This presentation was from the Zendesk Boston User's group kick-off event. These slides show you a little bit about how Compete PRO uses Zendesk as well as some other projects within our group. For questions regarding these slides feel free to reach out to me.
Here's a simple PPT I put together to help you understand the basics of twitter - there's nothing about trending - but you'll see there is an explanation of some simple concepts.
Hope it helps :-)
This presentation was from the Zendesk Boston User's group kick-off event. These slides show you a little bit about how Compete PRO uses Zendesk as well as some other projects within our group. For questions regarding these slides feel free to reach out to me.
Here's a simple PPT I put together to help you understand the basics of twitter - there's nothing about trending - but you'll see there is an explanation of some simple concepts.
Hope it helps :-)
Today’s innovative prospect researchers are more focused on making business impact via informed decisions based on research, fact and business intelligence than ever before. In this session, learn about the direction in which the field of prospect research is moving, with the addition of social media and increased focus on data, analytics and ROI. This session will discuss the skills necessary for the prospect development professional, the “business intelligence agent," of tomorrow. Discussion will include how we spend our time, what is trending, and how to understand, measure and demonstrate the impact of prospect development in the context of nonprofit development. Prospect researchers are no longer the deckhands and are now steering the ship. Make sure that you are on the cutting edge of this shift.
Returns to Public Investments in ECEC Oslo, Norway Implementing Policies for ...EduSkills OECD
Why invest in ECEC?
First 5 years lay foundations for language, academic abilities, habits & socio-emotional development
The window for change does not close after age 5, but “catch up” is costly
Worldwide more than 200 million children under 5 are failing to reach their developmental potential
Preschool interventions can enhance development and yield high economic returns
Presentation given by Jodie Slaughter, FASAE and Jodie Slaughter, FASAE President and Founding Partner, McKinley Advisors and
Michelle Mason, CAE, FASAE, CQIA
Managing Director, ASQ
at ASAE Annual Meeting 2012
Member Models and Their Relation toValue in a Time of Change
7th annual Planning Survey Report
Emotions about our jobs Career path
Students, Interns and Junior Planners
A note on salaries
Salary Results – US
Salary Results – Brazil
Salary Results – UK
Freelance
Open-ended responses Closing thoughts
1. John Massman, Ph.D.
Giving voice to data
Real-life examples creating the
“wow” factor
2. Example
Organization: Non-profit service provider
Context: Presenting a cash flow report to the board of
directors.
Task: Present data, analysis and consequences without putting
people to sleep.
I prepared an “emphatic graph” that combined the key
information and the foreseeable consequences.
The board had a pointed discussion, instituted structural
changes, and the organization thrived.
3. Standard Table vs. Emphatic Graph
Data (internal only) Presented to Board
today
4. Case Study
Organization: Non-profit adult-child mentoring program
Goal: long-term mentoring relationships.
o Much effort is expended in establishing relationships and initial
management of the relationship.
o Short relationships are ineffective and consume scarce
resources.
Approach: analyze voluminous data of both adult and child.
5. Results and Outcomes
Results:
o Identified demographic characteristics of ideal long-term adult-
child matches.
o Quantified benefits of the long-term relationships.
Outcomes:
o Dramatic increase in effectiveness of matching efforts.
o Quantified benefits reported to external stakeholders including
donors.
6. Making an initial adult-child match
Analyze 1700+ recent adult-child matches each with dozens
of demographic items.
Identify key characteristics that correlate with a long-term
relationship.
All data is non-linear, non-logarithmic, non-parametric.
Comparison with current practices would be especially
valuable.
7. One graph makes a difference
• Green markers All Matches
are long-term 21
successes.
19
• Red markers are
short-term (low 17
“ROI”).
15
• This plot directly
Age of Child
resulted in a 13 Successes
In Progress
programmatic 11 Misses
change to avoid
pairing older 9
adults with
7
younger
children. 5
15 25 35 45 55 65 75 85 95
Age of Adult
8. Quantifying Outcomes
Raw data Effective Presentation
Social Acceptance Social Acceptance
90 (different groups of children)
40%
80
35%
70
Relative Frequency of children
30%
60
No. of children
25%
50
Guided < 1 yr 20%
40 Under 1 yr
Guided 1+ yrs
30 15% At least 1 yr
20 10%
10 5%
0 0%
1 1.5 2 2.5 3 3.5 4 1.0 1.5 2.0 2.5 3.0 3.5 4.0
Survey Score Survey Score
(similar charts were done for several characteristics)
9. Data Mining and Geocoding
Location of students
served together with
school attendance
areas.
Student color
indicates number of
target demographics
student has.
Results used for
geographically-
concerned purposes.