Martech Day 2
ARCHITECTURE, INTELLIGENCE & TRANSFORMATION
09:00 - 11:00
Block 4 - Built to Adapt: Stack Strategy & Integration
09:00 - 09:30
PANEL
Martech stacks look modern on paper, but integration, ownership and architectural discipline still decide what they can really deliver
- Assessing how today’s Martech stacks appear advanced from the outside, yet still depend on integration quality and architectural choices behind the scenes.
- Identifying where unclear ownership, inconsistent data flows and legacy dependencies slow down the stack and limit what teams can actually execute.
- Aligning architecture, governance and business goals in one stack strategy, so Martech evolves as a scalable capability rather than a collection of disconnected tools.
09:30 - 09:50
Composable Martech sounds simple in theory, but real architecture depends on how data and systems actually work together
- Unpacking how composable and modular architecture patterns only create value when they connect cleanly through shared data and consistent integration logic.
- Highlighting where mismatched data models, unclear handoffs and legacy system behaviour undermine even the best-designed stack diagrams.
- Structuring architecture patterns, integration rules and data flows into one coherent approach, so the stack becomes adaptable in practice - not just on paper.
09:50 - 10:10
True stack scalability starts with identity and data models that work across every channel, not just inside individual tools
- Structuring how identity resolution, profile stitching and shared data models form the base layer that every Martech capability depends on.
- Pinpointing where inconsistent schemas, overlapping identifiers and channel-specific data logic break the path to a unified customer view.
- Aligning identity rules, data standards and cross-channel models into one foundation, so the stack becomes scalable, consistent and ready for future growth.
10:10 - 10:40
PANEL
Composable stacks promise flexibility, but they collapse quickly when ownership, governance and ways of working don’t keep pace
- Aligning stack ambition with the governance, ownership and cross-team coordination needed to make a modular architecture work in practice.
- Surfacing where siloed decision-making, mismatched priorities and legacy ways of working limit what even the best-designed stack can deliver.
- Linking operating models, architectural discipline and shared accountability in one approach, so the stack performs as a coherent system rather than a set of disconnected tools.
10.40 - 11:00
Coffee Break
11:00 - 13:00
Block 5 - From Data to Insight: Intelligence Engines in Action
11:00 - 11:30
PANEL
Data and dashboards keep multiplying, yet shared truth and decision-quality insight remain stubbornly out of reach
- Analyzing why more data and more dashboards do not automatically create clearer insight or better decisions for retailers and FMCG.
- Revealing where fragmented logic, inconsistent metrics and disconnected data sources block teams from building a single version of the truth.
- Synthesizing data sources, shared definitions and decision logic into one intelligence engine, so teams can act with confidence instead of reconciling competing reports.
11:30 - 11:50
Intelligence engines only add value when they reduce noise and embed decision logic teams can trust
- Revealing how intelligence engines need to reduce data noise and surface only the signals that matter for real business decisions.
- Highlighting where unclear decision rules, mixed modelling approaches and tool-specific logic stop insight from becoming actionable.
- Combining signal filtering, shared decision logic and transparent model behaviour in one intelligence layer, so teams can act with clarity rather than interpreting competing outputs.
11:50 - 12:10
Insight turns unreliable when measurement frameworks and AI models drift apart - calibration keeps them aligned and actionable
- Calibrating how measurement logic and model behaviour need to stay aligned, so insight remains consistent across campaigns, channels and customer journeys.
- Revealing where KPI conflicts, model drift and inconsistent scoring make intelligence engines difficult to trust or scale.
- Integrating measurement standards, model governance and recalibration routines in one reliability layer, so teams can act with confidence instead of questioning every output.
12:10- 12:30
Predictive models create powerful signals, but the real challenge is turning their outputs into decisions teams can use at scale
- Interpreting how predictive signals should guide decisions across campaigns, journeys and operations without overwhelming teams with model complexity.
- Revealing where unclear model outputs, inconsistent confidence levels and limited explainability make predictions difficult to trust or operationalise.
- Synthesizing predictive insights, decision rules and operational context in one practical framework, so teams can apply predictions consistently across the business.
12:30 - 13:00
PANEL
Intelligence engines produce more insight than ever, but turning that insight into real decisions remains the hardest part
- Synthesizing data, models and business context into decisions teams can understand, trust and act on at the right moment.
- Highlighting where unclear ownership, competing priorities and fragmented decision routines stop insight from shaping everyday actions.
- Bringing decision frameworks, shared accountability and repeatable insight-to-action paths together into one operating approach that makes intelligence a real organisational capability.
13:00 - 14:00
Lunch Break
14:00 - 16:00
Block 6 - Talent, Teams & Transformation
14:00 - 14:30
PANEL
Martech capabilities evolve fast, but teams and ways of working often change far more slowly
- Examining how rapidly expanding Martech capabilities outpace the skills, roles and working patterns inside many retail and FMCG organisations.
- Surfacing where tight timelines, shifting priorities and talent gaps make it hard for teams to absorb change and deliver results at the speed leaders expect.
- Connecting skills, operating models and learning routines in one capability approach, helping organisations keep pace with technology instead of reacting to it.
14:30 - 15:00
PANEL
Roles and capabilities change quickly, but ownership and job definitions often remain stuck in older models
- Redefining how modern Martech, data and product roles should work together, beyond the outdated job descriptions many organisations still rely on.
- Surfacing where unclear ownership, overlapping responsibilities and legacy expectations slow down how teams coordinate and deliver.
- Bringing role clarity, shared responsibility and cross-functional collaboration into one capability model that helps teams move with the pace of technology.
15:00 - 15:30
PANEL
Fast, cross-team flow is becoming critical, as old decision habits still slow how Martech work gets done
- Navigating how Martech, data, product and commercial teams can work together at the pace required by modern customer and business expectations.
- Highlighting where legacy decision cycles, slow approvals and function-by-function workflows block the flow of ideas, insight and execution.
- Bringing shared priorities, faster governance and cross-team rhythms into one operating approach that helps teams move with the speed Martech demands.
15:30-16:00
PANEL
Leadership expectations keep rising, while future-ready Martech teams still require continuous capability building, not one-off transformation bursts
- Building future-ready Martech teams that can learn continuously, adapt quickly and operate confidently in environments where change never slows down.
- Highlighting where episodic transformation, inconsistent team development and unclear long-term capability plans leave organisations unprepared for what leaders expect next.
- Connecting capability roadmaps, modern learning routines and cross-functional team structures into one sustained development approach that supports transformation year after year.
- Supply Chain Plenary Stage
- Sustainable Supply Chain & Operations Stage
- eRetail & Omnichannel Logistics Stage
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