The State of Inventory Management for Distributors: A Demand for Better Forecasting

Last year, we surveyed large industrial distributors about their inventory management challenges. Only 19% said their inventory workflows had significantly improved from 2022 to 2023.

Has 2024 changed these numbers?

2024 Inventory Management Trends: Forecasting at the Forefront

In 2023, Sikich teamed up with Modern Distribution Management to scope out the trends largest distributors faced. We found:

• Distributors struggled with end-to-end visibility of their inventory.
• Only two-thirds said data on their inventory levels were 95% to 100% accurate.
• Just 21% said they had fill rates between 95% and 100%.

Large and mid-sized distributors often struggle with inventory visibility due to several factors:

• Complex supply chains
• Legacy technology
• Data silos
• Data inconsistency
• Human error
• Demand and supply chain fluctuations
• Returns management
• Global operations complexities

This year, distributors say they’re focusing on better visibility for greater operational efficiency, cost reduction, and customer satisfaction. From technology integration challenges with legacy software, to global uncertainty and its impact on the supply chain, not to mention growing use of multiple sales channels—this has grown more difficult.

There is a growing interest in integrated cloud solutions and emerging technologies to manage inventory more efficiently. Distributors must also adopt real-time tracking and analytics to improve visibility with inventory management.

This situation requires better forecasting. Enhanced inventory visibility provides valuable data that distributors can use for more accurate demand forecasting. Better inventory management forecasting helps these companies plan and align their inventory levels with market demand.

Forecasting Challenges in 2024 and Beyond

Distributors know they face several forecasting challenges that can significantly hurt operations. Here are some key challenges and risks of inaccurate demand planning:

Demand Variability

• Challenge: Planning around customer demand is hard due to seasonal trends, economic shifts and, in the case of 2024, an uncertain election year.
• Risk: Inaccurate forecasting leads to overstocking or understocking. Overstocking results in excess inventory, leading to higher storage costs and potential obsolescence. Understocking can result in stockouts, missed sales opportunities, and dissatisfied customers.

Lead Time Uncertainty

• Challenge: Variability in supplier lead times can complicate forecasting efforts. Delays in receiving goods can disrupt inventory levels and affect order fulfillment.
• Risk: Long or inconsistent lead times cause stockouts, forcing distributors to expedite orders at a higher cost or lose sales due to unavailable products.

Data Quality and Availability

• Challenge: Accurate forecasting relies on high-quality data from various sources, including sales history, market trends, and supplier performance. Incomplete or inaccurate data can lead to poor forecasts. It’s a problem that technology can remedy, but most distributors have data in multiple silos.
• Risk: Poor data quality results in erroneous forecasts, leading to excess inventory or shortages.

External Factors

• Challenge: External factors such as economic conditions, geopolitical events, and natural disasters can affect demand and supply chain stability.
• Risk: Failing to account for these factors can result in significant forecasting errors. For example, a sudden economic downturn can drastically reduce demand, leaving distributors with unsellable inventory. Distributors need to be able to change directions quickly.

Product Lifecycle Management

• Challenge: Different products have varying lifecycles, from introduction to growth, maturity, and decline. Accurately forecasting demand at each stage is difficult.
• Risk: Misjudging the lifecycle stage can lead to overbuying of declining products or underbuying of new, high-demand items, affecting profitability and customer satisfaction.

Promotional Activities

• Challenge: Promotions and marketing campaigns can temporarily spike demand, making forecasting challenging.
• Risk: Overestimating the impact of a promotion leads to excess inventory post-campaign, while underestimating can result in stockouts and lost sales during peak promotional periods.

Supplier Reliability

• Challenge: Supplier performance and reliability variability can affect inventory levels and forecasting accuracy.
• Risk: Inconsistent supplier deliveries can lead to either surplus inventory or shortages, disrupting the supply chain and customer service.

We now have the technology to mitigate many of these ongoing risks to master planning and operations.

