Successful Automated Inventory Replenishment starts with Change Management


Automated Inventory Replenishment Remi AI retail software

Rather than tackling your most difficult supply chain challenges first, it's best to begin your business' AI journey by handing over the most mundane tasks, to free your people to focus on what's most important.


As anyone who sells more than one product will tell you: when it comes to managing your supply chain, not all products are created equal. Often, a small number of high-profile products directly contribute to the lion’s share of revenues – the key value items. Others have less of an impact, but are still an important part of your wider offering and strategy, or are stocked because they turnover at a nice, regular frequency and complement your range.



Key value item, Remi AI retail software
Products tend to fall into different groups

This means stock levels for some products must be managed strategically to avoid expensive incidents which can impact your bottom line and reputation – from supply delays and stockouts to over-ordering.


Meanwhile, there are other products which you replenish like clockwork, simply going through the motions each month.


As more and more businesses look to adopt an automated AI decision engine, it is often assumed the first job for AI is to tackle those most challenging decisions. In fact, the opposite is true.


It might seem counterintuitive, but your first step should be to hand over those simple replenishment tasks. Remember, the idea of AI isn't to take people out of the loop. The idea is to ease the burden of mundane decisions, so your people can focus on what matters most.


Effectively implementing an automated AI decision engine is all about change management, which generally takes at least a few months. The idea is to start small, with a handful of frequently ordered but relatively inconsequential products.


Starting this way reduces the consequences if mistakes are made while bedding down your AI system. It also helps build trust around the decision-making before you hand it more important decisions.


For example, a number of Remi AI's clients are in the automotive spare parts space. They handle everything from spark plugs worth a few dollars right up to the engines of luxury cars, components worth thousands, which can be slow-moving parts.


Putting the Remi AI platform in charge of the regular spark plug replenishment frees up people to spend more time making strategic decisions about ordering those expensive engine components.


It’s important to note that even when it comes to spark plugs, you don't start by completely automating decisions. It takes time for orders to be processed and stock to flow.


At first, the Remi AI platform makes recommendations which must be approved by a person. This offers the chance to confirm orders and tweak the system where required.


Once things are running smoothly, the next step is for Remi to make recommendations which are automatically approved after a set amount of time - unless a person intervenes.


The final step is to automatically process recommendations immediately, unless they clash with your specified constraints, such as thresholds for the total value of an order. This way, you can still intervene when something is out of the ordinary.


For some,there is a misconception that an automated

AI decision engine is just a fancy rules-based system.

It is so much more than that.


As the name suggests, a rules-based system blindly follows the rules. Those rules must constantly be changed to suit market conditions, to ensure they deliver the right business outcomes. This requires constant maintenance, often to the point where time saved constantly making ordering decisions is instead wasted constantly making decisions about rules.


AI presents a vastly different opportunity: tell the AI your objectives and it makes the best decisions based on the current and predicted future conditions to reach those objectives. Rather than slavishly following the rules, AI can look at the big picture to ensure it's always delivering the best outcomes for your business.




Want to know more about inventory management and replenishment? Head here to find out how AI can help you avoid stock-outs, or here to learn all about the things you need to consider before implementing AI. You can also see our platform in action via our case studies - including how we helped a wholesale distributor reduce stock-outs by 24%.Once you’ve had your fill of content from our blog, why not drop us a line here.