This document provides an overview of visualizing software ecosystems. It begins with an agenda and definitions of ecosystems and industry platforms. Examples of mobile payment, cloud computing, and telematics ecosystems are described. The methodology used to generate ecosystem visualizations is explained, including identifying companies, relationships, and attributes. Semantics are assigned to visualize firms by size, shape and color and relationships by thickness and color. The document concludes with findings on charting your own ecosystem and considering strategic moves.

1. Visualizing Software
Ecosystems
Prof. Bala Iyer
Twitter: @balaiyer
04/04/14

2. 2
Agenda
 Ecosystem basics
 Examples
 Visualization Methodology
 Lessons
 Future directions

3. 3
Ecosystem
 Loose networks – of suppliers, distributors,
outsourcing firms, makers of related products or
services, technology providers, and a host of other
organizations – that affect, and are affected by the
creation and delivery of a company’s own
offerings. [Marco Iansiti]
 An economic community supported by a
foundation of interacting organizations and
individuals—the organisms of the business world.
The economic community produces goods and
services of value to customers, who are themselves
members of the ecosystem [James Moore]

4. 4
Creating Awesome Users
 Don't make a better [X], make a better
[user of X].
 Kathy Sierra
 Think about how customers experience
the product or service

5. 5
Computer Industry [circa 1980s…]
Source: Bill Gates Testimony - link
Bill Gates, DOJ testimony 2002.

6. 6
Computer Industry circa 2002…
ony - link
Bill Gates, DOJ testimony 2002.

7. 7
Network -- 2002
Linux
Unix
Windows
Other
IBM
MSFT
SAP
Environments
companies
1144 Nodes
232
68
630
520

8. 8
Layered model of capabilities
Hardware (consoles)
Data
Services (safety, entertainment, insurance)
Connectivity (broadband, mobile)
Operating SysStems
Social or Community Layer
Gaming Layer
Apps

9. 9
Software Ecosystem
 .. ―a set of actors functioning as a unit and
interacting with a shared market for software
and services, together with the relationships
among them. These relationships are
frequently underpinned by a common
technological platform or market and operate
through the exchange of
information, resources and artifacts.‖

10. 10

11. 11
Networks
 Deliver value to customer segments
using a portfolio of capabilities some of
which are achieved through links or
dependencies.
 People
 Objects
 Systems
 Organizations

12. 12
Roles
 Platform provider
 Component supplier
 Systems integrator
 Orchestrator

13. 13
Industry Platform Definition
 Technology or set of components (or services) that
creates a common foundation,
 That brings together multiple parties beyond a
single firm (―market sides‖) for a common purpose
and generates network effects,
 Where the value can increase exponentially
with (a) more users and (b) more ―complementary‖
products & services built around the platform
Michael Cusumano, Platform Strategy Fundamentals 2014.

14. 14
Examples
 Mobile Payment
 Telematics
 Cloud services

15. 15
Example 1

16. 16

17. 17
Google Wallet
 Phones: Google Wallet will work with the Android & iOS
 Cards: Citi MasterCard, a pre-loaded Google Prepaid Card
(which can be ―refilled‖ from any source of funds) and gift
cards from various participating merchants.
 Markets: available in San Francisco and New York
 Participating merchants: American Eagle Outfitters,
Bloomingdale’s, Champs Sports, The Container Store,
Duane Reade, Einstein Bros. Bagels, Foot Locker, Guess,
Jamba Juice, Macy’s, Noah’s Bagels, Peet’s Coffee & Tea,
RadioShack, Subway, Toys―R‖Us and Walgreens.
 Google Wallet relies on the MasterCard PayPass
infrastructure it will work ―at more than 124,000 PayPass-
enabled merchants nationally and 311,000 globally.‖
17

18. 18
Google Wallet
 Google Offers linked to Wallet: Offers are
directly integrated into Google Wallet.
Consumers will be able to send offers they
encounter to Wallet with a single click (if you’re
signed in). Redemption will be accomplished
with a ―SingleTap‖ at the point of sale or via
scanning or keying in a code if the POS system
doesn’t support SingleTap.
 Future uses: Google envisions that ―receipts,
boarding passes and tickets will all be
seamlessly synced to your Google Wallet.‖
18

19. 1919

20. 2020Link

21. 2121

22. 22
M-payment Stakeholders
 Platform provider
 Network Operators
 Banks
 Credit Card Issuers
 Device Manufacturers
 Merchants
 Consumers
22

23. 23
Market
 Forrester Research estimates the size of the opportunity
will grow to $90 billion by 2017, growing at a 48% rate
since 2012.
 Worldwide mobile payment transaction values will
surpass $171.5 billion ... according to Gartner, Inc.
 By 2015, about half of the 863 million phone
handsets sold yearly worldwide will contain the
chips, according to Frost & Sullivan.
 150,000 merchants on Google Wallet
 ―only about 7 percent of retail sales occur
online, compared to $4 trillion that is still spent in person
at stores. "We're going after the 93 percent," Google
VP, Osama Bedier.
23

