The company was dealing with inefficient and redundant data management practices across traditionally siloed operational processes for their radio, broadcast and cable divisions. There were no standard definitions of common media domain subjects such as advertiser, agency, brand, product, etc. Their cross-division, cross-platform analytics were suffering from data inconsistencies and errors. There was little transparency into the increasingly manual and time-consuming processes necessary to compile regular reports and metrics. Independent efforts to remedy all of this were underway within business areas without centralized information technology support .
Knowledgent worked closely with the newly-formed Office of Architecture to define a current-state assessment and future-state Master Data Management recommendations and roadmap. We conducted 50+ key stakeholder interviews and workshops across the cable, broadcast, radio and digital divisions. We then established common data nomenclature to facilitate master data conversations and highlight commonality and disparity in terms being used for advertisers, agencies and brands, and documented systems and core attribution being maintained in similar processes within the siloed functions. The Knowledgent team established a foundation for the Master Data Management program and proposed use cases and technical capabilities to inform the tool vendor selection process. This helped establish the notion of a common data governance organization structure to facilitate cross-divisional ownership of common Master Data terms.
The future-state recommendations were delivered to their executive committee and helped secure funding for the cross-organization Master Data Management program. The recommendations for cross-divisional Data Governance to remedy business definition inconsistencies helped establish a tactical data stewardship committee with accountability to the office of the CEO. The Master Data Management vendor selection process was initiated to evaluate and select a toolset. The previously distinct and separate data architecture efforts began to unify towards a common Enterprise Logical Data Model, prioritizing focus on Master Data subject areas as prescribed by the roadmap.