Mandate Data Valuation Before It’s Mandated
Organizations have data problems because they struggle to establish the real business value of their data. Understanding the value of your data is the first step towards solving your data problems.
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Organizations have a constant struggle with data.
- Data can be valuable if used properly or dangerous when mishandled.
- 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.
- Fake news and hacking of critical information have shown potential liabilities incurred by these organizations.
Calculating the value of the data is something every organization must do to ensure the future growth of the organization.
- Facebook, Google, and many other tech giants have successfully offered value-added services as a result of the underlying value of data.
- Understanding the value of your data is the first step towards solving your data problems.
- We can no longer hide data value under “intangible assets.”
- Organizations are starting to consider data as a key strategic asset.
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Onsite Workshops offer an easy way to accelerate your project. If you are unable to do the project yourself, and a Guided Implementation isn’t enough, we offer low-cost onsite delivery of our Project Workshops. We take you through every phase of your project and ensure that you have a road map in place to complete your project successfully.
Book NowModule 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: | |
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1.1 | Review common business data sources and how the organization will benefit from data valuation assessment. |
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1.2 | Understand Info-Tech’s data valuation framework. |
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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: | |
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2.1 | Assess data sources and data collection methods. |
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2.2 | Understand key insights and value proposition. |
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2.3 | Capture data value chain. |
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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: | |
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3.1 | Introduce data valuation framework. |
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3.2 | Discuss key data valuation dimensions. |
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3.3 | Align data value dimension to data value chain. |
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Module 4: Plan for Continuous Improvement
The Purpose
Improve organization’s data value.
Key Benefits Achieved
Continue to improve data value.
Activities: | Outputs: | |
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4.1 | Capture data valuation metrics. |
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4.2 | Define data valuation for continuous monitoring. |
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4.3 | Create a communication plan. |
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4.4 | Define a plan for continuous improvements. |
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