ops-process-optimization

name	ops-process-optimization
description	Analyze an existing process for inefficiencies, bottlenecks, and automation opportunities with a concrete improvement plan. Triggers on "optimize [process]", "improve our [process]", "why is [process] slow", "process improvement", "streamline [workflow]"
metadata	{"openclaw":{"tags":["operations","optimization","efficiency","improvement"]}}

Process Optimization

When the user asks to optimize or improve a process:

Step 1: Understand the current process

Gather from the user:

• Process name: which process to optimize
• Pain points: what is currently not working well
• Goals: faster, cheaper, more reliable, more scalable, fewer errors
• Constraints: budget, team size, technology limitations, compliance requirements
• Volume: how often the process runs and at what scale

Step 2: Map the current state

Use capability_execute with capabilityId "docs.search_files" to find:

• Existing process documentation
• Related SOPs and runbooks
• Historical process metrics or reports
• Previous optimization attempts

Use capability_execute with capabilityId "project.list_tasks" to analyze:

• Tasks associated with the process
• Average completion times by step
• Frequently blocked or delayed tasks
• Task reassignment patterns (handoff friction)
• Overdue task patterns

Step 3: Gather stakeholder input

Use capability_execute with capabilityId "chat.search_messages" to find:

• Complaints or frustrations about the process
• Workarounds team members have developed
• Suggestions for improvement already made
• Confusion or questions about process steps
• Mentions of manual work that could be automated

Use capability_execute with capabilityId "calendar.read_events" to check:

• Meetings dedicated to this process (overhead signal)
• Recurring syncs that exist because the process is unreliable
• Wait times between handoffs visible in calendar patterns

Step 4: Research improvement options

Use capability_execute with capabilityId "research.web_search" for:

• Industry best practices for this type of process
• Automation tools and platforms relevant to the process
• Case studies of similar process improvements
• Benchmarks for process efficiency in the industry

Step 5: Analyze and identify improvements

Evaluate the process against these dimensions:

• Value stream: which steps add value vs waste
• Bottlenecks: where does work queue up
• Handoffs: where does work change ownership (each handoff = delay risk)
• Rework loops: where does work get sent back
• Manual steps: what could be automated
• Approval gates: which approvals are necessary vs bureaucratic
• Information gaps: where do people lack context to do their work
• Tool friction: where do tools slow people down

Quantify where possible:

• Time per step (current vs potential)
• Error rate per step
• Wait time between steps
• Cost per process execution

Step 6: Design the optimized process

Create a target-state process that addresses findings. Prioritize changes by impact and feasibility.

Step 7: Create implementation plan

Use capability_execute with capabilityId "project.create_task" to create:

• Task for each improvement action
• Milestone for process optimization completion

Use capability_execute with capabilityId "docs.create_brief" to save:

• Complete optimization analysis and plan

Output Format

Process Optimization: [Process Name]

Executive Summary 3-4 sentences covering the main inefficiencies found and the expected improvement from the recommended changes.

Current State Assessment

Metric	Current	Benchmark	Gap
End-to-end time	X hours/days	Y hours/days	delta
Steps involved	X steps	Y steps	delta
Handoffs	X	Y	delta
Manual steps	X of Y	target	delta
Error/rework rate	X%	Y%	delta
Cost per execution	$X	$Y	delta

Process Map: Current State

[Trigger] -> Step 1 (Xh) -> Handoff -> Step 2 (Xh) -> Wait (Xh) -> Step 3 (Xh) -> [End]
                                                         ^
                                                    Bottleneck

Findings

Bottlenecks

Bottleneck	Location	Cause	Impact	Evidence
description	which step	root cause	time/cost impact	data source

Waste

Type	Location	Description	Time Wasted
Waiting	step X to Y	what causes the wait	X hours per cycle
Rework	step Z	what causes rework	X hours per cycle
Overprocessing	step W	unnecessary work	X hours per cycle

Automation Opportunities

Step	Current (Manual)	Proposed (Automated)	Tool/Method	Time Saved
step	what happens now	what could happen	tool	hours saved

Unnecessary Handoffs

Handoff	From	To	Why It Exists	Recommendation
handoff	role A	role B	reason	eliminate / simplify

Recommended Changes

Priority	Change	Type	Expected Impact	Effort	ROI
1	specific change	Automate/Eliminate/Simplify/Reorder	impact description	effort level	high/med/low
2	specific change	type	impact	effort	ROI
3	specific change	type	impact	effort	ROI

Process Map: Target State

[Trigger] -> Step 1 (Xh) -> Auto -> Step 2 (Xh) -> [End]

Expected Improvements

Metric	Current	Target	Improvement
End-to-end time	X hours	Y hours	Z% faster
Manual effort	X hours	Y hours	Z% reduction
Error rate	X%	Y%	Z% reduction
Cost per execution	$X	$Y	$Z saved

Implementation Roadmap

Phase 1: Quick Wins (Week 1-2)

• Changes that require no tooling and deliver immediate improvement

Phase 2: Process Redesign (Week 3-4)

• Structural changes to the process flow

Phase 3: Automation (Week 5-8)

• Technology-enabled improvements

Success Metrics

• How to measure whether the optimization worked
• Baseline measurements to take before implementing changes
• Review cadence to track improvement over time

Risks

Risk	Impact	Mitigation
change resistance	adoption failure	communication and training plan
automation breaks	process stops	manual fallback procedure