Collaborative Workspace for Incremental Data and AI Strategy
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Solution Overview
Problem
Organizations face challenges in creating a well-defined data and AI strategy that can be implemented effectively across multiple sub-groups within a complex organization, as traditional approaches focus on high-level goals and short-term rewards, neglecting cross-functional business strategies and organizational blocking factors, and are often costly and time-consuming due to the involvement of numerous stakeholders.
Innovation Solution
A system that provides a collaborative digital workspace where users can incrementally develop a data and AI strategy by populating dedicated content areas with user-generated content, detecting votes, and generating an ordered sequence of actions for implementing a cloud platform, allowing for rapid and incremental development of a data and AI strategy aligned with business objectives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional approaches involve numerous stakeholders and interviews to create data and AI strategy, then comprehensive coverage of organizational goals and principles is improved, but time consumption increases to months and cost increases
Solution Approach 1:
The patent segments the monolithic data and AI strategy creation process into multiple independent work streams, each focusing on specific objectives (e.g., data quality, AI use cases, governance). These segmented work streams can be executed in parallel by different user groups, reducing overall time while maintaining comprehensive coverage through the aggregation of results from each segment.
Solution Approach 2:
The system performs preliminary actions by pre-defining standardized templates, frameworks, and content areas for strategy development. Instead of starting from scratch with each stakeholder interview, the system provides pre-structured workspaces with predetermined categories and guidance, enabling faster completion while ensuring comprehensive coverage of necessary strategic elements.
2Adaptability or versatility
If traditional approaches focus on high-level organizational goals and data management principles, then strategic alignment is improved, but implementation guidance is insufficient
Solution Approach 1:
The patent implements a nested structure where high-level organizational goals and principles are contained within broader strategic frameworks, which in turn contain specific implementation work streams. Each nested level provides guidance for the level below it, ensuring that implementation activities remain aligned with high-level strategy while providing actionable detail at each tier of the hierarchy.
Solution Approach 2:
The system adds a new dimension to traditional strategy planning by introducing an implementation-focused workspace that complements the strategic planning dimension. This additional dimension includes practical elements such as specific use case development, technology selection, and operational roadmaps, transforming the strategy from abstract principles to actionable implementation steps.
3Productivity
If traditional approaches focus on near-sighted or short-term rewards and a few business use cases, then quick wins are achieved, but cross-functional business strategy support is insufficient
Solution Approach 1:
The patent creates a universal platform that serves multiple functions simultaneously: it supports short-term use case development while also enabling cross-functional strategic planning. The system's workstream templates and collaboration tools are designed to be applicable across different time horizons and functional areas, allowing the same platform to deliver quick wins and support enterprise-wide strategy without requiring separate systems.
4Reliability
If monolithic projects are used for data and AI strategy, then comprehensive coverage is improved, but difficulty to break down into incremental value increases
Solution Approach 1:
The patent divides the monolithic data and AI strategy project into multiple independent, manageable work streams that can be executed incrementally. Each work stream represents a discrete unit of work with its own objectives and deliverables, allowing the organization to achieve incremental value while maintaining comprehensive coverage through the collection of all work stream outcomes.
Solution Approach 2:
The system implements dynamic workstream selection and prioritization, allowing the organization to adapt the scope and sequencing of work streams based on emerging priorities, resource availability, and early results. This dynamic approach enables incremental progress while maintaining the option to expand or adjust the overall strategy as conditions change.
Data Source
AI summary
An example operation may include one or more of displaying, via a uniform resource location (URL), a user interface for data and artificial intelligence (AI) planning, incrementally populating the user interface with different dedicated content areas for different objectives of the cloud implementation, incrementally detecting content that is added to the different dedicated content areas of the user interface via user devices of a collaboration of users, detecting votes submitted via the user interface by the user devices regarding the detected content, and generating an ordered sequence of actions to perform for implementing a cloud platform and displaying the ordered sequence of actions via the user interface.