vault backup: 2026-08-04 16:51:01
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**Date:** 2026-07-22
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**Status:** 💡 Idea
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## The Idea
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Create a formal framework connecting the organization's strategic pillars and objectives to measurable indicators of success.
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The organization already has:
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1. Strategic pillars
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2. Strategic objectives
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3. Large amounts of operational and audience data
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What appears to be missing is the layer connecting strategy to measurement:
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Strategic Objective
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→ Definition of Success
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→ KPI
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→ Target
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→ Supporting Metrics
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→ Data Source
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→ Business Owner
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→ Reporting / Analysis
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The objective is not to have Data & Analytics independently decide what the company's KPIs are.
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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.
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## Problem / Opportunity
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The organization has five strategic pillars:
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1. Offer content reflecting communities and their reality
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2. Become the educational reference for Francophones in minority contexts
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3. Build a technological and operational ecosystem supporting a digital-first model
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4. Become an employer of choice
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5. Diversify revenue sources to ensure sustainability
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There are also strategic objectives under each pillar.
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However, many of the objectives are directional rather than directly measurable.
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Examples:
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- "Devenir la référence éducative"
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- "Adapter nos contenus aux besoins du public"
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- "Optimiser notre écosystème technologique"
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- "Être un employeur de choix"
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- "Diversifier les sources de revenus"
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These are valid strategic directions, but they do not by themselves answer:
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> How will we know whether we succeeded?
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A recent example exposed this gap.
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A cross-platform video analytics report was created using data from several platforms.
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When the VP Technology saw the report, one of his first questions was:
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> "What are the KPIs?"
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At the time, I interpreted the question as asking which metrics were available.
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In retrospect, the more important question was:
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> Which of these measures tell us whether the organization is succeeding?
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The report solved the data availability problem.
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It did not solve the strategic measurement problem.
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## Why It Matters
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Without clearly defined KPIs:
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- Reports can contain many numbers without showing whether the organization is succeeding.
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- Departments may select different metrics to describe success.
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- A department may emphasize numbers that make its performance look favourable.
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- Leadership cannot easily compare actual results against strategic objectives.
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- Different analysts may interpret success differently.
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- Strategic plans can become difficult to evaluate objectively.
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- Data exists without necessarily supporting decisions.
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A KPI framework would connect strategy directly to measurement.
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Instead of leadership seeing:
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> 1.4M views
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leadership should eventually be able to understand:
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> Our objective is X.
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>
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> We measure success using Y.
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>
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> Our target is Z.
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>
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> Current performance is A.
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>
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> These supporting metrics explain why.
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## Who Benefits?
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- CEO
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- Executive leadership
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- Content leadership
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- News
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- Education
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- Marketing
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- Technology
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- HR
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- Finance
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- Data & Analytics
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- Other business units
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## Possible Approach
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### 1. Start With Strategy, Not Data
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Do not begin by asking:
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> What metrics do we have?
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Begin with:
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> What are we trying to accomplish?
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Then:
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> What does success look like?
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Only then determine the appropriate KPI.
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Example:
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Strategic objective:
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Increase the relevance and consumption of our content.
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Definition of success:
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More members of our target audience consume and return to our content.
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Candidate KPI:
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Viewing hours
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Target:
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To be determined by leadership/business owner
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Supporting metrics:
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- Reach
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- Starts
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- Completion rate
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- Average viewing time
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- Returning audience
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- Platform
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- Content type
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### 2. Distinguish Metrics From KPIs
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A metric measures something.
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A KPI measures something specifically selected to indicate whether an important objective is succeeding.
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Example:
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Views = metric
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If the organization's objective is to increase digital content consumption and leadership agrees that viewing hours represents success:
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Viewing Hours = KPI
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A report may contain dozens of metrics while leadership only needs a small number of KPIs.
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### 3. Distinguish KPI From Target
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KPI:
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Monthly Active Educators
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Target:
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Increase Monthly Active Educators by 15% YoY
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The target determines the desired performance.
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The KPI determines what is being measured.
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### 4. Establish Ownership
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Data & Analytics should not independently decide what success means for every department.
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The appropriate business domain should participate in defining success.
