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Industry Report: Data Driven Innovation: Disruption Vs Optimization

Data-Driven Innovation

Any successful innovation is a result of a good measure of disruption. Over this, you must add a very generous helping of talent and a lot of creativity to go into the mixture and finally a splash of intuition and you’re good to go.

While this may be the probable recipe for any innovation, but does it also happen to be the recipe for a successful innovation? That seems to be a different story altogether, because usually the one thing that any successful innovation depends on, is whether it meets or exceeds the assigned business goals.

It also finally boils down to the inclusion of big data into the mix. It is this ingredient that would help you ensure that your innovation is very successful. This is how you will figure out the coveted je ne sais quoi for your success. So one must remember to always get out their big data analytics tools and crunch some data in order to get amazing results.

Innovativeness, responsiveness, and resilience happen to be the trifecta of deriving business agility. These happen to be the core business drivers, which when put together, you have a great picture of how businesses deal with change.

Analysing the information that you have gathered or that is at your disposal, will help any organization deal much better with change as a result of a thorough optimization process. All a professional is required to do is gather all the data that is available on anything that they are doing, crunch all the numbers and go on to make recommendations on what all changes need to be made in order to ensure the betterment of the process.

While data analytics may be supremely efficient in making human processes more efficient, it has also experienced one flaw. That flaw as surprising as it may sound is humans. This would be more clear as the processes become complex. For example, when the data grows, it inadvertently means that the need for analysing the same also grows. But the downside here is that people, as a rule, have a limited attention span. So when it comes to analysing information, this attention span can prove detrimental in the processing of the information. So in a way no matter how good and exemplary your data analytics tool is in giving off results, it is redundant if there happens to be no one to read them or even understand them.

This is the reason why in order to eliminate the weakest link, there are many organizations which are trying to establish totally automated feedback loops. For instance take a firm which is responsible for managing giant amounts of data, from airports to factories and data centres. While the traditional approach to handling any kind of glitches here would be, drawing up of a number of reports, based on mathematical formulas and adjust the maintenance schedule accordingly. On the other hand, if there are mechanisms that would know beforehand when the glitches would occur and correct them way before happening, this would be a better arrangement.

This is why Data Analytics is becoming the most sought after profession, with many data aspirants trying to get professionally trained from Imarticus Learning.


Enjoyed reading this report? Read more here:

The Future of India in the Field of Big Data Analytics

How Credit Managers can optimise the use of Big Data Analytics?

 

  • March, 25th, 2017
  • Posted in

Role of Analytics in today’s Scenario

Although analytics has been around for a long while, it wasn’t until the last 5 to 10 years that its importance in the business field has been realized. It was in the last 10 years that technology has been revolutionized and we now produce about 2.5 quintillion bytes of data every day. This is more data than what was collected in two years, previously. During big data training classes, it is known that 90% of the data in the world today has been created in the last two years alone.


This data comes from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals to name a few. This data is big data. What has also changed in the last decade is that we now have the means to sift through these 2.5 quintillion bytes of data in a reasonable amount of time. All these changes have major implications for organizations today.

In organizations, analytics enables professionals to convert extensive data and statistical and quantitative analysis into powerful insights that can drive efficient decisions.

Therefore with analytics, organizations can now base their decisions and strategies on data rather than on gut feelings. Moreover, with the rate at which this data can be analyzed, organizations are able to keep tabs on the customer trends in near real time. As a result effectiveness of a strategy can be determined almost immediately. Thus with powerful insights, analytics promises reduced costs and increased profits.

The analytics Industry is one of the fastest growing in modern times with it poised to become a $50 billion market by 2017. With this sudden surge in the analytics industry, there is a tremendous increase in the demand for analytics expertise across all domains, throughout all major organizations across the globe. It has been predicted that by 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.
IBM’s recent study revealed that “83% of Business Leaders listed Business Analytics as the top priority in their business priority list.”

Deloitte has mentioned in its study that – Decision makers who can leverage everyday data & information into actionable insights for the growth of their organization by taking reliable decisions, will find themselves in a much better position to achieve strategic growth in their career.

There is an information overload in today’s world and data analytics helps to cut out the clutter to help businesses make safe and smart choices.
A recent report by Nucleus Research found that companies realize a return of USD10.66 for every dollar they invest in analytics.

In the developed economies of Europe, government administrators could save more than €100 billion ($149 billion) in operational efficiency improvements alone by using big data, not including using big data to reduce fraud and errors and boost the collection of tax revenues. Thus big data courses in India are going to be essential in a few years.

This is a small taste of what you will learn in BAP R, business analytics professional program. Learn more about the program here.

  • December, 26th, 2015
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