7. FPX Cluster Metrics
FPX analyze of e-mail communication
To identify the volume and frequency of
communication against different ‘bridges’
(categories) within the cluster network
Analysis methodology and May – Dec 2013 Data
Prepared by TSG Inc.
Confidential. Copyright TSG 2014
9. FPX Data Analysis : Step 1
Confidential. Copyright TSG 2014
1. Extract Raw Data
1. Establish connections to mail server(s)
2. Extract emails from Mail server(s)
3. Consolidate mail data from different sources
4. Update mail extraction routines
10. FPX Data Analysis : Step 2
2) Clean and Categorize Data
1. Extract From and To Domains only to
protect privacy
2. Remove domains that are not needed
3. Categorize domains by Bridge
4. Store into data warehouse
5. Update extraction routines
Confidential. Copyright TSG 2014
Domain Frequency Category
movexum.se 30 1
aronssons.se 2 2
persamuelsson.se 3 2
reflectus.se 3 2
fanky.se 4 2
gullers.se 4 2
interlan.se 4 2
agima.se 5 2
cartesia.se 5 2
teria.se 5 2
trolskaskogen.se 5 2
Domains with less
than 4
communications
were ignored.
We also
eliminated ‘Junk’
emails
11. FPX Data Analysis : Step 3
3) Analyze Data and Create Visualizations
• Calculate frequency of interactions
• Calculate Actual metrics against Goals
• Create Visuals
• Update analysis and visualization routines
Confidential. Copyright TSG 2014
0%
50%
100%
Capital Company Research Public
Sector
Cluster Global
Average vs Goal for Number of Contacts
Per Category
Actual Number of Contacts Contact Gap
On average each month a
total of 140 valid domains,
and approx. 2000 email
communications per month
included in analysis.
1610 domains not included in
Analysis (junk or
uncategorized low frequency)
12. Bridge Metrics Summary
• Volume = Number of communications per bridge
• Diversity = Number of unique contacts per bridge
• Intensity = Average Number of Communications
per contact per bridge
• FPX has set Goals for its email communication per
Bridge for
• Diversity
• Frequency
Confidential. Copyright TSG 2014
13. FPX Goals
Confidential. Copyright TSG 2014
Capital Company Research Public Sector Cluster Global Market Education
Goal for Number of Contacts
Per Month (Diversity Goal) 5 150 15 40 25 30 15
Goal for Number of
Communications per Contact
Per Month
(Intensity Goal) 6 4 6 4 4 2 4
15. Total Volume of Communication across Categories
Confidential. Copyright TSG 2014
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
May June July August September October November December
Total # Communications
Capital Company Research Public Sector Cluster Global Market Education
Geo Life Region Project caused spike in communication
16. Total # Contacts Per Month across Categories
Confidential. Copyright TSG 2014
0
10
20
30
40
50
60
70
80
Capital Company Research Public Sector Cluster Global Market Education
Total # Contacts
May June July August September October November December
Education
Contacts appear
to be increasing
17. Diversity of Contacts: Actual vs
Goal
Confidential. Copyright TSG 2014
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Capital Company Research Public Sector Cluster Global Market Education
Contact Gap - Actual vs Goal # Contacts
May June July August September October November December
On average, FPX is reaching up to 70% of its Diversity goal… How can this be increased given staff email workload?
18. Average Intensity of
Communication across Categories
Confidential. Copyright TSG 2014
0
10
20
30
40
50
60
70
Capital Company Research Public Sector Cluster Global Market Education
Intensity of Communication Per Contact
May June July August September October November December
19. Intensity of Communication :
Actual vs Goal
Confidential. Copyright TSG 2014
0%
200%
400%
600%
800%
1000%
1200%
1400%
Capital Company Research Public Sector Cluster Global Market Education
Intensity of Communication Per Contact
- Actual vs Goal
May June July August September October November December
Intensity goals generally exceeded. Management should review if intensity can be traded for diversity
20. FPX Management Insights
• The analysis shows that the total volume of communication each month is
about 2000. Staff is generally at their maximum email load at this level.
• This means that to reach the diversity goals, management will have to discuss
the intensity in each cluster category, since a reduction in intensity
(communication frequency) would allow for an increase in diversity (number of
contacts) of email communication work load.
• Given there are no additional people resources in any given month, the data
allows management to review and potentially make changes to the underlying
and hidden nature of how staff are communicating. This kind of insight has
never been revealed before until this type of analysis.
