Data analysis Overview

For data analysis, I believe that every enterprise that uses the information system has its own understanding. Some of them come from books, some from work experience, and some from software supply. However, enterprises and information systems I know have different definitions of data reports and basic understanding of data analysis. Some are true differences in understanding, but some are caused by different terms. In addition, I think that the true understanding of data analysis is a key part of enterprise process design. Therefore, I would like to give a brief introduction to data analysis:

I 'd like to explain a few points before I proceed.

1. Here, the data analysis I mentioned is not a theoretical data analysis, but mainly about the data analysis application. Therefore, I will not discuss the mathematical methods and theories of data analysis very professionally here. If you are interested in data analysis methods, you can find some relevant professional books.

2. for different enterprises, data analysis is applied differently. Here I will mainly explain the application of data analysis for supermarket chains. Therefore, the related examples are related to supermarkets without being explained. Even so, the basic concepts related to analysis and application can also be signed by other enterprises.

Scope of data analysis:

A correct understanding of the scope of data analysis is to analyze all quantifiable data of an enterprise. At present, for supermarkets, because of their own sales forms, the first thing that is quantified and managed is the import and sale of commodities and the storage of data, so that some enterprises can, once it comes to data analysis, it is the product Inventory sales data. In the process design, it is designed only based on the product Inventory sales data, so that the information management effect is greatly reduced.

In a survey of some enterprises, it was found that some supermarket businesses are still available locally, but they were overwhelmed by small wholesale stores. When asked about the number of people in supermarkets, not only did the operator speak clearly, but he could not even speak specifically about the number of people. Such enterprises cannot talk about human effect analysis and management, which is also common in some medium and large supermarket enterprises.

The reason is that the company's information development is not balanced. For modern chain enterprises, on the one hand, the flow of personnel is relatively frequent, and on the other hand, the area of enterprises is relatively wide, so that in the chain enterprises with strong headquarters in thin stores, traditional Personnel Management Methods inevitably lag behind. Therefore, it is necessary to clearly understand the scope of enterprise data analysis. This is a basic understanding of implementing comprehensive information management, restructuring processes, and improving core competitiveness of enterprises.

As mentioned above, data analysis covers the following aspects:

1. Correct Understanding of the quantification process

The necessary condition for quantification is relative standardization of operations. Please note that in information application, there is often a saying that enterprise management is messy and it cannot be implemented. Or, to implement informatization, you should first standardize it.

These two ideas are somewhat one-sided. Some enterprises have found such a situation (I believe many people feel the same way). Some people say: I really cannot understand it, A lot of management principles are combined with good management principles, so good enterprise efficiency is not good. Some enterprises have a mess of management, but the business is very good. In fact, this is a misunderstanding. for standardization, quantification, and information management, they are a gradual process. They share a common goal: to maximize the benefits of enterprises. Therefore, in the investigation, for those companies with chaotic management, it is actually doing well in some aspects of information management. Don't forget, for supermarkets, the first thing to quantify is the inventory data of goods. For these enterprises, they have done a good job in using quantified data. Although they still have some gaps in comprehensive quantitative analysis, their benefits have been improved. On the contrary, for companies that are well-managed, although there are many quantitative data, there is no good use of the data, so the benefits are much worse.

To put it bluntly: some enterprises cannot manage people because they do not know the number of people. Some enterprises know the number of people, but cannot manage people effectively, the latter may have a higher cost, which can be used in the same way.

Therefore, correct understanding of the relationship between quantification and information management, and the relationship between information management and enterprise benefits are the basis for enterprises to reorganize processes and achieve information management.

2. Analyze the quantified data and quantify the data as needed:

I have already mentioned the advantages of quantitative data analysis. To do this well, enterprises need to invest the minimum cost to obtain the largest and fastest benefit income.

