Data analytics has far more than what meets the eye. While it might seem like a one-off technology like implementing a machine learning model, the reality is farfetched. Data analytics is a comprehensive study and has a complex pipeline. This being the reason, a lot of organizations shy away from using data analytics services and solutions in their business.
The Relevance of Data Analytics in 2020
Data analytics has existed for quite some time in this world, but it is only very recently that business leaders have started feeling its importance and relevance in the current market scenario. While many are using it as an exclusive process which means they just use it to solve one problem in their organization, there are others who are using it as an integrated tool for their business.
No matter how data analytics is used in a business, it brings value to their core processes and enhances their understanding of the market along with their own key departments. But, there is also a significant difference between businesses who use it as a one-time affair and those who religiously adopt it for their organizations.
It is always a great idea to have a comprehensive data analytics plan for an organization because then there is an introduction of consistency which aims to dig deeper into the reality of an organization. While most businesses think that data analytics is used to make some sense of the outside information, they forget that the ultimate input data is coming from their organization. In other words, data analytics has a far greater contribution to revealing factual information about the organization itself as compared to the outside market trend.
Having said this, one of the biggest roles of data analytics lies in decision making. After all, it is 2020 and businesses are no longer guided by intuition. Even if they try to make a vague decision not only will they be thrown out of the market race but forgotten faster than anything else.
Along with many things, the year 2020 brings a cut-throat competition to the table of the market. While this directly implies that organizations need to take proactive measures to carve a niche for themselves, there is a large shift in the tools that they used to differentiate themselves. A majority of businesses for the longest amount of time relied on tech to differentiate themselves or establish their dominance over their competitors.
But with digitization sweeping the world off its feet and emerging technologies penetrating every other industry, it won’t be incorrect to say that technology has taken the form of the ordinary in the market. Name any prominent technology today- be it artificial intelligence, machine learning development services, data analytics or any other technology, all are readily available in the market, open those who want to harness their potential. The only way that organizations and enterprises can capitalize on them is through data.
Data is one of the biggest assets in today’s times. It won’t be incorrect to call it the key driver of decisions for any organization. So, when we talk about scaling decision making, the quality of data directly comes into play. In fact. The entire success or failure of data analytics depends on the data that businesses choose to provide it with.
When it comes to a production environment, data analytics can play a huge role in improving operational efficiency and performance is given in the hands of operational experts. While there are only a handful of organizations using it right now, it is helping them digitalizing and energizing the entire value chain. The intuitive step towards digitalizing the production industry starts from empowering the operational experts with the capabilities of data analytics.
Introducing data analytics to the production industry would directly mean supporting them in catering to the demand of their customer in a more effective manner. While on the other hand, they will become self-sufficient in meeting requirements that are encountered in the digital age.
As beneficial as data analytics can be for the industry, it is equally challenging to convince operational experts to adopt these new practices or start using new tools. In other words, data analytics will have to prove its metal to the stakeholders at the beginning. The first step lies in making the data available and once that is done the users will have to be shown the benefits of data analytics. Once a segment of users starts seeing the value it will be easier to convince the others to be on board with the tool and tactics of data analytics.
Let’s say that the adoption and usage of the analytics is already known tot he users. The next thing in demand will be the analytics tool itself. With cloud technology to the rescue and several web-based applications available, this will also be possible. However, the challenge will be making data available in a standardized format.
One of the toughest tasks while introducing data analytics to scalable industries would be to model the change management tactics in itself. While some people are easily convinced, there are others who would require more effort to get convinced. Therefore, there will be a need for common change management strategies and decision making at the global level.