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Examples:
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Education owns the business context of Education.
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News owns the business context of News.
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HR owns HR definitions.
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Finance owns financial definitions.
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Marketing owns Marketing's business context.
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Data & Analytics should facilitate the measurement framework and ensure that:
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- definitions are documented
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- calculations are consistent
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- sources are known
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- data quality is understood
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- historical information is preserved
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- reports use the same definition
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- authorized departments can access the information
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Business ownership does not automatically mean exclusive control over reporting or distribution.
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### 5. Interpretation Model
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The desired model is collaborative.
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Data & Analytics / embedded partner:
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- What happened?
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- Where did it happen?
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- What changed?
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- Are there patterns?
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- Is the data reliable?
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- Which segments/platforms/content explain the change?
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Business department + embedded Data partner:
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- Why did it happen?
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- What operational/business factors contributed?
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Business leadership:
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- Is the result acceptable?
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- What should be done about it?
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The dedicated team members assigned to departments should develop enough domain expertise to interpret performance with those departments.
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Marketing should not automatically become the interpretation layer for News, Education or other business domains.
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### 6. Candidate KPI Framework
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These are candidates for discussion, not official KPIs.
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#### Pillar 1: Content / Communities
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Strategic questions:
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- Are we reaching our target communities?
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- Are people consuming our content?
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- Are they returning?
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- Does the content actually represent the communities named in the strategy?
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Candidate KPIs:
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- Audience reach
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- Viewing hours
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- Returning audience rate
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- Audience growth
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Supporting metrics:
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- Views
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- Starts
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- Average viewing time
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- Completion rate
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- Platform
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- Content category
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- Geography
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Available sources:
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- YouTube
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- JW Player
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- Roku
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- Apple TV
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- Amazon Fire TV
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- GA4
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- Numeris
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- Numeris ETAM
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Important gap:
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Digital analytics can show what people consume.
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It cannot by itself prove that content reflects the needs and realities of Francophone minority communities.
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Other research, survey or qualitative measures may be required.
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#### Pillar 2: Education
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Strategic questions:
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- Are we becoming more widely used by educators?
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- Are educators returning?
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- Are we expanding outside existing markets?
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- Are educational resources actually being consumed?
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Candidate KPIs:
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- Active educators
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- Returning educator rate
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- Educational resource consumption
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- Geographic adoption
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- Growth outside Ontario
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Sources:
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- Drupal API
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- GA4
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#### Pillar 3: Digital-First Transformation
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Strategic questions:
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- Is more consumption occurring digitally?
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- Are our digital services reliable?
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- Are technology operations improving?
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- Are we delivering strategic projects effectively?
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Candidate KPIs:
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- Digital audience / consumption
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- Platform adoption
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- Service availability
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- SLA attainment
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- Strategic project delivery rate
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Supporting metrics:
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- Jira tickets
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- SLA breaches
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- Incident counts
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- Sentry errors
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- Uptime
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- Project delivery
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- Resolution time
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Sources:
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- Jira
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- Sentry
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- Uptime monitoring
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- GA4
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- JW
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- OTT platforms
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- YouTube
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#### Pillar 4: Employer of Choice
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Strategic questions:
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- Are we retaining employees?
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- Are employees voluntarily leaving?
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- Is the organization able to attract and retain talent?
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Candidate KPIs:
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- Employee retention
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- Voluntary turnover
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- Headcount evolution
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- Employee engagement if available
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Sources:
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- Dayforce
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Potential supporting data:
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- Employee counts
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- Departures
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- Leaves
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- Hiring
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- Tenure
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HR should own the business definitions while Data & Analytics supports consistent measurement.
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#### Pillar 5: Revenue Diversification
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Strategic questions:
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- Are revenues increasing?
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- Are revenues becoming more diversified?
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- Is the organization less dependent on a small number of sources?
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Candidate KPIs:
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- Revenue by source
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- Revenue growth
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- % of revenue by source
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- % of revenue from new/non-core sources
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- Advertising revenue
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- Commercial revenue
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- Philanthropic revenue
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- Revenue outside Ontario
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Sources:
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- Finance
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Current gap:
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Data & Analytics currently has limited financial data.
