In a world inundated with data, the need to derive meaningful insights from information is paramount to the decision-making process. Amidst the colossal efforts of collecting, collating and classifying data, an important question we need to consider is why we do so. Do we spend an inordinate amount of time in ‘putting the data together’ and too little time actually consuming it? A vast majority of businesses find themselves in this conundrum.

The Five Steps to Discovering Data

The following steps help businesses achieve effective data analysis and discovery:


This is the first and the most elementary step. Yet many companies still have data in silos, and a seemingly common task such as writing a brand performance report entails toggling between multiple scorecards or data suppliers. Bringing all the key datasets together on one platform enables businesses to identify meaningful relationships between disparate data points.


Organizing data on a chart or graph for easy assimilation clarifies data patterns and increases the opportunities to play with them. The ease with which a chart can be created sometimes acts as a catalyst to generate new hypotheses. A visual representation also paves the way to engage more with the data and develop new ideas.


Today’s business intelligence tools come with high license costs that prevent organizations from distributing data access effectively and equally. A myopic calculation of who gets access to data and its return on investment restricts the responsibility of data discovery to only a few, and limits opportunities to bring in new ideas or challenge the status quo. Open source platforms are empowering and can be achieved through democratization of data.


By this I mean socializing ‘observations’, and not just data. Seeing data and its related commentary in the same frame is stimulating. Such verbalization adds spontaneity and interaction to the process of understanding and building insights. In the absence of such collaborative tools, precious comments stay hidden on post-its, email threads or conversations, and retrieval of the right information at crucial times becomes near impossible.

Facilitate Self-help Console

Once a dashboard is created, tasks (such as adding new entities) that typically do not come in a new data format or range should be made simple. Very often, the dreaded ‘change request cost’ renders the application rigid and kills its agility to adapt to changing business requirements. A self-help console, as part of the dashboard design, will keep it relevant and enable reasonably minor changes to be executed with very little or no cost.

So, the next time you streamline your decision-making process, remember not to confuse data collection or data collation with data consumption.

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