Data Innovation Summit turns five next March. Along the way, we have had fantastic speakers unselfishly sharing their knowledge on stage with their peers. Without them, this journey would be impossible.
This interview is part of an interview series dedicated to humanising Data and AI innovation and celebrating speakers who have presented on Data Innovation Summit. The emphasis lies on the Data/AI people/practitioners, their professional journey and their stories.
The retail giant H&M has been aiming for the AI leadership position by investing heavily on tech and big data to improve its supply chain and operations, optimise the business and give their customers what they really want.
But they’ve only just started, states Errol Koolmeister, Product Area Lead Engineer AI Foundation at H&MXAI.
Their next steps are to spread AI to all aspects of H&M providing our services to all lines of business and truly enable the data-driven enterprise.
Errol is one of the Data Innovators that have stuck with the Data Innovation Summit since the very beginnings. And it’s only fitting to have his story on the Data and AI Innovators wall of fame.
Hyperight: Hi Errol, it’s a pleasure to welcome you as one of the most familiar faces on stage at the Data Innovation Summit. You actually presented at the very first edition in 2016. But to introduce yourself to our readers, please tell us a word or two about yourself.
Errol Koolmeister: Hi, and many thanks for welcoming me over the years. It has been an absolute pleasure attending and presenting at Data Innovation Summit. To briefly introduce myself; I am a tech enthusiast that has spent the last decade working with implementing data-driven solutions. To summarize a bit, I have worked primarily for large companies such as Nordea, Vodafone and H&M but also spent some time in the startup scene and as a consultant. My primary drive has been to implement smarter decision making and enabling the companies I have worked with to be more relevant and precise in what they are doing.
Retail will go through a major change in the next decade that will be enabled by data & technology.
Hyperight: As 2020 is the year in which the Data Innovation Summit turns 5, could you point out what have been the most important breakthroughs with data analytics and AI in the last 5 years according to you?
Errol Koolmeister: So much has happened the last five years it is hard to grasp some of the achievements we have done. I have a hard time pointing towards a specific event or breakthrough, I would rather point out what we are better at now. Today we are able to scale our solutions in a completely new way making life easier for us working in the data field. We have seen concepts as cloud come in and helped us become more agile in the way we approach technology. Obviously, data is at the core in the things that we do but the surrounding technology is what makes it possible. We do not only focus on the models but rather the surrounding processes trying to implement full model lifecycles end-to-end.
We are far from done but much of the foundation we have solved. Now I am personally excited about the next steps in making data into a commodity in companies. Truly democratizing the access to it ensuring we base all of our decisions on facts whether if it is automated or not.
Hyperight: You have been in the industry for more than 15 years and have a profound experience with data and analytics. What are some of your personal learnings you’ve gone through during your career, as a Data Scientist first and foremost?
Errol Koolmeister: The major personal learning I have done the last 15 years as a Data Scientist, and one I have come to realize that I share with other Senior Data Scientist, is that it doesn’t matter how good your model is – if you can’t put it into production and keep it there you will never get the results. In the beginning, it was much focus on only creating great models but now we have seen a major shift in that we need more focus on the enabling engineering effort. The field of AI has drifted more towards software engineering best practices to enable Data Scientist to focus on what they do best i.e. creating insights from data.
As a data practitioner, you should focus on the simple solution in the beginning and not immediately jump into the deep end of the pool. In this analogy, it means you would jump into the pool without having any water in it in some cases without even having built the pool yet. Following the routine of the test, implement and then improve is better than the other way around.
It doesn’t matter how good your model is – if you can’t put it into production and keep it there you will never get the results.
Hyperight: You are currently in the role of Head of AI Tech and Architecture at H&MxAI. And in your Data Innovation Summit 2019 presentation, you talked about the AI-driven retail story of H&M and key learnings with putting ML into production. Your presentation was also featured in an article on our Hyperight Read channel. Could you share with us what H&MxAI is working on lately?
Errol Koolmeister: A major focus for us the last year has been to scale our solutions and implement them in all markets. We have also taken the first steps towards becoming a leader within AI in retail by starting cooperation’s with different partners and hiring top talents.
We would like to spread AI to all aspects of H&M providing our services to all lines of business and truly enable the data-driven enterprise.
Hyperight: We are now aware that it’s not humanly possible to run a global brand as H&M without the help of AI. But where do you see the future of AI-powered retail taking us in the next decade to come?
Errol Koolmeister: I know that we have only seen the first steps into this journey. Retail will go through a major change in the next decade that will be enabled by data & technology. Some of the first visual steps will probably be to provide a full omnichannel experience and increasing the customer experience by providing relevant interactions. Making sure the customers’ demands are meet end-to-end. We will see a larger use of digital enhancements of the customer experience where you should be able to see and get support immediately.
In addition, I foresee great improvements in the supply chain by more use of smart technology. Not only in our warehouses working with fulfilment but also in our interactions with factories and other suppliers.
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