84% of the CEOs think that Data-Science & AI will be required to reach their growth target.
This figure is one of the main conclusion of a survey done by Accenture last November, polling 1,500 CEOs worldwide.
¾ of these CEOs think that if they don’t develop these skills internally, they may well be out of business within 5 years.
But, 76% of them admit that so far, they fail to scale their AI/Machine Learning initiatives.
Data-science (whether we talk about Analytics | AI | Machine Learning |Mathematical modeling..) is somehow new in many industries. Not that these techniques didn’t exist before, but they were mostly used in academic research and in some advanced fields.
Now, as data are plentiful, we need data-science everywhere!
We need Data-Science:
Problem: experienced data-scientists are a scarce resource .. and once their Proof of Concept is done, deployment in production (according to I.T standards) is hard to achieve.
2 elements to solve this challenge:
1 – A centralized platform for Machine Learning is required to easily check models once they are trained, and push them into production. We will demo how such a platform could work using open-source solutions within a webinar we host during DevTalks on 12/06 at 14h40 – JOIN US!
2 – But besides that we need to help people become at ease with data-science so that they can progressively handle projects on their own. We need to train them so that they embrace this
The volume of available online courses is just enormous! Beginner, Intermediate or Advanced levels ? pick your desired level
Unfortunately, it doesn’t work this way – The reality is that it is very difficult to really take off on data-science without a sustain effort in time. People will give up, people will drop out – massively.
Solution: Be part of a community. Do some hands-on projects.. and get some mentoring.
How such a mentoring program works:
Within Societe Generale European Business Services, we have already several people who entered this program. And they also transitioned in their work. They still have the job title of Business Analyst, Team Lead (SME), Front-End Web Developer Java Developer, Project Manager.. etc.
Within our Data Community, as mentors – we welcome everybody with a solid enthusiasm for data. We support women in data-science to develop this vibrant community.
All in, Mentoring data enthusiasts & setting up a centralized Data-Science platform are the 2 essential axes to succeed in this transformation.
Within this survey from Accenture, the most advanced companies report a Return on Investment (ROI) x3 on individual data-science projects once this scaling is achieved.
Nicolas Boitout, PhD & Radu Lupu, Professor
CoE AAA – AI, Analytics and Automation