The impact of artificial intelligence (AI) on retail continues to grow, finding its way into enabling better processes and outcomes throughout the industry. With the power of AI, retailers can make major improvements to the customer experience, in-store features, and more. Lots of pieces have been written about AI’s effect on these aspects. Now, it’s time to shine the light on the impact of AI and the supply chain
A retail supply chain is a complex ecosystem. It’s been known to be fragmented and disjointed. This puts a strain on cash flow, customer service, and operations. No wonder it’s so in need of something as potent as AI. Here’s an inside look at AI and the supply chain.
One of the biggest challenges with supply chains has been that data was isolated in different systems. There was nothing aggregating it together, so it was impossible to analyze it holistically. Consider all the different data sets—order management, inventory, shipping, warehousing, e-commerce, and transportation.
Having an engine to integrate all this data brings insights, the first being where inventory is actually located. This allows for better inventory planning and when coupled with historical sales data, you are likely to prevent out-of-stock situations as well as excess inventory. Better decisions can be made with the full picture.
Where does prediction take your brand? Being able to learn and predict future buying patterns has the ability to alter the way products are developed, sourced, and sold.
Integrate AI and the Supply Chain from the Start
This ability is also necessary as demand becomes more real-time. Retailers have to think about AI and the supply chain during the initial stages of planning. AI handles large pieces of data and spots trends and provides recommendations. This isn’t, however, done in a vacuum. Ultimately, AI enables humans to make better decisions.
When retailers monitor POS data in real-time, they can then use this to predict demand. These demand forecasts can be compared to real-time demand. When deviation is detected, forecasts or future replenishment can be adjusted. These adjustments are then disseminated across the supply chain to trading partners in real-time around the clock considering the cost of change and the propagation impact.
Demand Signals Become More Visible
One critical part of the influence of the marriage of AI and the supply chain is the availability of better insight on demand signals. Previously, the transaction was the first and only demand signal. Then the wheels start turning—is the product available? What if supply chains could have more of a jump start? Well, this is no longer an if—AI makes it possible.
The key is data that indicates the probable demand for some particular item. What are consumers searching for either by traditional search or through their digital assistants?
AI can capture this data and use it to make more informed decisions on what’s needed. Your supply chain gets a dose of clairvoyance.
Consider the ability of Amazon to collect data from questions asked to Alexa. If a consumer is asking Alexa about specific types of window coverings, it may infer that the supply chain will need more of the types the user asks about. These little signals build to create a full picture of predictive analysis in supply chain management.
Reducing Costs throughout the Supply Chain
When talking about AI and the supply chain, one of the primary benefits is cost reduction, which is something every retailer wants to hear. How does AI cut costs? First, it makes almost every part of the process more efficient. It can reduce redundancies that normally wouldn’t be identified. Another benefit of the union of AI and the supply chain also helps with risk mitigation. The “knowledge” that AI brings to the table also influences forecasting with the benefit of those being more on target because predictions are better.
Finally, delivery and logistics can be improved with AI. Routes are optimized to determine the lowest cost, most effective solution. This does require an investment in updating IT systems and removing data silos. The foundation of technology and connections has to exist before benefits can be reaped.
Intelligence in logistics reduces lead times and transportation expenses. What makes AI in this part of the supply chain so intriguing is the emergence of autonomous vehicles. The impact of a full-scale fleet of these types of vehicles would revolutionize logistics. After all, drivers can only be on the road 11 hours per day; these restrictions don’t exist with autonomous vehicles. It would actually double the output of the U.S. transportation network at only 25% of the cost.
Items May Never Be Out of Stock Again
AI closes the loop between in-store and e-commerce to create a supply chain term, the endless aisle. This concept allows a customer to purchase something from a store even if it’s out of stock at that location.
For example, any retailer can set-up kiosks in-store to help shoppers find what they need. If the store doesn’t’ have their size, they can see that the one across town does. Or, the consumer can order it to be delivered. This process dictates the supply chain. Whereas before, maybe the store could have tracked it down and been able to get the item shipped to their store, which wasn’t efficient. With a kiosk that has real-time inventory information, if an item is available it can be found easily and routed to the buyer.
Automation Via Chatbots Streamlines the Process
Chatbots have become a popular tool for retailers, but they can do more than handle customer questions. Through an autonomous chatbot, data sets can be accessed and enable a better procurement experience. Here are some examples:
- Use a chatbot to set and send actions to suppliers related to regulations or compliance
- Submit purchase requests
- Answer certain questions about procurement functionality
- Receive invoices, payments, and requests
Warehouse and Inventory Management
Inventory is a recurring aspect of the supply chain that keeps coming up because it’s crucial for revenue. You have to have the right products in the right channel at the right time. A big part of that is where is the inventory and is it in the right place.
Demand forecasting, especially when enhanced by AI, should be on the mark, but there are always those outliers that cannot be accounted for. A forecasting engine that is “learning” keeps looking at the data to find the combinations of algorithms that are deemed to be the most predictive power. This is an endless cycle of forecasting, which is always self-improving and “learning.” This new way to look at inventory will be the major catalyst in what warehouse management of the future will look like.
The AI Retail Revolution Is Here
The nature of AI and the supply chain will evolve—part of that evolution is tied to consumer in-store behavior. POS data is a goldmine. If you’re curious about how CB4 helps retailers tap into it, you can request a demo , followed by a proof of concept in as little as 24 hours.