24. 2424

25. 25
Platforms
25

26. 26
Method used for Ecosystem
generation
 List of platform players created from
virtual currency platforms, experts, and
 Created a list of partners from news
feeds and websites
 Visualized using Pajek

27. 27
Mobile Payment
-- complementors
-- platforms
-- partnerships

28. 28
Analysis
 237 companies, 25 platforms
 Many approaches to M-payment
 Diversity is good
 Many fragmented platforms
 Carriers and card issuers are working
across platforms
 Still evolving ecosystem
 Many experiments in emerging
economies

29. 29
M-payment Platform Wars
 A few platforms may emerge
 Unique value proposition
 Too expensive to carry multiple systems
 Direct (developers) and Indirect (end
users) Network Effects
 Business models and subsidies
 Emergence of standards like OpenSocial
29

30. 30
Product vs. Platform
 Winners in a platform market generally have
the ―best‖ platform, not the ―best‖ product!
 Best products? Hard to define & while
good, usually not enough to win or dominate in a
platform market
 Best platforms? = (1) Open access &
interfaces (but not too open). (2) Modular
architecture (easy to build on, extend). (3)
Most compelling complements (usually result
of most vibrant ecosystem).
Michael Cusumano, Platform Strategy Fundamentals 2014.

31. 31
Example #2: Cloud computing

32. 32
Methodology
 Start with a focal set of firms (55 – 631)
 Determined dependencies
 Identified core
 Capture definitions of cloud from the web
(~70)
 Read descriptions
 Run through a tag cloud analysis
 Identified capabilities

33. 33
Infrastructure Platform
Applications Collaboration Services
Cloud Ecosystem (partnerships)

34. 34
Core players

35. 35
Example #3: Telematics

36. 36

37. 37
Telematics Ecosystem

38. 38
January 2007
Mashups

39. 39
2002
Highest
High
Medium
Low
Higher
Clustering coefficient
Central firms:
Between 1990 and 2002,
these firms account for
35 to 69% of the industry sale

40. 40
Illustrative list of
software firms in the
cluster
• NEC
• Computer Associates
• RealNetworks
• CheckFree Corp.
• Yahoo!
Link strength
High (5 or more links)
Medium (3-4 links)
Low (1-2 links)
The size of each node is proportional to the number of alliances

41. 41
Platform moves
• Open sourcing
• Cutting off air supply
• Entrants with network effects
• Creating and defending IP
• Acquisitions
• Creating exclusive links
• Complementor incentives and subsidies
• Envelopment (absorb & bundle)
• Facebook with social layer and FB credits

42. 42
Coring & Tipping
Strategic Option Possible Technology
Actions
Possible Business Actions
CORING
(How create a new
platform when none
existed before)
• Solve “system” problem
• Facilitate add-ons
• Keep key IP closed or
“open but not open”
• Strong
interdependencies --
platform & complements
• Solve “business”
problem
• Create complementor
incentives to innovate
• Protect revenue & profit
• Raise switching or multi-
homing costs
TIPPING
(How win a platform
battle when multiple
platforms compete)
• Develop compelling
features
• Absorb & bundle from
adjacent markets
(―envelopment‖)
• Complementor
incentives
• Coalitions of also-rans
• Pricing or other
subsidies to attract
users/complementors
Source: Gawer and Cusumano SMR 2008

43. 43
Findings
 Chart your ecosystem
 Ford (telematics, healthcare,
entertainment, ..)
 Consider shifts in network
 Own and third-party moves
 Portfolio of proactive and reactive
connections
 Ecosystem moves

44. 44
Methodology: EcoSysNetworks™
 Determine industry structure or stack
 Identify companies and attributes
 Get dependency information and attributes
 Enter information into database
 Determine semantics for firms
(size, shape, color)
 Determine semantics for links
(thickness, color)
 Create input file for visualization
 Visualize and interpret

45. 45
Stacks
Video Games SmartOS
Content providers
Software developers
Software publishers
Platform provider
Retailer
Consumer
Network operator
Handset manufacturer
Mobile OS provider
Content providers and aggregators
Application developers

46. 46
Identify companies and attributes
 Sources
 Competitive list from industry publications
 News feeds
 User generated input (bookmarks or
brainstorming)
 Inputs
 Name
 Revenue
 Business type (stacks)
 Platform provider?

