Full mastery of data analysis requires strong executive power

Absrtact: In the past 30 years, many companies have added new management to cope with the vagaries of the business environment. In the middle of the 80, the CFO was a strange position for most companies. However, along with the value management and the relationship between enterprises and investors

In the past 30 years, many companies have added new management to cope with the vagaries of the business environment. In the middle of the 80, the CFO was a strange position for most companies. However, with the increasing transparency of value management and corporate-investor relations, more and more companies have CFOs. With the growing importance of brand building and customer management to the company, the chief marketing officer becomes more and more important, and many companies set up a chief strategist to help the company deal with the challenges from the market.

Now, the power of data analysis is profoundly affecting the business landscape. Seizing the opportunities brought by data development, increasing profits, enhancing productivity and even creating new business units, has become a new requirement for enterprises-this requires not only the talent and investment in information infrastructure, but also the reform of ideas, the organization of front-line training, and the improvement of the team's executive power. Without strong executive power, it will be particularly difficult to fully harness the huge wave of data analysis.

The impact of large data on the company is very broad, involving marketing, risk, operations, etc., senior management can participate in different ways. In some cases, tasks can be delegated to CIOs, chief marketing officers, and chief strategy officers. Other companies may need new roles, such as chief Data Officer, CTO, or lead analyst, to build a first-class team of data analysis centers.

This article is devoted to clarifying the most important tasks of the relevant executives and to the key issues, and the answers to these questions help to reset the structure of the executives. It may sound very difficult to rethink the roles and responsibilities of senior executives, but given the opportunities and challenges created by the current data development, the development of the enterprise will be confronted with a crisis and possibly into a more competitive environment without restructuring the executive structure.

The six major tasks of the data Analysis team

The development and implementation of a large data and advanced analysis strategy, not only to provide data to external service providers for data mining, but let the company in the day-to-day business of the way to respond to changes. The unpredictable environment puts strict demands on the executive team. Experienced executives are irreplaceable, they can apply theory to reality, guide companies through difficulties, make difficult trade-offs, and show authority when decisions diverge. The new data analysis culture will become the new focus of enterprise leadership, which is the inevitable trend of development. Experience has shown that the data analysis team needs to complete six tasks. When assigning tasks and adding new jobs, business leaders need to fully assess these six tasks.

Innovative thinking

With innovative thinking, the senior team of innovative ideas needs to acquire data analysis knowledge to understand the role of large data. They also need to accept the fact that data has become the core of the business. Only when the thinking and ideas of the company's top managers change, can the long-term behavior change radiate the whole company. In the early stages, a very important question is "how can data analysis help companies achieve leapfrog development?" This development usually takes place in every important business and functional department of an enterprise, led by an influential senior executive.

The leader of a large transportation company asked its chief strategist to be responsible for data analysis. To spread new ideas and knowledge among company executives, the chief strategist arranged for executives to visit large companies with data minds. He then asked each business unit to make data analysis one of the priorities for next year's strategic plan. The practice was very successful. On the one hand, large data is integrated into the strategic goals of each sector, and on the other, it encourages managers in various sectors to focus on large data. Soon they began to share their ideas and explore new opportunities for analysis-all of which gave the company new energy.

Develop data analysis strategies

As with other emerging business opportunities, the potential for data analysis has not been fully exploited because of a lack of clear strategies, plans and standards. Many companies have been frustrated in this area, in part because there is no clear executive responsibility for data analysis or planning, or because there is no adequate discussion or time to prioritize large data analysis.

The chief executive of a telecommunications company is committed to developing data analysis, especially the use of data analysis to optimize customer relationships and pricing. Although the company hired a senior analyst, it quickly stalled. To be sure, the analysis team has worked hard to delve into model and analysis techniques. However, colleagues in the business sector did not train the level of managers in time to use these models: they had not yet understood the potential of these analyses and models, as these were not their strategic priorities.

As mentioned earlier, a clear plan is needed to fully realize the potential of data analysis. Planning needs to focus and clear the path to achieve the expected business performance, which is similar to the process of strategic planning. Making such a plan requires the support of the team.

In a North American company, the chief executive asks the head of online digital operations, who has a wealth of data knowledge, to develop an enterprise development strategy. The chief executive also requested that the person in charge of developing a development strategy should work with other business units that are unfamiliar with large data. This collaboration-combining data with analytical technologists and experienced frontline operators-ensures that the analysis objectives outlined in the plan focus on practical, influential business decisions. In addition, this collaboration pattern has become a blueprint for other business units to plan their practices after the executives have shared each other's processes.

Decide on a construction project, a service that needs to be purchased or leased

Other important decisions also require authoritative, experienced senior leaders who are involved in data integration, build advanced analysis models and tools to improve operational conditions, and thus raise huge resource requirements. More and more external vendors are now able to provide core data, models and tools. Therefore, the enterprise needs the experience of the executive to weigh the "independent development or purchase service"? Is it necessary to develop these models and analysis tools in-house and to fully possess the intellectual property of these customized analysis technologies to meet the immediate development strategic needs and anticipated operational improvements? or scale expansion is vital, Is it wiser to borrow experience and manpower from external suppliers? Creating powerful data assets also requires the involvement of senior leaders. Restricting access to critical external data requires the establishment of high-level partnerships with customers, suppliers, or third parties in other value chains.

Different retailers have chosen a completely different path, which allows business leaders to understand the range of factors they must weigh. Some retailers and data analysis companies have signed long-term contracts that cover a wide range of data analysis requirements. Other parties, including traditional and online enterprises, have also invested deeply in the internal data and analysis technology. Each option reflects a dynamic set of strategic, financial and organizational requirements that should be determined by top management rather than by mid-level managers.

Ensure the technical expertise of data analysis

In any strategic plan, the enterprise always needs to analyze experts to help achieve rapid and stable development. The current era of data analysis game based on open, cloud infrastructure, so that all internal and external data can easily be integrated in a user-friendly manner. The new environment also requires new management skills to mobilize more senior data specialists. These experts can develop forecasting or optimization models to ensure the reliability of development.

At present, in the hottest market in the world, many companies are scrambling to find these advanced technology talents, gain the valuable manpower and let them interact with the business leaders, thus changing the development of the company is the real task of the senior managers in the future, which usually requires creative solutions.

The big data leader of a major consumer goods firm decided to invest in a data analysis center in a region far from the company's headquarters, which has a wealth of data scientists and data engineers in favor of talented people and cultural environment. Next, the company leader completes the final step by making direct contact between each analysis team and the business team of this part.