Based on the roster of labor dispatch employees provided by a human resources company in Suzhou, this study reveals that the human resource flow of labor dispatch employees has the following characteristics through data mining and statistical analysis:
First, the flow of human resources shows a trend of high outflow and high inflow;
Secondly, there is a significant positive correlation between turnover rate and new entry rate;
Third, the flow of human resources presents an unbalanced trend; Fourth, gender and intergenerational factors have a significant impact on turnover rate and new entry rate.
Keywords: human resource flow, labor dispatch, turnover rate, new recruitment rate
First of all, the questions raised
Human resource flow refers to the inflow or outflow of human resources between different countries, regions, urban and rural areas or industries and enterprises, which can be divided into macro human resource flow and micro human resource flow. Among them, the macro human resource flow mainly refers to the flow of human resources between countries, between regions within countries and between urban and rural areas within countries; Micro-human resource flow mainly refers to the flow of human resources between different industries, enterprises or enterprises. It is normal and necessary for enterprises to maintain the moderate flow of human resources. As the saying goes, "flowing water does not rot, and the family members don't bite." Moderate mobility will bring fresh blood to enterprises and help to maintain vitality. However, if the flow of human resources is unbalanced or the level of human resources flow is too high, it will bring many challenges to enterprises. Among them, the most important challenges are two:
First, the imbalance in the flow of human resources may lead to the shortage of employment in enterprises.
There are generally two commonly used indicators to reflect the flow of human resources, one is the turnover rate and the other is the new employment rate. When the turnover rate is equal to or less than the new employment rate, the staff size of the organization can be balanced or expanded continuously; On the other hand, when the turnover rate is greater than the new rate, the scale of employees will be reduced, resulting in the problem of "labor shortage". Under normal circumstances, a small number of employees leave their jobs and can be replenished in time through recruitment. However, if there are too many employees who leave in a short period of time and the turnover rate is too high, it will be more difficult for enterprises to fill vacancies, or even unable to complete recruitment tasks, and "job vacancies" will continue to exist.
Second, a high level of human resource mobility will bring "high" human resource costs to enterprises.
The flow of human resources, especially the resignation of employees, will bring additional costs. Turnover costs generally includes explicit cost and implicit cost. The obvious costs such as direct economic losses caused by employee turnover will erode the operating profit of enterprises and cause the operating profit of enterprises to decline. Hidden costs are often indirect losses. The management risks caused by these indirect losses are sometimes higher than their direct economic losses. Generally speaking, the higher the level of human resource mobility, the more job vacancies and the number of people who need to be recruited, and the higher the corresponding costs.
It can be seen that in order to maintain sustainable development, enterprises must keep the internal human resource flow at a moderate level and maintain a dynamic balance, otherwise enterprises will encounter the problems of "labor shortage" and "high labor cost". If the long-term new employment rate is less than the turnover rate, the scale of employees will inevitably shrink and eventually "no one is available" and go bankrupt. Because of this, it is necessary for enterprises to establish a set of indicators monitoring system on the flow of human resources. The monitoring content of this system should include the level and balance of human resource flow, and the monitoring object can be all employees or some important positions or key groups.
Considering the cost, the construction of this monitoring system should be based on the existing data without additional resources for collection. If we can build such an index monitoring system on the basis of existing data through data mining and statistical analysis technology, this work will be more operable and valuable. Considering that among all kinds of employees in enterprises, the human resource flow level of labor dispatch employees is high. Therefore, this study intends to start from this group, analyze the level and balance of human resource mobility of this group, and actively explore the connotation behind relevant indicators and potential influencing mechanisms, such as the impact of demographic variables such as gender and generations on human resource mobility, so as to provide decision-making basis for enterprises to manage and control human resource mobility.
Second, research methods.
1, material analysis and data mining steps
In order to achieve the above research objectives, this study takes a 7-force resource company in Suzhou as an example. With the permission of the company, this study selected eight labor dispatch projects of the company's manufacturing enterprises in Suzhou. These eight labor dispatch projects began to exist in July of 20XX and have continued to this day. In this study, the employee rosters of these eight projects with a total of 265,438+0 months from July 20XX to March 20XX were selected as the analysis materials. The monthly employee roster provided by the company includes the following fields:
① ID number (hereinafter referred to as ID card);
② gender;
3 entry time;
④ Time of resignation (non-resignation record is blank).