Integrating new technologies and systems for better inventory management forecasting can be complex and resource-intensive. At the same time, implementation issues or system mismatches can lead to inaccurate forecasts. For example, if a new forecasting software does not integrate well with existing systems, it may produce unreliable results.

Enterprise distributors are living with risk each day they fail to leverage new technologies. AI-powered tools, for example, can create the kind of inventory visibility distributors long for. It’s bringing new tools to an industry struggling with a real-time view of supply chains and inventory. It’s also understandable that enterprise distributors admit to these challenges—their businesses are complex, with thin margins and high competition.

But upgrading is costly and time consuming. At the same time, there is a healthy dose of skepticism around AI; the question is—does it really live up to the hype?

Can AI Solve Distribution Forecasting Challenges?

Yes, AI-driven tools can address and mitigate many forecasting and inventory visibility challenges plaguing the distribution industry.

AI algorithms analyze large volumes of data, including historical sales, market trends, and other internal and external factors, for more accurate master planning. These tools can analyze supplier performance data to predict lead times more accurately and identify patterns or issues that could cause delays. AI can even recommend buffer stock levels or alternative suppliers.

Your data won’t hold you back from adopting these tools, either. AI tackles the muddied waters of data quality. These tools clean and standardize data from a variety of sources. An AI supply chain solution captures and integrates data from disparate systems. Data becomes the critical source of truth that distributors need for more accurate forecasting. An AI platform can do something similar with external data sources, incorporating economic indicators, weather patterns, and social media trends to adjust forecasts dynamically based on real-time information.

Let’s take Microsoft Dynamics 365 Finance and Supply Chain solution as an example. How could this work in your business?

Improving the State Inventory Management for Distributors

Microsoft applies next-generation AI to the supply chain visibility problem—from suppliers to customers.

This transparency helps identify potential disruptions and proactively adjust inventory plans.

Behind the scenes, Microsoft Dynamics 365 Finance and Supply Chain Management (Dynamics 365 FSCM) integrates data from various sources, including sales, inventory, procurement, and external data like market trends and economic indicators. This unified approach ensures that forecasts are based on comprehensive and accurate data. The system processes data in real-time, allowing for up-to-date forecasting and quick adjustments based on the latest information.

Once true visibility exists across the data, Dynamics 365 FSCM uses machine learning to analyze historical sales numbers, market trends, and external factors to generate accurate demand forecasts. The system can identify and account for seasonal patterns and trends, helping distributors anticipate demand fluctuations and plan inventory levels accordingly. The system calculates reorder points to ensure timely inventory replenishment, balancing the costs of holding inventory with the need to meet customer demand.

From a visibility perspective, Dynamics 365 FSCM provides the features you need to track supplier performance, including lead times and reliability.

Speaking of risk management, Dynamics 365 FSCM allows distributors to run simulations to understand the impact of different variables on demand and inventory. For example, the system can simulate the impact of promotions and marketing campaigns on demand, helping to ensure adequate stock levels during peak periods.

Finally, Microsoft Dynamics 365 automates various inventory management tasks, such as order generation, replenishment, and stock transfers, reducing manual effort and the potential for errors. The system can even identify exceptions and anomalies in inventory levels or demand patterns, triggering alerts and workflows to address these issues promptly.

How could this work in your business?

• A retail distributor can use Dynamics 365 FSCM to forecast seasonal demand for fashion items accurately, ensuring the right inventory levels are maintained throughout the year.
• An electronics distributor can leverage Dynamics 365 FSCM to manage the rapid lifecycle of products and forecast demand. The system tracks product launches, market adoption rates, and other data to adjust inventory predictions.
• Food and beverage distributors can forecast based on historical data, weather forecasts, and seasonal trends. Dynamics 365 FSCM can help minimize waste and ensure fresh products, optimizing inventory turnover and customer satisfaction.

While distributors worry that a lack of supply chain visibility hampers their demand forecasting capabilities, the tools exist to erase these inventory management concerns. Sikich can help by facilitating the deployment, customization, and integration of advanced inventory management tools. Call on our team today to finally gain the kind of supply chain visibility that will supercharge your business.