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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. 

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. 

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. 

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.