7 key advantages of AI-based demand planning

In a world that is becoming increasingly complex and volatile, it is easy to lose sight of the big picture. Particularly in demand planning, where huge amounts of data come together and things can get very complicated very fast. Artificial Intelligence can help tremendously here, especially when it is combined with human expertise.

If you've always wondered how AI can help you with demand planning, today is your lucky day! We have summarised the 7 most important advantages that AI-driven demand planning has in store for you.

1. "Au revoir" manual and time-consuming demand planning processes

Do you know that feeling when the forecasts for the next quarter are due again and you have to prepare figures for several weeks before you even have the optimal starting point for a reasonable demand planning process? With artificial intelligence, all this happens at the push of a button! A good AI ensures that all data can be put into the right structure and analyzed in a couple of minutes. The time-consuming data preparation processes are thus handled by the AI which frees you up time for more important things.

2. Accurate forecasts at all levels

Demand forecasts are the optimal foundation for all important decisions along the supply chain. It is therefore even more important that these are as precise as possible and are updated frequently. AI brings enormous advantages here because it not only saves time by autonomously selecting suitable forecasting methods for the corresponding product levels, but also by automatically combining those. This brings a unique forecast model for each individual product without doing everything manually. Say"au revoir" to tedious forecast modeling.

An increase in forecast accuracy of only 15% can lead to an EBT improvement of up to 3%.

3. Consideration of external and internal data

Probably you know roughly which internal data impacts demand. But what about external data? Not every AI can do it, but the one that is good manages to identify clear causal relationships between demand patterns and external effects. Moreover, a good AI can automatically include the corresponding data into the forecast creation. And here we are not only talking about seasonality, such as the winter and summer season, but also about sector-specific price indices, mobility data, economic data and many others. Imagine how long it would take to figure all this out manually. Clearly, it would take a very long time.

4. Rapid responsiveness to fluctuations

Black Swan events can rapidly change many things. The Covid-19 pandemic has proven it quite well. The demand for certain products has changed tremendously in the last two years and is still doing so. Automated analysis of the changing demand leads to a faster response to fluctuations and more proactive planning. The ability to automatically identify causal relationships between demand and external effects provides an enormous advantage against competitors, both in terms of profitability and customer satisfaction. 

5. Clarity in decision-making

AI-based detection of outliers in demand planning helps to make the right business decisions. This helps to identify fluctuations at an early stage and to initiate effective measures at the right time. A good AI even goes one step further and suggests clear courses of action that consider internal constraints and predefined parameters. The risk of ineffective interventions to meet demand is thus reduced and inefficiencies along the supply chain are counteracted.

6. Better relationship with supply chain partners

The bullwhip effect leads to a demand ramp-up along the supply chain. AI-supported demand planning not only leads to optimal stock levels, but also to happier partners who are able to plan more efficiently. This prevents short-term requests and leads to less stress for all supply chain parties. Establishing a cross-supply chain demand planning process that includes all parties in the planning process leads to even lower stress levels along the supply chain.

7. Data science takes a back seat

With a smart AI, everyone becomes a data science professional. The prerequisite for this is a self-learning system that automatically creates and adapts forecast models at the push of a button. This is a crucial success factor, especially in demand planning. As a result, time is freed up for important strategic tasks and the more complex quantitative part is delegated to a self-learning system.

About Quantics

Quantics is a SaaS forecasting and decision-making solution that enables accurate and agile demand forecasting for smarter and more sustainable decision-making. Our mission is to equip decision-makers with a self-learning system that combines artificial intelligence and professional expertise to facilitate a cutting-edge planning process.

Learn more.

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