Program eval webinar final v2

© 2014 IBM Corporation

Using data to improve and predict outcomes for

nonprofitsAlex Oftelie – Subject Matter Expert, Non Profit Business Analytics, IBM

Mario Gallegos – Director of Quality and Systems Improvement, McKinley Children’s Center

© 2014 IBM Corporation2

Agenda:

Our point of view on Advanced Analytics

IBM Advanced Analytics Portfolio in Action

Advanced Analytics at McKinley Children's Place

Q&A


Our Point of View on

Advanced Analytics

© 2014 IBM Corporation 3


Why Program Evaluation?

Inform stakeholders on impact for

participants, strengths, and limitations

Discover problems or needs early to

prevent more serious problems later

Demonstrate ROI for grants and private gift

support


A focus on Predictive Analytics

Predictive Analytics helps connect data

to effective action by drawing reliable

conclusions about current conditions and

future events

Gareth Herschel, Research Director, Gartner Group


Advanced Analytics delivers ROI by upgrading operational

decisions

Evidence basedWhat you know

ProactiveAnticipate what´s likely to happen

DynamicAutomatically detect and

respond to changes

Based on “gut feel”What you think you know

ReactiveRespond to

what has happened

StaticLong time to adjust to

changing circumstances

FROM TO


Key challenges uncovered

Difficult to deliver end-to-end constituent analytics

solution able to consume, integrate, analyze, score and

determine most appropriate action with individual

constituents

Inability to gather and synthesize insights from analysis

of social, text and interaction data to generate real-time

information to predict sentiment and needs

Incomplete view of constituent information at the time of

interaction, resulting in inappropriate or incomplete

offers, communications or both

Inconsistent service delivery and weak constituent

relationships, resulting in poor service or high churn

Lack of channel integration and siloed lines across

organizations, causing inconsistent or fractured

constituent interactions

Focus on uncoordinated messaging offers — scattered

one-hit selling, instead of broader strategic message

Challenged in using analytics to add short-term value

or enhance long-term strategy


Predictive Analytics in 3 steps

AlignAlign your organization

around information

Manage, integrate and govern

both traditional and big data

information sources to create a

foundation for analytics

Anticipate See, predict, and shape

Organizational outcomes

• Understand, at all times, what is

happening & why

• Look forward to model & predict

what could be happening

ActAct with confidence at point of impact

• Embed analytics into key

organizational processes

• Empower a culture of data-

driven decision making

Transform

Learn

Capabilities include:

Data collection, statistical analysis, data mining, predictive modeling, text analysis, decision management


Analytics in K12



IBM SPSS Predictive Analytics for Student Performance

10

Student Information

Systems

Learning Management

Systems

Evaluations...

At-Risk Students

Indicators of Performance

Recommended Intervention

Principals

School Boards

Departments of

Education

Predictive Scores & Prescriptive Recommendations

Scorecards Reports & Analysis

Dashboards At-Risk Notification

Predictive Models

Early Literacy

Graduation Rate

Student Performance

Curriculum Evaluation…

Business Analytics

Full view of students

Results

STUDENT SUCCESS

1. Student back

on track

2. Dropout

avoided

3. Visibility,

transparency

Align Anticipate Act

Feedback Loop: outcomes fed back as additional data source for increased accuracy

Data mining & statistical analysis

uncovers hidden patterns &

associations within structured &

unstructured data


Business scenario: Lower graduation rates

Principal

“Our graduation rate of 69% is lower

than the average for a all other high

schools in our district of our size.

We must do something to address

this now.”

Student Guidance Counselor

“We are now able to better

identify those students at-risk

and get to them before the

situation escalates. This helping

to reduce drop-outs which was

impacting our graduation rates.”

District Superintendent

Sees improvement in the

graduation and drop-out rates

of the school and begins to

implement a district-wide

program.

Chief Financial Officer

“Predictive analytics has helped to

identify those students at risk before

it becomes an issue. Once

identified, we can put in place a

personal intervention strategy.”

Detect a

problem

Analyze the

situation

and build

models

Deploy

analytics to

solve the

problem

Monitor

improved

outcomes


Teachers Can proactively implement

personalized education plans

for at-risk students

PrincipalsCan determine, improve

and implement solutions

for low-performing

students before funding is

impacted

Budgeting and PlanningCan actively contend for grants

and incentive programs for

tangible progress in improved

graduation rates

School superintendents Can predict district performance

and track progress to ensure

schools are meeting

requirements for graduation rates

IBM SPSS Predictive Analytics for Student Performance:

Empowering decision-makers

AnalystsCan efficiently &

effectively gain deep

insight into student

performance


Capabilities Overview



The statistics approach involves:

• Forming a theory about a

possible relationship

• Converting it to a hypothesis

• Testing that hypothesis using

statistical methods

It is a manual, user-driven, top-

down approach to data analysis.