According to these four fields, according to the following steps, the following data information can be mined:
First of all, using the uniqueness of ID, the data of 2 1 month can be combined to generate a file, with one line of data for each ID. Each row of data includes:
①ID (ID number);
② gender;
3 entry time;
4 departure time.
In addition, the variable "date of birth" can be extracted according to the ID, and the intergenerational information of employees can be determined based on this variable (1=90, before 2=90).
Secondly, by using the information in the fields of "Entry Time" and "Exit Time", we can judge the working status of each employee every month since he took office. In each month, the following four variables can be used to describe the working status of employees:
① New employees (1= Yes, 0= No) are employees whose "Entry Time" is the current month;
② Resigned employees (1= Yes, 0= No) are employees whose "Resignation Time" is in the current month;
(3) Employees who started working at the beginning of the month (1= Yes, 0= No) are employees whose starting time is before 1 day of the current month, but whose leaving time is after 1 day of the current month or whose value is blank (20XX is still working on March 3 1 day);
④ On-the-job employees at the end of the month (1= Yes, 0= No) are employees whose starting time is before the last 1 day of the month, but whose leaving time is after the last day of the month or whose value is blank (they are still on the job on March 3 1 day of 20XX). Since the statistical period is 2 1 month, repeat 2 1 time according to the above operation rules, and * * get the working status of 2 1 employee (monthly 1 employee).
Thirdly, taking all employees, male employees, female employees, post-90s employees (1990- 1999 employees) and pre-90s employees (1990 employees) as the analysis objects, all employees in February1month can be counted separately according to their monthly salary. Calculate the new employment rate and turnover rate of all employees, male employees, female employees, post-90s employees and pre-90s employees in each +7 1.
2. Sample characteristics
At the beginning of statistics (20XX July 1), there were 2,663 on-the-job labor dispatchers. After 2 1 month of inflow and outflow of human resources, by the end of statistics (20XX March 3 1), there were 52 on-the-job labor dispatchers, with a net loss of 1406544. During the statistical period of 2 1 month, there were 17562 dispatched workers who left their jobs successively, with an average of 836 people leaving their jobs every month. Together with 1262 dispatched workers who were on duty at the end of the period, the total number of dispatched workers involved in this study (including those who left their jobs and those who were on duty) was 18824.
Third, the result
1, analysis of human resource flow level
The turnover rate and new employment rate are the most important indicators to reflect the level of human resource mobility. In order to describe the level of turnover rate and new employment rate of all labor dispatch employees, and analyze the internal relationship between them, this study conducted descriptive statistics and related sample T test on these two sets of data, and the results showed (as shown in Table 1):
① The lowest turnover rate of all labor dispatch employees is 29.2%, the highest is 88.2%, and the average is 42.1%;
(2) The lowest new employment rate of all labor dispatch employees is 9.3%, and the highest is 103.6%, with an average of 38.5‰.
③ There is a significant positive correlation between the turnover rate of all labor dispatch employees and the new recruitment rate (R=0.443, P = 0.044);
④ There is a difference of 3.6 percentage points (MD=3.6%) between the monthly average turnover rate of all labor dispatch employees, but this difference is not statistically significant (t = 0,707, df=20, p=0.488).
2. Comparison of differences
(1) Comparison of gender differences in the level of human resource mobility
In order to analyze the horizontal differences and internal relations between different sexes in the turnover rate and new employment rate of labor dispatch employees, this study conducted descriptive statistics and related sample T test on the turnover rate and new employment rate of male and female labor dispatch employees. The results show (as shown in Table 2):
1. The lowest turnover rate of male labor dispatch employees is 33.0%, the highest is 109.3%, and the average is 47.1%; The lowest turnover rate of female labor dispatch employees is 22% and 2%, and the highest is 55%, with an average of 34% and 4%. There is a significant positive correlation between the turnover rate of male labor dispatch employees and that of female labor dispatch employees (r = 0,757, P
Secondly, the lowest new employment rate of male labor dispatch employees is 9,2%, and the highest is116,0%, with an average of 43,7%; The lowest employment rate of female labor dispatch employees is 6.2%, the highest is 83. 1%, and the average is 37.0%. There is a significant positive correlation between the new recruitment rate of male labor dispatch employees and the new recruitment rate of female labor dispatch employees (r = 0,942, P
(2) Comparison of intergenerational differences in the level of human resource mobility.
