For Companies, Data Analytics is a Pain; But Why?

Businesses across the globe are facing the brunt, one of huge data influx and second of increasing data complexity and of course the market volatility. To address these challenges, companies and all their verticals are turning to data-driven analytics and insights as a means to better understand their organization’s customer bases and to grow their businesses; and manage the increasing uncertainty up to a certain extent. 

The shift from conventional to data driven analytics is steered by technology and automation across organizations. Growth in digital technologies is enhancing the abilities to analyze more and more data, ultimately increasing the appetite of enterprises for more data, better data, advanced analytics, implementation of best practices and what not. Data analytics is the primary enabler to derive insights and reach out to meaningful truth, resulting in business growth and increased revenue.

The world is going gaga over the promise of analytics and what enterprises can attain by harnessing it, compelling brands to make significant investments in analytics tools, or analytics service providers. However, somewhere down the line it feels as if analytics is a bubble, which is likely to burst anytime. And there are various reasons and several related technology pain points which surface, as conveyed by brands trying to leverage analytics to reap benefits of data-driven improvement across the enterprise. In no particular order, enlisted are some of them:

1. Analytics is not a vaccine, but a routine workout

Companies looking out for instant solutions, usually think of analytics as a vaccine shot and undertake it in an ad-hoc way, a kind of a one-time process to find value. It should not be the case at all. If enterprises are keen on improving their businesses continuously, they need analytics to be systematic, and repetitive like a routine work out in gym.

2. Insights are just the initiations, and don’t add immediate value to your business

USP for some of the analytic players is the promise to convert data to “insights”. Organizations should understand what is insight? Usually insight is a static or an interactive dashboard, comprising of graphs enabling the slicing and dicing of tons of data, the way one wants it.

But does it add any immediate value to the business? For these insights to be really of importance, human intervention is required to make sense of it. And also to figure out what actions should be taken. You as a business would not make investments in analytics, because you want insights – would you? Unless it gives out answers, such insights are of no use. Businesses need answers, specific and practical, to improvise the metrics with immediate values.

Enterprises and organizations, in that rat race have or start collecting high volumes of data  from every machine and transactions available. However, the aspect that needs to be thought about is, are they equipped with the right kind of tools or data analytics team or have they even partnered with decision analysts who can help them keep pace with the volume and speed at which the data is generated. Usually, most of them are yet to get associated, and unfortunately few of them are yet to think about taking up the data analytics approach.

4. Descriptive analytics is a post-mortem, does it really help

Data analytics offered by most of the online tools, or analytics service providers is a kind of post-mortem; a look back to the old data to assess what happened and why – just in order to make beneficial changes in the future. It really is helpful to know when male customers visited your eCommerce site for a particular product, and will get easily churned if no promotion is offered in the first three months. If you succeed in pitching a promotional offer to this customers meeting this kind of profile, you will succeed in reducing the churn as well – and it’s a valuable takeaway.