• nShore Team

Data Agility : Key to Digital Transformation

Updated: Oct 17, 2019


Whether you are a data driven business or data driven enterprise, data is critical for protecting, creating and growing the value of your organization. And data is ever changing in its forms, sources, quality, usage and quantity. How effectively your organization, teams and tools can make use of changes in data ,data sets and data sources defines the Data Agility within your organization. Data Agility impacts the speed and quality of decision making at all levels from marketing rep to CFO and CIO. Lack of it makes your Data scientists to spend long time in mundane job of data preparation or in waiting for the data (coming from IT) before they could put their science to it. Lack of data agility also forces any CXO to look at old data or incomplete data to plan and strategize with less degree of confidence.



 

So what brings “inertia” to your data? And what we should be doing about it?

Two major factors in our opinion being -


1. Organization structure:

Data and data enablers either centralized within IT departments or existing in silos with various functional units – organization structure can hamper the free and fast flow of Data through the organization and through cross functions.


“Data can be the lifeblood of an organization if it is allowed to flow freely across the entire ecosystem.” Herman Heyns Partner, Data Analytics, Ernst & Young LLP (UK) observed in one of his researches.


Certainly this may bring the governance and compliance issues around data, but those should not discourage organizations to leverage the power of data in decision making across its ranks. Because in current competitive market place that may not be an option anymore and robust data governance policy framework and discipline can take away/ minimize those anxieties and risks



2. Tools and technologies:

Traditional tools and technologies to capture data, to curate it, to store it and to analyze it demand technical knowledge and training for its users. This also contributes to centralized technical teams and centralized “custody” of data as mentioned above. It is time to move to self-service tools that are available as another productivity tool for data users and empower them in their jobs



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