In order to analyze the "level" of turnover rate and new employment rate of labor dispatch employees in different generations and their internal relations, this study conducted descriptive statistics and relevant sample T-test on turnover rate and new employment rate of labor dispatch employees after 1990s and before 1990s. The results show (as shown in Table 3):
1. The lowest turnover rate of post-90s labor dispatch employees is 29% and 9%, and the highest is 89 and 1%, with an average of 44 and 0 ‰. Before 1990, the lowest turnover rate of labor dispatch employees was 2 1 and 3%, and the highest was 85 and 5%, with an average of 37 and 0%. There is a significant positive correlation between the post-90s employee turnover rate and the post-90s employee turnover rate (r = 0,791,P < 0,001). The monthly average turnover rate of post-90s labor dispatch employees is 7 or 0 percentage points lower than that before (MD=7, O%), and the difference between them is statistically significant (t = 3,438, df=20, P = 0,003).
Secondly, the lowest new employment rate of post-90s labor dispatch employees is 8% and 9%, and the highest is 103 and 7%, with an average of 39 and 7%. Before 1990, the lowest new recruitment rate of labor dispatch employees was 28 and 9%, and the highest was 103 and 7%, with an average of 35 and 5%. P & lt； There is a significant positive correlation between the new employment rate of post-90s labor dispatch employees and the new employment rate of post-90s labor dispatch employees (r = 0,953, P
Four. Main conclusions and discussion
According to the above results, some main conclusions can be summarized as follows:
1. At present, the human resource flow of labor dispatch employees is relatively high, showing a trend of "high outflow" and "high inflow".
According to the above results, we can see that in 2 1 month, the lowest turnover rate of labor dispatch employees is 29.2%, the highest is 88.2%, and the average is 42 1%, while the lowest turnover rate is 9.3% and the highest is103,6%, and the average is. In other words, during the low peak period, nearly 29% and 9% people leave every month, 9% and 3% people leave, while during the peak period, 88% and 2% people leave every month, 103 and 6% people enter. Judging from the minimum turnover rate of 29 or 2%, enterprises are often unbearable. If there is no inflow of personnel, the turnover rate of 29 or 2% means that all employees in the enterprise will be lost in only 3 or 425 months; Based on the average turnover rate of 42 1%, it may be all lost in 2375 months. These data fully reflect the current high level of human resource mobility of labor dispatch employees, in other words, this group is facing serious employment instability.
2. There is a significant positive correlation between turnover rate and new entry rate.
This means that there is an associated relationship between the two, and there may be a high level of turnover rate behind the strong recruitment demand (high and new rate) of enterprises. In recent years, some developed coastal cities have experienced the phenomenon of "labor shortage" at a certain time (such as September, June, June, June, 10, around the Spring Festival). Many media will attribute it to the exhaustion of the demographic dividend-that is, the human resources market cannot provide enough supply. In fact, the decrease in the supply of human resources market is not the main reason for the phenomenon of "labor shortage". The main reason is that the "employment demand" of enterprises has suddenly increased. There are two reasons for the sudden increase in "employment demand".
First, the increase of enterprise orders or the expansion of scale.
Another situation is that a large number of job vacancies are caused by the "high turnover rate" of employees. If an enterprise wants to maintain a dynamic and balanced development, it will inevitably recruit a large number of people in a short time. If the human resources market cannot provide enough supply in a short time, the problem of "labor shortage" will persist; If the human resources market can provide sufficient supply in a short time, the problem of "labor shortage" will be alleviated, but at the same time, it will be followed by a high "new rate". As shown in the above results of this study, the average monthly new employment rate of labor dispatch employees is 38.5%, which is significantly lower than the average monthly turnover rate of 42. 1%. This means that at present, almost all labor dispatch agencies recruit employees to supplement the brain drain.
