Sr. Director, Business Intelligence and Analytics

The Senior Director, Business Intelligence and Analytics is a senior enterprise leader responsible for building and leading GS1 Canada’s business intelligence, analytics, and market insight capability. The role gives the organization a clear, trusted, and evidence-based view of strategic performance, subscriber growth and retention, product and service adoption, sector opportunity, and emerging market dynamics.

The role leads a team of analysts and market intelligence professionals who measure organizational performance, identify growth opportunities, assess subscriber and sector trends, and translate data into clear recommendations for senior leadership. The function will move beyond traditional reporting toward predictive, decision-oriented analytics that explain what is happening, why it matters, what is likely to happen next, and where action is required.

A central mandate is to transform the analytics function through the responsible adoption of artificial intelligence. This leader will establish the roadmap, operating model, capabilities, and governance needed to embed AI into analytical workflows; improve the speed, quality, and reach of insight; and equip the team and business leaders to use AI effectively and responsibly.

The role translates GS1 Canada’s enterprise strategy into measurable outcomes, owns the enterprise KPI and performance framework, and ensures executives and business leaders receive timely, consistent, and decision-ready insight. It partners closely with Product, Subscriber Management, Finance, Marketing, Industry Relations, Community Engagement, Technology, Operations, Data Governance, Privacy, Cybersecurity, and the AI Council.

This is a high-impact, enterprise-facing leadership role requiring analytical judgment, strategic thinking, executive communication, change leadership, people development, and

Build and Lead the Business Intelligence and Analytics Function

• Build, lead, and mature GS1 Canada’s business intelligence and analytics capability, including enterprise reporting, subscriber and sector analytics, product and service usage analytics, market intelligence, and growth insights.
• Establish a trusted and consistent single version of the truth by aligning data definitions, metrics, dashboards, and reports across business units
• Lead enterprise dashboards, executive scorecards, and recurring insight products covering subscriber growth, retention, churn, adoption, engagement, service usage, sector penetration, revenue performance, and strategic execution.
• Advance the function from descriptive reporting to diagnostic, predictive, and prescriptive insight that identifies drivers, anticipates risks and opportunities, and recommends action.
• Establish standards for analytical quality, metric definitions, dashboard governance, documentation, reproducibility, and executive communication.
• Partner with Technology, Data Governance, and business teams to improve data accessibility, quality, reliability, and fitness for analytical and AI use.

Lead Subscriber, Sector and Market Intelligence

• Build an integrated intelligence capability that combines subscriber and operational data, sector insight, competitive intelligence, and external market trends.
• Monitor changes in subscriber expectations, digital and agentic commerce, product data management, regulation, sustainability, 2D barcode adoption, AI-enabled data management, and other developments affecting GS1 Canada’s relevance and growth.
• Synthesize quantitative and qualitative signals from sector boards, working groups, subscriber interactions, support channels, research, and industry forums in partnership with relevant business teams.
• Identify enterprise-wide patterns and sector-specific needs, and provide regular executive briefings on market shifts, subscriber expectations, competitors, opportunities, and strategic risks.
• Recommend where insights indicate a need to adjust strategic focus, product priorities, positioning, education, or market engagement.

Own the Enterprise KPI and Measurement Framework

• Define and maintain the enterprise KPI framework, aligned to strategy, subscriber value, growth, adoption, financial performance, and operational outcomes.
• Set consistent definitions and ownership for core measures, including subscriber growth, retention, churn, engagement, adoption, product and service usage, sector penetration, revenue trends, and strategic progress
• Partner with Finance and functional leaders to ensure measures are reliable, decision-useful, and consistently applied across executive, functional, and sector reporting.
• Identify gaps or inconsistencies in measurement and recommend improvements to data, instrumentation, reporting, and accountability.
• Focus leadership attention on the few measures that matter most, connecting activity to subscriber outcomes, growth impact, and strategic value.

Lead the AI-Enabled Transformation of Analytics

• Develop and execute a multi-year roadmap to transform the analytics function through AI, aligned with enterprise strategy, the AI Council, and GS1 Canada’s technology and data priorities.
• Prioritize high-value use cases such as automated data preparation and reporting, insight synthesis, anomaly detection, forecasting, segmentation, churn and propensity analysis, and conversational or self-service analytics.
• Redesign analyst workflows and roles to combine automation with human judgment, enabling the team to spend less time producing reports and more time interpreting results, advising leaders, and driving action.
• Establish a disciplined path from experimentation to production, including use-case intake, value assessment, pilots, validation, adoption planning, controls, and scaling.
• Partner with Technology and Data Governance on approved tools, architecture, secure data access, semantic models, data quality, integration, and production support; retain business ownership of analytical use cases, adoption, and outcomes.
• Partner with the AI Council, Privacy, Legal, Cybersecurity, and Data Governance to ensure appropriate human oversight, transparency, confidentiality, intellectual property protection, bias testing, accuracy, and responsible use
• Build team capability in AI-assisted analysis, prompt and context design, model limitations, validation, documentation, and effective human review.
• Measure transformation value through adoption, time-to-insight, productivity, analytical quality, decision impact, and measurable business outcomes.

