Digital interruption: How to improve analytics

The analytics in the age of digital disruption has paved ways to unlock dormant potential in ways not seen before. The power of analytics is a major paradigm shift in gaining extra mileage on your rivals and keeping your business relevant in a competitive landscape. Data is omnipresent and in this digital age if you fall behind the capabilities of analytics, then you leave your relevance in the hands of competitors.

Digital disruption is one of the reasons which has seen the evolution of HR from doing an administrative role to a more strategic one. The digital disruption backed by the unique capabilities of technology has put HR in a vantage position where it can provide strategic insight into human resources and their deployment.

So, how can the capabilities of analytics be improved and realized in the current integrated IT landscape? Well, one way is to train HR professionals and make them realize the power of data-driven analytics. This will foster the emergence of dedicated teams and individuals who would understand the dynamics of the business and produce actionable insights.

Another way to improve analytics is to strive for an IT landscape which is less convoluted and is devoid of too many of integrations with the legacy systems. A complex integration of multiple systems can be a stumbling block in collating real-time data for analysis.

Analytics have different connotations to different people. It’s imperative to understand the personas and their type of data consumption to design a perfect analytical model. There are numerous instances of laborious hours spent on designing beautiful dashboards but never gets on board. The CEO and CFO, require dashboard which gives them snapshot across operations, financial areas to understand the performance level of the business whereas financial analyst might require a completely different data set.

Also, when it comes to information delivery method, one type doesn’t fit all. An understanding of the delivery mode, for instance, whether via web-based dashboards, mobile devices or even via excel will help is finetuning the analytics.

Analytics have become the focus of businesses due to the growth of unstructured data; data which can be extremely useful in identifying patterns and creating a predictive model which can leverage the capabilities of machine learning and help the stakeholders make an informed decision. Analytics is an ongoing activity which constantly needs finetuning.