to understand what data is required. As with forecasting, demand sensing incorporates both historical and current data. But given its focus on short-term demand and rapid fulfillment, real-time demand signals are relied upon more heavily. These can include weather patterns, social media buzz, what else customers have bought or viewed, and even when they get paid.
In essence, demand sensing takes forecasting to the next level. To engage in it, you must do the same to your business by incorporating technologies that prioritize automation and AI-enabled data analytics.