Data Strategy & Data Management Disciplines
Digital disruption is driving innovative capabilities through Big Data and Analytics at an exponential pace, opening business opportunities onto new horizons, at a much faster pace, that organisations have never seen in previous decades. However, it also poses significant challenge on managing the quality of data. ​
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Digitisation and data-driven business model are critical differentiator for organisations’ success and their sustainable existence in the current highly competitive market. Many companies are, hence, focused on their Data strategy to leverage the opportunities of digital disruption, focusing on Cloud based Data lake, API based data interfaces, advanced analytics, AI and BI Technologies and capabilities to deliver Data, Information and Insights . Below illustration shows the relationship between Information maturity and Business value.​
Right Data
Right Consumer
Right Time
At RegCentric, we define Data Strategy as a plan charting a course of action, to deliver targeted business strategic goals. It contains following four components:
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Collecting internal and external data, relevant to business
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Harnessing, transforming and enriching data to useful information with business context, calculations and time horizon
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Disseminating current and historical information for business consumption
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Empowering business with BI, Analytics, AI and Robotics capabilities to derive valuable and timely insights
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We see 7 Data management disciplines as an integral part of all components of the Data Strategy, laying an essential foundation for Data Quality , as lack of it will quickly undermine the benefits of the Data strategy and significantly downgrade its expected return on investment.
Experts think organisations spend between 10-30% of revenue, handling data quality issues. Gartner indicates the average cost of poor data quality on businesses is expected to be anywhere between $9.7 million to $14.2 million annually!! In addition to the cost, the organisations can face significant risks including reputation, regulatory and operational, if their critical business decisions and operations are based on poor quality data.
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We support our clients to take an iterative business use-case based delivery approach for Data Strategy, to successfully generate progressive organisational benefits that include:
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Tangible short-term business success that can be linked to outcomes of Data strategy
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Sustainable Information maturity uplift for Innovation and speed to value, enabling competitive advantage and enterprise growth
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Improvement in Data quality compliance in alignment with Regulatory/Industry standards, resulting in risk and cost reduction
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If you like to discuss about the Data Strategy, Data management disciplines, delivery roadmap and approach, tailoring to your organisation’s needs, you can contact us.