News and Articles

By Kaila Johnson

E-commerce has grown significantly across different platforms and changed how people shop for goods. Trends online can change very quickly and consumer behavior along with it. The majority of current forecasting models are time-consuming, and static and cannot adapt to the rapidly changing market. Supply chain companies need a more responsive method that can work in near real-time rather than after a trend may have already passed. The good news is that an advanced technology called causal-AI modeling can transform the way manufacturers to retailers uncover and forecast sudden product demand shifts in their marketplace. 

It can be difficult to predict when a product will get its well-deserved recognition after years of flying under the radar. Matcha, a popular coffee alternative, has been on the rise due to health benefits and, more importantly, the aesthetic of a green drink on social media. According to The Business Research Company demand for this drink is predicted to rise at a significant rate nearly doubling in global sales by 2030.

However, traditional forecasting methods often fail to properly account for similar emerging trends until it’s too late including any looming raw material shortages also on the horizon. This is where market sensing causal-AI modeling comes to the rescue by identifying and validating key root cause factors, automatically adjusting the forecast in concert with current consumer buying pattern changes.

Causal-AI machine learning is a branch of artificial intelligence that focuses on automating current explainable cause-and-effect relationships within data, allowing systems to not only predict outcomes but also logically explain “why” something happened rather than relying on simple correlations. In contrast, most forecast systems today focus on past historical results that minimally use basic reasoning modules. For example, as illustrated in figure 1. below, the application of causal-AI can help balance inventory management by ensuring that each warehouse is properly stocked with the right items at the right time to help satisfy customer demand, ensuring that tea aficionados can enjoy their own matcha latte, any time they desire.

In conclusion, it can be challenging when the time and effort spent crunching inventory numbers and communicating with suppliers does not keep up with TikTok fame. Instead of scrambling to satisfy the growing customer base, causal-AI can help by decreasing forecast reaction time, showing the impact that changing market trends have on a business’s results and automatically adjusting the current forecast to perfect the entire planning process.