7 ways to reduce costs through AI inventory optimization

By: Jul Domingo

The future is here. Cutting-edge technology has become an essential part of day-to-day business operations.

Firms with strong AI initiatives have reaped twice the benefits as those that don’t.

AI has led to a 54% reduction in costs and inefficiencies–a staggering half of the expenses they can divert to growth initiatives.

Introducing AI into your operations can contribute greatly to the success of budding and expanding companies. It works in various functions, but the best place to start is where most of your money goes: your inventory.

AI inventory optimization can help you overcome a slew of operational pain points. It can improve your processes, eliminate inefficiencies, and save costs. In this article, where you can use it in your operations and how it works.

Key areas where AI inventory optimization can help

Intelligent systems are a valuable asset in any retail environment. These are the key operations where you can efficiently use inventory optimization machine learning.

• Inventory monitoring. Knowing your inventory level 24/7 enables you to make smarter purchasing decisions. 1 in 4 companies (26%) uses AI to achieve this real-time inventory management. With real-time tracking and accurate forecasting, they can prepare replenishments or reduce holdings without overspending or underspending.
• Warehouse optimization. AI inventory optimization, like digital maps and tracking systems, can streamline warehouse spaces. A study stated that these tools facilitate the movement of goods from one point to another at the right time and place. This way, your team is less likely to commit costly logistics errors, such as mismatches in batch processing and order picking.
• Supply chain visibility. Forecasting, warehouse automation, supplier relationship management (SRM), and other tools offer supply chain visibility. 42% of firms find this crucial as it affords them to enhance their vendor sourcing and take timely actions when supply and demand shocks occur.
• Risk management. Businesses face internal and external risks (e.g., biased judgments, poor control, and economic downturns). AI inventory optimization can mitigate these risks with data and analytics. During a downturn, for instance, AI tools can help you decide on the optimal inventory investment with the lowest risk of loss. Less guesswork, fewer business risks.

If your goal is to reduce costs and risks, investing in inventory optimization machine learning is a good start.

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7 ways AI inventory optimization reduces costs and risks

AI isn’t a rocket; it only puts fuel into your inventory management. Observe your operations and identify which parts it can best assist you with. Here are 7 ways inventory optimization machine learning can help reduce operational costs.

1. It maximizes inventory investment
2. It eliminates manual work
3. It minimizes human errors
4. It reduces labor costs
5. It maximizes warehouse efficiency
6. It streamlines your cash flow
7. It improves order fulfillment

It maximizes inventory investment

Investing heavily in inventory doesn’t always give you the income you expect. Without proper guidance, it can result in excess stocks you can’t sell. You’ll have to drop prices or bundle your goods just to breakeven.

Purchasing too little, on the other hand, puts you at risk of running out of stock, affecting profitability and customer satisfaction.

Finding a good balance is a common concern among retailers. You must keep your shelves well-stocked, but without leftovers.

AI inventory optimization can identify the optimal inventory investment between these extremes. Because it’s sophisticated enough to detect errors and inconsistencies, it can understand data sets faster than humans and traditional record-keeping can.

For instance, Inventoro’s forecasting tool collects your past sales data to predict future demand. It then accounts for any promotions or seasonal sales that may alter their purchasing habits. With AI inventory optimization, you’ll only stock up on in-demand and profitable goods without going overboard.

By analyzing historical data, tracking real-time balances, and predicting future demand, you’ll have a better chance of forecasting how much inventory you’ll need for a specific period.

There are a lot of ways you can use inventory optimization machine learning to improve your bottom line. But as a business that sells merchandise, it’s most effective when you reduce inventory and maximize it.

It eliminates manual work

AI inventory optimization eliminates repetitive, time-consuming tasks. These tasks can sap your team’s productivity, resulting in low performance and operational delays.

They may even eat into your budget in the long run. Unmotivated employees cost the global economy $7.8 trillion.

Unless your employees are enthusiastic about encoding POs, punching sales, and auditing stock balances on Excel or paper daily, your company contributes to this statistic. You can avoid such losses by upgrading to advanced inventory systems.

In this case study, AI redirects employees to more vital areas as it relieves them of repetitive tasks. It also boosts their performance by reducing manual errors and providing accurate and up-to-date data. It also prevents bottlenecks (e.g., sudden stock shortages) before they occur.

One aspect of AI inventory optimization you should focus on is automated replenishment. Based on our observations, it can save you up to 20 hours of admin tasks per week.

Ordering from suppliers as needed is something you should do frequently. But you don’t have to do it manually. Platforms, such as Inventoro, handles all the manual and technical work, so you don’t have to waste hours drafting POs from scratch. It also includes order list suggestions you can export and send to suppliers.

Mundane, recurring tasks can take a toll on your business. Implementing inventory optimization machine learning in your operations can funnel your time, money, and human capital into growing your business.

