A study conducted by Deloitte in Bersin shows that more than 60% of enterprises spend a lot of money on big data analysis tools, hoping that these tools can help their human resources departments to make more data-dependent decisions. But few companies have really done this.
A huge gap
Through the investigation of 480 enterprises, we found that only 4% enterprises have realized the "predictive analysis" of employees. In other words, only a few companies can really understand the factors that affect employee performance and retention, know how to use data to determine recruitment targets, and know how to analyze the correlation between performance and salary. In our research, only 14% enterprises have done substantial data analysis on employee data.
So what are the remaining 84% doing?
A mess of reports. These enterprises are still confused about how to manage data effectively and are trying to organize data. In the face of successive data reports, they still can't generate standardized operational indicators, thus realizing the real use of data.
In fact, many enterprises are still at a relatively early stage in using data.
Maturity model of data analysis
Sharp tools make good work.
If you want to apply big data like a duck to water, software and tools are important, but you can't ignore other inputs: efficient data management mode, providing high-quality data sources; Business consulting ability, so as to be able to identify problems and needs; Keep close contact with financial and operational analysis department; Visual design and communication skills. These skills are as important as statistical knowledge, data analysis technology and mathematical application ability.
In fact, most HR teams point out that it is not difficult for them to find a statistician, but it is difficult to find a project manager who can combine data with business applications and turn research results into a landing plan.
From the functional level, an efficient analytical technical team has good multidisciplinary ability, including business understanding, consulting skills, data visualization technology, data management ability, statistical knowledge and leadership ability. They should not only diagnose and solve the business problems of enterprises, but also provide fresh and timely information for management.
In the process of enterprises using big data, the biggest problem is how to make people change their inherent behavior after having data. Most managers have a set of "thinking system" and the so-called "experience model" accumulated over the years. These are all factors that prevent decision makers from believing and using data.
Human resource manager of "intentional crime"
In the research object, a company analyzes the turnover rate and retention rate of employees with salary increase as a variable. Their previous salary levels were roughly in line with the positive distribution, and employees with better performance received a slightly higher salary increase than those with lower performance. The report says this:
"As our other research results show, the company's current salary distribution is a mistake. Those employees in the second and third bands (excellent employees) will still choose to stay in the company even if their salary increase is only 9 1% of the average. In other words, these people take too much.
On the other hand, those employees at the far right of the positive distribution will only stay if the salary increase is higher than the average level of 15%-20%. "
Most managers believe that the performance of senior employees is much higher than that of middle-level employees. If these people can stay in the company, paying them a high salary is actually extremely beneficial to the company. Therefore, even after learning the research results, they still pay their employees as before. Therefore, the company has to launch a training plan and new software tools to correct the managers' inherent way of thinking, so that they can decide the salary and reward distribution more according to the data.
Only 14% of enterprises actually use big data.
There are too many examples to prove that HR decision supported by data can bring higher return on investment.
But unfortunately, too many companies have not set foot in this field, so they can't profit from it.
If you can't integrate data analysis ability into HR strategy and generate a set of internal management and salary distribution system supported by big data, then the fate of becoming a loser is inevitable.
The above is the data analysis maturity model shared by Bian Xiao. What stage are you at now? For more information, you can pay attention to Global Ivy and share more dry goods.