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The first step should be a conversation with Finance about how they currently measure revenue diversification.
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### 7. Current Data Inventory
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#### Video / Streaming
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- YouTube
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- JW Player
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- Roku
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- Apple TV
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- Amazon Fire TV
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#### Websites
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- GA4
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- Umami planned
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- Main website
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- News website
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- Education website
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#### Education
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- Drupal
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- API access available
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#### Linear TV
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- Numeris
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- Numeris ETAM upcoming
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#### HR
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- Dayforce
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- Employee retention
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- Employee counts
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- Leaves
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#### IT / Technology
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- Jira
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- Sentry
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- Uptime monitoring
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- Tickets
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- SLA
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- Project information
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#### Finance
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Limited current integration.
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Requires discussion with Finance.
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#### Marketing
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Marketing currently manages its own reporting environment, including Google Looker.
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This creates a broader question around:
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- organizational ownership of historical data
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- long-term retention
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- shared definitions
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- integration with company-wide analytics
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The governance question should not initially be whether a specific tool should be eliminated.
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The requirement should be:
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> Strategic KPI history must be retained for sufficient time to evaluate long-term organizational performance.
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Technology decisions should follow that requirement.
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## Effort
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**Estimated complexity:** High
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The technical work is achievable.
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The more difficult work involves:
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- agreeing on definitions
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- establishing business ownership
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- obtaining executive sponsorship
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- aligning departments
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- creating targets
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- changing the organization's data culture
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- avoiding information silos
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- establishing the mandate of Data & Analytics
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This should therefore be implemented incrementally.
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## Risks / Questions
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- There is currently no clear organization-wide KPI framework.
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- Departments may define success differently.
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- Departments may resist measurement when results are unfavourable.
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- Marketing currently has strong influence with executive leadership.
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- Marketing is building its own analytical capability.
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- HR and Finance may be hesitant to expose data outside their departments.
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- Business ownership may be confused with exclusive control of data and reporting.
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- Data & Analytics does not yet appear to have a formal enterprise-wide governance mandate.
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- Targets do not appear to be clearly defined for many strategic objectives.
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- Some strategic objectives cannot be measured using digital analytics alone.
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- Cross-platform unique audience measurement may be difficult because users cannot necessarily be deduplicated across platforms.
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- Who ultimately approves corporate KPIs?
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- Who resolves disagreements between departments?
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- How much historical data should be retained for strategic measurement?
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## Next Step
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Use the existing Content and Education strategy as the first pilot.
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Rather than proposing an organization-wide KPI framework immediately, discuss with the VP Content:
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> How do we currently know whether the Content and Education strategic objectives are succeeding?
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Use the discussion to identify:
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1. What success means
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2. Which measures demonstrate success
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3. Who owns the definitions
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4. Which data is currently available
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5. What data is missing
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6. Which targets should eventually be established
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Then discuss the broader framework with the VP Technology, using his previous KPI question as the starting point.
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If leadership sees value in the approach, expand the framework to:
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HR → Finance → IT → other business domains.
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## Related
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- [[Organizational Data & Analytics Operating Model]]
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- [[Data Governance]]
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- [[Data Quality]]
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- [[Data Lineage]]
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- [[Semantic Layer]]
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- [[Business Glossary]]
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- [[KPI]]
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- [[Data Owner]]
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- [[Data Steward]]
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- [[Self-Service Analytics]]
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- [[Data Culture]]
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- [[CTO]]
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## Update - 2026-07-27
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Discussed the concept with CTO.
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The organization currently has many metrics and reports, but we have not consistently defined which KPIs demonstrate whether strategic objectives are being achieved.
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CTO agrees that this is worth pursuing.
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### Approach
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This needs to be handled carefully because KPI definition touches organizational priorities and executive accountability.
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Rather than immediately proposing a new KPI framework, prepare a presentation that:
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1. Demonstrates the distinction between metrics and strategic KPIs.
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2. Shows the current gap using concrete examples.
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3. Connects KPIs to existing strategic objectives.
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4. Proposes an approach for defining them collaboratively.
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### Next Step
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- [ ] Prepare presentation for discussion after CTO returns from vacation.
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Reference in New Issue
Block a user