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Retail Data Valuation case study

Use Cases / Data Valuation & Monetisation / Case Study

CASE STUDY

Understanding and Unlocking the Commercial Value of Enterprise Data.

How a major retailer valued its information assets to improve priorities, supply-chain intelligence and responsible commercial sharing.

Industry

Retail

Use Case

Data Valuation & Monetisation

The challenge.

A major high-street retailer wanted to understand the commercial value of the information held across its business.

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The organisation was interested in identifying opportunities to improve internal data management, share useful information with supply-chain partners and potentially generate additional revenue from suitable datasets.

The DataBelt solution.

DataBelt was used to discover, categorise and assess the organisation’s information assets.

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Using the retailer’s data valuation framework and defined value drivers, datasets were assessed and assigned value indexes and grades.

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These assessments supported the calculation of estimated financial values for different information assets.

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The results provided a structured view of which datasets were most valuable and where investment in hosting, maintenance and information management should be prioritised.

Fashion retailer

The outcome.

The retailer gained a clearer understanding of the commercial importance of its information.

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High-value datasets were prioritised for appropriate management and protection.

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Selected information was also shared with supply-chain partners to improve demand planning and identify cost-saving opportunities.

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In addition, certain non-sensitive datasets were commercially licensed to logistics providers to support more efficient delivery planning.

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