This presentation provides an analysis of the relationship between the size of a community (or Yammer group as a proxy for a community) and the business value that can be derived from the community. It looks at a variety of factors across a large set of communities to conclude that, yes, size does matter.

1. Yammer Groups and Business Value
Lee Romero
October 2014
Does size matter?

2. Preface 3
Background 4
Hypothesis 6
Data source and methodology 7
Findings
•Activity levels 11
•Responsiveness 16
•Knowledge impact 18
•Private vs Public Groups 19
Summary 21
Contents
2

3. This material has been assembled as part of an informal review of communities at Deloitte
It presents some insights relating the size of a community to its value
It does not represent an official Deloitte position
Preface
Disclaimer
3

4. As part of Deloitte’s Community program, we have long used a health report to help drive desired changes
That health report considers a number of factors – the goal is to identify specific factors which, if we can effect change, will improve the value of our communities
One specific factor used is the size of the community
The rationale has been that, in light of the “90-9-1” principle*, there is a certain minimum size of a community need to reach a critical mass of activity
Background
Deloitte’s Community program
4
* See http://en.wikipedia.org/wiki/1%25_rule_(Internet_culture)

5. As part of our Community program, Deloitte has adopted the use of Yammer as a primary tool of discussion within our communities
Yammer provides a completely user-driven means to create “groups” – which, roughly speaking, can map to communities
Following the same logic as our communities, through some moderation of new groups, we have pushed for fewer, larger Yammer groups to increase their value
Recently, the importance of size of a community / Yammer group has been challenged with the assertion that people are more comfortable and therefore more likely to communicate in a smaller group of people
Background
Deloitte’s use of Yammer
5

6. I decided to try to address this assertion with data.
My hypothesis:
•Larger communities are more likely to be active and vibrant – and, therefore, more likely to deliver business value to Deloitte
To test this hypothesis, we need to define “value” – which is a hard problem
So I simplify the problem and assume that the value of a community / group is proportional to the activity within that community / group
•Certainly, it is true that a community / group with no activity offers no value
My Hypothesis
Size does matter
6

7. In order to test the hypothesis, I collected data from Deloitte’s global network
The data included
•All public messages from July 2012 – April 2013, including:
−Group
−Sender
−Time stamp
−Threading
•A listing of all groups as of early June 2013, including:
−Current group size
−Create date
−Summary counts of messages and total posters
Data source and Methodology
How to address the hypothesis?
7

8. I did not have detailed data about Private groups in our network
I also did not have access to detailed data on “Likes” or “Shares” of conversations
For the purposes of the analysis here, I aggregated the data as follows:
•First, for each group, I averaged measures across months to represent that group
•In order to aggregate across the groups, I used the size of the group (as of June 2013) and grouped together groups by size
−Groups are represented by the largest multiple of a power of 10 smaller than its size, though any group smaller than 100 members was grouped into a “0”
−For example, a group of 250 members is grouped into a 200 range, a group of 1180 members is grouped into a 1000 range
Data source and Methodology
Part 2
8

9. In order to provide some context on the remaining slides, this chart shows you the number of groups (both private and public groups) for each size grouping
The Landscape
Overall view of the landscape
9
Group Size
Public Groups
Private Groups
0
1112
1178
100
223
67
200
81
22
300
42
8
400
33
5
500
18
2
600
17
3
700
7
1
800
2
2
900
4
2
1000
24
4
2000
7
3000
4
4000
2
6000
4
10000
1

10. Findings
10

11. Activity Levels by Group Size
11
 Number of messages does positively correlate with size of group
As does the number of distinct posters 

12. You might notice a relatively low correlation in the data on the last slide – however, if we remove just 4 groups (the four largest in our network) we get this – significantly higher correlation!
Activity Levels by Group Size
Another view
12

13. Besides raw size, another factor in our health report is a minimum amount of activity (messages) – one message per week
This chart shows the percent of groups for each size that achieve that minimum
The impact of size flattens but from this, in order for a group to have a good chance of meeting this minimum, they need to achieve at least 200 members
Achieving “green community” status
Minimum activity
13

14. So overall activity does correlate with size – is an individual member more or less likely to contribute based on size?
So in larger groups, it can be harder to get people to post but once someone does post, they will be as active as in any group
Messages per Member
14
Engagement with the community

15. Similar to messages / member, on a monthly basis, the percentage of members who will post at least once does negatively correlate with size
Similar to activity in the groups, if you ignore the largest 2 groupings (the four largest groups), once a group is larger than 100 members, this becomes nearly flat at 2.5%-3%
Percent of members that are active
How likely is someone to say anything?
15

16. Beside pure levels of activity, another important factor is how quickly someone gets a reply – how does that correlate with size?
Answer: You will in general get an answer faster in a larger group. Faster to get an answer and faster to get value for clients.
Time for reply
How long does it take to get an answer?
16

17. Besides how quickly you might get a reply, what is the likelihood of getting any reply?
Not only will you get a reply more quickly, you are more likely to get any reply at all in a larger group
Likelihood of a reply
Are you ever going to get a reply?
17

18. Another effect of size of a group to consider is the impact on the lurkers in the groups – people who join and read but don’t post
One way to approximate this impact is with a calculation I call “knowledge flow”*
Knowledge flow estimates the overall impact on the members
This shows a very strong correlation with size (note the Y axis is logarithmic!)
Impact on Lurkers
What about the silent majority?
18
* See http://blog.leeromero.org/2008/11/20/measuring-knowledge-flow-within-a-community-of-practice/

19. The data I have for private groups is very limited – just total posts and posters and size
Based on this, though, we can compare the percent of members that are active at each size for public and private groups
Because large private groups are much fewer in number, the average varies a lot
However, overall, the likelihood of a member in a private group posting does not appear any different than in a public group
Private vs. Public groups
Are people more likely to share in private?
19

20. Summary
20

21. Based on the insights here, I believe there are a lot of compelling reasons why fewer, larger communities with broader topics provide more business value
Based on the data, a community manager may want to encourage members to post but once they post, they seem more comfortable in doing so again
I would encourage you to guide your communities to start broad and go narrow if the community becomes so active as to be overwhelming to newcomers
What are your thoughts and experiences with regard to this?
Summary
Size does Matter!
21