How Is Artificial Intelligence Used in Demand Planning?

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While many technological advancements have led to changes and progress in the global supply chain, there’s one tech development that’s currently reshaping the landscape: artificial intelligence, or AI. 

AI is already being used in several distinct aspects of the supply chain, from optimizing truck routes to automating things like warehouse packing and sorting. But AI is also increasingly used to anticipate stock and inventory needs, enhance forecast accuracy, and optimize inventory management. This is being done through AI demand planning.

AI demand planning is offering a new, more accurate approach to demand planning that can be done more quickly. As we’ll discuss, AI-powered systems can produce broader, more detailed insights into demand than previous methods. They can reduce the amount of manual labor that needs to be done and can even account for unusual scenarios.

Here’s everything you need to know about the use of artificial intelligence in demand planning and how AI is being used to enhance what we’re learning from demand planning.

The State of AI Today

Artificial intelligence has been exploding in popularity in recent years, and subsequently, it’s been reshaping and influencing many industries. The numbers show us just how rapidly this space is expanding: the AI global market is projected to balloon with a CAGR of 42% over the next 10 years, growing to a value of $1.3 trillion by the year 2032. 

AI is already transforming several different industries. Data shows us that the manufacturing industry expects to gain $3.78 trillion from AI by 2025, and that the banking industry is expected to earn $1 billion more in revenue in the next three years, thanks to AI. Additionally, further data has found that AI is mostly being used for product and/or service development, marketing & sales, service operations, and risk modeling and analytics.

As we’ll discuss shortly, AI is also leading to substantial changes in the supply chain, and in inventory-related businesses. 

The Traditional Approach to Demand Planning

To understand how AI is influencing demand planning and how it can best be deployed in this area, it’s important to understand what traditional demand planning typically looks like.

Demand planning is the process of anticipating future demand of inventory by using historical data and analytics. A day in the life of a demand planner might include things like reviewing and analyzing data, forecasting future stock needs, reporting, and managing inventory. 

Demand planning heavily relies on historical data and trends to predict future needs. For example, demand planners use past sales figures and trend data to make future predictions about what future inventory needs will look like. They need to consider both stable and “regular” conditions, as well as outlier and special conditions (such as changes in consumer behavior or market fluctuations). 

While there are already advanced data analysis and prediction tools available today to assist with demand planning, some companies still use manual methods of calculations. For example, many businesses still use spreadsheets for these mission-critical figures, with 60% of businesses saying they rely on Microsoft Excel for demand planning. 

While every business’ approach to demand planning is different, it is possible for it to be challenging and time consuming if approached manually, without advanced tools. For example, calculations and analysis can be difficult to conduct manually with full accuracy, and it’s possible for people to miss insights from data that advanced systems can easily detect. 

Advanced tools have already been in use in the demand planning space for some time, such as inventory analytics programs, and these tools have already automated many aspects of demand planning. For example, demand forecasting tools already can generate sophisticated forecast hierarchies, generate more accurate forecasts for special events, and will automatically incorporate adjustments for future promotions. 

Today’s AI demand planning tools are further enhancing the abilities and processes surrounding demand planning, and are building on the advanced tools that are already available. 

AI in the Supply Chain

It’s not just AI demand planning: artificial intelligence is transforming many aspects of the supply chain. Experts already say that “AI is reshaping the supply chain,” and that it could lead to a “once in a lifetime kind of disruption” in this industry. 

Here are some areas where you can already see AI in the supply chain, aside from demand planning:

  • Inventory management

AI-driven algorithms can optimize inventory levels in real-time, considering demand fluctuations, lead times, and supplier performance.

  • Route optimization

AI-powered route optimization can help companies plan more efficient delivery routes, potentially reducing transportation costs, fuel consumption, and delivery times.

  • Warehouse automation

Robots and machinery powered by artificial intelligence can be used for tasks like packing and sorting in warehouses. 

  • Predictive maintenance

Artificial intelligence can be used to predict when systems and equipment will require maintenance or even when they might fail. This can be used to proactively schedule maintenance and to reduce downtime. 

  • Supplier selection

AI can be used to assess supplier performance and can identify the potential risks and benefits of each supplier.

  • Customer service and chatbots

AI-powered chatbots and virtual assistance can improve customer service by providing real-time support for tracking shipments, resolving issues, and answering queries. 

AI’s Role in Demand Planning

While AI is widely available across the supply chain and inventory-related businesses, it’s playing a significant role in demand planning. One recent survey identified “AI as the technology that will have the largest impact on demand planning in the next seven years.” AI has introduced a new level of sophistication and accuracy to the process, addressing many of the limitations or restraints that demand planners might have encountered in the past.

Here is a deeper look at the role AI is playing in demand planning:

  • Advanced data analytics

AI brings advanced data analysis capabilities to demand planning. Machine learning algorithms can process vast datasets, including historical sales data, market trends, consumer fluctuations, and more. This can allow for a more comprehensive and dynamic understanding of factors which might impact demand and can lead to more advanced and accurate insights. 

  • Predictive modeling 

AI uses predictive modeling to forecast demand, and these models can identify complex patterns and distill insights from data which humans might overlook. By continuously learning from new data, AI-driven models can adapt to changing market conditions, take irregular factors into account, and can improve forecast accuracy over time.

  • Real-time insights

AI provides real-time insights into demand patterns. This can be particularly crucial in today’s supply chain, where demand can rapidly change, particularly when it comes to certain industries (such as fashion or consumer electronics). Businesses can make rapid, data-driven decisions, and can quickly adjust production, ordering, and inventory levels as needed. 

  • Demand sensing

AI can power more advanced demand sensing, which involves detecting demand signals as they happen, to adjust based on short-term fluctuations. This can be especially useful when products have short product lifecycles or frequent promotions. 

  • Distilling answers from data

When it comes to demand planning, AI-powered software provides you with insights and answers, instead of just data. For example, it can help you understand what you’re going to sell, what you’re going to buy, what hasn’t shipped, and what your most important items are. These tools can also help you quickly understand if you’re meeting service level targets, and if your inventory is turning. 

AI demand planning allows for accurate data and insights in real-time, which can be used to ensure that stock and inventory-related decisions are as accurate and optimal as possible. 

StockIQ’s Intelligent Supply Chain Planning Solutions for Next-Generation Businesses

If your inventory-based business is looking for an intelligent supply chain planning solution, we’re here to help. StockIQ is a supply chain planning suite targeted at 3PL’s and distributors, which provides you with the advanced features you need to run efficiently, improve forecast accuracy, and reduce inventory levels.

Let us help you with your forecasting, replenishment, inventory analytics, supplier tracking, and promotion analysis, so you can focus on providing unmatched service to your customers and shippers. Contact us to learn more.

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