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Barriers in adoption of Business Analytics

Mar 26th 2020 at 11:38 PM

The last decade has seen phenomenal transformations in the technology scene all across the world. Data has become such an integral part of functionality for all things machine-related that making the most of out of it has become a priority for all practices. So much so is its impact that it is now being used to estimate future behaviors. One such important term that is helping to gain some control over data is business analytics. In layman terms, it is a tool that helps to collect processes and produce meaningful insight for relevant parties. A similar term is business intelligence, but it is limited to only the collection part of it. Business analytics has had its level of importance rise at an increasing rate and will continue to do so in the future. Tools similar to this that were previously limited to the IT sector are now being used for almost every department in the organization, be it HR, marketing, finance or operations. Volumes of data for each data are collected and processed which further helps in decision-making for future activities. One such case was for companies like Capital One, which used past historical data to predict the type of credit card a particular customer would be interested in, and the results managed to be 70% accurate. This percentage can translate into a huge share of revenue, which surely no company can choose to ignore.

As appealing as this may sound to the companies, adopting the process is a different scene altogether. It requires an arduous process of first filtering out the data which usually also involves heavy amounts of information with no value. Then comes the process of separating mixed data and finally the end result is something useful. That undergoes processing to create information that can be used by the concerned parties.  However, it is followed differently according to the type of business analytics required by the party. These have three main categories: descriptive, prescriptive and predictive. They can further be divided as per their main division and requirement. They mainly define what it is, how it should be done, and what we should do in the future.

Although the rate of adoption of business analytics is likely to see an increase in the future, it still faces some major barriers for mass adoption. Its benefit cannot be harnessed unless the relevant parties are involved in the process. For example, experts are trying to bring business analytics in the agriculture sector, but that cannot be fully implemented unless farmers are fully willing to invest themselves in the process. Furthermore, to bring this change, the experts required are less in numbers since India is currently facing a shortage in the skill sector. Hopefully, if private sectors along with government can engage the population to become more skill-developed, the rate of adoption will also see better numbers. People have been hesitating to accept these advancements in technology, but it must be realized that they are here to facilitate better and more precise operations. The data put out is as good as how the expert uses it to act. This makes the companies responsible for how effectively, they choose to use it and for what purpose. Right or wrong, complete or partially, companies will play the crucial role of deciding the fate for these tools and the people impacted by them.

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