Too many metrics
Teams spend time maintaining measures that do not support a clear priority or decision.
Performance Management System
Turn operational data into decisions, actions, and follow-through.
The Pragy AI-Enabled Operations Review System connects trusted KPIs, decision-ready dashboards, exception thresholds, management-review routines, action tracking, and optional human-reviewed AI summaries into one practical operating system.
Designed for leaders who need more than another dashboard.
Discuss Managed Review Support
Need workflow implementation first? Explore the Workflow Intelligence Sprint
Govern AI-assisted reporting
Explore the Responsible AI Starter KitStrengthen the controls around optional AI-assisted narratives.
The Responsible AI Starter Kit provides practical governance templates for approved use, risk classification, human review, incidents, monitoring, and accountable decisions alongside an operations review system.
Governed KPI framework
Decision-ready dashboard
Review and escalation routine
Action and ownership system
The performance gap
Reporting is not the same as managing performance.
Organizations often invest significant effort preparing reports, but the review still depends on inconsistent definitions, manual explanations, unclear thresholds, repeated status updates, and actions that are difficult to track.
The Operations Review System turns reporting into an operating routine by connecting the data to decisions, owners, escalations, and follow-through.
Conflicting definitions
The same KPI can use different formulas, scopes, sources, owners, or refresh dates.
Dashboards without action
Performance is visible, but thresholds, decisions, actions, and escalation are not connected.
Manual narrative preparation
Leaders and analysts repeatedly consolidate context and write the same review commentary.
Meetings dominated by status
Review time is spent presenting information instead of resolving exceptions and making decisions.
Weak follow-through
Actions lack clear owners, due dates, closure evidence, or a reliable escalation route.
The difference
A dashboard is one component. The management system connects the full decision cycle.
A dashboard shows information. An operations review system defines what the information means, who reviews it, what requires action, who owns the response, and how follow-through is sustained.
Dashboard only
- Displays measures
- Shows trends
- Supports exploration
- May include filters
- Often ends at observation
Operations Review System
- Defines measures and assigns ownership
- Establishes targets and thresholds
- Identifies and reviews exceptions
- Sets cadence and structures decisions
- Assigns actions and tracks escalation and closure
- Supports sustainment and governs AI-assisted summaries
The operating model
Connect priorities, measures, data, review, actions, and improvement.
Priorities and decisions
Business questions, outcomes, decisions, and escalation risks.
KPI governance
Metric purpose, formula, owner, source, refresh, target, threshold, and limitation.
Data and dashboard
Approved sources, transformations, quality controls, scorecard, trends, and exception views.
Review routine
Cadence, agenda, roles, preparation, decision rights, time-boxing, and outputs.
Actions and escalation
Owner, due date, priority, blocker, status, evidence, closure, and decision log.
AI assistance and improvement
Approved sources, controlled logic, draft label, verification, human approval, version, fallback, and backlog.
AI is optional. The system must remain usable, auditable, and accountable without AI.
Clear boundaries
A management-review system is not an autonomous management service.
The engagement gives accountable leaders a clearer operating rhythm. It does not take ownership of client decisions, certify data, or replace investigation and judgment.
- Not a dashboard-only engagement or generic Power BI build
- Not unlimited reporting support, a data warehouse, or an ERP replacement
- Not master-data management, cybersecurity assessment, compliance certification, or computer-system validation
- Not legal or tax advice or a guaranteed performance or financial-return program
- Not a replacement for process owners, accountable leaders, or root-cause investigation
- Not unrestricted AI summarization or a public portal for confidential operational data
- Not a managed service that takes ownership of client decisions
- Not a subscription product available for instant checkout
What you receive
A practical performance-management system - not a disconnected report.
Decision and priority map
The business questions, operating priorities, decisions, risks, and escalation needs the review must support.
KPI dictionary
Clear purpose, formula, scope, owner, source, refresh, target, thresholds, response, limitations, and approval for each metric.
Data and refresh design
Source, transformation, reconciliation, refresh timing, data-quality checks, access, and ownership requirements.
Dashboard or scorecard
A decision-ready operating view showing status, trends, exceptions, owners, actions, and required decisions.
Threshold and exception framework
Defined red, amber, and green logic with data-quality checks, review expectations, and escalation paths.
Management-review charter
Purpose, cadence, agenda, roles, preparation, decision rights, meeting outputs, and time-boxing.
Action and decision system
Action register, decision log, priorities, owners, due dates, blockers, evidence, closure, and escalation.
