From Software …

to Social Software

How Enterprise Social Graphs Can

Transform Enterprise Applications

Kapil Gupta

Standard Disclaimer

Views and opinions discussed in

the following presentation are mine

alone, and do not reflect the views

of JP Morgan Chase or IBM

Where companies or vendors are

mentioned, there is no implied

endorsement by me or my

employer

Outline

Business & Technology context, and

why we should care

Case study: IBM ThinkPlace

Brief primer on Social Graphs

Implications for the Enterprise

context

5 Steps on the road to transforming

your Enterprise Applications

We’ve come a long way from

1993

… To 2013

Ad Targeting is just the tip of the

iceberg: understanding who we

know, what we like -

can help almost every functional area

in an organization

Social CRM

Recruiting

Customer Journey

Influencer Analytics

Social org

chartsBusiness

development

Business

Intelligence

Social LearningExpertise Location

Collaboration across

silos

Even though this is a space that

did not exist

just 10 years ago,

the industry

landscape

has evolved

Source: McKinsey 2012

Source: McKinsey 2012

Growth in “Social” is

fueled by a broader

set of technology

trends

Source: McKinsey 2012

CEO, CMO priorities:

engagement,

connections,

collaboration

… all of which are in the sweet

spot for Social

Social Graphs and

Social Network Analysis

are the architectural foundations

for the use of Social technologies

+

+

Graphs represents those Objects,

Connections and Relationships

as

structured data

Public social networks –

Facebook, Twitter, Linkedin –

are built on

social graphs and

interest graphs

Social graphs represent

connections between

people who

know each other

Interest graphs

represent

connections

between people

with common

interests

When used together, applications

can start with who you know and

surmise what your connections like;

properly-designed interfaces and

interactions can provoke the

desired outcome

Not bad: All the same

genre

Even better: Recommendation across different

genres

This is the promise of Social

Software

aka Social-enabled software

aka Social-aware software:

Software that can enable

discovery – and promote

outcomes – through

Recommendations

Example: IBM ThinkPlace

A worldwide collaboration

platform to drive innovation

across the enterprise

My role at IBM (2005-2010) on this effort:

Product Manager/Product Owner

IBM ThinkPlace: A platform for

sharing ideas and collaboration

1 2 3 4 5

Year

Bu

sin

ess i

mp

act

1 2 3 4 5

Year

Nu

mb

er o

f id

eas

Our problem wasn’t too few ideas: it

was actually too many

But This raised the bar for finding

good ideas

Photo by Flickr user MayaEvening, licensed under Creative Commons, Attribution 2.0 Generic

Some good ideas

were seen, but

many remained

hidden

Photo by Flickr user giladr, licensed under Creative Commons, Attribution 2.0 Generic

Identity - who you are

Contacts - who you know

Activities - what you are

doing

So we designed and implemented a

set of features across the system

designed around people

(vs. designed around ideas)

The approach taken for ThinkPlace

can be applied to applications

across the enterprise, but

requires a set of infrastructure

components to support it

Source: Mike Gotta, Gartner

Enterprise Social Graphs can

bridge the gap between

“Systems of Engagement”

(interactions inside, outside firewall)

and “Systems of Record”

(data stores inside the firewall)

Netflix has a “movie graph”

Visualization of my Linkedin Graph

Linkedin has a “Professional contacts

graph”

Just like them, every Enterprise has a

unique Social graph

… and

unique interest graphs

Relationships between Employees,

Clients, Partners, Competitors

Relationships can also be inferred

from enterprise meta data

(directory, email, collaboration tools)

or be user-submitted

Relationship information can be

augmented from external sources

(public graphs: Linkedin, Facebook,

Twitter)

Analogous to Integrated Supply

Chains, but for connections &

relationships: Integrated Supply

Graph

(of course, view of data is not shared

outside enterprise)

Most commonly cited enterprise

uses: (ad) targeting, retargeting

Customer journey: identifying

influencers; empowering advocates;

predicting customer behavior (via

interest graph changes)

Improving web experience: product

discovery, user communities

Talent management: identifying

“connectors”, leaders; as a

basis for referrals, evaluation

Business development &

Business Intelligence:

employee alumni in other

companies; new hires from

potential clients & competitors

Org charts of suppliers, clients,

competitors

5 steps on the road to

transforming Enterprise

Applications into

Social Software

1) Examine:

a) how your customers use your

products, how they interact with each

other and you

b) what kind of data already

exists in enterprise data stores

2) Review your application

design and infrastructure stack

Your approach will have

significant implications for

application design, and the

software stack to support such

applications

3) Create your own graph with all

known internal and external

relationships and data sources

4) Customize application design

depending on the kinds of ties, and

types of interactions desired

Define social objects and interactions

Redesign UI experience

Leverage activity streams

5) Seek to make existing

interactions easier and more

effective – avoid the trap of creating

a set of social-driven interactions

that exist separately

Two places to target: where goal of

user interaction involves

Discovery and

Collaboration

Thank You.