Focus on Data infusion and Analytics
Over the past 6 months, I have been focusing on a Journey to AI. In the first episode, I talked about how AI was born and what changes it has brought to our world. We have seen a lot of improvements in innovation, disruption and transformation thanks to this smart technology.
In the last episode, I discussed how to optimize the use of data for AI purposes. We discussed data relevance through 4 steps: data collection, data organization, data analysis and data infusion. The journey to AI has never been easier, more reliable and more relevant.
In this new episode I would like to focus on the down to earth use of AI. Every day when you are involved in any AI project, you need to think about what use you are going to make of it and how you will reach success. In other words, you will need to understand what has worked and what has not worked. You will need to make precise, fast and comprehensible decisions to ensure pivoting when needed.
More and more businesses hire data scientists to help them with data value and relevance. These scientists create very useful AI models that will then be shared with business owners and create reports that will benefit concretely P&L analysis, HR and Operations optimization, as well as greater ROI. However, once these models are created, many companies are faced with challenges in operationalizing them to attain broader business value. This means that very often models are made by people who have thought about the best way (thinking on paper) to improve results, though once faced with business reality may well be challenged to put them in place. In other words, like business plans that must be confronted by the market to know if they are reachable and feasible, AI models need to be proven to become practical and useable. You need to be able to automate and operate AI across its full lifecycle, speeding the time to value, shaping future business outcomes and giving real time information to act upon.
But how do you know if you are successful?
Analytic tools are available, usually which you can personalize to ensure your KPIs are tracked and monitored, hence guaranteeing your success.
Planning analytics allows real-time reports on all data available. Multi-dimensional analysis and scenario models are easily produced and used to check on your activity.
You will be able to make decisions based on actionable data.
You will be able to explore many and varied relationships within your data.
With an AI visualization tool, you will be able to get the most personalized and relevant analyses for your business.
AI is based on data and models and as such allows very precise analyses and calls to action for any type of business.
When we speak about a Journey to AI we are describing the advancement from the existence of data, to the collection of data, to the organization of data and finally, to the analysis of data.
Once these 3 steps are done, infusing data will allow you to take control of all of your data and give the best business use for it.