Optional AI-assisted narrative
A draft-only narrative workflow using approved sources, traceability, reconciliation, verification, human approval, and manual fallback.
Training and handover
Role-based guidance for leaders, metric owners, data stewards, users, and system administrators.
Stabilization and sustainment
A 45-day review of adoption, data health, control effectiveness, review behavior, actions, and improvement needs.
Illustrative review system
See performance, exceptions, actions, and decisions in one operating view.
Metric discipline
Fewer, clearer measures are more useful than a crowded scorecard.
Every KPI should support a business question, decision, accountable result owner, data steward, approved calculation, useful refresh, target, exception rule, expected response, and known limitation.
On-time completion
- Purpose
- Identify work at risk of missing the committed operating date.
- Formula
- Items completed on or before commitment / completed items
- Owner / source
- Operations manager / approved work register
- Frequency / target
- Weekly / illustrative 95%
- Required action
- Review overdue exceptions, assign a response, and record the decision.
From signal to response
Make exceptions actionable.
Not every variation requires escalation. AI may organize approved context, but the accountable owner decides what the signal means. Closure requires evidence and learning returns to the next review.
- Metric refresh
- Threshold or anomaly identified
- Data-quality check
- Owner review
- Cause or context recorded
- Decision or escalation
- Action assigned
- Evidence and closure
- Learning added to the next review
Controlled AI assistance
Use AI to prepare a draft - not to approve the story.
Where the client environment and governance allow, AI may prepare a first draft of the review narrative from approved metrics, exception notes, and action information. The draft remains clearly labelled and must be verified and approved by an accountable person before distribution.
- Approved source data
- Controlled prompt or logic
- Draft generated
- Metric and statement verification
- Human edits
- Approval
- Distribution
- Feedback and version control
AI assistance is optional and is excluded when it does not meet the client’s security, privacy, validation, or operating requirements.
Operating rhythm
Design the meeting around decisions - not presentation.
The standard public package covers one primary weekly or monthly review routine. Daily systems, multiple cadences, and enterprise operating reviews require custom scope.
- 0-5 minutes: Purpose, changes, and decisions required
- 5-15 minutes: Data quality and major context
- 15-30 minutes: Critical exceptions and trends
- 30-45 minutes: Decisions, risks, and escalations
- 45-55 minutes: Actions, owners, and due dates
- 55-60 minutes: Confirm commitments and next review
Where the system can help
Build a review system around the decisions that matter.
Manufacturing performance
Connect safety, quality, delivery, productivity, capacity, downtime, exceptions, and accountable action.
Quality operations
Review quality signals, aging, risks, ownership, escalation, decisions, and action closure without automating accountable approval.
Supply chain
Bring delivery, backlog, inventory, supplier, service, exception, and follow-through information into one review rhythm.
Finance operations
Structure the review of service, close, working-process, exception, and action measures for accountable owners.
PMO and portfolio delivery
Connect milestones, risks, dependencies, resources, decisions, actions, owners, and due dates.
Shared services
Review demand, service levels, aging, capacity, exceptions, escalations, and improvement work.
Customer or service operations
Use demand, response, quality, backlog, escalation, and closure measures to drive action.
Small and mid-sized business leadership
Create a focused operating review with fewer trusted measures, visible priorities, and clear follow-through.
These examples illustrate possible engagement shapes. They are not named client results, guaranteed outcomes, or recommendations to automate accountable decisions.
Implementation method
From KPI confusion to a sustained review system.
Fit and operating scope
Confirm the business area, review purpose, sponsor, owner, decisions, cadence, users, systems, and boundaries.
Decision and KPI discovery
Map priorities, business questions, candidate measures, ownership, thresholds, and expected response.
Data and readiness review
Assess sources, definitions, refresh, reconciliation, quality, security, licensing, and access.
Review-system design
Design the scorecard, exception logic, charter, agenda, action system, AI decision, and controls.
Build and configure
Build the approved reporting, workflow, review, and action components within scope.
Test with users
Run data, dashboard, exception, action, access, fallback, and acceptance scenarios.
Train and launch
Transfer role guidance, administration, review behavior, ownership, and support.
Stabilize and improve
Review adoption, data health, controls, actions, and improvement needs after launch.
Production deployment depends on client access, approved data, security, licensing, testing, and release decisions.
Start with a blueprint, build the system, or strengthen the operating rhythm.