47. 47
Get alliance information and
attributes
 Sources
 Company websites
 News feeds
 Inputs
 Alliance type
(technical, marketing, strategic or financial)
 Single or multiple alliances

48. 48
Enter information into
database
 The database has two tables
 Firms
 Relationships
Visualization semantics can also be stored in
the database

49. 49
Semantics for firms
 Size
 Currently we use
revenue
 Shape
 Platform players are
denoted as
diamonds, rest as
circles
 Color
 Based on stack layer
Access Light Magenta
Advertiser Green
Content Lavender
Hardware Tan
Default Red
Operator Melon
Services Blue
Investors Yellow

50. 50
Semantics for links
 Thickness
 Based on repeat links
 Color
 Based on relationship type
 Technical
 Marketing
 Financial
 Strategic

51. 51
Pajek
 Download:
http://pajek.imfm.si/doku.php?id=down
load
 Reference manual

52. 52
Create input file for
visualization
 We use Pajek for the visualizations
 A sample Pajek input file has two parts
 Vertices
 A vertex record contains vertex
number, name, color, shape, size and the time
it appears on the visualization.
 Edges
 An edge record contains
from, to, thickness, color and the time it
appears in the visualization

53. 53
Data entry
 Open Notepad
 Enter data
 Save as .net file
 Use Excel
 Save as Tab delimited DOS file
 Replace tabs with spaces using Notepad

54. 54
*Vertices 8
1 "Google" ellipse ic Green x_fact 3 y_fact 4
2 ―Zynga" triangle ic Lavender x_fact 2 y_fact 2
3 ―Facebook" box ic Lavender x_fact 2 y_fact 2
4 "Accel" diamond ic Yellow x_fact 3 y_fact 3
5 "Accenture" circle ic Blue x_fact 2 y_fact 2
6 "IBM" box ic Orange bc Black
7 "MSFT" circle ic Cyan bc Magenta
8 "Intel" cross ic Purple bc Pink x_fact 3 y_fact 3
*Edges
1 2 1 c Tan
2 3 3 c Green
3 4 3 c Yellow
4 5 1 c Lavender
5 4 1 c Blue
5 6 2 c Gray
1 7 2 c Red
2 8 2 c Purple
3 5 2 c Brown
4 1 2 c Black
Data file

55. 55

56. 56
Visualization steps
 Launch program
 Load data into Pajek
 Use the draw option
 Chose Layout/Energy/Fructerman-
Reingold/2D

57. 57
Ecosystem Health

58. 58
Network Measures

59. 59
Degree centrality
 The degree centrality of a node is
defined as the total number of
connections the node has

60. 60
Density
 Density is the number of connections a
node has, divided by the number of
possible connections

61. 61
Betweenness
 It is important to find which units lie on
the shortest paths among pairs of other
units. Such units have control over the
flow of information in the network. Idea
of betweenness centrality measures:
unit is central, if it lies on several
shortest paths among other pairs of
units.

62. 62
Closeness centrality
 Closeness is preferred in network
analysis to mean shortest-path
length, as it gives higher values to more
central vertices, and so is usually
positively associated with other
measures such as degree.
Source: wikipedia

63. 63
Clustering Coefficient
 A node’s clustering coefficient can be
defined as the proportion of alters that
are themselves directly connected

64. 64
Pajek measures
 Network/Create
Vector/Centrality/Degree/, while other two
centralities can be found under Degree
 Network reduction
 Net/Transform/Reduction/Degree
 Core players
 Net/Partitions/Core/Degree
 Operations/Extract Network/Partitions
 Draw-partition

65. 65
Exporting pictures
 Export/2D/bitmap
 Save file
 Import into PowerPoint

66. 66
What did we find in the software sector
(1990-2001)?
 Small worlds
 Degree – 3.1 to 2.8
 Density – decreased from 0.005 to
0.001
 CC – 0.21 to 0.28
 Structure of the network and firm
performance

67. 67
Platform Leadership Process
 Create & communicate a vision of platform evolution
 Build consensus & coalitions among a small group of
influential firms for new initiatives
 Identify and target “system” bottlenecks
 Distribute tools & enabling technologies to help partners
develop complements fitting the vision
 Highlight business opportunities and help leading firms act
as “rabbits” to lead the market
 Facilitate multi-firm initiatives to promote standards,
platform interfaces, and complementary innovations
Michael Cusumano, Platform Strategy Fundamentals 2014.

68. 68
Data sources
 Website
 Lexis/Nexis
 Sort search results by subject (alliances and
partnerships)
 SDC Platinum
 Programmableweb.com
 http://www.programmableweb.com/neoapi.xml
 http://www.programmableweb.com/neomatrix.xml
 Appdata
 www.compete.com ; www.socialmention.com;
www.google.com/trends

69. 69
Future directions
 Decision Environments
 automate data collection
 Visualize
 collaborate
 Shared repositories
 Strong theory and cases
 Better understanding of ecosystem risks
 API-based networks
 Communities to share findings