How AI Can Help Brands Get Ahead of Growing Inventory Issues4 min read
Table of Contents
What is AI?
If it suddenly feels like you’re seeing the term “AI” everywhere, that’s because you are. Whether it’s an app like Siri and Spotify, or a software solution related to supply chain optimization, AI has made a significant impact on the way that people streamline their personal and professional lives.
Artificial intelligence, or AI, refers to the programmed ability of a computer to perform tasks that were previously managed by humans. These tasks are extremely complex and typically require human intelligence and discernment.
With this definition, AI in the context of personal apps makes sense. For example, you may have once relied on your friends to recommend new artists based on your musical tastes. Spotify amplifies this concept of musical recommendations and automatically provides an even larger and more precise list of artists based on the historical data of music you’ve played. Similarly, AI is improving upon existing processes that were once performed by humans across the supply chain. There have been substantial innovations in the supply chain industry to improve everything from forecasting and inventory management to last-mile delivery, and with that, the creation and growth of new companies and spaces within the market.
The Growing Importance of a Digital Supply Chain
The recent COVID-19 pandemic has changed consumer habits, causing global supply chain weaknesses to be exposed. In addition to facing severe inventory challenges and financial uncertainty, brands are required to change the way they operate to accommodate remote work and its associated logistical challenges.
Even before COVID-19, businesses were searching for digital enterprise solutions that could streamline and optimize processes – not only to cope with volatile demand, but also to protect their supply chains from lasting disruptions.
Digital solutions provide businesses with tremendous value:
- Centralizing key information that once lived in disparate silos
- Automating time-intensive and manual tasks
- Providing greater visibility into inventory performance and where it’s stored
- Enabling remote cross-collaboration across teams
Digital solutions that incorporate AI specifically also provide businesses with the added benefit of being able to make more strategic decisions based on historical data or algorithmic recommendations.
How AI Can Help Reduce Slow-Moving and Excess Inventory
Slow-moving and excess inventory are inevitable. Even with the best planning solutions in place, there are uncontrollable external factors that can lead to the buildup of excess inventory. These factors can include market disruption, changing consumer trends and spending habits, unexpected weather, to name a few. Brands are implementing tools to help them manage and sell excess, but an even more cost-effective approach would be to proactively address excess inventory with strategy—before it’s even deemed as excess.
To fuel this sort of planning, businesses are seeking AI-powered solutions that can help them identify or even predict which inventory is at risk of eventually becoming slow-moving or excess (and when).
Digital solutions that utilize AI in inventory management can potentially provide value by:
- Creating simulations based on a set of criteria and recommend actions
- Providing teams with a real-time view into the supply chain
- Utilizing historical sales data, expiration dates, forecasting trends, and unique business data in combination to make strategic decisions earlier in the product lifecycle
- Selling more products in full price channel
- Freeing up capital tied to excess inventory
For any existing excess inventory, utilizing an AI solution for inventory management can help you understand the most effective way to offload that inventory depending on your goal (ie higher margins, transactional volume)—taking into account factors such as quantities, pricing, even which channels you sell the inventory into.
The Risk of Not Using AI
Inventory exponentially loses value as it ages and reaches the end of the product lifecycle. With no way to identify inventory that is expected to underperform, or no solution to manage inventory once it’s been deemed as slow-moving and excess, brands face an enormous financial burden and environmental responsibility. With excess inventory comes higher warehousing costs and more resources allocated to manage that inventory—time, effort, and money that could be allocated to other profitable areas of the business. As the products age, they also become more difficult to sell. As a result, many brands are often left with selling inventory into excess channels at a significant loss, or being forced to donate or even destroy goods.
Conclusion
With so many different types of AI inventory management solutions in the marketplace, brands now have the ability to optimize every aspect of their supply chain digitally. Slow-moving and excess inventory in particular, presents an excellent opportunity to utilize this type of technology. By incorporating AI into strategic decision-making, brands can identify slow-moving and excess inventory earlier in the product lifecycle and take proactive steps to strengthen their full-price business, reduce operating costs, and eliminate waste.
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