Provide Executive and Board-Level Insight

• Prepare executive and Board materials that clearly communicate strategic progress, performance trends, subscriber outcomes, growth opportunities, and emerging risks.
• Translate complex analysis into concise narratives that connect metrics to strategy, market conditions, implications, and decisions required.
• Support executive decision-making by identifying the most important insights, dependencies, risks, options, and recommended actions.
• Serve as a trusted enterprise advisor by providing balanced, objective, transparent, and analytically rigorous insight.

Partner Across the Organization to Enable Insight-Driven Decisions

• Act as a strategic partner to Product, Subscriber Management, Finance, Marketing, Industry Relations, Community Engagement, Technology, Operations, and Data Governance
• Provide Product and Subscriber Management with insight on adoption, usage, lifecycle performance, acquisition, retention, churn, account health, sector performance, and growth potential.
• Support Marketing, Product Marketing, Industry Relations, and Community Engagement with analysis of awareness, engagement, campaign effectiveness, market positioning, sector signals, and subscriber sentiment.
• Align revenue and performance analytics with Finance while preserving Finance’s accountability for budgeting, forecasting, accounting, and financial controls.
• ·Promote a culture in which data, evidence, and insight consistently shape leadership discussions, priorities, and resource decisions.

Build and Lead a High-Performing Analytics Team

• Define the team structure, roles, capabilities, workflows, service model, and operating rhythms required for a modern enterprise analytics function.
• Coach analysts to progress from report production to insight generation, storytelling, analytical judgment, business partnership, and strategic advisory work.
• Set clear objectives and quality standards, manage performance, allocate capacity to the highest-value work, and establish transparent intake and prioritization practices.
• Create a high-performance culture grounded in curiosity, objectivity, experimentation, collaboration, accountability, and subscriber value.
• Develop talent, succession plans, and future-ready skills across business intelligence, analytics, market intelligence, and AI.

• 10+ years of progressive experience in business intelligence, analytics, market intelligence, enterprise performance, strategy, or related business leadership roles.
• Demonstrated experience building or transforming a business intelligence or analytics function, including changes to operating models, processes, tools, and team capabilities.
• Demonstrated experience leading the adoption of AI, machine learning, automation, or advanced analytics in business workflows and taking use cases from pilot to sustained use.
• Experience leading and developing analysts and influencing cross-functional teams in a complex organization.
• Proven ability to translate data and market signals into executive-level insight, decisions, and strategic recommendations.
• Experience developing enterprise KPIs, dashboards, scorecards, performance frameworks, and self-service analytics
• Experience analyzing customer or subscriber behaviour, retention, churn, adoption, engagement, revenue trends, market opportunity, or product and service performance.
• Experience supporting executive leadership and Board-level reporting.

Experience in B2B, data services, SaaS, digital commerce, retail, healthcare, supply chain, standards, or member- or subscriber-based organizations is an asset.

Skills & Capabilities**

• Strong enterprise strategy, business intelligence, analytics, and performance management capability.
• Strong understanding of practical AI applications in analytics, including generative AI, predictive methods, automation, conversational analytics, and human-in-the-loop control
• Demonstrated change leadership and the ability to redesign work, build adoption, develop new capabilities, and realize measurable value from new technology.
• Strong analytical judgment, including the ability to distinguish signal from noise, challenge assumptions, validate outputs, and communicate uncertainty.
• Ability to translate complex data into clear business narratives, executive-ready insights, and actionable recommendations.
• Strong understanding of subscriber or customer analytics, including segmentation, adoption, engagement, retention, churn, lifetime value, and market opportunity.
• Strong people leadership with the ability to elevate the quality, relevance, efficiency, and strategic impact of team outputs.
• Strong executive communication skills, including Board-level writing, presentation, data storytelling, and facilitation
• Strong cross-functional collaboration and influence without direct authority.
• Sound understanding of data governance, privacy, security, responsible AI, metric consistency, reporting standards, and analytical quality control.
• Ability to build structure