Tegile IntelliFlash VMcentric Storage Provisioning

Demand forecasting is not a new concept in the supply chain. In fact, it’s often referred to as ‘guessing between the goalposts,’ and for the most part, that was right. Now, using algorithms that not only predict demand to drive forecasts but also incorporate external data sources and continuously learn and optimize the algorithm without intervention we have the ability to significantly reduce the size of those goal posts. Using AI we can improve the accuracy of our forecasts and then allow us to predict where and when those products should be deployed ahead of customer demand. The result? Improved forecasts, reduced freight costs, better customer service levels, and optimized working capital.

Join Chris Badger of ClearSlide as he leverages the latest research to frame the discussion around the next wave of sales process transformation — sales engagement insights, content recommendations, and AI.

Marketers know that relevance is a critical component to telling impactful brand stories that move audiences through the consumer journey. Artificial intelligence—when fueled by the right data—can help marketers create relevance and drive engagement at scale, amplifying their clients’ brand impact.

We’re witnessing an astonishing growth in the volume of information stored and processed in real time - now measured in zetabytes! As such, the world is well past the point where making sense of all this information is humanly possible and we need specialised tools such as AI/ML to reveal new intelligence and drive actionable outcomes.