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**Date:** 2026-07-22
**Status:** 💡 Idea
## The Idea
Create a formal framework connecting the organization's strategic pillars and objectives to measurable indicators of success.
The organization already has:
1. Strategic pillars
2. Strategic objectives
3. Large amounts of operational and audience data
What appears to be missing is the layer connecting strategy to measurement:
Strategic Objective
→ Definition of Success
→ KPI
→ Target
→ Supporting Metrics
→ Data Source
→ Business Owner
→ Reporting / Analysis
The objective is not to have Data & Analytics independently decide what the company's KPIs are.
The objective is to establish a process where business owners and leadership define what success means, while Data & Analytics ensures those definitions can be measured consistently, reliably and transparently.
## Problem / Opportunity
The organization has five strategic pillars:
1. Offer content reflecting communities and their reality
2. Become the educational reference for Francophones in minority contexts
3. Build a technological and operational ecosystem supporting a digital-first model
4. Become an employer of choice
5. Diversify revenue sources to ensure sustainability
There are also strategic objectives under each pillar.
However, many of the objectives are directional rather than directly measurable.
Examples:
- "Devenir la référence éducative"
- "Adapter nos contenus aux besoins du public"
- "Optimiser notre écosystème technologique"
- "Être un employeur de choix"
- "Diversifier les sources de revenus"
These are valid strategic directions, but they do not by themselves answer:
> How will we know whether we succeeded?
A recent example exposed this gap.
A cross-platform video analytics report was created using data from several platforms.
When the VP Technology saw the report, one of his first questions was:
> "What are the KPIs?"
At the time, I interpreted the question as asking which metrics were available.
In retrospect, the more important question was:
> Which of these measures tell us whether the organization is succeeding?
The report solved the data availability problem.
It did not solve the strategic measurement problem.
## Why It Matters
Without clearly defined KPIs:
- Reports can contain many numbers without showing whether the organization is succeeding.
- Departments may select different metrics to describe success.
- A department may emphasize numbers that make its performance look favourable.
- Leadership cannot easily compare actual results against strategic objectives.
- Different analysts may interpret success differently.
- Strategic plans can become difficult to evaluate objectively.
- Data exists without necessarily supporting decisions.
A KPI framework would connect strategy directly to measurement.
Instead of leadership seeing:
> 1.4M views
leadership should eventually be able to understand:
> Our objective is X.
>
> We measure success using Y.
>
> Our target is Z.
>
> Current performance is A.
>
> These supporting metrics explain why.
## Who Benefits?
- CEO
- Executive leadership
- Content leadership
- News
- Education
- Marketing
- Technology
- HR
- Finance
- Data & Analytics
- Other business units
## Possible Approach
### 1. Start With Strategy, Not Data
Do not begin by asking:
> What metrics do we have?
Begin with:
> What are we trying to accomplish?
Then:
> What does success look like?
Only then determine the appropriate KPI.
Example:
Strategic objective:
Increase the relevance and consumption of our content.
Definition of success:
More members of our target audience consume and return to our content.
Candidate KPI:
Viewing hours
Target:
To be determined by leadership/business owner
Supporting metrics:
- Reach
- Starts
- Completion rate
- Average viewing time
- Returning audience
- Platform
- Content type
### 2. Distinguish Metrics From KPIs
A metric measures something.
A KPI measures something specifically selected to indicate whether an important objective is succeeding.
Example:
Views = metric
If the organization's objective is to increase digital content consumption and leadership agrees that viewing hours represents success:
Viewing Hours = KPI
A report may contain dozens of metrics while leadership only needs a small number of KPIs.
### 3. Distinguish KPI From Target
KPI:
Monthly Active Educators
Target:
Increase Monthly Active Educators by 15% YoY
The target determines the desired performance.
The KPI determines what is being measured.
### 4. Establish Ownership
Data & Analytics should not independently decide what success means for every department.
The appropriate business domain should participate in defining success.
Examples:
Education owns the business context of Education.
News owns the business context of News.
HR owns HR definitions.
Finance owns financial definitions.
Marketing owns Marketing's business context.
Data & Analytics should facilitate the measurement framework and ensure that:
- definitions are documented
- calculations are consistent
- sources are known
- data quality is understood
- historical information is preserved
- reports use the same definition
- authorized departments can access the information
Business ownership does not automatically mean exclusive control over reporting or distribution.
### 5. Interpretation Model
The desired model is collaborative.
Data & Analytics / embedded partner:
- What happened?
- Where did it happen?
- What changed?
- Are there patterns?
- Is the data reliable?
- Which segments/platforms/content explain the change?
Business department + embedded Data partner:
- Why did it happen?
- What operational/business factors contributed?
Business leadership:
- Is the result acceptable?
- What should be done about it?
The dedicated team members assigned to departments should develop enough domain expertise to interpret performance with those departments.
Marketing should not automatically become the interpretation layer for News, Education or other business domains.
### 6. Candidate KPI Framework
These are candidates for discussion, not official KPIs.
#### Pillar 1: Content / Communities
Strategic questions:
- Are we reaching our target communities?
- Are people consuming our content?
- Are they returning?
- Does the content actually represent the communities named in the strategy?
Candidate KPIs:
- Audience reach
- Viewing hours
- Returning audience rate
- Audience growth
Supporting metrics:
- Views
- Starts
- Average viewing time
- Completion rate
- Platform
- Content category
- Geography
Available sources:
- YouTube
- JW Player
- Roku
- Apple TV
- Amazon Fire TV
- GA4
- Numeris
- Numeris ETAM
Important gap:
Digital analytics can show what people consume.
It cannot by itself prove that content reflects the needs and realities of Francophone minority communities.
Other research, survey or qualitative measures may be required.
