The COVID-19 pandemic uncovered an unexpected production upheaval, catching many off their guard. With the sudden shutdowns, lockdowns and stay-at-home orders enforced, certain sectors experienced a surge while the other plummeted. The automotive industry encountered its first unique set of challenges as the supply chain slowed amidst consistent demand. However, in this period of reflection, a silver lining emerges like an opportunity for all the automotive sectors to pause, reassess, and formulate new strategies for inventory optimization and supply chain management as we further progress into 2024 with time.
In this blog, we will discuss the various practices that have proven to be the best for the perfect supply chain inventory optimisation for this year! So, let’s not waste any more time and get started to make your inventory more manageable.
Inventory Optimization Definition
To define inventory management, we first have to understand what an inventory does. Every warehouse has it to mainly store their products in a safe environment and be able to access them whenever needed. But more often than not, managing and optimizing such huge warehouses might be tough.
Inventory optimization involves maintaining the right amount of stock to meet demand and buffer against unexpected disruptions while avoiding wasteful surpluses. Ideally, inventory optimization is an agile practice that not only responds swiftly to risks and opportunities but also has the foresight to predict and prepare for them.
Types of Inventory
From the consumer’s perspective, inventory primarily consists of finished goods. However, for a business, inventory encompasses everything they need to stock, maintain, and replenish.
For a soup company, “inventory” could range from the seeds used to grow tomatoes to the fuel in delivery trucks. Viewing inventory management in this comprehensive manner highlights its complexity.
There are four fundamental types of inventory:
- Raw materials: This includes all items that eventually become part of the finished product.
- Work-in-progress (WIP): As the name suggests, this is all the inventory currently being prepared and packaged. This stage is expensive and risky, making it a prime target for inventory optimization solutions to find the most cost- and time-effective processes.
- Finished goods: This is the most commonly understood form of inventory, referring to products in their packaged, ready-to-sell state.
- Maintenance, repair, and operating supplies (MRO): These are the items necessary for the manufacturing, production, and delivery processes. Inventory optimization is applied to balance the surplus and shortage of these non-consumer items.
Challenges of Traditional Inventory Optimization
Balancing “just enough” and “not too much” inventory has always been a major challenge. Traditionally, demand forecasting has been a backwards-looking practice, limited by the capabilities of human analysis. As a result, linear supply chains powered by legacy systems remain vulnerable, regardless of expertise applied. Some common challenges include:
Legacy Systems
These systems cannot gather or manage big data effectively. Manual and non-connected technologies struggle with handling volumes of disparate and unstructured data. Smart technologies like AI, machine learning, and advanced analytics are crucial for achieving accuracy in risk prediction and demand forecasting.
Fast-moving Customer Demands
Consumer demand for speedy delivery and customized products grows annually, with shorter product lifecycles. Companies face high costs to ramp up logistics and supply chain networks to meet these demands, necessitating greater precision in inventory optimization.
Increased Competition
Industry 4.0 and intelligent, connected supply chain technologies enable businesses to set up and grow rapidly, managed from a central hub. This has intensified competition and consumer choice, prompting a higher demand for inventory optimization solutions to gain a competitive edge.
Weather Events and Natural Disasters
The frequency of debilitating storms and destructive wildfires is increasing. While these events cannot be accurately predicted, advanced analytics and cloud-connected solutions give inventory managers a fighting chance during periods of fluctuating demand.
Building on Fundamental Inventory Optimization Forecasting Processes
Inventory optimization challenges vary widely between businesses. For seasonal or B2B products, the process may be straightforward. In contrast, large retailers with thousands of SKUs face a highly volatile market and customer base.
While the fundamental practices of inventory optimization have remained unchanged for decades, software solutions have evolved to augment these processes. Even the most sophisticated digital systems are grounded in traditional inventory optimization protocols and formulas:
ABC Analysis
This identifies the most and least popular products and the most and least profitable ones. Traditionally done through past sales data analysis, advanced analytics and smart technologies now allow for better trend prediction and anticipation of inventory needs.
Demand Forecasting
Predictive analytics anticipate customer demand and predict trends or risks. Inventory management software now enables supply chain managers to minimize shortages and waste and more accurately forecast demand.
Materials Requirements Planning (MRP)
This system handles planning, scheduling, and inventory control for manufacturing. Legacy MRP systems are increasingly replaced by integrated business planning systems and demand-driven MRP (DDMRP) systems, offering greater accuracy and resilience.
Reorder Point Formula
This formula determines the minimum stock level before reordering. Traditionally complex due to varying reorder points for similar products, inventory optimization technologies maintain accurate, real-time inventory levels across multiple locations.
Perpetual Inventory Management
Particularly relevant for fast-moving consumer goods (FMCG), perpetual inventory management processes can be fully automated across omnichannel purchasing touchpoints. Machine learning enhances these tools over time, delivering live insights and stock status reporting.
Safety Stock and Inventory Buffers
Ensuring realistic inventory buffers to guard against the unexpected has always been a fundamental challenge. Modern supply chain software solutions bring speed, connectivity, and advanced data analysis to optimize buffer margins accurately.
Inventory Optimization Systems: Benefits and Outcomes
Historically, even small improvements in strategic inventory optimization could lower costs and improve profit margins. Integrated business processes and inventory management software now make these benefits more robust and measurable, continuously improving as the software learns and adapts.
Greater Business-Wide Visibility
Inventory optimization software enhances transparency across sales, marketing, accounting, raw materials suppliers, and global partners. Cloud connectivity allows all supply chain teams to collaborate in real-time.
Improved Demand Forecasting and Predictive Abilities
Smart technologies process complex data from various sources, delivering accurate predictions and insights. AI and machine learning-powered supply chain technologies make predictive analytics and demand forecasting more accurate and insightful.
More Sophisticated Optimization Outcomes
Smart systems analyze complex data sets, helping inventory managers identify profitable products, optimal locations for SKUs, and the best product combinations for different times of the year.
Scalability
Companies must scale up quickly due to success, growth, unexpected events, or seasonality. Smart software and modern databases are infinitely scalable, optimizing operations on a global scale.
FAQs: Supply Chain Inventory Optimization in 2024: Complete Guide
Is inventory optimization costly?
Inventory optimization can be costly due to the investment in advanced software, technology, and skilled personnel. However, the long-term savings from reduced waste, improved efficiency, and better demand forecasting often outweigh the initial costs.
How can I reduce the cost of inventory optimization effectively?
To reduce the cost of inventory optimization, leverage cloud-based software solutions, automate processes, use predictive analytics, and integrate supply chain systems. Focusing on data-driven decision-making can also enhance efficiency and reduce overall expenses.
Is a whole team needed for inventory optimisation?
A whole team is not always necessary for inventory optimization. Small to mid-sized businesses can often be managed with a few skilled individuals or by outsourcing to specialized firms. Advanced software tools can also minimize the need for large teams.
How to reduce the cost of inventory optimization?
Reduce inventory optimization costs by adopting cloud-based solutions, automating routine tasks, utilizing AI and machine learning for predictive analytics, and training existing staff on these technologies to minimize the need for extensive personnel.
Conclusion
Looking back on the chaos caused by COVID-19, inventory optimization stands out as a vital part of managing supply chains in 2024. Despite the challenges, there’s a chance for businesses to rethink and strengthen their strategies.
By using smart tools and strategies mentioned in this guide, companies can adapt better and plan. As we move forward, businesses need to consider modern solutions like those offered by Qodenext to keep improving how they manage their inventory.