It minimizes human errors

Humans make errors, but well-trained AI doesn’t. While some oversights are minor and tolerable, others can hemorrhage your funds. A smart system prevents and corrects such mistakes.

Inventory errors can arise at any stage of operation. The most common examples are erroneous encoding, shipment of wrong items, missed expiry dates, and Excel or manual forecasting errors. Their common culprit: manual recording and tracking.

AI inventory optimization not only takes care of the manual work, but also reduces forecast errors by 20% to 50%.

It doesn’t matter if it’s as simple as barcode scanning or as intricate as Inventoro’s forecasting automation. Inventory optimization machine learning can administer your processes and reports to help you stay on top of your inventory. The less human intervention there is, the lower the possibility of error.

As the technological age progresses, automation plays a more critical role in success. Make no room for mistakes, or limit such instances, with reliable AI solutions.

It reduces labor costs

The more your business grows, the more experts you need to help run it. You can start with a few salespeople. Yet if you plan to expand your product line and vendor sourcing, you’ll need to hire procurement experts.

Paychecks and salaries add up soon after. But not as fast if you have artificial intelligence on your team.

AI substitutes for your supposedly new hires, but it does far more than that. The automation of repetitive tasks increases workforce efficiency. As a side benefit, 39% of companies use it to mitigate labor and skills shortages.

Let’s say you want to identify your top-selling products and strategize your portfolio. An AI inventory optimization tool with product segmentation features is a great substitute for market planning experts.

For example, our tool analyzes each product’s movement and categorizes them as Winners, Chasers, and Losers depending on their sales performance. You won’t have to wait days or weeks to get your hands on the reports. You’ll know your products better, but faster and without bias.

Low staff availability can increase labor costs by over 5.5% in a year. Inventory optimization machine learning is cheaper; it has an average cost of $100 or less per month (Inventoro offers tiered pricing starting at $49/month). And there’s no long-term contract required. Most providers allow you to cancel at any time.

AI solutions are created with labor-intensive tasks in mind. So as it keeps labor costs low, it also ensures that performance and output are of the highest quality.

It maximizes warehouse efficiency

AI helps your warehouse staff to work more efficiently and accurately. 73% of companies believe warehouse automation works best when AI and humans collaborate. AI doesn’t do all the work, but it does enable your team to perform their best.

It knows how many stocks you have and where they are, as well as understands the flow of incoming and outgoing items.

These insights will help you maximize the space and layout of your warehouse. For instance, you can place the best-sellers near the shipping area to save time when picking orders.

You can integrate an inventory optimization tool with mobile devices, scanners, sensors, and asset location technology. Keeping all workers up-to-date prevents delays and omissions of tasks.

It streamlines your cash flow

With optimized replenishments and accurate forecasts, AI inventory optimization can help reduce cash outflows.

Investing in productive inventory allows you to maximize your returns. You can reduce, if not 100% eliminate, your holdings of slow-moving stocks.

The less stock you have on hand, the lower your storage and maintenance costs. That’s more money in your pocket.

Being smart and prudent with your inventory investments can keep you from running out of cash. You can pay your purchases and liabilities on time. Thus, avoiding costly interests and charges from your suppliers and other third-party vendors.

Cash flow forecasting can help release up to 20% of cash from your inventory. With our tool’s self-learning algorithms, it is easy to identify optimal balances, identify slow-moving stocks, as well as budget, plan, and forecast disbursements.

Businesses run on cash. You can keep yours going in the long run with inventory optimization machine learning.

It improves order fulfillment

Humans can only detect, but not quantify change. Artificial intelligence is capable of both.

AI inventory optimization is incredibly helpful in terms of responding to ever-changing customer demands.

AI tools can send real-time alerts on low stock levels, delivery delays, and emergencies. You’ll know what products are in stock, out of stock, in transit, and of good quality. Thus, you can avoid selling items that won’t meet your customers’ requirements.

This would prevent complaints and product returns from driving up your costs. On average, returns account for 16.6% of total retail sales. The frequent causes are what AI tries to solve: late deliveries, limited product selections, and unmet quality expectations.

Inventory optimization machine learning software like Inventoro lets you stock up on items your shoppers love the most. Product segmentation identifies best-sellers and clues you in on how to expand your product offerings. These AI-driven strategies can help you reduce returns.

Product returns and dissatisfied customers increase costs and reduce profits. So, use your AI initiatives to dump stock outs, low-quality products, and delayed shipments in your operations.

Reduce your operational costs with Inventoro

Technology is every business owner’s best friend. It can speed up operations, eliminate bottlenecks, and bring costs down to a minimum.

Start cutting down your operational costs with AI inventory optimization tools like Inventoro. AI overcomes the challenge of increasing sales while decreasing your stocks.

Maximize your investment, prevent errors, and reduce your expenditures. Get a demo here.