Why Do We Need Real Time Data Analytics

Analogy to project management lifecycle


The landscape and the value of data has changed significantly since the dawn of the internet over 25 years ago. In today’s world, the quicker a company can take action, the more impact they can have on the outcome. With stronger competition, every company in every industry needs to be more alert than ever before. 

The importance of data over its lifecycle has therefore become a vital factor in decision making. While the older method of accumulating data, analyzing it and then making a business decision (across a time period of a few weeks) is still practiced, we need look no further than software industries to see a better way.

A decade ago, most IT companies preferred to follow the Waterfall model of project management. However, today most modern companies follow the Agile model, where continuous engagement is required. Agile methodology gives a team the ability to act quickly in case any change is needed.  This eventually makes the final product more stable and suitable. A continuous iteration process also squashes the bugs that would otherwise plague the product if it were developed through the Waterfall model. While both models have their pros and cons, the Agile model provides more dynamism to the whole approach.

The need of the hour can be simplified by drawing an analogy to the project management methodologies. The continuous process of product development is extremely important. In the same manner, it is important to provide key inputs for the requirement phase. That is only possible if one gathers information from the market and other sources. Hence the data that we feed into our software development process has a different value as time passes.

On a brief note, the data we gather keeps losing its value on decisions as time passes. On the other hand if one had to make a decision on the stored data, with passing time more storage will be required. For a given business and considering that the daily volume of data collected remains constant, a team that analyses their data every month would require storage capacity higher than a team that analyses their data every week.

As our software development methodologies have changed to accommodate the faster development requirements and quicker change management, our business models and modus operandi are also changing to accommodate faster decision-making and to stay competitive in the market. Any business should seriously consider analyzing their data in real time to gain insights that could give them an edge over their competitors.

'To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of' – Ronald Fisher

As we navigate around the worlds of agile/scrum, unit economics and nanotechnologies, one thing becomes certain. Continuous iteration and management at unit level will be necessary to stay ahead of the curve in any industry in the near future. In terms of data, every second will count when we think of impactful data analytics.



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