A short note on Data Strategy

Data has a definitive impact on every organization’s decision processes, enabling better decision making, decisions that are not based on poor quality, or inaccurate data, impacting every business process that uses data and that have direct impact on day-to-day activities, impacting customers, production, etc. Data is present in all the organization’s processes, from risk or regulatory compliance to routine operations.

Data can be the most powerful asset an organization has; however, it is still an under-managed and under-exploited asset. Having a comprehensive data strategy gives organizations a substantial competitive advantage, laying out a comprehensive vision across the organization and incorporating the guiding principles to accomplish the data-driven vision, direct the organization to specific business objectives, acting as a starting point for data-driven planning.

A data strategy must answer the question: How will data enable the business strategy?

A data strategy will act as a guide and aggregator of every data initiative, and because data related business needs and requirement exist and need to be addressed, we witness the spread of multiple, independent, and uncoordinated initiatives - be it data analytics, business intelligence, data science initiatives, or even data governance, master data or data quality initiatives - that address contextual, circumstantial needs, driven by different business areas, without an integrated perspective. Initiatives that most often than not will fall short of its objectives.

Being, as I am, a strong advocate of focused, targeted data initiatives driven and oriented by business units – pretty much like the ones described above – I must also be a strong advocate of a structured and comprehensive data strategy, grounded on strategical business objectives, designed, and implemented at executive level, as a foundation each data initiative, everything data dependent or data related within the organization.