In the dynamic world of data monetization, the right enterprise capabilities can significantly accelerate initiatives and reduce costs. These capabilities are the bedrock upon which successful data-driven strategies are built. Imagine these capabilities as elements of a Formula 1 (or E-Formula) race track, where initiatives are the racing team striving for victory. Here’s how each capability contributes to your success:

1. Acceptable Data Use: Security Barriers
2. Customer Understanding: Luxurious Stands and Amenities
3. Data Science: Well-Fitted Facilities for Your Pit Crew
4. Data Platform: Beautifully Engineered Track
5. Data Management: Shared and Secure Fueling Stations

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Acceptable Data Use: Security Barriers

In a race, security barriers are essential for protecting the drivers and maintaining the integrity of the race. Similarly, acceptable data use ensures that data is handled ethically and complies with all regulations. It involves internal oversight, external oversight, and automation to prevent misuse and maintain trust.

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Key Components:

• Internal Oversight
• External Oversight
• Automation

Key Questions:

• Are your data governance policies comprehensive?
• How do you ensure compliance with regulations?

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Customer Understanding: Luxurious Stands and Amenities

For a race to be successful, the spectators’ experience is crucial. Luxurious stands and amenities keep the audience engaged and satisfied. Customer understanding is about making sense of customer data, co-creating solutions, and experimenting to refine offerings. It ensures that your products and services are desirable and meet customer needs.

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Key Components:

• Sense Making
• Co-Creation
• Experimentation

Key Questions:

• How well do you understand customer needs?
• Are you engaging customers in the co-creation process?

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Data Science: Well-Fitted Facilities for Your Pit Crew

The pit crew’s facilities must be top-notch to ensure quick and efficient car maintenance during the race. Data science facilities should be well-equipped to generate actionable insights from data. This involves using reporting, statistics, and machine learning to support decision-making.

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Key Components:

• Reporting
• Statistics
• Machine Learning

Key Questions:

• Are your data science capabilities generating actionable insights?
• Do you have the necessary tools and expertise?

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Data Platform: Beautifully Engineered Track

A beautifully engineered race track is essential for a smooth and exciting race. Similarly, a robust data platform ensures efficient data handling and accessibility. It involves advanced technology, internal access, and external access to enable seamless data flow.

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Key Components:

• Advanced Technology
• Internal Access
• External Access

Key Questions:

• Is your data platform scalable?
• Do you facilitate secure access for internal and external users?

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Data Management: Shared and Secure Fueling Stations

Fueling stations need to be shared and secure to keep the race running smoothly. Data management involves creating and maintaining accurate, integrated, and curated data. It ensures that data is reliable and readily available when needed.

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Key Components:

• Master Data
• Integrated Data
• Curated Data

Key Questions:

• Are your data management practices ensuring accuracy and consistency?
• Do you integrate data from diverse sources?

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Assessing and Utilizing Enterprise Capabilities

Enterprise capabilities that are not utilized become sunk costs. It’s crucial to ensure that these capabilities are effectively harnessed to support your initiatives. Assess your data monetization capabilities using a capability assessment worksheet to identify strengths and areas for improvement.

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Questions to Ask Yourself:

• What kind of value do you frequently create with data?
• Do you know it made it to the bottom line?
• Can you think of an opportunity for each of the three methods in your organization: improve, wrap, sell?
• Is the term data monetization okay to use in your organization, or does it have some unethical associations?
• Consider your weakest capability. What practices do you need to adopt?
• Which capability is most enterprise-wide?
• What policies, habits, or norms do you have that will ensure that the initiatives underway find and use capabilities?
• Do you distinguish between data and data assets?

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Conclusion

Building robust enterprise capabilities is like designing a world-class race track. Each element plays a crucial role in ensuring your initiatives are successful, efficient, and cost-effective. By focusing on data management, data platforms, acceptable data use, data science, and customer understanding, organizations can accelerate their data monetization efforts and achieve better outcomes. Remember, capabilities that are not used are just sunk costs, so it’s essential to leverage them fully to drive success.

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Book Reference

For a deeper understanding, refer to Data is Everybody’s Business: The Fundamentals of Data Monetization by Barbara Wixom, Cynthia Beath, and Leslie Owens.

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