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Full Glossary

Foundations

Operational Efficiency
Delivering the same or greater value with less waste, delay, and effort across an organization's workflows.
AI for Efficiency
Applying AI to accelerate, automate, or augment steps in a workflow so work flows faster and with higher quality.
Smarter, Faster Workflows
Workflows improved with AI to reduce manual effort, cut cycle time, and surface better information for decisions.
Assessment Approach
A structured way to evaluate current workflows and identify where AI and automation deliver the most benefit.

Analyze

Workflow Mapping
Documenting the steps, handoffs, and information flows in a process to understand how work actually moves.
Value Stream Analysis
Examining end-to-end flow to find delays, rework, and waste that AI could help reduce.
Bottlenecks
The constraints that most limit throughput; targeting them yields the greatest efficiency gains.
Manual and Repetitive Work
Tasks that are repetitive, rules-based, or knowledge-heavy — prime candidates for AI assistance or automation.
Cycle Time and Lead Time
Measures of how long work takes, used to quantify inefficiency and improvement.

Opportunities

Automation Opportunities
Steps where AI can perform or accelerate work, reducing manual effort and errors.
Augmentation Opportunities
Steps where AI assists people — drafting, summarizing, analyzing — to work faster and better.
Decision Support
Using AI to surface insights and options that speed and improve human decisions.
Information Retrieval
Using AI to find and synthesize information quickly, reducing time spent searching.

Evaluate

Value vs. Effort
Assessing each opportunity's benefit against the effort to implement it, to focus on the best options.
Feasibility and Data
Checking whether the data, tools, and skills exist to make an improvement work.
Risk and Compliance
Weighing privacy, security, and governance considerations before automating or augmenting a step.
Quick Wins
High-value, low-effort improvements that build momentum and prove value early.

Roadmap

Prioritized Roadmap
A sequenced plan of efficiency improvements ordered by value, feasibility, and risk.
Proof of Concept
A small experiment to validate an efficiency improvement before scaling it.
Success Metrics
Defined measures — time saved, error reduction, throughput — used to track and prove improvement.
Continuous Improvement
Treating efficiency as ongoing, repeatedly reassessing workflows as AI and needs evolve.

Responsible AI

Responsible Automation
Keeping humans accountable, protecting data, and ensuring quality when automating with AI.
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