Author: Tronserve admin
Wednesday 4th August 2021 11:20 AM
5 Common Inventory Management Mistakes — And How to Solve Them
For businesses in the fast changing food and beverage industry, having the perfect inventory levels to avoid excess and stockouts is a frequent yet elusive objective. Food wholesalers continue to feel evolving pressure from e-commerce and omnichannel:
• 70 percent of consumers are going to do their grocery shopping online by 2024
• This creates a $100 billion market and other channels to think about when forecasting demand
• 54 percent of grocery customers say product accessibility is more crucial than cost
• Customers visit two to three stores on average to do their food shopping, and expect to find customized offerings on the shelf
• 75 percent of wholesale suppliers say keeping up with new competitors, customers and channels including e-commerce is their greatest challenge in forecasting demand
Food-based businesses battling to combat complex, unknown demand patterns often turn to stockpiling as a strategy. Many are finding out that more is not always better.
Too Much of a Good Thing?
Stockpiling inventory to meet any predictable situation can create additional holding costs and affect profits. In a recent survey, in excess of 60 percent of retailers report having more than one month of inventory on hand, an increase from 2018.
But even with these record inventory levels, customer service levels are in fact falling. The same survey found that 77 percent of businesses had lost gross sales, and 27 percent of wholesalers missed sales of more than 4 percent, an 8 percent increase from 2018.
No matter how much products you have on hand, some missed sales are inevitable – the key is to develop a data-driven strategy for optimizing inventory levels. That’s an area many food-and-beverage businesses did not explored yet. They depend on elementary forecasting models or just trust their gut, instead of using data to make informed purchasing decisions. Food-based organizations can easily enhance customer service levels without the added cost of stockpiling inventory. It just takes some simple math and awareness of what NOT to do.
Here are the five common inventory management mistakes made by food-and-beverage demand planners, and how a much more streamlined, data-driven approach can help:
1. Not optimizing by product. Almost four in 10 businesses report challenges forecasting the lifecycle of individual products. And so, businesses take a blanket strategy and adjust levels across their total portfolio, rather than considering the factors that affect demand for each SKU. To create an effective service-level strategy, food wholesalers will need a comprehensive baseline forecast that builds in the nuances of individual items.
2. Not responding to customer preferences quickly enough. From gluten-free to keto-friendly, what’s popular today can quickly become tomorrow’s castoff. Cultural trends and purchasing preferences can cause quick shifts in the products and channels customers want to use. Not having a way to track these factors in real-time, businesses struggle to predict deviations from expectations and can end up inappropriately assigning inventory levels.
3. Inability to make seasonal adjustments. Altering product levels based on seasonality is an obvious, but often ignored, forecasting tool. Almost half (45 percent) of businesses say that guessing seasonal demand is a challenge. To take care of these swings successfully, businesses have to have an inventory optimization system that can create these adjustments and results in a better accurate forecast.
4. Not considering external factors. What happens to product demand if a sudden hurricane appears off the East Coast or a restaurant chain’s workers go on strike? Without a platform that considers macro changes in demand, businesses are destined to stumble on inventory optimization.
5. Not optimizing order frequency. To offset rising transportation costs, 63 percent of businesses are placing less, bigger orders. Without taking cost dynamics into account, however, businesses can turn out overpaying for products and ending up with more items than they need. Rather than holding more inventory, businesses need to consider all relevant costs to make more profound decisions about what – and when – to order.
Managing Demand with Data
As demand patterns become more complex, companies across the food industry are discovering that outdated forecasting models are no longer sufficient. Yet businesses have been slow to implement technology-based approaches, with 50 percent of wholesale suppliers reporting they have not used machine learning in their forecasting yet. Developing a measurement platform can yield significant outcomes for businesses, differentiating them in an industry which nevertheless relies largely on manual methods.
The accurate demand planning technology helps businesses to perform excellent modeling techniques, such as economically optimized replenishment cycles, cost of service analysis and safety stock cycle, so they can forecast with confidence for every product in their portfolios. Using the power of predictive analytics, these technologies empower businesses to produce accurate forecasts based on factors like:
• Customer demographics
• Sale price of items by transaction
• Item promotions
• Competitor information
Complimentad by the right support, these data-driven demand planning instruments can help businesses manage inventory levels more effectively, improve customer service and drive revenue growth. In an industry where customer demand is increasingly elusive, companies that leverage technologies to boost decision-making have a powerful advantage.
This article is originally posted on manufacturing.net