Case Studies

The Light Bulb Moment

By Daragh O Brien
July 21, 2023
8min read
Data GovernanceData LiteracyData ProtectionData Strategy

Castlebridge assisted a retail electricity provider to tackle data quality issues that were affecting customer service and operational efficiencies in the delivery of products and services. This issue also posed potential data protection compliance risks to the organisation. The solution: A strategic view of data and a coherent data model!

The Pain Point

The client contacted us through our outsourced DPO service to confirm if there was a data protection issue arising from difficulties they were having searching for and finding customer data solely by address or telephone number. In addition, the client was encountering difficulties in developing consistent reporting and implementing self-service Business Intelligence solutions due to the fragmented and inconsistent nature of key data.

What We Did

Castlebridge assigned one of our experienced data quality and data strategy consultants to lead a short engagement to triage the issue and identify the root cause of the problem searching for and finding customer information.

This stage of the engagement involved conducting a review of the core CRM system used by the client and analysing their data model to determine the root cause of the reported data quality issue. Significant duplication of fields such as telephone number and address were found in the underlying data model.

Castlebridge then recommended a remediation project to address the strategic and operational data issues identified:

  1. Define and develop a Conceptual and Logical data model, with supporting data definitions for all critical entities in the business. The objective here was to establish a consistent ‘data language’ in the business.
  2. Re-engineer the underlying CRM system physical data model to remove duplicate and redundant fields and to ensure consistency with the Business Logical Data model.
  3. Re-engineer Contact Centre screens to reduce duplication of data capture and improve the logical flow of data input.
  4. Define the “system of record” for critical data and map the critical-to-mission data flows in the organisation.
  5. Focus on capturing critical data such as eircode as part of onboarding to allow for enrichment of data and cleansing of data quality issues.

The client agreed and we executed a rapid remediation engagement to address the identified root causes of data quality issues and operational failures.

The End Result

  • Improved ‘searchability’ and ‘findability’ of customer data by reducing the duplication of key data.
  • Restructured call centre screens to reduce the number of data capture points, introducing dropdown lists for static reference data, and prioritising the capture of address using eircode.
    • Reduced contact centre call handling times by between 20-25% on average.
  • Improved traceability of key data elements in the business
  • Common data language supported the rapid onboarding of newly acquired subsidiary business and the planning of systems and process integration.

Key Takeaway

The development of a strategic approach to managing and designing data in the business was recognised as a key capability that had been overlooked in the rush to scale and grow the business.

Taking a step back, defining the language of the business and how the critical data elements of the business (customer, contract, account, supply) related to each other helped clarify the future steps in the business for process and systems improvement.

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