We built a data product and analytics platform to power the dashboard system that manages $400+M in maintenance and operations expenses for one of the world’s largest manufacturers of paper and building products. The flexible, scalable platform provides the client with an accurate and easy-to-access single source of insights for reporting and decision-making.
We helped this building products manufacturer to move from a chaotic data landscape to a modern data strategy and scalable analytics product platform that enable rapid, value-based decision-making. One example of the impact: A freight lane analytics solution powered by data from Snowflake’s Data Marketplace that’s delivering an estimated $3M- $5M in annual savings.
We built a data product and analytics platform to power the dashboard system that manages $400+M in maintenance and operations expenses for one of the world’s largest manufacturers of paper and building products. The flexible, scalable platform provides the client with an accurate and easy-to-access single source of insights for reporting and decision-making.
We helped this building products manufacturer to move from a chaotic data landscape to a modern data strategy and scalable analytics product platform that enable rapid, value-based decision-making. One example of the impact: A freight lane analytics solution powered by data from Snowflake’s Data Marketplace that’s delivering an estimated $3M- $5M in annual savings.
Start with stakeholder interviews to understand the current state of your analytics—pain points, user community dynamics, current backlog of needs, team capabilities, etc.— and catalog opportunities and recommendations.
Conduct a gap analysis, along with an envisioning session, to:
> Identify specific product development projects and proof of concepts
> Estimate relative revenue opportunity for each
> Prioritize projects based on value and alignment to vision.
Conduct a deep-dive assessment of the current data environment and an exploration of future-state data platform needs to gain a full understanding of the existing platform architecture and data assets.
Use this information to conduct a gap analysis and develop a reference architecture that aligns with and enables the Analytics Product Roadmap.
Enable your organization to deliver on the Data Strategy and Analytics Products roadmaps by establishing the capabilities, roles, and processes necessary for success.
> Facilitate a thorough self-assessment of your internal team’s current capabilities.
> Conduct a gap analysis that provides a score for your current capabilities and a desired score for your future-state team.
> Identify ways to close score gaps, catalog improvement recommendations, operationalize the team, and prioritize investments—all based on alignment to value and the data and analytics product vision.
