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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.

  • 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.

Mandate Data Valuation Before It’s Mandated

Start here – read the Executive Brief

Read our concise Executive Brief to understand the value associated with the organization's data. Review Info-Tech’s methodology for assessing data value and justifying your data initiatives with a value proposition.

1. Demystify data valuation

Understand the benefits of data valuation.

2. Data value chain

Learn about the data value chain framework and preview the step-by-step guide to start collecting data sources.

3. Data value assessment

Mature your data valuation by putting in the valuation dimensions and metrics. Establish documented results that can be leveraged to demonstrate value in your data assets.


Member Testimonials

After each Info-Tech experience, we ask our members to quantify the real-time savings, monetary impact, and project improvements our research helped them achieve. See our top member experiences for this blueprint and what our clients have to say.

8.0/10


Overall Impact

$25,000


Average $ Saved

10


Average Days Saved

Client

Experience

Impact

$ Saved

Days Saved

Natural Resources Canada

Guided Implementation

8/10

$25,000

10


Onsite Workshop: Mandate Data Valuation Before It’s Mandated

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 roadmap in place to complete your project successfully.

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

1.1

Review common business data sources and how the organization will benefit from data valuation assessment.

  • Organization data valuation priorities
1.2

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

2.1

Assess data sources and data collection methods.

  • Data Valuation Tool
2.2

Understand key insights and value proposition.

2.3

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

3.1

Introduce data valuation framework.

  • Data Valuation Tool
3.2

Discuss key data valuation dimensions.

3.3

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

4.1

Capture data valuation metrics.

  • Data valuation metrics
4.2

Define data valuation for continuous monitoring.

4.3

Create a communication plan.

  • Data Valuation Communication Plan
4.4

Define a plan for continuous improvements.

About Info-Tech

Info-Tech Research Group is the world’s fastest-growing information technology research and advisory company, proudly serving over 30,000 IT professionals.

We produce unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. We partner closely with IT teams to provide everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.

Member Rating

8.0/10
Overall Impact

$25,000
Average $ Saved

10
Average Days Saved

After each Info-Tech experience, we ask our members to quantify the real-time savings, monetary impact, and project improvements our research helped them achieve.

Read what our members are saying

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Author(s)

Rajesh Parab

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
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