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Defeating the Multi-Channel Silo Challenge
Matt Wright, Hewlett-Packard Enterprise
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Matthew WrightHewlett-Packard Enterprises - Analytics Strategy
• Internal Analytics & Intelligence Consultant with HPe• Work with different teams to establish digital measurement
strategy, including customer intelligence and online behavioral research, measurement strategy, and analytics operations strategy
• Intimately familiar with digital data operations – which includes TMS & Audience identification solutions
Headshot Here
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What is a Silo, Anyway?
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How do Data Silos Form in Organizations?
Systems Follow Org Structures• Data is typically used by "Users"• Users are defined by
organizational structures with different measures of success
• Use cases reflect user requirements
• The more concentrated the use by certain user groups, the more likely the data is modified / shaped / organized to reflect those use cases
RESULT:• Data that is largely setup for one
use• Difficult to allocate to other uses
Positive ViewCorporate "Scarcity" Model• Every organization is subject to
scarcity and limited resources• Use of data by other teams
constitutes • At best a consumption of a
direct resource, • At worse, a loss of
opportunity• Control the data and you control
the story
RESULT:• Data is 'hoarded' and 'protected'• Data is only shared within
groups that have non-competing interests
Negative View
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What Does a Data Silo Look Like?• Different KPIs of an organization
may lead to vastly different approaches to typical execution
• Underlying data that drives the KPIs tends to reflect what makes the KPIs look best
• Data is protected as a resource to tell a story
Examples• Marketing and eCommerce• Finance and Operations• UX Team and Everyone Else• Cats and Dogs
Marketing
eCommerce
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Impact of Data SilosCollaboration Doesn't
HappenData is ActionedSub-Optimally
Missed Opportunities
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Rise of the "Federated" ArchitectureFederated Topologies• Complex architectures are extremely
hard to manage• Approach is not to create single-systems
with everything, but to join together independent systems into a cohesive meta-system
• Underlying technology shares key information between solutions while maintaining control
RESULT:• Greater agility and flexibility, because
you're not designing to one standard, but many
• Lower risk and cost-containment, because you're not re-designing the world
• Data can flow between disparate silos
Systems
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AudienceStreamFederates
Disparate Data
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AudienceStream: Federated Customer Intelligence Federated Topologies
• Complex architectures are extremely hard to manage
• Approach is not to create single-systems with everything, but to join together independent systems into a cohesive meta-system
• Underlying technology shares key information between solutions while maintaining control
RESULT:
• Greater agility and flexibility, because you're not designing to one standard, but many
• Lower risk and cost-containment, because you're not re-designing the world
• Data can flow between disparate silos
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Case Study: Aligning Offline & Online Data Sales
Engagement
MRM
MRM
Digital Data Offline Account Data
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Federation: Our ConceptKey issue with Federated Data Design is Exchange
• Same problem of "common database keys", but amplified by disparate solutions, APIs, and political overhead
• Key design needed to be flexible, but resilient enough to be actionable up-front
• Building from Scratch: very difficult and expensive
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Federation: From Concept to Implementation
Connecting Data Became Easier
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Once the Key Systems are Setup, Actions on Customer Data are Second Nature
Actioning the Data Became Second Nature
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What Doesn't AudienceStream Solve?Non-Customer Centric Approaches• Collaborative Filters based on product
or asset level decisioning• Cross-sell by product (not
customer)• Asset recommendation
• Provided you can map the decisioning back to a customer identifier, you can still make it work
Political Alignment• Focus on win/win outcomes• Less threatening to focus on connected /
collaborative pilots than full-blow projects
• Open framework lowers the risk of losing control of one's data
• Action & Success Sells
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Key Takeaways Data that is largely specialized or
protected as a means of controlling outcomes between competing groups
The larger the company, the more likely you'll run into data silos
Data Silos Are Real Federation of data takes disparate
systems and aligns them through a series of consistent technologies and processes
Aligning the data into a 'meta' store of data solutions rather than the 'big-bang' one data store to rule them all
Federation Solves Many Silo Issues
Keying structure between systems has to be correct and customer-centric
Actioning becomes second nature for audience definitions
AudienceStream Breaks Down Data Silos
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AUDIENCE Q&A
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