Data model builds intelligent reports, which increases the turnover of goods by more than 20%

FineMonkey · Post time 2020-5-12 10:01:29

Company: Hunan Mendale Hometextile Co., Ltd.
Industry: Retail Fashion
Region: Hunan Province
Product: FineReport
Scenario: Marketing, Procurement, Production, Inventory
Scale: 1 billion
Position: The industry leader
Year: 2019

Facing the new demands of the home textile industry and the challenges of commodity management in the new market environment, the company builds a complete commodity control system, establishes commodity archives, predicts commodity sales, and embeds automatic replenishment models in reports, which realizes automatic replenishment and adjustment of the model, greatly improves the efficiency of the goods, and the inventory turnover speed is over 20%.

1. Company Profile

Hunan Mendale Hometextile Co., Ltd. began in 1956, adhering to the core concept of "love in the family" while abiding by the corporate culture of character and fraternity.

The company has been practicing high standards of quality control, with superb craftsmanship, excellent quality, and original design, dedicated to creating the most comfortable home experience in China for the majority of users.

Relying on a solid brand foundation and a unique brand concept, it has developed steadily, continuously exploring domestic and foreign markets, and successfully transformed into a listed company in 2010.

2. Project Background

There are many brands in the traditional home textile industry, and no real giant enterprises have been formed, and there are not many large-scale enterprises.

On the one hand, there are a few industry-specific solutions. Solution providers mostly divide the solutions of the home textile industry and the shoes and apparel industry into one category, ignoring some characteristics and specific needs of the home textile industry.
In this way, the targeted and scientific nature of the solution will be greatly reduced. In addition, the home textile industry mostly uses multi-season trade fairs to determine production capacity and production plans. With the continuous development and growth of the company, the mode of the trade fair is gradually difficult to meet the growing business needs because of its shortcomings of poor elasticity, and a new model is urgently needed.

On the other hand, retailing has entered a new stage, and consumers have gradually diversified into two levels, namely the pursuit of cost performance and the pursuit of personalized freedom. In the new retail environment, how to develop scale effects to reduce production costs, provide consumers with more cost-effective products, and at the same time pay attention to customer needs and provide personalized products has become the challenge of current commodity management.

Facing the new demands of the home textile industry and the challenges of commodity management in the new market environment, the company hopes to make efforts and changes. After the selection and evaluation, they finally chose to cooperate with FineReport, which opened the road of commodity data management.

3. Application Scenarios

3.1 Commodity console system

3.1.1 Problems
After more than 60 years of development, the company's business has continued to expand. In the process, the commodity management and control system gradually exposed some problems.

1) The current mode of ordering meeting is gradually difficult to meet business needs, specifically reflected in the following two points:

Can't accurately predict the real needs of customers for half a year or longer;
Production is inelastic, and once market changes occur, it is easy to backlog inventory;

2) The production cycle of home textile products is relatively long (from embryonic fabric, printing and dyeing to processing and forming, generally more than 30 days, if it contains complex processes, it will exceed 60 days), need to confirm the relationship between sales and product supply;

3) The company has more than 3,000 stores across the country, and the operating capacity of each store varies greatly. How to help store operators operate better is a very important issue.

In summary, the company needs a comprehensive product control system to get through the entire production and sales process and optimize the operation of enterprises and stores.

3.1.2 Solution
Considering that there is no commodity control system specifically for the home textile industry on the market, based on the understanding of the business, the company has innovatively established an inventory integration model and embedded prediction models, automatic replenishment models, etc. into the FineReport platform.

1) Inventory integration mode

For products that are poorly sold in someplace, use other stores across the country as a backstage to help;
Find relevant factors suitable for sales in each store through the data center, and convert them into corresponding products for the recommendation;
Monitor the operation of the overall commodities. Once a change in sales trends is discovered, immediately link with the back-end supply chain to ensure that there is no shortage of good-selling goods, and there are no unsellable goods.

2) Report example

① Establish a complete file of the product.
Include the various attributes of commodities, expand the capabilities of commodity attributes, avoid ignoring some unremarkable but important commodity attributes, improve the accuracy of commodity analysis, and provide the necessary factors for model analysis;

② Establish sales forecasts.
Based on multiple factors, innovatively combining the FineReport and the forecasting model in data mining to predict the sales of the product in the next three months, contacting the inventory and production plan to determine the possibility of smooth sales of the product, can be more early adjustment of the corresponding inventory, production and sales plans;

③ Automatic replenishment model.
Innovatively apply the automatic replenishment model to the home textile industry and reports. The combination of decision factors, rule factors, and algorithm factors constitutes the basic rules of the replenishment forecast model. According to the model rules, the store that needs to be replenished and the store needs to be replenished are calculated. The number of goods, so as to make replenishment recommendations for the store.
In addition, the replenishment model also has automatic adjustment and learning capabilities. With the enrichment of historical data, it can gradually improve the accuracy of replenishment.

④ Actively grab the missing data and let the data to help production.
The platform captures the data needed for replenishment, direct orders, and safety inventory, returns purchase requests through MRP, and APS schedules production to increase the delivery rate.

3.1.3 Value brought by commodity console system

The product life cycle is under control, and the products with poor performance are eliminated and cleaned up, the efficiency of the product increases, the SKU is reduced by 1/3, and the money efficiency is increased by more than 30%;

As the efficiency of commodities increases, inventory is reduced, inventory turnover can be accelerated, and turnover can be increased by more than 20%;
Open up the front-end and back-end data interactions, which speeds up the overall response speed of the goods. The order placement has been changed from one time a day before and can only be processed during working hours to any time without human intervention; the development team does not need to invest too much energy in the front-end interface;

The use of FineReport to modularize the business is convenient for later iterations and upgrades. Under agile development, it can quickly respond to business needs and greatly reduce development and operation and maintenance costs.

4. Project Experience

1) In addition to attaching more importance to data and analysis in the era of big data, enterprises also need to improve the response requirements for executive power and speed. How to find the center of gravity is the scope that every IT team needs to think about next;

2) It is very important for the traditional industry to connect the terminal to the supply chain business. It has been verified in the project of speeding up the commodity turnover, and it also confirmed the will of the enterprise to digital transformation.

[Retail & Fashion] Data model builds intelligent reports, which increases the turnover of goods by more than 20%