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The Square Research Center broadens Square’s expertise so as to bring theoretical and practical solutions to the current and future needs of our clients.

WHO ARE WE? 

The Square Research Center has been founded to promote the development of applied R&D work carried out within Square. It aims to design and test the most innovative approaches and tools to deliver relevant answers to the main issues of organizations. The Square Research Center brings together researchers (PhDs, PhD students), consultants, academic partners and public and private organizations, to jointly produce new, action-oriented knowledge and solutions that are meant to be implemented in a concrete manner. 

WHAT DO WE DO? 

The Square Research Center engages its teams to unlock the scientific and technological barriers preventing organizations from thoroughly addressing the “issues” they are facing, whether new, emerging, or already known. To this end, we develop models, solutions and tools for our clients, our partners and our consultants. We share our results at academic seminars, professional trade shows, or in scientific publications and use our discoveries in the frame of assignments brought to us by our Clients. 

HEAD OF THE SQUARE RESEARCH CENTER

David Alcaud graduated from the Paris IEP, holds a Master of Arts from Kent University and a Master 2 in comparative literature from Paris III University. He has studied Sociology at Paris X University and holds a PhD in political sciences from the Paris IEP. Recipient of the « Bourse de l’Ecole française de Rome » award and grantee from the Lazard Foundation, he held teaching positions at the Lille IEP and Paris IEP, as well as at several American Universities. He was an associate researcher at the CEVIPOF and the CURAPP and Vice-President of the Interdisciplinary Foundation for comparative research in social sciences. He has directed collections and books and has been a contributor to many conferences and academic publications. David has joined Square ten years ago to concurrently lead applied research work and consulting assignments. He is currently head of the Square Research Center and contribute to multiple projects. 

THE PROGRAMS

Data management

Data management

We offer an organizational model that goes beyond a mere technical architecture and allows to combine technology and human resources management. This organizational model builds on three components identified in the Data Vault 2.0 modelling and suggests new avenues such as data literacy to overcome the current barriers to data usage. 

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Causal inference and improvement of customer knowledge models (Uplift)

Causal inference and improvement of customer knowledge models (Uplift)

Our work demonstrates the limitations of Big Data in the field of customer knowledge. It has paved the way for new research avenues on Machine Learning, especially Preference Learning. Applied to target marketing, this analytical technique makes it possible to characterize profit-generating customers and can be extended to other fields (health, etc.).

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Digital twins of warehouses – intralogistics

Digital twins of warehouses – intralogistics

A digital twin is a type of simulation that relies on the principle of a virtual clone of a physical system or process. While digital twins are broadly used in industrial and scientific settings to support product-associated decision-making, little research work has looked into the use of a digital twin to support process-associated decision-making. Management of the carbon footprint and greenhouse gas emissions in intralogistics is a process that would benefit from the digital twins we are currently developing. 

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Models of portfolio alignment on climate trajectories

Models of portfolio alignment on climate trajectories

We are developing a new, complete conceptual framework to make the analysis of investment portfolio more objective and thus create a series of models able to integrate and process data on an organization’s greenhouse gas emissions ; to adapt the projection methods of gases emissions to the data available, and to rely on mixed methods to optimize such projections ; to bring transparency to the operation and organization of the algorithms underlying the model. 

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Data management

Value-based performance management

A value-based approach enables decision-makers to develop a strategy integrated across their entire value network (ecosystem), encompassing performance stakes (financial, extra-financial, operational) as well as the most modern challenges of competitivity, innovation and profitability. Managing performance trough value enables executive boards to align strategy, organization, operations and management. 

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Platformization and Innovation Strategies

Platformization and Innovation Strategies

Our research work aims to provide a new reference framework for designing and managing new business model projects and determining to which extent platformization can — or cannot — be a good development lever. We especially focus on the platformization perspectives in the context of Open Banking, and their impact on value creation models. 

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Banking Sustainability

Banking Sustainability

We have developed an econometric modelling to analyze the determining factors (both exogenous and endogenous) impacting profitability and banking risks. Thereby interrogating the durability of the banking business models, formerly called “banking sustainability”, our work offers a new analytic framework to measure and anticipate impacts on the profitability and banking risk profile, depending on their specificities: retail bank, investment bank, mass retail bank, universal bank.

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Responsible Digital Technology

Responsible Digital Technology

Our R&D program aims to develop a tool that measures the immaterial value of digital technologies, thus ultimately delivering an analysis and decision-aiding tool. We allow responsible digital technologies to be an integral part of the CSR and IT strategies of organizations, thus consolidating the management of extra-financial performance.

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Causal inference and improvement of customer knowledge models (Uplift)

Organizational culture modelling for change management

We strengthen the capacity of organizations to grasp and evaluate the cultural factors that are directly and indirectly impacting their ecosystem as well as their capacity to effectively change and manage such transformation. Organizational culture analysis, in particular, often remains relegated to the background, making any cultural diagnostic difficult, or even useless, thereby depriving organizations from an instrumental lever to promote the chosen change. 

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Causal inference and improvement of customer knowledge models (Uplift)

New ways of working and managing

We are developing a model of an approach to understand the way in which business practices are applied in organizations. The program aims to model the best possible way to set people, teams and the eventually the whole organization in motion, and thereby lead the change depending on an organization’s practices and structure. 

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Causal inference and improvement of customer knowledge models (Uplift)

Interpretability of automated learning models

Our research work is focusing on developing solutions to improve the evaluation metrics of interpretability models in terms of plausibility and fidelity. The design of robust substitution models against adversarial attacks. The generation of adversarial attacks and suitable counterfactuals, which are especially difficult for NLP applications, to eventually optimize the interpretability of AI algorithms. 

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CONTACT US

173 avenue Achille Peretti
92200 Neuilly-sur-Seine
+33 1 46 40 40 00

GIVING A FUTURE TO TALENT