Are you focusing on the right part of your supply chain?

BZIMPLE - Demand Planning can help reduce the lead-time for products, so the planner doesn't have to look too far ahead in the future.

We are now all aware of the serious consequences Covid-19 has had for the fashion industry worldwide. We are in the coming years facing a world with a very unpredictable future and for demand planners a historic sales pattern that will challenge existing planning and forecasting platforms who mainly focuses on statistical models. We need to be able to adapt faster to this unpredictable environment, which is why we can and should rethink how we can become even faster to create our forecasting and demand planning. The opportunity is here now to throw it all up in the air and start over.

During the Covid-19 crisis at the beginning of the year and which for many still is happening today, we have run a “crisis program” throughout demand planning. When we have finished this and we are back to the new “normal”, demand planning must be stabilized. The article here focuses on which areas can/should be rethought.

Get your basic processes fixed first

I believe a lot of fashion companies are hoping for AI and machine learning to fix the challenges they have had for 20 years in their management of stock investments. But when I meet with the brands:

  • They do not have a clear strategy for which products to invest in
  • They do not focus enough on getting all needed data from retail and online stores and suppliers
  • The importance of planning and forecasting is often not reflected in the resources available
  • Supplier agreements for order minimums, fabric- and capacity bookings can often be optimized
  • Because most planning platforms are not tailored to the needs of fashion brands, it takes too much time to evaluate styles, and most companies often only evaluate the demand plans monthly
  • With product lead-times up to 26 weeks and a constant search by the customers to only have the most relevant products active, machine learning and AI does not provide as much help for the long term fashion purchases as it can do for other businesses with a more constant flow and shorter production lead-times. Machine learning and AI will have a positive impact on the replenishment from the distribution center to stores but will not provide nearly as much help for the purchases from the far east to the central distribution center.

Transparency in the supply chain

First, the Covid-19 pandemic necessitates transparency throughout the supply chain so that fashion companies can respond much faster and have the momentum needed in a changing environment. When visiting fashion companies, we either see a lot of time being used on updating and using multiple excel sheets and systems which is very time-consuming or we see silo-based buying where planners, buyers, and sales teams are challenged with a lack of transparency end hence speed in the planning process.

It is critical, that data is easy to display and that it can help planners to react very fast to any changes in sales. By having all data available easily planners can react much faster to any changes in the supply chain.

Historical data for demand planning

The Covid-19 pandemic and the coming unpredictable future mean that a constant change in demand is expected. Many forecasting software uses historical data that goes back two years, they are focusing on complex algorithms creating a black box for the demand planners when the demand shifts like it have done in with Covid-19. In fashion, demand planning should be created by using short-term forecasting models which are more influenced by the current demand rather than historical data. Due to the shutdown in most parts of the world, much of the historical data will not be current and relevant next spring. We should therefore arrange our demand planning from a very complex model to a much simpler model focusing more on current demand.

Demand planning and forecasting at BZIMPLE
Forecasting is complex, we help you to make it more simple

The constant change in demand

As mentioned earlier, the world is moving towards a more unpredictable future, which is why the fashion industry should be more aware of rapid changes in consumers and at the same time be able to react quickly. We can no longer just expect tomorrow to be like today. If a similar situation as the Covid-19 pandemic happens again, the players in the fashion industry must be able to react quickly so that a huge inventory of obsolete goods is avoided. Fashion companies that can limit their inventory are much stronger and at the same time, it is possible to achieve the maximum profit by ensuring that bestselling styles are available to consumers.

Combine human skills with demand forecasting

Because of the nature of fashion, we believe you cannot just let software and algorithms control your purchases but instead you should create a fast-reacting organization and use all needed data to help your planners to make the right decisions.

Planners and the sales team must work together, as these parties can achieve stronger forecasting together. And if a new pandemic hits the world, we need to use data to help the planners react as fast as possible, because when something like Covid-19 hits you instantly find out the need for human interactions as they can react significantly faster to a pandemic as any software can look at the long term forecast.

By combining quantitative data from the forecasting software with the qualitative insights from the planners and the sales team, we can strengthen forecasting and hit closer to perfection. Also, it is necessary to fashion companies to ensure that there are enough employees to handle forecasting. As people become more necessary, it is also a necessity that there are enough hands to handle the workload and secure the tasks that may arise. By that forecasting becomes more accurate, costs of obsolete goods are minimized, so a balance is achieved.