Performance Review Blueprint
CAD $4,500
Approximately 2-3 weeks after complete intake and stakeholder availability
For leaders who need a build-ready KPI, review, action, dashboard, and implementation design before technical work.
- One business area and one primary weekly or monthly review
- Up to five stakeholder sessions
- Review up to 15 candidate KPIs; recommend up to 12
- KPI dictionary, ownership, targets, thresholds, and data readiness
- Dashboard wireframe, review charter, action register, and decision log
- Optional AI-summary feasibility and human-control requirements
- Implementation backlog, 90-day roadmap, executive readout, and branded blueprint
Main output: A build-ready performance-management system blueprint.
Excludes: Production dashboard, data model or engineering, configured automation, integration, AI deployment, licenses, migration, custom APIs, validation, travel, and ongoing support.
Request the BlueprintOperations Review System Build
Starting at CAD $12,500
Approximately 6-8 weeks after scope, access, security, data, licensing, and stakeholder prerequisites are complete
For one business area ready to build and pilot a controlled scorecard, dashboard, review routine, action system, and optional human-reviewed AI draft.
- One primary weekly or monthly review; one sponsor and system owner
- Up to seven stakeholder sessions and 12 final KPIs
- Up to three standard data sources and one scorecard or dashboard
- One management summary and up to three supporting views
- Thresholds, exceptions, actions, decisions, agenda, and escalation
- Optional AI narrative proof of concept with verification and approval
- UAT support, training, SOP, handover, 45-day stabilization, and final readout
Main output: A controlled performance-review system and operating routine.
Scope note: Final scope and price depend on data condition, source systems, connectors, volume, transformations, security, row-level security, licensing, refresh, KPI complexity, AI approval, validation, users, cadences, deployment, and client availability.
Request the System BuildManaged Review Support
Starting at CAD $1,500 per month
Three-month minimum after an approved implementation or readiness review
For clients strengthening one approved monthly review rhythm through KPI-health checks, pack preparation, action follow-through, facilitation support, and a controlled improvement backlog.
- One approved review system and monthly cadence
- KPI refresh-health and data-quality check
- Draft exception and optional AI-assisted narrative support
- Human verification before client use
- Action-register and overdue-action health check
- One preparation session and one facilitation or coaching session
- Up to two hours of minor advisory or configuration support
- Monthly backlog and quarterly system-health summary after three months
Boundary: Pragy Consulting does not make client decisions or certify metric accuracy. Major changes, new integrations, frequent reporting, or extensive analysis are separately scoped.
Inquiry only. No subscription checkout or recurring billing is active.
Discuss Managed Review SupportEnterprise, Multi-Site, or Complex Review System
Custom scope
Timeline confirmed after qualification, data, security, and architecture review
For multiple sites, cadences, scorecards, languages, regulated needs, complex security, extensive data engineering, custom integration, or sensitive-data processing.
Custom-scope triggers
- More than 12 KPIs or three sources
- Multiple business units, sites, or review cadences
- Data warehouse, lakehouse, Fabric, semantic model, or large migration
- Complex row-level security, identity, custom APIs, or ERP modification
- Regulated, validated, quality-critical, multilingual, or high-availability scope
- Large user population, on-site delivery, major change management, or custom AI
Main output: A separately approved architecture, scope, delivery model, controls, and acceptance plan.
Discuss Enterprise ScopeGood fit
The strongest review system has decisions, owners, and usable data.
Strong fit
- Business area can be defined
- Sponsor and system owner are available
- Review has a clear purpose
- Candidate KPIs exist
- Metric owners can participate
- Data sources are known
- Leaders will make decisions through the review
- Actions and escalation can be assigned
- Users can support testing
- Organization can approve access and deployment
Scope review required
- Request is only "build a dashboard"
- No decisions or review purpose are defined
- No metric owner exists
- Definitions are disputed
- Source data is unavailable
- Multiple sites or business units are bundled
- A data warehouse must be built
- Complex security or regulated validation may be required
- Organization expects autonomous AI conclusions
- Confidential data is expected through the website
- No one can approve metric definitions
Need to improve the underlying workflow first? Explore the Workflow Intelligence Sprint.
Where this fits
Assess the opportunity, improve the workflow, then sustain the operating result.
Organizations may enter at the stage that matches their current readiness.
Why Pragy Consulting
Connect operational discipline, data, technology, and management routines.
Pragy Consulting combines operational excellence, Lean Six Sigma, Power BI, process automation, change management, project governance, and practical AI-in-operations thinking.
