Demand forecasting enables companies to predict a company’s sales, profits, and revenue for a particular time in the future, analysing past sales data are important, but companies may also consider customer feedback, expert insights, market indicators, as well as the viewpoints and predictions of the business sales team. Demand forecasting is crucial to the long viability of your store because it allows you to avoid waste, reduces the risk of ordering large amounts of stock, and assists you in making the right decisions about stock orders. Having the necessary stock on hand, with effective inventory management within the business, helps to ensure you have the correct stock on hand for your consumers, but not too much so that it goes out of fashion and then becomes outdated. Businesses that do not use demand forecasting risk running out of stock, leaving customers disappointed, or receiving excess stock, resulting in money being wasted on a stock that cannot be sold (Marijana Kay, 2021). To use Machine learning and artificial intelligence, companies and organizations could really make use of Machine Learning techniques to predict changes in consumer consumption as best as possible. The Machine learning techniques can identify trends instantly, seize the correct information from customers’ feedback and identify all relevant interactions in massive data. This technique detects all the above information in real-time. Businesses use artificial intelligence to avoid problems that could arise because of not having the right information at the right time, this then can provide the company with the ability to reduce inventory costs while also improving financial preparation this includes when a company is recruiting, they have an idea of how many staff they may need (Dilmegani, 2021). There are numerous advantages to Artificial intelligence in demand forecasting such a big one would be that it can assist Human Resources within making effective decisions when it comes to recruitment such as if the business may need full-time or part-time employees this reduces the cost for Human Resources expenses because it has a better plan for its hiring budget, Helps to maintain high levels of customer satisfaction because when things are out of stock, the consumer feels disappointed as a result, the consumer is more likely to shop where there is always supply that meets his or hers wants and needs. Helps to reduce markdown pricing as a common difficulty for businesses has been "cash-in-stock," which is an excess stock that needs to be marked down in price so the company could indeed make some money from the stock (Dilmegani, 2021). Implementing machine learning in demand forecasting can also benefit stores, as the system can be trained to gather data such as "weather, financial, and third-party data such as social media and prior sales." By doing so, artificial intelligence could assist in the planning of future events, such as fashion shows and store launch dates for a specific season (Brosset, et al.). Bibliography
Kay, M. (2021). How to Forecast Demand for Your Retail Store (and Why You Should). [online] Shopify. Available at: https://www.shopify.com/retail/demand-forecasting [Accessed 20 Mar. 2022]. Tradecloud. (2021). Demand Forecasting using Artificial Intelligence. [online] Available at: https://www.tradecloud1.com/en/ai-case-study-1-demand-forecasting-using-artificial-intelligence/#:~:text=AI%2Dpowered%20demand%20forecasting&text=Using%20AI%2C%20organisations%20can%20make,[ Accessed 20th March 2022]. Image Referencing Segura, A. (2018). Artificial Intelligence in Fashion Retail, [Available at], https://fashionretail.blog/2018/04/30/artificial-intelligence-in-fashion/. Singh Bisen, V. (2018). How AI is Changing Fashion: Impact on the Industry with Use Cases ,[Avaible at], https://medium.com/vsinghbisen/how-ai-is-changing-fashion-impact-on-the-industry-with-use-cases-76f20fc5d93f.
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