Industry Report: Data Driven Innovation: Disruption Vs OptimizationMarch 25, 2017
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: