Five ways of data analysis technology subverting business model

Five ways of data analysis technology subverting business model

In recent years, more and more large enterprises have begun to invest in data analysis technology, hoping to prove that "I can do better". The rise of cloud computing also enables start-ups with limited scale to combine big data technology with advanced data analysis. In today's article, we will discuss five ways that data analysis technology brings subversion to business model.

20 17 10 10, Tencent announced that it would invest 1 1000 billion US dollars to Ole, who ranks first in the horse racing market. But Ola is not the only company that challenges the existing business model.

Look at the rise of Uber, Amazon, Airbnb, edX, Netflix, Society One and Catway Eagle. They all looked at a determined person in their industry and said, "I can do better."

80% companies predict that their industries will be affected by new technologies in the next three years.

With the help of cloud computing, even the smallest startup can combine big data technology with advanced data analysis. Every day, the ability to discover new operational and market insights and undeveloped customer base is growing.

More than 90% companies think big data and analysis are strategic priorities, but Bain said that only 65,438+09% companies continue to collect high-quality data!

Most competitors may not use data technology, but what about you? If you are lazy, you can guarantee that an entrepreneurial or innovative competitor will look at you.

The power of data

Big data has become a powerful resource. If you blindly aim at potential customers, the company will not succeed. In order to flourish, you need to know exactly where you are going, why you are going there, and the efforts you are willing to make in your journey.

Big data is your guide.

However, you need to have a clear vision, strategic approach and use cases to advance your big data discovery. You need to participate in usage analysis in order to have a comprehensive understanding of the business.

To do this, we need to redefine the way data is handled and set a benchmark for the use of data.

Five Methods of Mining Transformational Data

1. Strategic analysis

Strategic analysis is a detailed and data-driven analysis of the whole system to help you determine the factors that drive customer and market behavior.

The key to strategic analysis is to follow the correct order:

Step 1- competitive advantage analysis to determine your abilities, strengths and weaknesses.

Step 2- Enterprise Analysis can obtain diagnostic information at enterprise, business unit and business process level.

Step 3- Human Capital Analysis Diagnoses at the individual level to gain actionable insights.

These data should answer the following key questions:

What are the key decisions that bring us the greatest value?

What new data have not been mined?

What new analytical techniques have not been fully explored?

2. Platform analysis

This helps you integrate analysis into your decision-making process, thus improving your core business. It can help your company use the power of data to discover new opportunities.

Important questions to ask include:

How do we integrate analysis into our daily processes?

What processes will benefit from automatic, repeatable real-time analysis?

Can our back-end system benefit from big data analysis?

Platform analysis must include a variety of technologies. Because it can be obtained through various formats and channels, it can be used to check the pulse of the organization.

It will help you integrate data analysis into key decisions of all departments, including sales, marketing, supply chain, customer service, customer experience and other core business functions.

3. Enterprise Information Management (EIM)

Nearly 80% of important business information is stored in an unmanaged repository. Through strategic and platform analysis, EIM can help you use social, mobile, analytical and cloud technologies (SMAC) to improve data management and usage within the company.

By using information creation, capture, distribution and consumption tools to build agile data management operations, EIM will help you:

Simplify your business practices.

Strengthen collaborative efforts.

Improve the efficiency of employees in and out of the office.

When you define your EIM strategy, identify business needs, key issues and opportunities, start EIM. In addition, identifying potential projects and their success rates will benefit from EIM.

4. Business model transformation

Companies that adopt big data analysis and parallel transformation business models will create new opportunities for revenue sources, customers, products and services.

From forecasting demand and purchasing materials to accounting, as well as employee recruitment and training, every aspect of your business can be redesigned.

The required changes include:

Have a big data strategy and vision and be able to identify and take advantage of new opportunities.

Cultivate a culture of innovation and experimental data.

Learn how to take advantage of new skills and technologies and manage their impact on how to access and maintain information.

Establish a trust relationship with consumers who have important data.

Establish partnerships inside and outside core industries.

Find ways to gain insight and implement results quickly.

5. Establish a data-centric business

Do you generate a lot of data? Will these data benefit other organizations inside and outside the industry?

Data-centric business is not only an asset, but also a currency. This is the source of your core competitiveness, and its value is reflected in gold.

There are three main types of data analysis:

Perspective: It includes data mining, cleaning, clustering and subdivision to understand customers, their networks, influence and product insight.

Optimization: analyze business functions, processes and models.

Innovation: Explore new disruptive business models and promote the development and growth of customer base.

The established business model has been attacked.

Data analysis is rapidly subverting the way we do business. These five revolutionary applications of data analysis will help you become a forward-thinking company and gain a competitive advantage in the market.

No industry's data analysis can't benefit from it.