Analytics Operating Models: Designing Teams That Turn Data Into Decisions

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Overview: Most organizations have more data, dashboards and analytical capabilities than ever before. Yet analytics leaders frequently face the same challenge: how do you organize people, priorities and processes so that analytics actually changes business decisions? The answer rarely lies in another technology platform. This masterclass explores how leaders can design analytics organizations around the decisions their businesses need to make. Participants will examine different organizational models, from centralized teams to embedded analysts and federated hub-and-spoke structures and discuss when each works, where they fail and how they evolve as organizations mature. Through practical frameworks, peer discussion and a live organizational-design case study, participants will explore how to define the mandate of analytics, select and prioritize use cases, establish clear decision rights, build effective business partnerships, measure the value of analytics and prepare teams for an increasingly AI-enabled future. Matz Lukmani Matz Lukmani based in London (UK) has worked with Google for the past +11 years on product Go-to-Market for products like Google Analytics 360, Google Ads, Search Ads 360, Firebase Analytics and YouTube Ads focusing on brands based in Europe, Middle East and Africa Markets. Previously Matz worked over 10 years in the USA in various Analytics leadership roles at SAP, Bristol-Myers Squibb, Toys R Us, MediaCom, Triad Retail Media and PricewaterhouseCoopers to name a few. He offers consulting and education in the field of web and marketing analytics and advanced marketing AI applications across a wide group of industries. In this masterclass, you will learn: The Analytics Value Landscape: Understand the broad range of jobs analytics can perform across marketing, customer, product, finance, operations and strategy — and identify where your organization is over- or under-investing.Analytics Organization Models: Compare centralized, decentralized/embedded and federated hub-and-spoke structures and understand the trade-offs of each.Analytics Operating Model: Go beyond the org chart and design the mandate, roles, decision rights, engagement model, governance and operating cadence of an analytics function. Move away from “who shouted loudest?” analytics and establish a structured way to evaluate competing analytical requests.Analytics → Decision Translation: Design ways of working that move analysts from producing reports toward influencing real business decisions.AI-Era Analytics Leadership: Explore how AI and agents are changing analyst roles, self-service, governance and the relationship between centralized and distributed analytics teams.Measuring Analytics Itself: Replace dashboard counts and query volumes with measures of adoption, decision velocity, business impact, trust and organizational capability.Designed for: Key roles: Heads / Directors / Managers of AnalyticsHeads of Insights or Business IntelligenceMarketing Analytics LeadersDigital / E-commerce Analytics LeadersProduct Analytics LeadersData Strategy & Transformation Leads Company type:Consumer brands and retailersFinancial servicesB2B businessesDigital-first / SaaS companiesAgencies and consultanciesHealthcare / pharmaceutical organizationsLarge multinational enterprisesScale-ups building their first formal analytics organization Experience level: Mid-to-senior analytics professionals, particularly responsible for leading analytics teams, and defining how analytics should work alongside Brand Marketing, Product, Finance and Technology.Session Structure Main Focus Areas: The Analytics Value Landscape:Explore the broad range of analytics use cases across Marketing, Customer, Product, Commercial, Finance and Operations. Understand how analytics teams can evolve from reporting on the past to influencing future business decisions. Analytics Organization Models:Compare centralized, embedded and federated / hub-and-spoke analytics structures. Explore the strengths, trade-offs and organizational conditions that make different models successful. Go beyond the org chart to explore practical frameworks for defining analytics mandates, roles, decision rights, stakeholder engagement and governance. From Analytics Service Desk to Decision Partner: Explore analytics maturity and how teams can move from reactive reporting toward strategic decision support. Discuss approaches for prioritizing analytics use cases, managing competing demand and measuring the impact of the analytics function itself. Analytics Leadership in the AI Era: Explore emerging trends reshaping analytics organizations, including AI-assisted analysis, self-service analytics and changing analyst roles.

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