Hi Marc,
Can you, please, introduce the RED Team and its work on big data and analytics for Franz' clients?
The Red Team federates Franz Partners' business analytics and data science skills to solve real-world, high-impact business applications. We embed data science at the heart of all our consulting engagements to solve complex problems, save time in data collection, and bring additional insights to our clients. Our goal is to put data and AI at the service of the business.
What is your approach to data science and how it could help Franz clients?
We systematically look at problems from a business perspective to identify THE central question, issues, key unknowns, and areas of uncertainty that should structure our approach. Our analysts assess all needed information and information assets that are available during an exploration phase at the beginning of the mission. Franz's structured information processing allows for high level of security and knowledge capitalization. A 10-step information tunneling process was designed to secure the database in terms of completeness, quality and relevance. The RED Team supports our European data focus and leadership strategy.
How does the RED Team work with other Franz Partners teams to add value?
Franz's information funnel federates consultants and data analysts on the same workflow. Our analysts, whether from the core team or the red team, work together on most steps of our information funnel. This both speeds up delivery and helps us better understand customer problems from a data perspective.
Can you illustrate some RED team's projects and successes?
We have recently led high-impact engagements on developing AI assistance solutions for active asset portfolio management or assessing cyber threats from publications available on certain networks. We have also used data science to automate error detection in collection application workflows for a banking client at a European level.
What are the most complex / impactful projects the RED Team has worked on?
From ou view, there are two types of complex data-science missions: on the one hand those where the data is non-existent/non-digitized or highly distributed in the company ; on the other hand missions requiring huge volumes of real-time data from public sources.
For examples,
- in the perfume industry, we had to support the digitization of information before developing our own learning models to allow effective patterns recognition where statistics and the usual machine learning algorithms did not allow to obtain stable results.
- In the media sector, we had to build a specific architecture to classify continuous streams of unqualified information in representative datasets before being able to extract relevant information for the client.
What makes the RED Team unique in terms of skills and experience?
We leverage a state-of-the-art data science lab established in Poland and pan-European network of data-scientists. The RED Team senio-leadership capitalize years of experience in successful relationships for a variety of industries.
What challenges and opportunities does the Red Team face in big data and analytics?
When data science seems to be a game changer in the industry we work for, the RED Team acts as a business catalyst with FaZ' to build dedicated AI verticals as a standalone company with and for our clients.
That's what we did with Predicity for perfumery and what we are doing with Quantific for asset management.
What are RED Team's plans for the future and how they can continue to help Franz' clients.
We just developed our first vertical dedicated to the fragrance industry and look forward to finding new disruptive opportunities in our clients' businesses.
What does the RED Team think about the future of big data and analytics?
We share the idea that open-data, the development of dataspaces (DMA/DSA), the availability of open-source bricks and the development of low-node/no-code will allow widespread access to AI algorithms by the business world. The central question will then be about use-cases identification and the level of confidence that can be given to a specifiic AI. This is why we are now working with French think-thanks on this topics ("IA de confiance").
Thank you.
Marc, RED Team Founding Partner.
Disclaimer: Lea is one of the research projects conducted internally by Franz Partners team to better understand the capabilities and limitations of data and AI. It is a python3-based conversational bot, davinci core (GPT-3), that was trained using Franz Partners' marketing materials to provide marketing support to our teams. Lea's interviews were reviewed with translations from DeepL to highlight the AI's writing capabilities. Lea's face on social medias was imaged by a generative adversarial network.
