AI-based demand planning

Requirements planning is a central element of corporate management. It ensures that you ideally have exactly the right quantities of goods and raw materials in stock - no more and no less.

Whether in production, retail or classic e-commerce, demand planning ensures that replenishment flows. Traditionally, it is based on empirical values, statistical methods and - not infrequently - gut feeling.

But in today's world, this is often no longer enough ...

Many companies struggle with the same challenges: Seasonal fluctuations, unpredictable leaps in demand, complicated supply chains. Until now, planning has often been based on assumptions such as: "This table lamp is stylish and will therefore sell well."

With the right experience and enough expert knowledge, this plan can work out - but success is anything but set in stone because Trends often change overnight.

If this scenario occurs, it leads to high overstocks that tie up capital in the long term - or, conversely, to stock shortages that slow down sales. What's more: In areas such as construction or production, incorrect inventory planning can lead to massive delays.

The biggest difference: artificial intelligence makes no assumptions - it bases its recommendations 100% on data. And it does so in a depth that is almost impossible for humans to comprehend.

AI-supported and benefit-oriented demand planning can recognize patterns from millions of data points: Sales figures, seasonal trends, customer behavior, even external factors such as weather or economic developments.

This enables highly accurate forecasts and more flexible inventory management.

E-commerce platforms: Webshops in particular, which offer many products, benefit enormously from AI-supported and consumption-driven demand planning. The AI analyzes purchasing behavior, seasonal trends and external data in order to have exactly the right quantities of products in stock at the right time.

Food industry: The demand for fresh products often fluctuates strongly and quickly. An AI can predict the need for fresh goods based on sales data and even weather forecasts to avoid spoilage and overstocking.

Automotive industry: Thousands of individual parts are often required in production. AI can help to prevent supply bottlenecks or surpluses and optimally control production chains.

Construction industry: Materials and tools are constantly in use on construction sites. Here, AI can help to monitor stocks, avoid delays and ensure that there is always enough material available without building up unnecessary stocks.

Healthcare: Clinics and hospitals need to stock a variety of medical products and drugs without tying up too much capital. AI-based and consumption-based demand planning helps to make accurate predictions to ensure that no shortages occur while minimizing overstocking.

Fashion industry: Seasonal trends are crucial in the fashion industry. AI can analyze buying behavior and make accurate forecasts of future sales to better plan inventory and reorders.

Mail order companies: Especially for international companies with global supply chains, AI can make inventory planning more efficient by taking delivery times, changes in demand and production capacities into account.

Smart manufacturing: In intelligent manufacturing, AI can help to analyze the demand for raw materials in real time so that companies can react quickly to production fluctuations or unexpected disruptions.

Aviation industry: Airlines and airports are using AI to better manage demand for spare parts, fuel and other essential resources, improving efficiency and saving costs.

Logistics companies: Here, AI can help to plan the demand for vehicles, drivers and means of transportation, leading to better capacity utilization and a reduction in operating costs.

Requirements planning can be divided into two main areas: Quantitative and qualitative demand planning.

While quantitative demand planning in typical areas such as business, industry or architecture is based on hard figures and statistics, qualitative planning is based on empirical values, expert assessments and strategic considerations. An AI can combine both approaches - it calculates hard facts, but also soft factors such as trends or external influencing factors.

If you are interested in such a solution, we would like to invite you to a free consultation. We will show you what a possible demand planning software with an AI interface could look like - and, if you wish, plan the next steps of a possible software development together with you.

Ensure above-average data quality
You can have the best software in the world: Unclean, outdated and less relevant data will sooner or later result in blatantly incorrect planning. It is particularly important for seasonal demand planning that historical data is regularly maintained. You will achieve the best results if you also integrate external data such as economic data, weather forecasts or geopolitical developments to ensure even more precise forecasting.

Continuous training and adjustments
Markets and demand patterns are constantly changing. For long-term effectiveness, the AI must be continuously fed with new data and regularly trained. What worked a year ago may already be outdated today. A well-functioning model requires ongoing adjustments, especially when it comes to unforeseen market events.

Set realistic expectations
AI will make demand planning much easier in the future. However, it is not infallible. Artificial intelligence can make predictions based on historical data and external factors. However, it cannot predict the future with 100% accuracy. In other words, sudden changes such as a pandemic or political changes cannot be accurately predicted, even with the best database. That's why you should always plan on a scenario-based and multi-track basis in order to be able to cushion the worst-case scenario at all times.

If you are wondering how you should implement these points in practice, we would be delighted to welcome you to a free consultation with a planning expert from our team.

Those who switch their demand planning to AI will secure a decisive competitive advantage.

Companies that are still hesitating should not wait too long - because the market is moving fast and AI-based demand planning could be the new standard in just a few years. At antares, we are happy to help you take your demand planning to the next level and develop customized software solutions together with our customers.

In a free consultation, we will be happy to take a look at our latest projects together and show you what an individual solution for your company could look like.