Analysis and Structuring of Data in the Deeptech Market

Category :

Consulting

Context

The client faced challenges related to the qualification, understanding, and analysis of its data, a critical element for this player operating in the strategic and highly competitive Deeptech sector. The client engaged OMS to structure the data of all Deeptech startups, analyze it, and draw insights supporting its strategic decisions.

Approach and methodology

  1. Audit of data quality and surprise report.
  2. Cleaning, structuring, and in-depth data analysis with advanced modeling.
  3. Creation of reports, studies, and ad-hoc strategic analyses for the Management.
  4. Continuous improvement on analyses, reporting, and data quality.
  5. Handover of tools and processes to the new Strategy & Data project manager.

Objective

  1. Understand data flows and data quality.
  2. Build robust and scalable analysis models to refine the understanding of Deeptech startups’ performance (2500 startups, 20 innovation & financing products).
  3. Establish quarterly reports for Bpifrance and the French State.
  4. Conduct ad-hoc analyses for the Deeptech Management (cannibalization analysis, Deeptech 2023 Plan, etc.).
  5. Become the Data reference within the Deeptech department.

Results obtained

  1. Automated quarterly reports, for Bpifrance and the French State.
  2. Formalization of data flows, continuous improvement in data quality.
  3. Creation of an analysis model for the 2500 startups, covering the twenty innovation & financing products.