From intuition to quantitative analysis enterprise management makes big data decision

Remember last year 8 15 competition? If you are the CEO of a certain electric company, would you adopt such a competitive strategy? Change is the eternal theme, business management can not be static. In the big data age, it is unwise for the electric trader to adopt price warfare, and to control the management based on the big data strategy will help you to surpass the existing CEO.

Cost leading strategy, differentiation strategy and centralization strategy are the three strategies that enterprises can choose in market competition. In the era of information explosion, the fourth strategy of big competition strategy becomes the support of the original three competitive strategies.

Big Data Change Enterprise decision

The traditional enterprise management process is the problem, logic analysis, find causal relationship, put forward the solution, make the problem enterprise become excellent enterprise, this is the reverse thinking mode. The consulting process of large data competition strategy is to collect data, quantify analysis, find out the mutual relation, propose the optimization plan, make the enterprise from excellent to excellent, is the positive thinking mode.

"Data is the basis for future competitive advantage and will be an important resource." "As cloud computing, mobile Internet, social networking and big data are growing fast, this technological advance will change every aspect of business," said IBM CEO Rometty at an event organised by the nonprofit Foreign Relations Association March 9. "Rometty that big data will change the way companies make decisions, value creation and value realization."

Now the management consulting industry pursues the "plan", "feeling" type of business management is to the leaders and managers based on their subjective perspective and experience to look at information. At present, even in a scientifically oriented field, decision-making is still based on fixed perceptions. "Later, more decisions will be based on large data analysis rather than personal intuition," says Rometty. "Rometty believes that with more and more information, if the data can be used rationally, enterprise decision-making will be better and more objective." An example of a project "Using data history to reduce crime", which IBM has collaborated with the U.S. Memphis Police, is a case in point. The project analysis found a link between the rape case and the outdoor pay phone. Therefore, the police decided to transfer the pay phone to the room, which led to a 30% reduction in the incidence of rape cases. Rometty further said that in order to make rational use of large data, the way of thinking needs to change.

The biggest shift in the big data age is to give up the search for causation, instead of focusing on relationships, as Schoenberg in the big Data age. That means just knowing what "is" without needing to know why. This is different from the existing thinking practice of scientific research, which provides a new model for human cognition and the way to communicate with the world. Schoenberg points out three thinking changes in large data applications: Random samples to all data, precision to confounding, and especially large data simple algorithms that are more efficient than complex algorithms for small data;

The technical challenges of big data are obvious, but the management challenges are more daunting to start with a shift in the role of the executive team. The most important thing about big data is that it will directly affect how companies make decisions and who make decisions. In today's entire business world, people still rely more on personal experience and intuition to make decisions, rather than on data. In an age of limited information, high cost and no digitization, it is in the real world to make decisions for people in high places. This kind of decision maker and decision-making process is a kind of intuitionistic school, which now encounters Big Data challenge.

Quantitative analysis based on platform

Big data challenges intuition, the first thing to do is quantitative analysis. Business management is divided into many factions because of different viewpoints, but the idea that "cannot be quantified cannot be managed" is a consensus. This consensus is enough to explain why the digital explosion of recent years has been extremely important. With large data, managers can quantify everything in order to master the company's business, thereby improving the quality of decision-making and performance.

The quantitative analysis of large data by enterprise managers should begin with the change of thinking mode. Industry experts point out, first of all, to develop a habit of thinking: "How to say the data?" Whenever there is a major decision, follow the question further and ask, "What is the analytical result based on this data?" The change of thinking of enterprise management will also improve the executive power of enterprise staff on large data management. Second, business managers should allow data to be the master. If employees use the big data from the first line to analyze the results, overturning the intuitive judgment of senior executives, this will be the biggest power to change the culture of corporate decision-making. Based on the large amount of data to make reasonable decisions, the middle of a long process of analysis.

The quantitative analysis of large data here is similar to the traditional "data analysis", where large data also seek to gather wisdom from the data and turn it into an enterprise advantage. The difference is that large data data are huge, the data is fast and diverse. When a data source has these three properties, it forms a platform. Companies that are born with digital genes, such as Google and Amazon, are already big data platforms. However, for traditional enterprises, the potential for using large data to gain competitive advantage may be greater. Companies can do precise quantification and management, make more reliable predictions and smarter decisions, and be more objective and efficient in their actions. These can be achieved in an area that has always been dominated by intuition rather than data and rationality. Although perceptual intuition and rational data are contradictory, perceptual judgment based on rational data is feasible, especially in the enterprise Operation level.

and June Consulting Group partner Senior Consultant Ling that the impact of large data on business management temporarily stay at the operational level, less internal management. Telecom operators, banks, Alibaba, such as platform-type enterprises have enough data, only hope to use large data for enterprise operation and Management. Ling said: "The higher the level of enterprise management strategy, the lower the value of large data contribution." Now, the big data to the enterprise's contribution mainly at the operational level. "In Ling's view, based on telecommunications, banks and other large data platforms, through quantitative analysis, can outline the image of the individual, including personality, temperament, height, weight and so on." With the constant spread of the tools and ideas of large data, the value of many deeply rooted experiences will be shaken. With some other profound changes in the business world, the company to "large data-driven" transformation will encounter enormous challenges, it requires managers to let go of the "Big Data" awareness, the ability to quantify the large data analysis, the use of large data to improve performance management capabilities.

(Responsible editor: The good of the Legacy)