Enterprise data analysis is a very complex project, which requires two knowledge of business and analysis technology. Here, from the perspective of business, we will talk about how to analyze the business. The article refers to the retail data management solution of FanRuan Software.
First of all, the analysis of the enterprise is mainly divided into management analysis and business business analysis. The overall thinking of the analysis is: clarifying the business scenario - determining the analysis target - building an analysis system - sorting out the core indicators .
Because the business of each enterprise/industry is different, the analysis system is also different, here we mainly talk about retail e-commerce, and discuss it according to different analysis scenarios. Other industries are also welcome to hook up with you, or you can take a look at the cases in this column (more inclined to the reporting system, there is a certain reference): FanRuan Data Application Research Institute
Taking e-commerce as an example, commonly used business analysis scenarios include sales, commodities, channels, competing products, members, etc., and commodities can be further subdivided into commodity inventory, commodity profit, and related sales analysis. In the whole business analysis system, the e-commerce industry follows the thinking logic of "people and goods market", and its indicators can be divided as follows:
1. Sales analysis
Sales analysis is mainly to track sales, compare with KPIs, adjust sales strategies, and further increase sales.
Analysis ideas: Basically, any problem can be analyzed by the "people and goods yard model". For example, to analyze the reasons for the decline in customer unit price, from the perspective of the people and goods market, the following analysis model can be established:
Analysis method: Data analysis can be analyzed through data comparison, extreme value, and prediction.
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Comparison: For example, the sales rankings of the divisions, the sales contribution, the city rankings, etc.
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Extreme value: such as the highest monthly sales record, motivating salespeople or business units to break records
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Forecast: Predict future sales based on a weighting curve
2. Commodity analysis
Commodity analysis is a process management based on commodities - invoicing . For example, if the inventory of goods is too large and takes up funds, the purchase and purchase are unreasonable; the display of goods is unreasonable, resulting in untimely delivery and lagging sales.
Commodity analysis system - the idea of "invoicing, inventory", commonly used indicators such as commodity discount rate, sales rate, turnover rate, etc.
3. Member data analysis
On the one hand, member data analysis can guide sales operations, and on the other hand, it can improve the accuracy of marketing, increase user stickiness, and reduce churn.
Member analysis management system:
4. Other management analysis
人力资源管理中的数据分析一般包括两个方面，一方面是人员结构分析，另一方面是人力效能的分析。在人效分析过程中最关注两个指标，人均产出和人员费用产出率。人员结构分析包括不同职能部门的人力结构、不同层级的人才结构、不同工作年限的人才结构等等。分析人力结构是防止人才的断层，在招聘上做好预案，优化薪酬分布。
数据分析领域的财务主要是管理财务，管理财务需要细化到每个子公司、每个业务、每个产品、每个业务部门、每个客户，以他们为主题的分析有：现金流分析、盈利能力分析、财务预算分析等。
这里只是概述了一个框架，每一个点展开都是一门知识，欢迎留言探讨~