• This can also lead to a review of Intensity Goals (Average Number of
Communications per Contact) since FPX has generally exceeded its original goals
Confidential. Copyright TSG 2014
21. FPX Management Insights
• The data shows a consistent picture each month for 2013, with FPX needing to
review its Intensity-Diversity balance. The data also reveals some of the stories
of FPX during 2013, such as the work-load of different months. The data
correctly reflected that in June the FPX team was extremely engaged in a special
‘Geo Life Region’ project. The data also seems to indicate FPX is growing its
education side - Education Partners appear to be trending upwards.
• A question for management is ‘What is the ideal communication data
‘constitution’ (profile) of a cluster?’. Is the data profile for FPX unique or will
there be common trends across all clusters? Will there be different profiles of
how the data looks based on the maturity of a cluster and/or its market focus?
• FPX will continue to measure the bridges of the cluster to better understand
work performance and strength of the cluster bridges during 2014.
• It is hoped that similar analysis and comparison with other clusters will help to
provide a more comprehensive and longitudinal insight into cluster innovation
management and performance.
Confidential. Copyright TSG 2014
FPX was founded in 2006 as a non-profit cluster organization with the aim to build a European center of excellence, an independent arena for GIS (geographic information systems) development, demonstration, marketing, and knowledge exchanging. As a young, vigorous organization, FPX has been developing and expanding rapidly and 2010 FPX was rewarded with the European cluster manager of the year award.
The members of FPX cluster in Sweden have more than 26 000 employees with a turnover of over 44 billion SEK. The network of FPX covers more than 15 countries and besides our headquarter and research and development labs in Gävle, Sweden we have our own staff and offices in Beijing, Wuhan and Zhuhai in China.
4
We extract email data, and respecting privacy, we only take the from, to, and date from the email server (we have a computer program to do this). We use Microsoft Exchange.
This gives us a big table of email headers to process
We then continue to ensure privacy by stripping away the email address to only leave the domain – e.g. movexum.se
And then we count how many emails were from that domain that month to fpx.
e.g. we may have 30 emails from Movexum in a particular month.
We then categorize the domains against the 7 bridges – Capital, company, research, public sector, cluster, global – and recently education.
This is manual process but we now have a database of about 3000 domains we have classified so each month we only classify new domains.
We only analyze communications of 4 per month or more – both meaningful and to make the process manageable. And we classify junk domains e.g. youtube etc
Once we have all the data we can do the analysis – we also set goals for our communication and we will see this. We obviously look at volume (how many) and intensity (frequency) of communication
Definitions: volume, diversity, intensity. E.g. 10 communications to the Capital domains in total, Diversity might mean there were 2 distinct domains we had emails from, and intensity was the average – e.g. in this example 5 emails per domain on average for the capital bridge.
By doing this analysis for all bridges, for month on month, and comparing to our targets, we can get meaningful information and business metrics, from data that has never been used before for such analysis. It complements other data, e.g. the physical meetings we have and that we track.
We set goals per bridge for each month..
And here is the data.
Month by month along the axis, and then broken down by bridge… and it already helped us to see some interesting events – here we did a big application for GeoLife Region in June
Here we can see we have a lot of contacts in Company, and Cluster as you would imaging. Perhaps we need to do more on the education and research side – so that’s why we are here at this conference!
This is the same data, but against goals. So now we see we are only half way towards our company goals of how many different companies we want to to communicate to each month, but we see we are actually doing better against goals for reserach, but not education.
Intensity: here we can see we had a lot of emails per month for capital, and a lot in the public sectore in June (again, the GLR application)
And the same data again, we see against goals. We see we exceeded goal in june, and are doing well on capital.
So while we are doing well on our intensity (number of communications), we might want to do better on the diversity of companies. This becomes a management discussion to action.
The work shows the ‘workload’ on our staff, and what we can trade. Perhaps we need to trade intensity for diversity – ie. Email less to the people we know, and more to the ones we don’t know yet.
Again, the data shows the workload across the year, including the dip in july/august (holiday).
Some questions we have, that we can now share with you:
As we discuss in our board meetings, what should the ideal communication profile look like?
Are they different depending on the cluster, the age of the cluster, the industry etc.
We have continued to do this analysis and are completing nearly the 2015 data.
We would love to collaborate with other clusters and to share our best practices (we can offer this analysis as a service) and we are also looking to expand the analysis to include analysis of the emails themselves to do text analysis – e.g what kind of conversations are we having and what are we talking about.
Thank you