Doing business is no child’s play. You need to out in the efforts to get every nuance right and fight your way through the market competition, only to gain visibility in the eyes of the customer. Sales, conversions and earning loyalties are the next challenges that only come if you get past the basic ones. The point of the start of a business is always understanding the customer concerning their likes, dislikes, preferences, etc. Once you understand these you get closer to understanding the behavior of the customer, and that gives you the advantage to place your products and brands correctly.
But for businesses understanding the customer can be one of the toughest nuts to crack. It would seem like researching the entire market segments just to find the one that is worth your targeting, then studying their customer personas and so on. More to this, as you go on selling products to the customer, their demands change and unless you have an in-depth understanding of the market and the key factors affecting it, there is no way that you can prepare your business for the same.
Data Analytics Scenario in 2020
Today, real time data analytics solutions is way more popular than it was a while back. There was a lot of resistance from organizations to the emerging technology because many didn’t know what might it bring to the table. A lot of organizations and enterprises though they had to out in everything to utilize the best of these technologies. This meant all of their money, dedicated resources and a large infrastructure because let’s admit it, data science largely revolves around machine learning that is directly impacted by the quality of hardware being used to run its models.
However, with changing trends and increased acceptance to emerging technologies especially digitization, a lot of leaders from small and medium organizations have started taking interest in the domain of technology and understood that it is one of the biggest factors that contribute to the stability and sustainability of their business. As a result, a lot of them are digitally transforming their cores and aligning themselves with technology.
Adopting analytics for different businesses would mean not just having to learn about the insights of the customer but also preparing one’s business for it. But, in spite of the fact that data analytics has existed for more than three decades now, tit’s adoption in businesses has largely been limited. Even the handful few that adopted it, have made a constraint around it that either limits its potential or confines it only to a limited number of tasks for a business. Either way, businesses are not truly utilizing the power of data analytics for their business.
For the starters, most businesses start by just bringing aboard data analytics just because it’s a hot trend in the market and they don’t want to feel left out since every other business is doing so. This means, while they have data analytics for their business, they don’t actually understand what problems are there to solve. In order words, having data analytics just for the sake of it doesn’t solve problems, because you don’t understand where to begin. This kind of scenario often starts at the level of the CEO when they hire data scientists for their organizations but don’t exactly know what they will do.
In another case, businesses have too many expectations from the data scientists, that are practically not feasible to accomplish even after investing a lot of money. In these cases either there are too many legacy datasets to be evaluated or too few members on the data science team, that even after putting years of work, businesses seldom come out with anything fruitful.
Data analytics for businesses is also in many organizations used just for enhanced reporting. In other words, when management leaders ask for a business-wide adoption of analytics, it ultimately comes down to the small departments and business units on how well they deploy the technology. While some do it, others find it too complicated and have no idea what to do with it. Therefore, understanding the impact of data analytics at an entire organizational level becomes challenging.
The Changing Perspectives
The way analytics must be looked upon for a successful outcome is, from the view of high leverage business problems. It directly means finding a business problem that is tightly defined and promptly addressable, Put differently, these kinds of problems have the potential to show business results with effect from data analytics. In other words, When predictions are made in such problems, they yield instant business value along with tangible results.
The point is that if organizations are trying to harness the true benefits of data analytics for their business, they must not try to do it in a silo. Data science must be integrated within a business for maximum and measurable impact. For businesses that find their endeavors unsuccessful, either leave their data scientists standalone or don’t make efforts to define their business goals precisely. For data science to do wonders, data scientists must closely work with leaders to understand their goals and aim that they are trying to achieve through analytics.
Conclusion
It is also imperative to remember that data analytics doesn’t always bring positive results. The goal must be to gain transparency into the data and the organization. Because in reality when the process is actually carried out, the outcomes are completely different from what the business was expecting. These inconvenient outcomes are nothing but myth busters that shatter the false impressions, an organization has been living under.
