Marketers and agency owners have eulogized the power of data science to an extent that can easily inspire enterprise owners to pour in large stashes of cash in exchange for expectations that are never to be fulfilled.
Data science is awesome. What it has achieved today and what it promises to achieve at some point in the future is incredible. No single discipline has impacted the industrial world so much in recent history. While none of this is untrue, the capabilities of data science are often overestimated. Companies are led to believe that deploying an analytics team will instantly bring revolutionary growth to their profits. Therefore there occurs a serious misalignment between the management’s expectations and the actual capacity of the data science team.
The reality of growth through analytics
A general discussion in this regard can be difficult and too simplistic. Let us instead look at some specific instances. The Target store is a major retail organization. Around the middle of the last decade, they had a formidable online and offline presence. They decided to utilize data analytics to further increase profitability. They made certain small changes with the help of analytics.
- They reduced inventory by predicting the demand for certain products.
- Modified marketing strategy by targeting niche customer belts.
- Used analytics to determine pricing and discounts.
Nothing too big, nothing too flashy, nothing that can instantly make a lot of difference. But gradually, over the years their profits grew and they expanded faster.
This approach has been taken by many over the years. The ideal practice is to set modest expectations. Then analyze each metric to find out the slight changes that have taken place post analytics implementation. And then build an investment strategy for the future.
Tackling the problem of misalignment
The misalignment of expectations and results occur mainly because the marketers sell analytics too highly. The management has to be faced by the data science professionals themselves so that they get a more practical perspective. This is why analytics education can become so crucial even among the ranks of sales or marketing personnel.
The word for data science enthusiasts
Whether you are looking to become an analyst or not you should go for data science training. It can be useful, in fact, crucial in a large number of different professions. Just enroll for a course and enroll with R training or whatever tools suit you for that matter. It will give you an edge over other candidates.
We are moving towards an era of more data-aware enterprises and professionals. There is an acute need for clarity and transparency to get things moving smoothly. And that is why data science education is becoming increasingly vital.