A data-driven model can help enterprises outperform competitors

A data-driven model can help enterprises outperform competitors

August 20, 2018

Many modern enterprises cannot make timely decisions because their performance reports are fragmented across several departments and businesses. As a result, they fail in linking the data together to form coherent conclusions, as they have no way to do so. Cynthia Stoddard, Senior Vice President and Chief Information Officer of Adobe, examines how a data-driven operating model can solve these challenges.

Fragmented and siloed data in enterprises create roadblocks for informed decision-making. In addition, the always-on cloud environment captures volumes of data at an accelerated rate that makes enterprises struggle when measuring their performance in real time and when pinpointing opportunities to connect with consumers. Hence, a common data model and unified data architecture can be truly transformational for IT organizations.

A data-driven operating model is the perfect antidote to disconnected datasets, fragmented key performance indicators (KPIs), inconsistent data definitions, and unreliable insights. Additionally, the existence of a single-source of truth across an enterprise empowers IT to develop robust self-service dashboards and analytical experiences for stakeholders.

Typically, if every team in an enterprise begins speaking the same data language and agrees on definitions for success, acting on data insights becomes easier. Furthermore, this will shift the conversation from tactical discussions to business impact conversations such as how to leverage data insights to further the business. In addition, every person from the CEO to the data analyst is well equipped to turn data into consumer insights.

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Brought to you by Scope e-Knowledge Center, an SPi Global Company, a trusted global partner for Digital Content Transformation Solutions, Knowledge Modeling (Taxonomies, Thesauri and Ontologies), Abstracting & Indexing (A&I), Metadata Enrichment and Entity Extraction.

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