Big data in China

Chapter 27 Big Data and Management Change (2)
However, at the end of World War II, a serious problem began to appear in the US talent supply and demand market-talent shortage.The veteran senior managers in the enterprise are getting older and need to abdicate. Who will take their place?New well-trained professional managers must be recruited.But here's the problem. From the Great Depression of the 20s and 30s all the way through World War II, the job market for recruiting was weak, and capable managers were in short supply like diamonds.Enterprises are anxious like ants on a hot pot. At this time, cultivating talents with potential among ordinary employees has become the most urgent task of the American business community in that era.

Since then, companies have begun to study formal recruitment and management systems.The reference at the beginning of the establishment of the system is mainly based on two parts: one is based on the latest research results of human behavior, and the other is derived from military technology developed during the two world wars.The first point is undoubtedly that ethology is of reference value in any era; as for the second point, because the country mobilized a large number of troops when the world war broke out, the casualties were serious, and the population was in short supply. Possibility to employ people efficiently.As long as you are a piece of gold, you can basically be found without shining light.

Until the 20s, the selection method that companies used to treat those candidates for professional positions was the layer-by-layer assessment method that we still use in companies today.That is to say, it takes several days for candidates to take part in a whole set of tests, including initial test, retest, interview and so on.

Every enterprise expects to unearth "tomorrow's star" in the vast sea of ​​people through rigorous testing. For this purpose, the process is tedious. A 1950 issue of "Business Week" wrote that when Procter & Gamble selected executive talent, it would start directly from colleges and universities.

It now appears that the selection system of that era was indeed blind and slow-acting.The recruitment process is like the assembly line of a factory. If a young man wants to become a senior executive, he needs to pass a series of tests such as IQ, mathematics, vocabulary, professional attitude, professional interest, Rorschach personality, personality, health status, etc. It stands out from a large number of "qualified products" and is labeled as "first-class product".

The intention of these large companies is obvious, that is, to test candidates through various tests, hoping that the tests can determine the right candidates.Some employees have been selected and entered the work process, but the test evaluation may not be over yet.

In 1956, "Business Report" reporter William White published a classic cultural critique titled "Organizing Man", in which he pointed out that about a quarter of the companies in the United States were using similar tests to evaluate managers and juniors. managers, and these tests are often used to assess the readiness of these managers for higher positions.

"Should Jones be promoted, or should she be put on hold? In the past, the employee's supervisors had to discuss this issue with each other to make up their minds. Now they can investigate with a psychologist and see what the psychological test results say." White in the book wrote in.

By 1990, this corporate recruitment method that was popular all over the world in the middle of the 20th century had almost disappeared from the market.Enterprises have given up the method of spending a lot of time on testing, but have begun to undertake temporary interviews. The content of the interview is that HR randomly asks a few questions, and candidates answer impromptu.

Regarding this phenomenon, Peter Cappelli said: "I think HR practitioners in the late 20s would have been shocked to see how casually recruiting is being done today."

What is the reason for this change?Cappelli cites many reasons for this change.For example, the phenomenon of employee hopping has increased, and the cost of testing is too high, which makes it unnecessary and unwilling for companies to spend resources on thorough testing; companies pay more attention to short-term financial profits, thus weakening the inherent function of long-term talent development; The "Bill of Rights" also makes some discriminatory recruitment companies have scruples, because they will be required to bear legal responsibility.Restricted and affected by various factors, companies slowly began to focus on less formal quantitative recruitment methods.This approach is still favored by many companies to this day.

However, the above-mentioned factors are all objective influences, subjectively because many evaluation methods used by those companies at that time were not scientific, and the development of recruitment methods later proved the defects of test recruitment.The funniest thing is that some methods have no real basis, just some psychological theories that have never been tested.There are also tests that were originally designed to assess psychiatric disorders, and are sometimes tested on an unrepresentative population, such as college freshmen, and the results of the test do not reveal anything meaningful other than that the test subject's response is " normal” or “abnormal”.

Interestingly, William White presided over some tests specifically for corporate presidents. The results of the tests found that none of the presidents scored up to the standard, and none of them were in the corporate standard recruitment category.

White believes that these tests are unscientific and cannot objectively assess the potential of candidates. Moreover, some tests are not very humane and involve too much privacy. For example, the testees need to answer personal habits or the emotional status of their parents. Wait.For this reason, many applicants are full of great aversion to these "aggressive" test questions.

Today, recruitment as a discipline is back on its feet thanks to new technologies and approaches to data analytics.Big data makes recruitment cheaper, faster, wider coverage, and more scientific results.In any case, technological creation has brought us endless possibilities, and a new era is beginning.

Information collection and analysis

☆The importance of information collection and analysis

For most companies in the world - I believe at least 80% of companies, even if they are holding high the banner of big data, big data itself is still just a very vague concept.Although they understand its significance very well, their words and deeds are inconsistent, and many wonderful ideas are difficult to be fully implemented.

For the application of management and the practice of big data, it is not only difficult for enterprises to participate, but it is also difficult to achieve perfect control over the process.One of the most common questions is: how to collect and analyze the massive data generated every day?This is a big problem, as one manager described to me: "I feel like I'm guarding a golden mountain, but I can't get started!"

Another boss complained: "What is the use of these data? It is said to be valuable, but here it can only give me a headache every day!"

For any company, such as practitioners in telecommunications, finance, retail and even the government, they all need data to help them make rational decisions, and they all have a strong demand for information collection and analysis.But the current situation is not ideal. For a long period of time in our country, more professional data analysis was limited to the financial and telecommunications industries.Companies in other industries lack sensitivity to this, and many practitioners even adopt an attitude of resistance or indifference.

