** (replenishment), according to the sales situation and inventory level, timely replenishment of out-of-stock goods in the store. **It is an important part of product management, the purpose is to ensure that the store's inventory can meet the needs of consumers, and avoid losing sales opportunities due to out-of-stock. In terms of scenarios, there are two scenarios.
One is that the warehouse replenishes the inventory to the store to meet the sales demand and keep the store inventory at an optimal levelForeign terminology: retail replenishment.
The other is for the warehouse to add orders to the ** chain to replenish the inventory to ensure that the warehouse inventory is sufficient to support the sales of goods in the futureForeign terminology: stock replenishment.
Due to the lack of a standard commodity management system in China, in most cases, both are referred to as "****Although it is true, for business communication, a term to refer to two concepts is not conducive to communication.
In order to facilitate the distinction, based on years of experience in retail services, NEXTSTONE refractory stone refers to the situation of replenishing inventory from the warehouse to the store, which is called "**The ** in this article belongs to this concept);The situation of adding orders from the warehouse to the ** chain to replenish the inventory is called "chasing orders".
Accurate ** has a positive effect on retail enterprises, which can prevent stores from running out of stock:No one wants to see consumers leave the store because they are out of stock when they buy, and lose sales opportunities;It is also able to prevent overstocking:The correct operation can help enterprises identify unsalable commodities and carry out allocation, order chasing and clearance operations in a timely manner.
The following is the general logic of the retail industry, no matter how the scene changes, most of them are re-replenished to the target inventory when the goods are consumed to the first point, of course, there are exceptions, such as Double Eleven, whether it reaches the first point or not, you need to replenish more goods to the store to support sales.
Although the logic is intuitive, there are still problems in the actual process:
*Data such as store sales, store inventory, in-transit inventory, and warehouse inventory are required for calculation.
Large enterprises will use ERP system management, and the commodity department can export ** from the system for calculation, which is relatively accurate, but it takes too long to calculate the process(1 person can calculate the maximum amount of 300 SKC per day for 10 stores).It still causes a lag in the calculation results.
Small businesses use their own Excel**, with missing data and different formatsIt takes longer to consolidate and organize before calculatingMake the results even more laggy.
Commodity specialists who work overtime.
The better situation is that although it is made up this time, it will not be out of stock, and the next time it can be made up to the target inventory. The most feared thing is that the goods have been out of stock for several days, and the store has called ** to complain.
Therefore, in order to avoid too lagging results, retail companies have to increase their manpower to cope with the huge amount of calculations.
*In addition to objective factors such as demand fluctuations and seasonal changes, subjective factors such as channel level and store level should also be considered to determine how much stock to replenish to the store, that is, the value of the target inventory.
In a slightly more scientific way, the best-selling products are adjusted individually, and the other products are divided into grades according to sales, and each level is set with a quantity, and then calculated according to this quantity.
However, how much this number is set and on what basis is still a question, and in the end, it is inevitable to make a decision.
Nextstone's intelligent commodity management system NEXTSTONE RAMA supports all kinds of ERP, automatically pulls commodity data every 10 minutes, and can also import data with one click, saving time for sorting.
In the past, it took three people two or three days to process the ** calculation of 100 stores, but now one person can complete it in two or three hours.
The intelligent ** model used by Nextstone is also summarized from its own years of practical experience in retail consulting
Best-selling ** model
The best-selling model is the best to make up but it is the most problematic place, the supplement is not sold out, the supplement is less than the goods are not sold, and the late supplement may not be sold out of season.
In actual operation, the best-selling models of the brand are different from the best-selling models in stores, and there may be 20 best-selling models promoted by the brand, but there are 30 best-selling models in store A, 15 best-selling models in store B, and 18 best-selling models in store C......
There are also many factors to consider when calculating, and the apparel and footwear industry also needs to be broken down into colors and sizes.
But at the end of the day, it's a matter of logical order:First of all, according to the sales data of the product, the number of days of turnover, the life cycle, the sales volume **, and the unsalable situation ......These indicators calculate the demand, and then calculate the shipped warehouse and the first store according to the store level, storage location level, and warehouse distance, and then follow the principle of first replenishment and then adjustment, first from the warehouse to the store, and then from the store when the warehouse is out of stock.
Clear logic, and then through the system to achieve, you can achieve the accuracy of the best-selling model**.
Most retail companies determine the volume based on the historical information of distribution to stores and channels, which is push, and many companies are still operating in this way.
However,Many companies still rely on the experience of commodity personnel**, and the accuracy rate is less than 50%.Often, there is a backlog of inventory at the end of the quarter due to overfilling and making up late.
As a result, the demand-oriented pull type has been created, which is simply divided into 4 steps:
1.Centralize goods in the headquarters warehouse;2.Set buffer stock according to the store level and carry out distribution;3.Each time, the minimum demand is calculated based on the store sales data and the demand order
4.Increase the frequency of **, less with more supplements.
One of the more difficult variables to control is the order demand of stores, which still exists in ways such as verbal demand or manual orders, which are difficult to manage and use as a reference for calculation.
Nextstone has specially developed a selection tool for stores to use, just like shoppingThe store only needs to add the required products on the mobile phone, click submit and generate the order form.
Later, when using the pull model calculation, the order form data can be automatically retrieved to generate the calculation results.
Since it comes to the same size, it must be the store's broken code: there are three consecutive sizes of goods with 0 in stock, or 0 in key sizes.
This situation is not complicated, and the merchandising personnel can quickly identify the broken code goods through the excel** formula.
However, it is more time-consuming to calculate how much to make up and where to make it up, although it does not take a day, it is common to spend two or three hours.
The beginning of the season is fine, the stock is sufficient, consider from the nearest warehouse**;If there is no chasing order in the middle of the season and at the end of the quarter, it will involve the allocation calculation, which will suddenly become complicated.
In response to this situation, NEXTSTONE has specially designed a Qi yard ** model.
Set the depth of each SKU SKC through the sales data, and then find out the broken code product with one click through the broken code standard, calculate the ** quantity and generate suggestions, so that two or three hours of work can be completed in two or three minutes.
A model that calculates based on the number of days available for sale weeks in the product lifecycle, and applies to all types of products.
In the past, in the face of the huge number of SKUs and stores, the merchandising staff worked overtime until midnight every day, but with the NextStone Resistant Stone Turnover** model, it can be completed in 5 to 20 minutes (depending on the amount of data).
By setting the standard turnover days for each product category at each store level, and then selecting the product range, store range, and warehouse range, the nextstone system can automatically pull the data to calculate the ** recommendation, and the whole process only needs the time to make a cup of coffee.
As we mentioned earlier, accurate ** can help stores always have the right, or the right amount of inventory, on hand to meet consumer demand, and avoid overstock caused by lag** to the greatest extent. Such a goal relies on manual calculation, which obviously cannot meet the needs of the business, and the commodity personnel have been doing it for a long time, and they can only become excel masters in the end.
And the use of intelligent commodity management system intelligent matching and supplementing system,It not only frees up commodity personnel to invest in more valuable data application work, but also enables enterprises to increase revenue and increase profits while reducing costs.