Data Science
Expertise

Companies have to take quick decisions about increasingly complex questions whose answers often lie in the vast datasets available to them. But being able to use these data is another matter.

We restore rationality to complex decision making

We combine consulting and data science to make your data talk, to simply depict the quantifiable aspects of complex business issues, and to facilitate strategic decision making or inform operational actions.

We support the implementation of digital strategies and data-centric transformations

We foster the emergence, prioritisation and assessment of valuable use cases up to their industrialisation; we sensitise business lines on data use and smooth out interactions with IT and data labs.

"A new use case emerges every day"
Romain Queuche, Director

Data scientists and consultants:
two sets of expertise to ensure project success

  • We strongly believe that data science projects developed in isolation are doomed to failure and that iterative co-construction with the business lines is essential.
  • We know that the right model is the one that will be deployed and embraced in the field. This is why our data science approaches are hyper-pragmatic, founded on a thorough understanding of business challenges and an analysis of performance drivers and operational constraints.
  • Our teams pull this off by combining the skills of a data scientist – programming, algorithms and applied mathematics – with the knowledge and know-how of a consultant.
  • Finally, our data science consultants speak the language of your business lines, IT and data to facilitate the dialogue among these stakeholders, ensuring project success.

We are well versed in the tools of the trade and know how to pick the right combination to achieve your goals

  • Leadership of data science and business line teams to identify and prioritise use cases
  • Work on data governance so the organisation can preserve the quality of this crucial asset
  • Collection, cleaning and structuring of data to facilitate accessibility and analyses using data engineering techniques
  • Simple and insightful depictions of complex data with Dataviz tools
  • Modelling and simulation of complex processes and scenarios to quantify the impact of an event or transformation
  • Forecasting, classification and detection of patterns in large datasets by employing machine learning algorithms

Data science:
selected use cases

  • In supply chain: demand forecasting, stock management, predictive maintenance, optimisation of logistics networks, etc.
  • In distribution: segmentation and potential of points of sale, optimisation of assortments, management of promotions, price recommendations and margin optimisation, etc.
  • In customer relations management: customer segmentation by uses, needs and journeys, customer potential, prevention of attrition, forecasting of call centre volume, etc.
  • In financial services: client scoring for loan approvals, fraud detection, budget forecasting and projections, etc.

3 case studies leveraging data science
to boost performance

Simulate and optimise short- and long-term logistics flows by applying a digital twin to the supply chain

For a worldwide leader in specialised retail, we built a comprehensive supply chain model, then fed it with 10 years of projected structural developments. This enabled us to redesign the client’s European master plan, optimise import containers, then industrialise the planning of physical and financial flows at 3 months and 1 year.

Improve the customer experience at points of sale and optimise the work of sales reps

For a chain of supermarkets and hypermarkets, we simulated customer flows to reorganise the checkout process at all points of sale. The result was smoother customer paths, reduced costs and a modernised brand image.

For an agricultural co-op, we analysed invoicing data to pinpoint sources of revenue and prioritise the next commercial actions to take, setting up a dashboard to track the performance of the sales force.

Predict and plan loads at a shared services centre

For a shared services centre, we modelled task completion times by activity type, analysed the load/capacity committed by resource type, built a volume prediction model and drew up a scaled projection based on skill sets.

Simulate and optimise short- and long-term logistics flows by applying a digital twin to the supply chain

For a worldwide leader in specialised retail, we built a comprehensive supply chain model, then fed it with 10 years of projected structural developments. This enabled us to redesign the client’s European master plan, optimise import containers, then industrialise the planning of physical and financial flows at 3 months and 1 year.

Improve the customer experience at points of sale and optimise the work of sales reps

For a chain of supermarkets and hypermarkets, we simulated customer flows to reorganise the checkout process at all points of sale. The result was smoother customer paths, reduced costs and a modernised brand image.

For an agricultural co-op, we analysed invoicing data to pinpoint sources of revenue and prioritise the next commercial actions to take, setting up a dashboard to track the performance of the sales force.

Predict and plan loads at a shared services centre

For a shared services centre, we modelled task completion times by activity type, analysed the load/capacity committed by resource type, built a volume prediction model and drew up a scaled projection based on skill sets.

If you want to harness the power of data to transform your data