The embarrassing part is that company decision makers are sometimes more willing to trust their intuition than data.While this awareness is gradually changing, some people never think about making a radical change.Mindset change is never easy, it's a hard rock.Only when some emerging industries start to emerge, and a group of companies that benefit from big data thinking emerge, can they realize that the benefits of data are so obvious.

But by this time, the era of big data has arrived on a global scale, and it is obviously too late for these people to catch up at this time.Even if you reflect deeply and are willing to pay the price to make up for the missed homework, you will only be able to play the role of a learner and a catcher for a period of time.

We have all seen that big data promises to drive a revolutionary overhaul in the field of management.Managers can use big data to make good measurements and make precise use of data to understand their company and make better business decisions.

This manifests itself in the importance we place on individuals of information, and managers must have the courage to translate this awareness directly into improved decision making and performance.Only by paying attention to the collection and analysis of data from the technical level and realizing "data is king" can we change the fate of the enterprise and even make ourselves the leader of the industry.

We know that Chinese companies such as Baidu, Tencent and Alibaba are already doing this.But we hope that all enterprises in China have the ability to collect and analyze data, not just a few typical enterprises.This is our dream of "Big Data China" and the ultimate goal of a data management reform related to the whole people.

In the past few years, according to my investigations on the practice of enterprises, the significance of big data management does not lie in the size of the data information you have mastered, nor in how well prepared your theory is, but in the understanding of these data. Whether the work of intelligent processing, analysis and digging out valuable information is in place.If you are absent from these practical tasks, all previous preparations will lose their meaning.

I find that it is still difficult for most companies to judge which data will become my good assets in the future, and how we need to extract and analyze the information and turn it into real income.For this point, even many professional companies engaged in big data services have difficulty giving a definite answer. People are still pondering and making progress. Even the best companies have only opened the first door in the wave of big data. The door entered the outermost room.But one thing is certain, in the era of big data, whoever has enough data will be able to control the future.Our current data collection is to accumulate liquid assets for the future.

☆Six key links of information collection and analysis

collection of information

Information collection is the first step and an essential first link.In foreign countries, giants such as Google and Amazon have already begun to deploy data collection.In China, Taobao, Tencent, Baidu and other companies have also collected and stored a large amount of user habits and user consumption behavior data.There is even a dedicated industry data collection system, and in the future, this system will be more developed, and more professional data collection companies will join in to provide information collection services.

information cleaning

After collection, it must be cleaned up.The reason is that after a large amount of messy and disorderly data is collected, how to filter out the useful data, complete the data cleaning work and pass it on to the next link smoothly is the first step we must carry out.There are already many professional data processing companies all over the world to complete such work, and similar companies have begun to appear in China, such as Huaao Data.They keep popping up, propping up China's data-processing industry.

Information storage and management
This is an intermediate link and also a medium link.After the information is collected and cleaned up, it must be stored and managed. These two links are connected and inseparable.Generally speaking, the way we manage data determines the storage format of the data, and how the data is stored ultimately limits the depth and breadth of our data analysis.If the data is not well preserved and managed properly, all subsequent links will become meaningless, and it will be difficult for us to achieve professional analysis and interpretation, and we will not be able to successfully realize the practical use of big data.

analysis of information

The purpose of analyzing information and data is to find out the correlation or causality, and then lay a good foundation for the next step of processing.In the past few years, data analysis companies based on Hadoop, an open source software infrastructure, have shown explosive growth.For example, Condre, which was established in 2008, is an excellent data analysis company that can help enterprises manage and analyze data based on open source Hadoop products.Because of its high-quality service, the company has a market value of more than 5 million US dollars in less than 7 years, and its regular customers include well-known multinational companies such as JP Morgan Chase.

interpretation of information

Interpreting information is to restore the results of professional big data analysis and embody it into specific problems, that is, to transform "problems" into "causes of problems" and "applications of problems".In this field, there are many data restoration companies that provide high-quality services, such as Wibidata and many emerging data restoration companies in China, who are doing this work and are increasingly specialized.

quantification of information

The last step, which is also the most important part of big data management, is to utilize the data.In this link, through the analysis and visualization of data, the conclusions that can be derived from big data are quantified and calculated, and then its application is realized.The purpose of quantification is to draw conclusions and put them into practice.

Another conundrum for you is: "How much information do I need to make a judgment?" In most startups, managers feel that the more information the better, ideally from everyone on the planet. data, but in my opinion, obtaining the personal data of key people is more meaningful for management.This will make our big data thinking move towards science, instead of blindly seeking massive data.

Big Data Management Application--Prediction and Control

What will be done after data collection, management and utilization?We must do some practical work to reflect the management value of big data, that is, to use it for prediction and control, and to achieve precise control.

☆Future management--Big data is well known

Any idea or technology, in the final analysis, serves people, and people must occupy a dominant position.In other words, human needs are actually another driver, and the same is true for big data management.If you are engaged in big data management not to manage people and manage people's future, then you will deviate from the essence of management and the original intention of using data.

Through big data management, we can "know the future like the palm of our hand".So if you understand the essence of big data management, you will be able to have this experience for your future.We use big data to help us understand the world, and then understand human nature and ourselves.If a person can reach this state, is it still difficult for him to manage a company?It's a piece of cake.

Therefore, one principle that must be followed when applying big data in management is to keep one eye on the data and the other on people.You not only need to know what’s going on during business operations, understand physical data such as how products are designed, how to control costs, etc., but also be able to gain insight into how your employees think and what needs they have at different stages. Thinking data.

How to do it?The solution is to virtualize the data.You have to convert it into a digital process, and use the digital process to describe physical processes, logical processes, chemical processes, and so on.When they are virtualized, we can conduct data analysis very calmly, see through the essence, summarize and quantify its laws.Finally, act according to the law, and you can grasp the future.

☆Prediction - we must first understand our own object
(End of this chapter)