Business models and sustainability for materials modelling software

We recently published a White Paper on Materials Modelling Software Business. Key findings are:

• A variety of business models are identified, mostly based on a hybrid software and services approach. Software sales as well as subscription licenses in combination with a range of services (from initial implementation to contract research) are the predominant revenue mix.
• Services play a significant role, with income ranging from 20-80% in many cases. Target software to services ratio is in the range of 70-80 / 30-20. Services are not as scalable but a substantial amount seems required due to the complexity of the software and science.
• Software as a Service (SaaS) is still in its infancy in the materials modelling field. Ways of overcoming industry reservations with SaaS (e.g. security concerns) should be found since SaaS can greatly reduce software maintenance costs and provide a faster route for new features to get to users. Also, SaaS would help to reach small and medium enterprises.
• New businesses developing services or SaaS based on proprietary software is somewhat hindered by the lack of business and licensing models between Software Owners and SaaS provider.
• There is opportunity for Materials Modelling Marketplaces but also reservations in particular regarding customer relations.
• Working closely with customers (via services and consortia etc.) is important to uncover why they are using your software and what it takes to retain them as well as to fund new developments.
• Sustainability of software requires a change in education and better recognition of the persons in charge. Lifecycle of software requires substantial rethinking and a vision for the future as software’s age reaches decades.
• It is important to engage with the academic community, find ways to make software engineering more exciting and bring in new standards to make software sustainable and maintainable.

The full White Paper is available via EMMC or Zenodo. The work was funded by the EU H2020 project EMMC-CSA, Grant Agreement No 723867.