I am sure we all agree that fluctuations in demand can be harmful to your business. Without proper demand planning, companies cannot meet an unanticipated surge in demand, leading to customers shifting to competitors to satisfy their needs. Businesses are left clueless about how much goods to stock, when to order for replenishment, and how much stock to reorder.
Effective demand planning enables companies to consider several aspects that influence demand. Modern businesses can access massive datasets, making demand planning more convenient and efficient. Demand planning is an essential part of the supply chain and commands the decisions related to business operations and inventory, and it helps to minimize unnecessary understocking and overstocking.
Let us know about demand planning and how companies can benefit from it.
What is Demand Planning?
Demand planning anticipates consumer demand for specific products across the supply chain for a particular period. The main objective of demand planning is to satisfy consumer demand by stocking goods to the optimal level while preventing overstocking. Economic shifts, upcoming events/holidays, historical data, and seasonality are examined to forecast future sales.
Demand planning software assists companies in estimating sales accurately and planning strategies accordingly. Businesses can get an idea about the upcoming trends and make decisions regarding marketing, advertising and sales well ahead of time.
How Does Automated Inventory Planning Work?
The difficulty for human forecasters comes from the fact that demand trends are frequently masked in massive amounts of raw data from numerous sources. Even highly skilled forecasters find it challenging to sort through this data flood and find trends that could be relevant to changes in demand in the future.
This is where big data analytics with AI becomes useful. Contrary to human brains, AI and machine learning are not overwhelmed by large amounts of data; in fact, the more data, the higher the accuracy and insights these technologies can provide. It’s significant that data may originate from recognised sources as well as previously untapped ones.
One of the finest sources for demand-sensing systems is point-of-sale terminals, which can show real-time images of what’s happening on the product front lines—whether in retail locations or online sales channels. However, anything from social media updates to weather predictions can be used to enhance actual sales data. For instance, it’s likely that demand may change as a result of viral social media posts—whether positive or negative—about a product.
Artificial intelligence (AI) and machine learning are powered by vast volumes of different data, but their engines are complex mathematical algorithms. And when it comes to demand-sensing, more algorithmic models are better than less, just like with data.
How so? Classification or decision trees are a predictive modelling method that is frequently used in AI and machine learning. In the past, forecasters would only run one decision tree model that they thought had the best chance of producing accurate findings.
Today, forecasters may run dozens or hundreds of slightly different decision tree models, each learning from prior models as well as from observations of actual sales swings, thanks to improvements in processing power as well as modelling methodologies. The ultimate outcome is a significant improvement in demand planning accuracy.
AI-Powered Demand Planning Software
Most businesses in contemporary times use analytics data rather than time series forecasting methods and traditional forecasting methods. Although analytics data can produce correct forecasts, they only work when societal trends and consumer behavior patterns are constant.
Advanced demand planning systems utilize AI and ML technology for reporting and reacting to fluctuating consumer trends. Manufacturers have been using machine learning for a long time and are now concentrating on deriving its advantages for demand planning. Past sales data, promotional analysis, and cyclical forecasting can be leveraged to optimize inventory.
Businesses need to take into account new sales trends and examine historical data. This allows planners to gauge future demand and keep overstocking and understocking under check. Production centers should leverage predictive analytics for producing long-term and short-term demands for obtaining accurate forecasts. With demand planning tools, you can access real-time data and leverage machine learning to make correct predictions and produce a proper dataset for refining the information.
Demand Planning Elements
For obtaining accurate forecasts, you need to take into account the following aspects:
Past sales data is one of the essential factors that is considered during demand forecasting. The information about how much product you sold in the last years lets you comprehend how much of the product you might sell in the following years. However, considering past data is insufficient, you should select a specific time and obtain the related data to generate an accurate report. You should have enough data to produce accurate forecasts.
The external factors that influence demand can include modifications in legal, cultural, technological, political, and economic sectors. External factors have a more significant impact than internal ones. Businesses might fail to establish their goals because of changes. Demand planning systems consider all the elements to generate sales forecasts, and components influencing product prices and sales are also considered.
These trends can be comprehended by observing the sales trends of specific products. Patterns also include sudden fluctuations such as downfalls and spikes. You may think of changing your plans for increasing sales. You also must consider seasonal sales and select a robust demand planning model depending on the sales trends. The accuracy might be hampered with the wrong model, and businesses can lose customers because of inaccurate forecasting.
Promotions and Events
Promotions and events have a more significant impact on product sales. Advertising and promotions can boost your sales, and businesses should think about running promotions to increase sales.
Importance of Demand Planning for Effective Supply Chain Management
Demand planning is necessary for businesses for the following reasons
- Organized Inventory
- Proper segmentation of resources
- Enhanced relations with suppliers
- Strategize sales plans
- Boost customer satisfaction.
About the Company
Fountain9 assists businesses in gauging future demand through their robust demand planning software, Kronoscope. The software considers nine unique factors to estimate demand accurately and helps companies plan inventory accordingly. This helps to meet consumer demand on time despite sudden fluctuations.