The system is designed around the decisions and operating behaviors the organization needs - not around a dashboard template or an AI feature.
Delivered by the Pragy Consulting Founding Team
- KPI and process discipline
- Power BI and data capability
- Management-review and action design
- Human accountability, adoption, and sustainment
Illustrative sample
Preview a complete monthly operations review pack.
Review a fictional performance pack showing KPI definitions, scorecard status, trends, exceptions, actions, decisions, risks, and a human-reviewed narrative workflow.
View the Sample Review Pack
QUALITY OPERATING SYSTEM
Explore the Quality AcceleratorNeed a quality-focused operating system?
The Quality & CAPA Intelligence Accelerator connects quality metrics, CAPA aging, recurrence candidates, data quality, authorized review, actions, effectiveness evidence and management-review preparation around one bounded quality domain.
AI narrative readiness
Explore AI Fluency for Operations LeadersBuild AI fluency before adding AI-assisted review narratives.
Pragy AI Fluency for Operations Leaders helps leaders understand the difference between metrics, summaries, signals, decisions, human approval, manual fallback and responsible pilot measures before AI-assisted reporting is considered.
FAQ
Questions about the Operations Review System
Is this only a Power BI dashboard project?
No. A dashboard is one valuable component. The engagement also defines KPI governance, thresholds, review cadence, decision rights, actions, escalation, ownership, training, and sustainment.
Do we need Power BI?
No. The reporting layer depends on the approved environment and operating need. Existing tools or another suitable platform may be used. Power BI is not mandatory and no vendor endorsement is implied.
Does the system require AI?
No. AI is optional. The system must remain usable, auditable, and accountable when AI is turned off. Standard process, reporting, and review controls provide the foundational value.
What does the starting price include?
The starting price covers the standard bounded System Build described on this page. Final scope and price depend on data, systems, connectors, security, licensing, KPI complexity, users, validation, deployment, and client availability.
Can you use our existing dashboard?
Potentially. The fit and readiness review determines whether the existing dashboard, data model, definitions, and controls can support the required review system or need scoped changes.
What data is required?
The engagement needs approved KPI definitions, representative data context, source and refresh information, known quality limitations, ownership, and secure access arrangements appropriate to the approved scope.
Should confidential data be submitted through the website?
No. Do not submit passwords, credentials, personal data, patient information, regulated records, or confidential production information through the inquiry form.
Can this be used in regulated environments?
Potentially, but regulated, validated, quality-critical, or sensitive-data scope requires additional review and custom scoping. Standard packages do not include legal advice, compliance certification, or computer-system validation.
Who approves the AI-generated summary?
An accountable person verifies the metrics and statements, makes any edits, and approves the narrative before distribution. The AI output remains a clearly labelled draft until that approval is recorded.
Are software licenses included?
No. Platform, connector, hosting, AI-service, or third-party license fees are excluded unless explicitly included in an approved scope.
What is Managed Review Support?
It is inquiry-only support for one approved review system and one primary monthly cadence, including review-pack preparation support, KPI-health checks, action follow-through, facilitation support, and a controlled improvement backlog.
Is recurring billing available?
No. Managed Review Support is contracted through an approved proposal or retainer agreement. No subscription checkout or recurring billing is active.
Are results guaranteed?
No. Outcomes depend on definitions, data, participation, technology, operating behavior, adoption, controls, and client decisions. No specific financial or performance result is guaranteed.
What happens after implementation?
The client may operate the system internally, stabilize or scale it, add a separately scoped review routine, request Managed Review Support, or expand the data, workflow, or improvement roadmap.
From reporting to operating rhythm
Build a management-review system people can use to act.
Request the Pragy AI-Enabled Operations Review System to define trusted KPIs, make exceptions visible, structure the review, assign actions, and support accountable follow-through.
info@pragyconsulting.com · +1 (514) 404-5435
Inquiry and qualification
Request the AI-Enabled Operations Review System
Tell us about the review, KPIs, data, reporting effort, and decisions your organization needs to improve. Do not submit passwords, credentials, personal data, patient information, regulated records, or confidential production data through this form.
Use a fit call to clarify the review purpose, KPI scope, data sources, current reporting effort, decision needs, and whether a Blueprint, System Build, Managed Support, or custom engagement is appropriate. Book an Operations Review Fit Call.
Information is used only to review and respond to this request. Do not submit credentials, confidential production information, regulated records, patient information, or personal data.