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In the past, relations between suppliers and retailers may have grown contentious over as little as ten cents over a case of soda, and the cumulative effect of these little decisions are what managed the grocery retailer's business. Instead of making decisions on a unit price basis, retailers need to be looking at the total business. A change in management style is needed. The ability to share data and use analytics to improve joint decisions has the power to transform profit margins on both sides. In today's competitive markets, this new approach can make all the difference. Regardless of what industry you're working in, it's very likely that competition within your business's field has only become more cutthroat in recent years. Indeed, thanks to the boom in ecommerce and the increasing ease with which people can connect with each other all over the globe, markets have become increasingly crowded as businesses go to battle over their potential customers. The post-mortem activity is just as messy. The current methods of having subject matter experts get into a war room, going through multiple product consoles and logs to identify the cause of an incident with a lot of finger-pointing and passing the buck that is inherent in the process, is putting companies at a severe disadvantage. This article will highlight how deep machine learning-based, root-cause analytics and predictive analytics technologies are helping organizations dramatically prevent such incidents, reduce mean time to repair and save brand reputation.
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