Sales forecasting for demand planning in the fashion and apparel industry can be complex and time consuming as there are a multitude of factors that impact demand, more so than in other industries.
In recent years, many bricks and mortar stores have transitioned to eCommerce platforms in a bid to extend their reach to digital customers and currently many fashion retailers have transitioned to selling online to adapt to Covid lockdown measures.
Online consumer behavior has been continuously changing with evolution of fast fashion trends due to social media influencers and the speed of purchase with digital device usage.
What are the different demand impacting factors in the fashion and apparel industry?
1. Short life cycle
The variety of clothing and apparel products can include basic, fashion and best-selling items requiring different replenishment timelines.
Basic items such as jeans are required throughout the whole year whereas high fashion products may be sold within a shorter period. Fashion retailers may also have short market lead times and short selling seasons in a marketplace that is extremely competitive.
2. Fashion trends
The industry is challenged by constantly changing trend cycles influenced by celebrities, innovations, and social factors that lead to difficulties predicting how long trends will last.
Impulse buying at point of sale and flash sales means there must be product availability to ensure successful order fulfilment. Understocking as well as overstocking are key issues that businesses can struggle with.
Consumers have a huge amount of choice when it comes to purchasing clothing and never more so when it comes to online shopping. They can instantly search or be presented with alternatives especially if their choice of product is not available.
5. Huge amount of product variability
There are many different sizes, styles, and sizes that retailers must consider when forecasting sales which can result in large amounts of data to mine through.
Some clothing and apparel products can be sensitive to seasonal variation such as swimwear or winter coats.
7. The weather
Fluctuations in weather conditions can influence demand for different types of clothing.
According to Fashion United impact is strongest is during the summer to autumn transition, from mid-August to early October, when warmer weather delays the purchase of autumn-winter ranges.
How can TrueStock overcome these challenges?
With the wide range of different challenges such as short or long lead times, short selling seasons, multiple flash sales and unpredictable demand the fashion and apparel industry has an even higher propensity for inaccurate sales forecasts.
In general, all industries have experienced issues with sales forecast accuracy and speed due to historical and legacy methods. However, the arrival of AI Machine Learning has provided a more intelligent method of sales forecasting.
By considering a multiple demand impacting factors, using data algorithms for processing, and learning from it over time, this data driven technology has the ability to deliver simpler, stronger, faster and more accurate sales forecasts.
The benefits of this methodology increases sales revenue, lowers the costs involved with overstocks and understocks (missed sales), and improves customer loyalty with satisfactory order fulfilment.
• Historical sales, pricing history, marketing activities and internal/external source data are processed at speed by an array of Machine Learning (ML) algorithms, demand patterns can be identified across an entire product portfolio, resulting in a more integrated, quicker and accurate forecast.
• Different forecast horizons are available including short-term forecasts that predict replenishment quantities for fast selling products for the weeks ahead. Longer term 120-day forecasts are also available.
• Improved demand planning with ML data driven sales forecasting results in optimum inventory levels and more resilient supply chains.
• More accurate sales forecasts ensure products are readily available for upcoming promotional events.
• Return on investment of marketing from different channels and locations are analyzed and the insights provided allow marketing to pinpoint their future spend and focus.
Seasonality, weather, and events
• Dynamic factors such as seasonality, the weather, events (Black Friday, Christmas) are included in the sales forecasting process.
Large amount of product variability
• (ML) has the capability to process with ease the large amounts of product variant data e.g., colours, sizes, styles that are synonymous with the fashion and apparel industry.
• With faster and more accurate sales forecasting and automated inventory replenishment, product availably is ensured, brand loyalty improved, and costs of missed sales opportunities are diminished.
• TrueStock’s market trends feature helps fashion and apparel retailers rank themselves against other stores and the industry itself so they can take required action.