Quantifiable data as needed is the maximum potential of an enterprise in a planned manner. For enterprises, process reengineering, standardization, and ultimately unsatisfactory performance, this is partly because the principle is not well grasped. Taking the Enterprise Personnel Management just mentioned as an example, human resources cost and energy, but the enterprise has no benefits. Of course, if the enterprise has no benefits, the individual will have no benefits, this will have some negative effects. Therefore, promoting enterprise information management in a planned manner as needed is the key to smooth process restructuring and informatization management.

Data analysis comprehension:

In terms of data analysis applications, we should consider the following aspects:

1. There are many aspects of the investigation data, so do not use the data.

For a data, it is caused by many reasons, so it is doomed that data can reflect the situation of enterprises in many aspects. For this reason, we should also be careful with the use of data. Don't rush to draw conclusions and read data on a one-sided basis.

For example, the analysis of enterprise sales shares. In information management consulting, there is such an enterprise that makes the sales proportion an assessment indicator to assess the store staff. In the beginning, his approach had greatly promoted the enthusiasm of employees and improved the sales of stores. However, after a period of time, the effect is still not obvious, and after a period of sales, it returns to its original level. When he asked me about this phenomenon, I read the data of several of his stores, and I suggest him regard the sales proportion as a yardstick of the store's operating ability, and then conduct personnel allocation, finally, try the assessment. This company allocates some managers who have sold well and have a reasonable proportion of their stores. Soon, the sales of the store, which had a bad share ratio, Rose. This increase was not only a reasonable share, but also a huge increase in the sales of the entire store area. Later, when talking to the manager, he said deeply that he had the following deep feelings:

1) unexpectedly, the sales proportion can be used in this way, and the effect is obvious.

2) I have a deep understanding of the power of data analysis.

3) this time I discovered a talent who had a real understanding of the rational use of enterprise human resources.

Soon afterwards, this company asked me another question. Why is the above method not useful to every store? This time I gave him some explanations. There are many reasons for this situation. For stores with the same external environment, this may be caused by the differences in the management ability, however, for some stores, it may be caused by other factors, so the effect is not obvious. At the same time, different operators have their own characteristics for their operational capabilities. Some are strong in product structure adjustment and some are strong in market operation. Therefore, the effects are different. For modern enterprises, the shortage of people is a problem. At the same time, it is critical to make good use of existing talents. This is why modern enterprises need to implement informatization, strengthen data analysis, and implement ERP plans.

2. Use a system method to process data. Do not read data in isolation.

The data analysis result must be processed by the system. The last time a supermarket operator talked to me about this problem: in management, the problem is clearly known and solved many times, but the problem cannot be solved. Why? Basically, there is no system to process data, that is, there is no proper reconstruction process.

Let's use the price management example of the company just now. I went to the company mentioned above and learned that they have learned the books on category management and their concept of Category Management, A low-cost image test was conducted. They organized some people to analyze the data and make some price adjustments, but a few months later, the effect seems unsatisfactory.

There are several problems with this phenomenon:

1) First of all, understanding the problem. The formation of the price image is a process. The time of this process varies depending on the company's operations, the environment, and the length.

2) The maintenance of the price image must have a complete management, instead of temporarily organizing analysis by some people on an irregular basis, and price adjustment can be completed. This enterprise simplifies the price management.

3) companies do not want to establish a low-price image, so they cannot view data and analyze data in an isolated manner, but also make adjustments based on local market conditions.

3. Perform Three-dimensional data research on management topics.

The research on data analysis should focus on certain management topics. For example, if an enterprise wants to strengthen supplier management. Then, he can analyze the sales situation of the suppliers in the enterprise, analyze the profits produced by the commodities for the enterprise, and compare the price of the commodities with the similar suppliers, analysis of its supply capacity and Analysis of Its services. Only in this way can we well complete a management topic.

Among the enterprises under investigation and consultation, some of the problems for large enterprises are not very prominent. This is a big bully, but some medium enterprises have outstanding problems, negotiation with suppliers becomes harder and harder. In addition, although the supply of goods sales is large, the support is smaller and smaller. Of course, there are many reasons for these situations, but I think one of the fundamental reasons is that the enterprise does not have valid data, so the internal and supplier management of the enterprise is out of control.