Extending the FIP (Forecasting Innovation Pathways) approach through an automotive case analysis

The ”FIP” approach seeks to Forecast Innovation Pathways for an emerging technology of interest. It does so by combining empirical ”tech mining” analyses with expert opinion. Tech mining extracts intelligence from multiple sources, but especially through bibliometric and text analyses of thousands of records retrieved from global R&D publication, patent, and business/context databases. FIP blends expert opinion from multiple sources, but especially by convening a focused workshop. SKF conducted an FIP exercise on Hybrid & Electric Vehicles (HEVs) that presents special challenges. HEVs combine multiple sub-systems, advancing at different rates technologically, with complex technical and market infrastructures. Asian automotive production and markets appear vital for the future of HEVs, and various technologies & applications (e.g., two-wheelers) warrant tracking. Grappling with this complex innovation system helped extend the FIP approach. Enhancements included extending the previous innovation tiers framework to array multiple technological and contextual factors in conjunction. This is the first FIP workshop to split into small groups to address three priority market segments and three prime geographical regions, then regroup to review and develop consensus.Manifold factors influence HEV innovation paths, so technology delivery systems are more complex than those addressed in previous FIP studies. We reflect on FIP process development, with suggestions regarding scoping, identification of sub-systems, and possible opportunities to systematize certain analyses.