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Consolidate information across xOps value chain, govern workflows, encourage collaboration, ease coordination and progress reports.
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How to track time spent on collecting the information?
How to detect if Data & AI initiatives delivery is efficient or not?
What are the project progress and interdependencies?
What risks is your initiative exposed to?
Does technical efforts align with expected costs & outcomes?
Easy collaboration across contributors all along delivery
Improve alignment and optimize coordination of efforts
Effective communication and progress reporting
Various participants and tools across an xOps value chain (DevOps, DataOps, MLOps, FinOps...) makes tracking Data & AI delivery challenging.
Thanks to a consolidated vision of progress, performance, quality metrics, the delivery cockpit ensures project goals are aligned, resources are distributed across products in the portfolio.
With raising risks and new regulations, orgnaizations need to ensure proper validation workflows are deployed and enforced while keeping pace and efficient delivery capabilities.
Integrate workflows and checklists in the cockpit centralizes reviewing, checking and validating different steps and orchestrating teams and tools.
The complexity of the value chain creates collaborations silos in each tool, which causes inefficient partnership and blocks participations from occasional contributors.
Consolidated vision and engaged stakeholders can smooth project progress from data sourcing, removing roadblocks, aligning objectives to deploying successfully.
Inconsistent clarity and project details across initiatives make it challenging to provide Data & AI project status reports and consolidate at the portfolio level.
Flexible and dynamic reports with visualizations allows streamlining reporting requirements, improving visibility, supporting decision agility and providing the much wanted efficiency gains.
