Written by Ramki Ranganathan, VP of Data & Analytics (Americas) at Systech
We frequently hear the mantra, “if it’s not broken, don’t fix it.” While I think there is a lot of merit to this statement, it impedes those in the data analytics space from innovation. In the late 90’s and early 2000’s, data management and reporting platforms made life routine. Pre-built Dashboards reigned supreme and were largely utilized by executive management to identify KPI’s, among other valuable details. At Systech Solutions, for example, one of our clients used reporting technology to track mostly sales reports from the previous week. Pre-built dashboards were extremely helpful in pinpointing specific insights when our client was trying to compare KPI’s from different years or interested in breaking down sales by stores and products. It was customary to perform data analysis if the pre-built dashboards were not applicable.
In some respects, life was easier back then. With a fixed set of data sources, it was effortless to anticipate what was coming down the pipeline. At the same time, this approach was not practical long term.
2005 and beyond, there was a huge explosion of data. Suddenly now, businesses were able to extract insights from various kinds of unstructured data outside their organization. Whether images, documents, outside enterprises, or social media, they now had access to a wealth of information that wasn’t accessible to them before in a meaningful way.
The sole reliance on pre-built dashboards became an obsolete business model, as nothing was fixed anymore. Sure, KPI’s perhaps remained somewhat consistent, but everything else became use-case driven. New tools like Tableau and later Looker broke the enterprise requirement of being tech-savvy to gain insights on your data. This democratized data analysis. Data could come from anywhere, without having to adhere to any traditional structure that it may have in the past.
Every enterprise needs to constantly innovate to keep advancing. It seems unlikely that up-and-coming businesses haven’t made note of where their systems are falling short, and how best they can retain their customers and acquire new ones.
As of 2021, we are in a transitional stage of the reporting system technology strongholds on this industry. While data visualization platforms and dashboarding tools still hold a competitive advantage in the market, it seems entirely plausible that this could change very soon.
What will the future look like for data analytics? Will dashboards be eliminated entirely? Are we making full use of the potential value that data offers? Will the analytical tools and platforms currently being used continue to support us on our quest for innovation, or holding us back from reimagining the business climate we are in, today? My prediction is that “Dashboards” will lose — more or less — their death grip on enterprises. Instead, analytical platforms that can perform discovery analysis intuitively and provide insights without supplementary technology will reign supreme. As we progress in applying AI and ML techniques to glean insights from data; platforms like Jupyter notebook with powerful data management and visualization libraries from Python are gaining more popularity in performing use case driven discovery themed and based analytics.
In light of COVID-19, businesses are being more prudent than ever to get the most ‘bang for their buck’ and this behavioral trend is here to stay. By my summation, dashboards are too restrictive and rigid. Today’s discerning customer is very likely to move away from them in short order — possibly in just the next 3 to 4 years.
Perhaps one day we will live in a world where the analytics technology backed by AI and ML will provide insights from data, at the right time to the right person, without even being asked or looked for, like how J.A.R.V.I.S supports Iron Man. That day is not far from being a reality…