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Showing posts with label Data Security Compliance. Show all posts
Showing posts with label Data Security Compliance. Show all posts

Saturday, September 21, 2024

From Raw Data to Real Profits: A Guide to Building a Thriving Data Business

In today's digital age, data has become one of the most valuable assets for businesses. However, merely possessing large amounts of raw data is not enough to create value - the key lies in effectively transforming this data into tangible business profits. This article will unveil the path from raw data to actual profits, providing comprehensive guidance for building a prosperous data business.

The Rise and Opportunities of Data Businesses

Nearly two centuries ago, during the rapid expansion of American commerce, Lewis Tappan and John M. Bradstreet pioneered the concept of commercial credit reporting. In an era of limited information, they established firms dedicated to collecting, analyzing, and selling business data, laying the foundation for modern credit bureaus and risk assessment practices. Their innovative approach filled a critical gap in the burgeoning economy, enabling more informed lending and investment decisions.

Lewis Tappan and John M. Bradstreet demonstrated the potential of transforming data into profitable products. They established companies dedicated to collecting, analyzing, and selling data, filling a critical gap in the business world that urgently needed reliable credit assessment methods. Today, with the rapid advancement of technology, the opportunities for data businesses are even more extensive. According to McKinsey's latest survey, approximately 40% of business leaders expect to create data, analytics, and AI-based businesses within the next five years - the highest proportion among all new business categories.

Why is Now the Best Time to Build a Data Business?

Technological advancements have created favorable conditions for the rapid and cost-effective development of data businesses:

  1. Enhanced Data Management Efficiency: Advanced data tools and technologies enable businesses to process, manage, and access real-time data more efficiently.
  2. The Rise of Generative AI: Generative AI has significantly reduced the cost of processing unstructured data (such as text, images, and videos), making it easier to analyze and utilize.
  3. The Proliferation of the Internet of Things (IoT): The decreasing cost of IoT technology allows businesses to collect and access real-world data faster and more economically.
  4. Widespread Use of Internal Data Products: Leading enterprises increasingly treat data as internal products, laying the foundation for data monetization.

Evaluating Opportunities and Formulating the Right Strategy

The foundation of building a data business lies in having unique data of sufficient scale or possessing a distinctive method for processing data and extracting commercial value from it. Businesses can consider the following three broad strategies:

  1. Creating Industry Standards: As Moody's, Standard & Poor's, and Fitch have done in the credit rating field. This strategy typically begins with large-scale aggregation of unique data and may eventually become an industry standard as network effects expand.
  2. Leveraging Insights from Active User Groups: Transforming data collected from active user groups into valuable insights for advertisers, suppliers, partners, and users.
  3. Converting Organizational Knowledge into Products: For example, evolving tools that solve internal business problems into profitable external products.

Key Considerations for Building a Sustainable Data Business

  1. Defining a Strong Customer Value Proposition:
    • Consider the type of "intelligence" provided by data products (from raw data to information, knowledge, and wisdom)
    • Choose an appropriate product delivery model (data platform, insight platform, or intelligent application)
  2. Adjusting the Operating Model:
    • Incentivize growth potential rather than short-term profits
    • Adopt new sales and pricing models
    • Invest in specialized technical skills
  3. Modernizing Data Technologies:
    • Establish a robust data infrastructure
    • Invest in core and advanced technical capabilities based on data types and delivery methods
  4. Managing Data Security, Privacy, and Intellectual Property:
    • Clarify data rights
    • Develop consistent data privacy principles
    • Pay attention to and comply with local laws
    • Prioritize data governance and security

Building a data business requires not only unique datasets but also the right capabilities to scale products. First movers often gain significant advantages in capturing untapped market opportunities. However, successful data businesses can not only create scalable and profitable models but also potentially establish lasting brands. By following the guidelines provided in this article, businesses can better navigate the complexities of data businesses, transform raw data into actual profits, and secure advantageous positions in the digital economy era.

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