3. At present, the flow of human resources is unbalanced, and the outflow of human resources is slightly higher than the inflow of human resources.
Although there is no statistically significant difference between the average monthly turnover rate of 2 1 month and the average monthly turnover rate, the difference of 3 or 6 percentage points per month can not be ignored. In the long run, the scale of labor dispatch personnel in this institution will definitely shrink gradually. In fact, this trend is happening. In the period of 265,438+0 months, the number of labor dispatchers on seven projects decreased from the initial 2,663 to 65,438+0,262, with a net loss of 65,438+0,406,5438+0, and the number of personnel decreased by 52% and 6%. For human resources institutions whose main business is labor dispatch, if this trend continues, the final outcome can only be the end of the project and the closure of enterprises. For an employment enterprise, if the new employment rate is less than the turnover rate, there is only one result, that is, the enterprise continues to be "short of people" and eventually "no one is available". On the other hand, if the enterprise does not have the problem of "high turnover rate", then the "new recruitment rate" will not be so high, and the problem of "labor shortage" will naturally disappear. Of course, the new entry rate is slightly lower than the turnover rate, which may also be the result of business adjustment or transformation and upgrading. For example, the employment enterprise has reduced the employment scale of dispatched employees, or the enterprise has improved the automation production level or employee productivity through transformation and upgrading, and reduced the employment demand. Therefore, when the monthly average recruitment rate is less than the monthly average turnover rate, we should also analyze the reasons. If it is not because of these factors, but when the recruitment demand of enterprises is strong, but the recruitment ability of themselves or cooperative institutions can not keep up with or attract enough employees, enterprises should be extra vigilant and put forward countermeasures in time.
4. Gender and intergenerational factors have a significant impact on the monthly turnover rate and new employment rate of labor dispatch employees.
Compared with female employees, male employees and post-90s employees have a higher level of human resource mobility. From the above results, it can be seen that the turnover rate and new employment rate of male labor dispatch employees are significantly higher than those of women; However, the turnover rate and new recruitment rate of post-90s labor dispatch employees are higher than those before. This conclusion confirms the long-standing impression of human resources practitioners that male employees and post-90s employees are more unstable and tend to leave their jobs. There may be many reasons why male employees are more inclined to leave their jobs than female employees. For example, there are differences in self-concept, occupational character, professional interests and professional values between the two sexes. For post-90s employees, it may be because they are in the probation period when they first enter the workplace. People at this stage are often more inclined to constantly change jobs in order to seek more attempts, experiences or experiences. The two conclusions, "the new recruitment rate of male employees is higher than that of female employees" and "the new recruitment rate of post-90s employees is higher than that of pre-90s employees", may indicate that there are more male employees and post-90s employees in the current human resources market.
At present, the human resources market seems to be booming in both supply and demand. Some enterprises recruit a large number of people, and a large number of people are looking for jobs. However, this does not necessarily mean that the human resources market in this region is healthy and sustainable, nor does it necessarily mean that the economy is recovering and prospering. This probably means that the current regional human resources market is in a state of internal circulation and self-circulation. Employees just flow out from one enterprise in the region and then into another enterprise in the region, and the new employees in the enterprise are just employees flowing out from another enterprise. Therefore, the more male employees leave the company, the more male employees join the company. The more post-90s employees leave the company, the more post-90s employees join the new company. This high-speed circulation of internal human resources market seems to have created a booming human resources market, but it is actually a sign of the deterioration of the living environment of enterprises and the employment environment of employees.
Verb (abbreviation of verb) abstract
Through the above analysis, we can find that the monthly employee roster, through data mining and statistical analysis, can effectively monitor the level and balance of human resource mobility of enterprise employees or important employee groups, and at the same time reveal the dynamic relationship and internal relationship between turnover rate and new employment rate to some extent, as well as the influence of gender and intergenerational factors on the level of human resource mobility. As far as the labor dispatch staff group analyzed in this study is concerned, its human resource flow presents the following characteristics:
First, the flow of human resources shows a trend of high outflow and high inflow;
Secondly, there is a significant positive correlation between turnover rate and new entry rate;
Third, the flow of human resources presents an unbalanced trend; Fourth, gender and intergenerational factors have a significant impact on turnover rate and new entry rate.
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