Statistics approach

The modeling approach involves:

• Interrogating the data

• Determining data by the

method and goal, rather than

by the user

It is a data-driven, self-

organizing, bottom-up

approach to data analysis that

works on very large data sets.

Modeling approach

The Modeling Approach is Different, but very useful


Classification

(or prediction)

Autoclassifiers, decision trees,logistics, supportvector machinesand time series

Predict group membership (e.g., will this student graduate on time?) or a number(e.g., how many students will struggle?)

Algorithms Usage

Segmentation

Autoclusters

and K-Means

Anomaly detection

Classify data points into groups

that are internally homogenous

and externally heterogeneous

Identify cases that are unusual

AssociationApriori, CARMA

and Sequence

Find events that occur

together or in a sequence

(e.g., a personalized educational

plan for at-risk students)

Full breadth of predictive techniques


Identify the context

and sentiment of

the text

Add Structure

to

Unstructured

Text

Text Analytics


Frontline staff and systems

benefit from recommendations,

offers and dashboards—

wherever they are needed.

• Rules

• Predictive

analytics

• Simulation and

optimization

• Scoring

Streaming data

Textual data

Applications data

Time series

Geotemporal

and geospatial

Relational

Social networks

Optimize decisions, predictions, and rules

© 2014 IBM Corporation18 © 2014 IBM Corporation 18

McKinley Children’s Center


McKinley Children’s Center

Founded in 1900, McKinley serves over 600 children and

families in the community offering the following services.

Special Education Services to both community and

children living in the center

Foster Care/Adoptions- Over 300 children, and 150

families

Mental Health- Over 200 children and families in the

community

Residential Care- We serve over 40 children.

McKinley’s mission is to provide a safe environment for

children that need help, and to provide services that will

improve our communities by offering:

Loving and stable homes for children

Rehabilitative and Psychological services

Case Management services


Analytics at McKinley

Measure outcomes and understand the make up of

the population we serve.

How can we improve those outcomes using data?

Access to data was key

Centralizing the data

The ability to manipulate the data

The ability to interact with the Data

The Ability to visualize data

The ability to set up systems that make the process

of data collection and data analysis easy for the

business user.


McKinley and IBM

McKinley decided to partner up with IBM because of their reputation for excellence.

The solution components offered by IBM fit our current needs for data analysis and

reporting.

The solution components are user friendly for the business user.

IBM has been supportive through this process.

IBM introduced us to a premier partner DATA 41 which helped us set up the

infrastructure for our data.

®


McKinley Children’s Center models and identifies variables that affect

permanency, helping improve child outcomes and program success

Solution Components

Business Challenge: McKinley Children’s Center sought to better understand the many

variables, such as age, ethnicity and types of serious incidents, that can affect a child’s

permanency. However, caseworkers used paper and pen to record data, plus manually

collected data from external databases, resulting in a highly fragmented view of each child’s

needs. The problem was not lack of information but rather an inability to access and analyze it in

an efficient and constructive manner.

The Smarter Solution: The center deployed a big data and analytics system that collects and

aggregates near-real-time data from disparate databases, giving caseworkers a comprehensive

view of each child’s profile plus an unprecedented understanding of how different social and

home variables affect that child’s success. Using modeling and predictive analytics,

caseworkers can uncover hidden patterns and relationships and use the insight to determine the

right combination of services for each child, identify risk factors, match children with adoptive

families, and speed progress toward an optimal outcome.

Most children receive services from multiple agencies. The solution enables data sharing with

other organizations, giving kids the best opportunity for success.

—Executive, McKinley Children’s Center

99% reductionin data collection time, from two

months to minutes, helping staff

spot trends in serious incidents

Pinpoints variablesthat affect positive outcomes,

helping ensure a better foster

home experience

Identifies at-risk kidshelping caseworkers reduce

frequency of serious incidents

• IBM® SPSS® Modeler

• IBM SPSS Statistics

• IBM Cognos® Business Intelligence

• IBM Business Partner Data41


Resources

SPSS Non Profit Resource Center

ibm.biz/smarterphilanthropy

Next Steps

Conversation

Alexander Oftelie

[email protected]

www.linkedin.com/in/alexoftelie/

Office: 303-353-7306


Questions


Technology

Program eval webinar final v2