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Achieving an Ecosystem AI-driven innovation engagement process

Paul Hobcraft

Thinking through any engagement process, one that is required to break through traditional innovation processes needs to break down the new areas of discovery. Scenario Selection: Identifying and selecting the right scenarios is crucial, especially where ecosystem engagement and the use of generative AI can be central.

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A New Integrated Innovation Engagement System

Paul Hobcraft

” We need to increasingly rely on problem-solving techniques that we generate through greater automated discovery and inquiry, those that emerge from analysis and data mining. In my view I visualize a new integrated innovation engagement platform to be like this shown below. Does it make sense to you? Your thoughts?

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Specific skills and toolkits are needed for cross-sector innovation ecosystem collaborations.

Paul Hobcraft

Project management : Effective project management skills are essential for keeping cross-sector collaborations on track. Communication and Engagement : Effective communication and engagement with all stakeholders, including participants, sponsors, and the broader community, is crucial for the success of the collaboration.

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Fusing Human and Technology to Enable Innovation Ecosystems to Thrive

Paul Hobcraft

“Fusing” human engagement with technology enablement involves creating a harmonious integration of human collaboration and technological tools to enable an ecosystem’s successful development and operation. Consider tools for communication, collaboration, data sharing, and decision-making.

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Best Practices for a Marketing Database Cleanse

Multiple industry studies confirm that regardless of industry, revenue, or company size, poor data quality is an epidemic for marketing teams. As frustrating as contact and account data management is, this is still your database – a massive asset to your organization, even if it is rife with holes and inaccurate information.

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Propel Your Innovation Strategy into Overdrive with Big Data

IdeaScale

Big data has been a foundation of innovation ever since the first suggestion box was put out. Since then, the data set has only kept growing, until now you can filter thousands or even millions of data points. How do you effectively use big data to drive innovation? Collect Only Relevant Data. Avoid Fishing.

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How to fuel your project with intelligent naivety?

Flying Fish Lab

We’re going to focus on two particular ones that we pay particular attention to during the set up stage of any project. We engage these different stakeholders with open ended questions and often it’s the case that what they don’t say is as important, if not more, than what they actually say.

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AR/VR Simulations for Sustainable, Regenerative, Circular Cities

Speaker: Nik Gowing, Brenda Laurel, Sheridan Tatsuno, Archie Kasnet, and Bruce Armstrong Taylor

In this session, participants will see how science data from such sources as NASA and NOAA, combined with local data inputs, can be used to both exponentially improve and accelerate net-zero carbon, climate positive and regenerative outcomes.

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5 Early Indicators Your Embedded Analytics Will Fail

In this White Paper, Logi Analytics has identified 5 tell-tale signs your project is moving from “nice to have” to “needed yesterday.". Many application teams leave embedded analytics to languish until something—an unhappy customer, plummeting revenue, a spike in customer churn—demands change. But by then, it may be too late.