Realize and increase the value of your data through effective data governance practices!!

Cost of Data

The "cost of data" refers to the various expenses associated with collecting, storing, processing, managing, and utilizing data within an organization. These costs can be both direct and indirect, spanning across different phases of the data lifecycle. Understanding and managing these costs is crucial for organizations to maximize the value derived from their data while ensuring efficiency and sustainability.

Several factors contribute to the cost of data, including but not limited to:

• Data collection cost
• Data purchasing cost
• Data licensing cost
• Data storage cost
• Data processing cost
• Data analysis cost
• Data utilization cost
• Data compliance costs (security, privacy, access)
• Support and maintenance cost
• Misuse or underuse cost
• Opportunity cost
• Technology depreciation cost (hardware & software changes)

The cost of data is multifaceted, encompassing everything from acquisition and storage to processing, management, and utilization. The cost of data can be substantial, and if an organization is unable to utilize data for business value creation, the value of that data will not be realized. In such cases, having large amounts of data becomes a burden, especially if the data cannot be utilized due to quality issues, utilization requirements, or use case-specific needs.

Value of Data

The "value of data" refers to the potential benefits, insights, and competitive advantages that an organization can gain by effectively collecting, managing, analyzing, and utilizing its data. Unlike the cost of data, which quantifies the expenses associated with data management, the value of data is about the positive impact it can have on a business's operations, decision-making, and overall success.

Key benefits of data include but not limited to:

• Informed decision-making
• Data-driven insights for developing new products and services that better meet customer needs
• Data-driven business models
• Operational efficiency
• Customer insight
• Personalization
• Market differentiation
• Speed to market
• Fraud detection
• Increased productivity with AI
• Data monetization
• Innovation
• Cultural transformation
• Long-term strategic planning

To realize the value of data, strong data governance practices must be implemented to ensure data quality, compliance, and efficient use of resources. If collected data cannot be used for any business scenario or use case, then the return on investment (ROI) cannot be achieved, meaning the benefits will not outweigh the costs. While the cost of data is not always prohibitive, it is essential to collect and maintain only the necessary data to achieve specific business objectives.

Calculate the value of your data

In general, the value of data is more challenging to quantify because it often depends on the outcomes that the data enables.

Example Scenarios:

Scenario 1: Increase Customer Lifetime Value (CLV) by analyzing high-quality customer data.

Assume you have 20,000 customers. Your team uses this high-quality data for analysis, and the results help increase the average CLV by $100 for all customers. The value of the data that you are collecting, governing, and utilizing to drive business improvement is:

(Average?CLV?increase) × (Total?number?of?customers) = ($100×20,000) =$2,000,000

Scenario 2: Reduce Time to Market and Add Additional Sales Revenue:

You are using data to analyze and determine how to shorten the time-to-market your product by 3 months, resulting in an additional $3,000,000 in early market sales. If the cost of data is $500,000 and the product development cost is $1,500,000, then the value of the data is:

(Additional early sales revenue – (Cost of product + Cost of data)) = ($3,000,000 – ($,1500,000 + $500,000)) = $1,000,000.

Govern your data assets to increase the value of your data

Microsoft Purview Data Governance offers integrated data governance experience which enables data producers and data owners to govern only essential data assets meanings data assets that matter for the business domain, data products, Critical data elements and other business concepts.

Business domain owners can define the business scenarios, processes, and use cases they need to support and then create the required business domains to be governed. Data product owners can develop data products for these specific business scenarios and use cases, associate relevant data assets with these data products, and govern them accordingly. If certain data assets are not associated with any data products or business domains, they do not require governance. This focused approach helps organizations prioritize what matters most and decide which data to collect, retain, and utilize to make better decisions.

There is a significant amount of untapped potential due to ungoverned and poor-quality data, which can be unlocked through effective data governance practices. Referring to Stephen Hawking, the cost of fixing a data error at the point of entry (the source of truth) is $1; fixing it an hour later costs ten times more ($10); and fixing it several months later can cost hundreds of times more ($100+).

Microsoft Purview Data Governance enables data practitioners to use out-of-the-box controls to manage and improve the health of their data estate. Data stewards and data health owners can set thresholds for these controls based on the criticality and expected values of their data. If the measured scores of these controls do not meet expectations, the application generates remediation actions.

Below is a list of available controls you can use to improve your data estate health and achieve a better ROI on your data:

The Return on Investment (ROI) of your data depends on how much value you create from using it. There is no doubt that your ROI will potentially increase if you govern your data to maintain a high-quality, compliant, and secure data estate.

Assume your total value derived from data is $1 million and the total cost of data management is $200,000. The ROI of your data investment is:

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Conclusion

The value of data lies in its ability to transform raw information into actionable insights that drive business growth, efficiency, and innovation. Organizations that effectively harness the power of their data can gain significant competitive advantages, improve customer experience, and create new revenue streams. However, realizing this value requires a strategic approach to data management, quality assurance, and the development of a data-driven culture. By implementing federated data governance practices, organizations can ensure and emphasize the collection, storage, and use of only the essential data necessary to achieve specific business objectives or outcomes and maximize the value of their data investments while maintaining cost efficiency.

References

(25) 10 Step Guide to Data Minimalism | LinkedIn

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