(Europe) Jean-Loup Loyer, Chief Data and Analytics Officer, Eramet, talks with Michael Sieczko, Business Development Director, Lingaro, about his perception of the technological side of digital transformation efforts versus the human side, and the organizational change that needs to co-occur to ensure a successful transformation.

Loyer shares that although essential for digital transformation at a practical and concrete level, technology alone is not enough to ensure overall success. More importantly, technology cannot be a means to an end.  For instance, you can put the best technology in the hands of business teams but that will not provide good results if that technology does not answer a company’s needs and users are not trained to use it properly. For business teams to adapt in their ways of operating and better take the outputs of an algorithm into their daily work routines, the human component is essential.

The key word in digital transformation, according to Loyer, is transformation. He shares that transformation starts with understanding the trends in an industry, as well as understanding a company’s strategy so that digital initiatives and data initiatives remain relevant and operate according to that strategy. Transformation also requires profound empathy  to understand a company’s pain points, intensify potential improvement and design solutions that will add up to success. Finally, and equally important, according to Loyer, follow-up is necessary to identify where work is needed regarding the ways digital products are being used and the actual, measurable value they bring. Working with cost control allows businesses to measure solutions, track progress and determine what they are funding for the following year. 

Loyer says that in a B2C company like L’Oreal, especially on the analytic side, there is more work around consumer behavioral modeling, sharpening prediction, and market signal analysis. So, it is more of a psychological, sociological-oriented type of data analysis. B2C companies also have a higher volume of data and more diversity of data. Therefore, it is not easy to have tech control on data quality. You also have privacy issues like General Data Protection Regulation (GDPR) in Europe. 

Although  B2B businesses have lower volumes of data, it’s more complex with small variables so it can be tricky. You have a bit of a grasp on the business processes generating the data, but you may still have many errors due to bad data management. If you want to have reasonable control of the data and have the know-how to do it, you can go back to the source of the data, which is often not possible in the B2C setting. In the B2B industry, there are fewer issues related to privacy or ethics because this industry does not operate with customer data. Hence, things are simpler, but explainability becomes more critical. 

Loyer shares that mining can be a challenging – yet exciting – industry for those in data analytics because it connects many local issues. So, managing relationships with local communities is vital. You also connect local issues with global issues, such as the global economy, commodity prices, and job politics.

At Eramet, they use deep learning AI techniques to save trees, fields, and wells. They ensure minimal impact on the local population and sometimes help with relocation or compensation, which is unique to the mining industry. So it’s necessary to track what has been modified, what has been restored. Some mining data comes from geologists, and Eramet also uses data from satellite imagery.