Article written by Federica Chierici, Computational Linguist and Technical Sales Representive at CELI.
It would be great to foresee what to do in the future and how to behave always in a good way, whenever there’s a problem. The good news is: this is possible! Unfortunately, not for our everyday life or for relationships or friendships; let’s start from the fields where this is a possibility.
What does it mean, for example, to foresee in the fashion industry? We could know what items and colours will be more successful in the next fashion season and in which city. Is this magic? No, it’s just maths – precisely, it’s Data Science!
Let’s start from the beginning. To have this projection, we need data coming from network, sales and catalogues: every company has such data. And they are incredibly useful: they tell about colour, size, style, place, items’ quantity, day of purchase, ect.
Such data are accompanied by information like the weather conditions: this happens because everybody is happier to go out (and, eventually, spend money while shopping) in a sunny day and not when it rains!
Putting all these information together, companies could know exactly how to supply their stores all over the world, avoiding the stockout – and also avoiding a ton of unsold items in the warehouses. A win-win situation, that allows companies to produce and distribute better – and save money, too.
To make this happen, it is possible to carry out a Forecasting survey – even starting from a small amount of data referring to a few months. This allows to start the Forecasting survey and to have some good results for the following months. The prediction could always be improved, but how? Continuing to feed the algorithm with sales data, until we get to a closer vision of the effective sales.
As everybody knows, fashion is art, creativity, surprise, so it may happen that some items sell better than we expected. This possibility is positive and could show that a change in the fashion line or in the palette colour has worked (maybe if we’re talking about a capsule collection), or maybe it could mean that fashion is changing. Including this fact in our mathematical model let us use those information in the future, and also include all those context elements that lead to that result.
Why did we start from fashion to tell about this instrument? First of all, because we have experience in this particular field; then, because it’s important to keep in mind how the fashion industry is pivotal in our society. As stated in the Consumer Market Outlook 2018 report by Statista, “in 2017 the global fashion industry earned 1.500 billions of dollars, 4,4% more than 2016. This annual grow rate should remain stable for the next five years. It’s not just about the growth of the market value: sales in fashion reached the incredible number of 154 billion of items (+2,3% compared to 2016)”.
One of CELI’s goals is to let people working in the fashion industry to have better results, efficiently and sustainably. We see forecasting as a true superhero!
Do you want to know more about how to use forecasting in your company?Reach out to us at firstname.lastname@example.org.