Modelling innovative systems and uncertainties


InnovML is a model-oriented language dedicated to innovative products and focused on mitigation of uncertainties and heterogeneous stakeholders requirements management.

This document is the English version of the following DOI to be cited


Developing a new really innovative product requires fixing a significant number of uncertainties. If not, the product is likely to become an assembly of technologies instead of a genuine innovation. For systems, or systems of systems, engineers use an approach called SysML [1] making it possible to represent a system to be built according to various diagrams but especially tracking the customer requirements. The team involved in the project transforms the functional/technical specifications from the customer into a requirements list linked to the parts of the product. This approach is relatively powerful and many softwares make it possible to build models, opensource (Papyrus, modelio) or commercial. But for an innovative product, the definition of systems will occur only at an advanced phase of the R&D process. These system engineering approaches are not convenient during these early steps, when creativity and experiments are dominant.

InnovML is a simplified language dedicated to the description of innovative products, focused on uncertainty management and useable by many developers with just a short training phase.


Why model an innovative product?

The creator of innovative products, the start-up founder, or the CEO involved in an innovation action, is not in a standard relationship with a well-defined customer having clearly expressed requirements. If it was, a sysML approach (or UML in software industry) would be convenient.  As a bonus, the customer is often absent since the product doesn’t still exist. However, he’s in front of various involved « stakeholders » : public authorities, lawyers, suppliers, funders, shareholders, associates… Each of them needs to view a representation of the future product. This representation cannot be a business model only, but has to address the development roadmap. An innovML chart makes it possible to pilot the project, addressing the uncertainties and also the potential bad faith of some of the stakeholders.


InnovML-The structure

InnovML is structured in 4 blocks (4 FOUR):

  1. Facts : Facts are experiments (and sometime experiences), information, validating events, allowing to fix uncertainties.
  2. Objects: Objects are items, material or not, representing parts of the innovative product. For example, a smartphone can be split in hardware and software parts.
  3. Uncertainties: Uncertainties are key points unknown at the early stages. They are not « risks »[6].They will have to be fixed prior to manufacturing and selling
  4. Requirements: The requirements are claims expressed by stakeholders. Some of them may derive from other ones?

These 4 FOUR are linked by 3 types of connections:

  1. Requirement attributions that may have 4 status (verify, derive, satisfy, refine)
  2. Uncertainties attributions linking facts to uncertainties they reduce (or to requirements they impact)
  3. Blocks attribution linking innovative product parts.

InnovML intends to :

  • Be a first approach making it possible to swap to sysML as soon as uncertainties will be fixed;
  • Strongly connect to the business model [2];
  • Take into account company strategy, being connected to Porter [3] forces;
  • Address uncertainties as a source of value and future cash flow enablers (according to Thiel[4]);
  • Compatible with technological readiness levels up to TRL 3-4 [5];
  • Be oriented to uncertainty management (Knight [6])

By strengthening the experimental approach, innovML is a tool for operational R&D[7] and improves team creativity by focusing actions on fixing uncertainties[8].


Using InnovML

An innovML module instance is available at

This is an autonomous web app that can also be used offline on tablets (use ‘add to the home screen’ button). All the operations are running in your browser and nothing is stored on our server. That means you need to save your work locally because we can’t restore your work remotely. You can use the embedded example as a tutorial.


Let’s Participate

This first release has be coded for R&D Mediation owns needs. You may contact us if you want to take part to the further development of innovML.





1.Canals, A. SysML/UML : comment les utiliser ? Techniques de l’ingénieur (2016).
2.Osterwalder, A. The business model ontology a proposition in a design science approach. (Ecole des Hautes Etudes Commerciales de l’Université de Lausanne, 2004).
3.Porter, M. E. How competitive forces shape strategy. (1979).
4.Thiel, P. & Masters, B. Zero to one: notes on startups, or how to build the future. (Crown Business, 2014).
5.ISO/FDIS 16290 – Space systems – Definition of the Technology Readiness Levels (TRLs) and their criteria of assessment.
6.Knight, F. H. Risk, uncertainty and profit. (Signalman, 2009).
7.BRUNET, L. E. Recherche développement innovation (RDI) en entreprise. Techniques de l’ingénieur Management et ingénierie de l’innovation base documentaire : TIB564DUO., (2016).
8.Brunet, L. E. & Le Meur, K. A big data and Darwinian approach of scientific creativity. in R&D Management Conference proceedings (ed. Fraunhofer, I. A. O.) 1, 401–407 (IAO Fraunhofer, 2014).

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