Contributors
- Raja Iqbal, Founder and CEO, Data Science Dojo
- Brian Wong, MBA,MMA,CPA, CMA, Management Consulting, Data & Analytics
- Ian Feng, FRM, Capital Market Innovator, Data Zenatic
- Slava Spirin,CFA, Data Scientist
- David Weber, Palm Beach State College
- Calvin Robinson, NASA
- Bruce Krogman, NASA
Your Challenge
- Data can be valuable if used properly or dangerous when mishandled.
- The organization needs to understand the value of their data before they can establish proper data management practice.
- Data is not considered a capital asset unless there is a financial transaction (e.g. buying or selling data assets).
- Data valuation is not easy, and it costs money to collect, store, and maintain data.
Our Advice
Critical Insight
- Data always outlives people, processes, and technology. They all come and go, while data remains.
- Oil is a limited resource, data is not. Contrary to oil, data is likely to grow over time.
- Data is likely to outlast all other current popular financial instruments including currency, assets, or commodities.
- Data is used internally and externally and can easily be replicated or combined.
- Data is beyond currency, assets, or commodities and needs to be a category of its own.
Impact and Result
- Every organization must calculate the value of their data. This will enable organizations to become truly data-driven.
- Too much time has been spent arguing different methods of valuation. An organization must settle on valuation that is acceptable to all its stakeholders.
- Align data governance and data management to data valuation. Often organizations struggle to justify data initiatives due to lack of visibility in data valuation.
- Establish appropriate roles and responsibilities and ensure alignment to a common set of goals as a foundation to get the most accurate future data valuation for your organization.
- Assess organization data assets and implementation roadmap that considers the necessary competencies and capabilities and their dependencies in moving towards the higher maturity of data assets.
Talk to an Analyst
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Each call will focus on explaining the material and helping you to plan your project, interpret and analyze the results of each project step, and setting the direction for your next project step.
Book Your Workshop
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Module 1: Understand the Value of Data Valuation
The Purpose
Explain data valuation approach and value proposition.
Key Benefits Achieved
A clear understanding and case for data valuation.
Activities
Outputs
Review common business data sources and how the organization will benefit from data valuation assessment.
- Organization data valuation priorities
Understand Info-Tech’s data valuation framework.
Module 2: Capture Organization Data Value Chain
The Purpose
Capture data sources and data collection methods.
Key Benefits Achieved
A clear understanding of the data value chain.
Activities
Outputs
Assess data sources and data collection methods.
- Data Valuation Tool
Understand key insights and value proposition.
Capture data value chain.
Module 3: Data Valuation Framework
The Purpose
Leverage the data valuation framework.
Key Benefits Achieved
Capture key data valuation dimensions and align with data value chain.
Activities
Outputs
Introduce data valuation framework.
- Data Valuation Tool
Discuss key data valuation dimensions.
Align data value dimension to data value chain.
Module 4: Plan for Continuous Improvement
The Purpose
Improve organization’s data value.
Key Benefits Achieved
Continue to improve data value.
Activities
Outputs
Capture data valuation metrics.
- Data valuation metrics
Define data valuation for continuous monitoring.
Create a communication plan.
- Data Valuation Communication Plan
Define a plan for continuous improvements.