Visualisations - From Data to Information
The one thing that there is no dearth of in the current world, is Data. Therein lies the boon as well as the bane. On one hand availability of large amounts of data would mean banks and financial institutions no longer need to make blackbox decisions. Strategic and operational activities are evidenced by supporting data which would mean the opportunity to consciously steer in the direction of choice. While there is no debate as to the advantages of data availability, petabytes and zettabytes of data presents another unique problem - the problem of plenty. Isolating and making sense of data which is critical amongst the mountain of gibber then becomes a humungous exercise. The ever faithful static reports which made their way to every desk and cabin in organisations suddenly seem to fall short. The necessity for consumption of data (through reports) quickly give way to the inevitability of interaction. The solution? Visual Analytics a.k.a Visualisations.
Visualisations, we believe, in their elemental character are defined by these basic qualities:
Interactive - The ability to not just consume the data presented but also interact with it
Perceptual Explanation - The ability to present clearly perceivable and direct analysis
Prospective Exploration - The ability to offer latent dimensions hitherto unavailable
Consolidated - The ability to combine multiple reports into a single visual for maximum effectiveness and presentation efficiency
Reflective - The ability to reflect the latest available information without delay
Visual Guide - The ability to connect the dots from multiple sources of data and present in best possible way
Drill-Down— The ability to present high level analysis and provide on-demand drill down to the lowest level of data
Visualisations offer a compelling proposition in navigating the unexplored waters of data. The main objective is not just to provide answers to expected questions but to present finer details hitherto illegible, to uncover questions hidden in plain sight and to make the connections - direct and indirect. An ideal visualisation should serve through the entire length of organization from CXO-level dashboards to detailed operational dashboards. This way, not only does the organization realises cost advantages but also can minimise the maintenance of multiple infrastructures. This can be possible if the visualisation sits on top on single data structure which effectively translates to 'everyone in the organisation is viewing the same data' - only in a way that makes utmost sense to each of them.
Another key point to consider is that a great visualisation is based on the right data. That brings us to the question ‘How do we know which is right data?’. The answer to which lies in the fundamental understanding of the underlying domain such as risk (market risk, credit risk, economic capital) or finance and accounting, or sales or even project management. The understanding of the nuances of functional aspects of measures and their dimensions is as critical as the visualisation itself. This enables us to differentiate and accurately present the measures (for e.g. additive/non-additive measures such as MarketCap/VaR) in a meaningful way. The choice of metrics then would be accurate representations of the underlying analytic realities. This is crucial in showing what’s required rather than what’s available.
Does the dawn of visualisation mean end of reporting system as we know? Definitely not. Not now anyway. Though it is tempting to say with the ubiquity of mobile and other portable electronic devices combined with the potential of visualisations-in-hand and on-demand, the case for static reporting seems to be dwindling. Nevertheless, an ideal scenario for the moment would be to make the best use of both the worlds. Or better yet, combine both the worlds. Deployment of visualisations which can support exporting custom data static reports in a variety of formats currently in vogue as part of static reporting is a prime example of this. This would mean banks and financial institutions (i) Need not go through the usual project lifecycle every time they wish to build/change any static reports (ii) Can satisfy all the use cases with single technological adoption/installation.
The need for a reporting stems from the basic necessity to understand the bigger picture. However, relying on heaps of static reports will no longer suffice. Making decisions based on large amounts of data at the right time is critical to gain strategic advantage - the difference between winner and loser. We can debate all day about the pros and cons of using visualisations, yet is safe to assume that the future surely belongs to visual analytics.