How it works
- An easy three-step modeling process to efficiently create agreement offers and streamline communication of underlying spend data with institutional partners.
- Automated affiliation enrichment technology to help reliably identify institution and funder affiliations for historically published manuscripts.
- Powerful data visualizations and export capabilities to showcase deal transparency and measure success.
- Reduce costly, manual affiliation data clean-up through automated affiliation enrichment technology.
- Optimize and scale OA programs with flexible tools to model “what-if?” scenarios for agile experimentation and innovation without spending hours on data aggregation, validation, and analysis.
- Build and maintain trust with partners through consistent, data-driven agreement proposals.
Why OA Agreement Intelligence?
Conceptualize your agreement offer, outlining its core parameters, and create your historical baseline to model a future deal with a specific partner.
Leverage comprehensive pricing parameters to simulate and experiment with new deal types and create agreement offers to propose to institutional partners.
Analyze, compare and adjust your pricing to meet your goals, partner expectations, market dynamics, and more.
As the power of computing and access to information has increased, data, and the knowledge derived from that data, has become an increasingly important driver for organizational decision-making.
Data is key to fueling the transition to Open Access publishing models, but it also presents some of the largest challenges. In the first part of a 3-part series, Herman Mentink takes a look at some of the data challenges publishers face in this transition.
CCC’s Senior Director, Information & Content Solutions, Jamie Carmichael looks at the importance of data quality in negotiating and implementing open access (OA) institutional agreements.