#### Pillar 2: Education
Strategic questions:
- Are we becoming more widely used by educators?
- Are educators returning?
- Are we expanding outside existing markets?
- Are educational resources actually being consumed?
Candidate KPIs:
- Active educators
- Returning educator rate
- Educational resource consumption
- Geographic adoption
- Growth outside Ontario
Sources:
- Drupal API
- GA4
#### Pillar 3: Digital-First Transformation
Strategic questions:
- Is more consumption occurring digitally?
- Are our digital services reliable?
- Are technology operations improving?
- Are we delivering strategic projects effectively?
Candidate KPIs:
- Digital audience / consumption
- Platform adoption
- Service availability
- SLA attainment
- Strategic project delivery rate
Supporting metrics:
- Jira tickets
- SLA breaches
- Incident counts
- Sentry errors
- Uptime
- Project delivery
- Resolution time
Sources:
- Jira
- Sentry
- Uptime monitoring
- GA4
- JW
- OTT platforms
- YouTube
#### Pillar 4: Employer of Choice
Strategic questions:
- Are we retaining employees?
- Are employees voluntarily leaving?
- Is the organization able to attract and retain talent?
Candidate KPIs:
- Employee retention
- Voluntary turnover
- Headcount evolution
- Employee engagement if available
Sources:
- Dayforce
Potential supporting data:
- Employee counts
- Departures
- Leaves
- Hiring
- Tenure
HR should own the business definitions while Data & Analytics supports consistent measurement.
#### Pillar 5: Revenue Diversification
Strategic questions:
- Are revenues increasing?
- Are revenues becoming more diversified?
- Is the organization less dependent on a small number of sources?
Candidate KPIs:
- Revenue by source
- Revenue growth
- % of revenue by source
- % of revenue from new/non-core sources
- Advertising revenue
- Commercial revenue
- Philanthropic revenue
- Revenue outside Ontario
Sources:
- Finance
Current gap:
Data & Analytics currently has limited financial data.
The first step should be a conversation with Finance about how they currently measure revenue diversification.
### 7. Current Data Inventory
#### Video / Streaming
- YouTube
- JW Player
- Roku
- Apple TV
- Amazon Fire TV
#### Websites
- GA4
- Umami planned
- Main website
- News website
- Education website
#### Education
- Drupal
- API access available
#### Linear TV
- Numeris
- Numeris ETAM upcoming
#### HR
- Dayforce
- Employee retention
- Employee counts
- Leaves
#### IT / Technology
- Jira
- Sentry
- Uptime monitoring
- Tickets
- SLA
- Project information
#### Finance
Limited current integration.
Requires discussion with Finance.
#### Marketing
Marketing currently manages its own reporting environment, including Google Looker.
This creates a broader question around:
- organizational ownership of historical data
- long-term retention
- shared definitions
- integration with company-wide analytics
The governance question should not initially be whether a specific tool should be eliminated.
The requirement should be:
> Strategic KPI history must be retained for sufficient time to evaluate long-term organizational performance.
Technology decisions should follow that requirement.
## Effort
**Estimated complexity:** High
The technical work is achievable.
The more difficult work involves:
- agreeing on definitions
- establishing business ownership
- obtaining executive sponsorship
- aligning departments
- creating targets
- changing the organization's data culture
- avoiding information silos
- establishing the mandate of Data & Analytics
This should therefore be implemented incrementally.
## Risks / Questions
- There is currently no clear organization-wide KPI framework.
- Departments may define success differently.
- Departments may resist measurement when results are unfavourable.
- Marketing currently has strong influence with executive leadership.
- Marketing is building its own analytical capability.
- HR and Finance may be hesitant to expose data outside their departments.
- Business ownership may be confused with exclusive control of data and reporting.
- Data & Analytics does not yet appear to have a formal enterprise-wide governance mandate.
- Targets do not appear to be clearly defined for many strategic objectives.
- Some strategic objectives cannot be measured using digital analytics alone.
- Cross-platform unique audience measurement may be difficult because users cannot necessarily be deduplicated across platforms.
- Who ultimately approves corporate KPIs?
- Who resolves disagreements between departments?
- How much historical data should be retained for strategic measurement?
## Next Step
Use the existing Content and Education strategy as the first pilot.
Rather than proposing an organization-wide KPI framework immediately, discuss with the VP Content:
> How do we currently know whether the Content and Education strategic objectives are succeeding?
Use the discussion to identify:
1. What success means
2. Which measures demonstrate success
3. Who owns the definitions
4. Which data is currently available
5. What data is missing
6. Which targets should eventually be established
Then discuss the broader framework with the VP Technology, using his previous KPI question as the starting point.
If leadership sees value in the approach, expand the framework to:
HR → Finance → IT → other business domains.
## Related
- [[Organizational Data & Analytics Operating Model]]
- [[Data Governance]]
- [[Data Quality]]
- [[Data Lineage]]
- [[Semantic Layer]]
- [[Business Glossary]]
- [[KPI]]
- [[Data Owner]]
- [[Data Steward]]
- [[Self-Service Analytics]]
- [[Data Culture]]
- [[CTO]]
## Update - 2026-07-27
Discussed the concept with CTO.
The organization currently has many metrics and reports, but we have not consistently defined which KPIs demonstrate whether strategic objectives are being achieved.
CTO agrees that this is worth pursuing.
### Approach
This needs to be handled carefully because KPI definition touches organizational priorities and executive accountability.
Rather than immediately proposing a new KPI framework, prepare a presentation that:
1. Demonstrates the distinction between metrics and strategic KPIs.
2. Shows the current gap using concrete examples.
3. Connects KPIs to existing strategic objectives.
4. Proposes an approach for defining them collaboratively.
### Next Step
- [ ] Prepare presentation for discussion after CTO returns from vacation.