IBM's OA D

1. The Power of Graph Analysis: Grasping
the Shape of Business Influence
James Kobielus [jgkobiel@us.ibm.com]
Big Data Evangelist
Open Analytics DC Summit, Arlington VA, March 25, 2013
© 2013 IBM Corporation

2. Graph analysis can help
you see deeply into
influence patterns that
you might in turn
influence for the better.
© 2013 IBM Corporation

3. Influence is often invisible, but has concrete value
 Getting things accomplished demands
effective use of influence.
 Organization charts don't tell the full
story of business influence:
 Internally: they flatter the chain of-
command
 Externally: they are next to useless
 Turning influence into a business
asset demands that first you identify:
 who has influence
 over whom
 with respect to what range of topics
and decisions, and
 with what potential impact on your own
bottom line
© 2013 IBM Corporation

4. Grasping influence = graphing engagement patterns
• 360-degree view of individuals
in full social context
• Hidden, latent, nonobvious
connections among people,
groups, and organizations
• Shifting patterns of
connectedness, proximity,
centrality, influence, status,
and importance
• Cooperation and collusion,
coalition and co-dependency,
influence and deference, and
affiliation and isolation
Dissect the interpersonal dynamics of communities.
© 2013 IBM Corporation

5. Graph analysis: what is it?
•Established branch of advanced analytics
•Mining, categorizing, and predicting
interactions and influence patterns in their
full social context
•Leveraging many sources of data, including:
•Behavioral
•Transactional
•Clickstream
•Geospatial
•Messaging
•Smartphone
•Usage
•Call detail records
•Social media posts
•Discovering, segmenting, exploring,
mapping, visualizing, forecasting, drilldown,
what-if analysis
•Sometimes known as “social network
analysis” or “small world” analysis
•Widely applied in social sciences
© 2013 IBM Corporation

6. Graph analysis: visual modeling of influence patterns
Same project flow as other advanced analytics modeling
disciplines
Data discovery
Data extraction
Data preparation
Variable assessment and
selection
Classification
Clustering
Statistical analysis
Regression
Scoring
Model deployment
Can leverage specialized graph analysis tools
and graph databases, or more general-purpose
tools and data platforms
© 2013 IBM Corporation

7. Graph modeling: engagement proximity = influence
“Nodes” = individuals
“Links” = interactions and relationships
“Graphs” = social networks of
interactions and relationships among
individuals
“Attributes” = characteristics of
individuals, relationships, and social
networks
4
“Proximity” = number, type, and weight of 5
links that connect one individual to another 1
2 6
3
© 2013 IBM Corporation

8. Graph analysis: customer engagement
Leaders?
Followers?
Influencers?
Mavens?
Mavericks?
Cliques?
Clusters?
Outliers?
Vanguards?
Laggards?
Late adopters?
Gauge customer influence and engage differentially to boost
customer lifetime value
© 2013 IBM Corporation

9. Using influence graphs in customer engagements
 CHANNEL INFLUENCE: Which customers are
more influential in some channels than others?
 PEER INFLUENCE: Which customers have the
greatest impact on awareness, sentiment, and
propensities of their peers?
 CAMPAIGN INFLUENCE: Which customers
promise the biggest bang for your marketing
bucks through their influence on their peers?
 LOYALTY INFLUENCE: Which customers
influence the most peers to stay with you and
grow the relationship — or churn and jump to the
competition?
 PROMOTER INFLUENCE: Which customers are
net promoters and potential brand ambassadors?
 ADOPTER INFLUENCE: What can influence
users to encourage late adopters to accelerate
their adoption of new products?
 SUPPORT INFLUENCE: Which customers have
valuable expertise and should be enlisted as
community resources for inquiries and support?
 NEGATIVE INFLUENCE: Which customers are
the squeakiest wheels who are most likely to
spread bad feelings if they are dissatisfied, or are
most likely to keep it bottled up?
© 2013 IBM Corporation

10. Graph analysis: employee engagement
COMMUNITY-OF-INTEREST INFLUENCE:
How do communities of interest emerge,
endure, and grow?
KNOWLEDGE-SHARING INFLUENCE: How
do cross-functional knowledge-sharing
relationship take root?
PEAK-PERFORMER INFLUENCE: Which
types of individuals, subject-matter experts, or
relationships have the greatest influence on
team productivity?
MENTOR INFLUENCE: How well are
mentors are fostering relationships between
mentees and other employees?
IDEATION INFLUENCE: Which people are
most effective at introducing, disseminating,
and gaining adoption for new ideas?
NEGATIVE INFLUENCE: Which people in a
distributed team are acting as bottlenecks to
collaboration, knowledge-sharing, innovation,
and ideation?
Source: managementpocketbooks.wordpress.com
Assess employee influence and create environment to boost
performance, innovation, knowledge sharing, and ideation
© 2013 IBM Corporation

11. Graph analysis: partner engagement
STRATEGIC INFLUENCE: Which
actual or potential partners have
the the right degree of influence for
realizing desired business
outcomes?
AGENDA INFLUENCE: Who
within our organization or our
partner has the influence
necessary to disseminate and gain
adoption of key messages, ideas,
or agendas among key internal or
external stakeholders?
TEAMING INFLUENCE: Who
within or organization or the
partners has the influence needed
to establish, strengthen, and
sustain the teaming arrangement at
the heart of the alliance? Source: www.ahrq.gov
Assess partner influence and create environment to boost
strategic goals, agendas, and teaming arrangements?
© 2013 IBM Corporation

12. How to use graph analysis to influence the influencers?
•CUSTOMER ENGAGEMENT:
•Engage with influencers on social media
•Use graph analysis to assess degrees of customer influence
•Establish differentiated engagement approaches and incentives based on degrees of
influence
•Experiment with mixes of all of these established and emerging influence channels,
including but limited to social media
•Compile the data, metrics and analytics needed to assess whether you achieved the
expected return on your investments across various influence channels
•Have an agile decision framework to help guide continual adjustments of your marketing mix
among channels commensurate with their relative effectiveness
EMPLOYEE ENGAGEMENT:
•Use social graph analysis is to feed back results to the entire network in a structured setting
in which discussion can be productively facilitated.
•Viewing the graph analysis diagrams seems to be particularly powerful
•Revealing these previously hidden barriers constructively can be a powerful tool for creating
new opportunities for cross-group relationship development.
•Graph analysis can also suggest ways of restructuring organizational charts or implementing
new processes.
•PARTNER ENGAGEMENT:
• Use social graph analysis on partner organizations to assess where they and their
employees stand in degrees of strategic, agenda, and teaming influence
•Use these analyses as inputs into strategic partnering decisions
© 2013 IBM Corporation

13. Thank You!
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© 2013 IBM Corporation