Evolution of Decision Making
Data driven decision making! Even though this term came into wide usage not very long ago, the process was already there. Even machine learning too is no new. However, the change is fascinating. The possibilities are countless. And, Of course we all are contributing to it.
When I say we contribute, often we contribute willingly but mostly it is kind of snatched from us. Needless to say, in this highly connected and convoluted world, information is a difficult thing to hide. Our data will keep exploring new places even when we are not.
So, are things out of control and we are trapped? Not really. If you can stay alert and updated you can make maximum use out of the latest advancements in tech. Staying updated by learning and sometimes unlearning, is important in today’s world of differing and evolving perspectives. However, we are not having the age old ‘Technology: A boom or a curse?’ debate. At least not right now.
Table of Contents
Deciding Data
Artificial intelligence when rightly integrated with big data, the possibilities are numerous. Even with the data available right now in different big data banks, the changes we can bring forth in decision making is enormous. Data including specifications of products, service history, customer data, feedback and resource data together can contribute to decision making using the possibilities of machine learning.
The Three Evolution
All the following three evolutions I’ve mentioned have elements of data and machine learning included. That is why I gave a briefing about their integration in the beginning.
New Levels of Collaboration
Power of collaboration is entering an entirely new dimension. Nowadays, we could see cross-department collaborations and even cross-company collaborations are seen. This may not be supported by a huge tech infrastructure. We can do these collaborations with a Slack or Whatsapp account even. So, how do these help in decision making?
Centralized repository is the answer. It can be well defined or not. No matter how organized the central repository system, collaborations are beneficial. Even if there is zero talk on the term, when we collaborate, we are creating a centralized repository bit by bit. Maybe even more.
Centralized repository is basically a collection of useful data accessible to every collaborator. According to the level of organization, it can be with or without authentication.
Extend of Automation
You might be already a part of a decision making team. And, you already know how tiresome decision making can be. Interestingly, in most cases some repetitive steps take up so much time. Especially when there are new additions to the team.
Wouldn’t it be nice if we use the possibilities of data science and machine learning to automate certain cliche steps in decision making? Yeah, you might be doing that already in certain cases. But, doing it in a more organized manner can save a lot of time for your team to focus on more important tasks.
Integration of virtual reality
How cool it would be to know the outcomes before you make a decision! I know, you might be thinking that’s what simulations are for. Simulations are good. But no. When compared to experiencing augmentation of most probable outcomes, simulations are not good enough.
Virtual reality uses data, machine learning and of course support of simulation techniques in providing the experience. This helps you in having a clearer idea of outcomes and making the decision with confidence.
Another major advantage is the ability of VR integrated systems to bring people from different locations together. No matter which location you are in, with VR, you can join the team to experience the probable outcomes together and contribute insights to decision making.
So, learn. If required, unlearn. And, stay updated to evolve with the world.
