Data is a new super power and no one would deny, I believe. I see, businesses are anxious to implement BI/ML/AI systems and wanting to do the decision-making using data. Unfortunately, the quantity and quality of data mercilessly pulls them down. Unlike a typical IT solution, BI/ML/AI solutions outcomes are binary (IMHO). If AI/ML system’s accuracy/prediction are good, then it’s worth the shot or it just turn as an ego consoler. 

The power of data is unstoppable. Anyone who has ‘required’ data can personalize, customize, optimize and innovate their service. So, it’s becomes tactical for many as they missed to act. 

The immediate step is rather than worrying about the competition, start enabling your IT landscape. While aspirations are appreciable to see the AI/ML systems are in production today, most of you are at infancy. The fundamental act is looking at the readiness of your tech ecosystem to procure/produce, persist and purify the data. 

In the ‘data’ world nothing is waste. Even if you think something is, have a second look 😉 don’t delete rather soft delete. Computing and storing is cost effective and robust today. Indeed, identify more data points and shameless persist it. 

Your existing IT systems may fulfill your current need. The disparate systems could have been managed to give a feel that they are integrated. That’s not intelligent enough to produce data to make meaningful decisions. There is nothing wrong about this. They are not meant to do this. Modernize your landscape, nothing wrong in get rid of a few and investing for the future. Have a two prong strategy for your newer systems, one to deliver present needs and the other to capture data irrespective of today’s need. Anyone ahead of you, just did this thoughtfully or otherwise.

Many a times, the reluctance starts from why should disturb existing systems that meets present demands (but actually they are not unless you are lucky. The data monsters are everywhere, they will beat you in no time and the countdown is started). Or not sure about where to start as the spaghetti of systems has no head and tail. Now the Software development methodologies and technologies are matured enough to incrementally modernize any system and that’s a savior. Instead of looking at what competitors are doing, get started. The right quantity and quality of the data proves AI/ML works or else you will be keep staring at someone else case study.