How to make digitalization further drive the development of business, improve the management ability of the whole business group by using data analysis, and make data a "weapon" for business personnel, so as to realize digital and refined operation, has become the next problem to be considered by this large manufacturing enterprise.
As a leading manufacturing enterprise in domestic sub-sectors, it has massive data from itself, market and customers. Therefore, data management is also very difficult.
After in-depth understanding of the situation, the following two problems were analyzed:
Indicators and reports are scattered, reports are not strung together by business logic, the purpose of management is not strong, and there is a lack of systematic analysis logic; Data analysis lacks in-depth analysis of the problems revealed by the results, and the data is scattered in all dimensions, so it is difficult to find the core root that affects business and the support for management decision-making is insufficient.
Insufficient application of daily data, unable to effectively guide the operation and management of front-line business units (war zones and stores) through data report analysis; Business analysis data lacks effective integration, analysis and presentation, and cannot support managers at all levels to make decision-making reference.
Combined with pain points, data optimization and support are carried out from four aspects: overall operation, channel expansion, store operation and commodity sales.
Monitor the key indicators of enterprise management from the aspects of regional sales, store operation, commodity sales, inventory, etc., such as showing the sales situation and market competitiveness of commodities in each region, showing the sales performance in a more detailed dimension, showing the actual comparison of the overall sales performance in the early stage, and comprehensively ranking and analyzing the key indicators of retail in various stores across the country, so as to help the top management of enterprises understand the performance completion of all aspects and provide effective guidance for all links. Clearly and intuitively see the overall operation and completion rate of the group and the operation center. For the dimension with poor completion rate, we can give an early warning and quickly drill down to related topics for analysis, find out the reasons and optimize the promotion.
Fully control the achievement of store expansion in real time, and timely warn and remind the risk market areas. Through the multi-angle analysis of store data, it helps the channel management center to plan existing stores and stores to be developed. Provide an evaluation and analysis system for channel management center to select suitable franchisees, franchisees and direct stores.
Around the shop scene, all business support such as customer analysis, daily operation monitoring, shop inventory analysis, order forecasting support, shop floor efficiency analysis, shop consumption analysis, etc. are built to help shop managers intuitively and conveniently obtain the changes of operational indicators, so as to adjust shop operation strategies in time and improve shop achievement rate, transaction rate, sales volume and profit rate.
The analysis of product structure, new product life cycle, product contribution, promotional products, marketing strategy and product mix sales is constructed, which helps commodity operation centers to effectively analyze and determine the role positioning of different products in various regions and find personalized product demand within specific stores and business districts. According to the analysis of commodity sales data, we can quickly match the relationship between commodities and market consumption demand, constantly adjust commodities, and optimize commodity operation planning and R&D design.
In this way, the enterprise has built a business data analysis platform composed of key business indicators, hierarchical structure and market region. Through the monthly report, the business is supported by data, which helps managers understand the overall business situation of the enterprise in that month, helps data analysis to find the key concerns and problems in business, and thus helps managers make scientific decisions. Establish a closed-loop application from result monitoring to finding problems, finding the root causes of problems, solving optimization and decision support, and finally realizing performance and data operation.
1. Build a one-stop big data analysis platform to integrate and summarize existing system data, reduce data islands, standardize data, and make data traceable, comparable and early warning.
2. According to the daily management methods, the management is digitized to form a perfect management system, which is connected with the group management system and analysis system, and improves the management level of enterprise groups to some extent.
3. Standardize store operation and management through the platform, and use PDCA cycle management method to focus store managers' energy on improving sales performance; Help to understand the expansion of stores in terms of channels, and provide a basis for selecting suitable distributors; In terms of commodity sales, it provides personalized needs for different people in different regions, thus achieving precise marketing. Combined with the above platforms, the labor cost can be greatly reduced and the work efficiency of managers can be improved.
In this way, the enterprise has gradually achieved the goal of full coverage of data scenes, effectively improved the digital ability of enterprise operations and realized scientific management.