Strategies for an Economic Downturn Learn effective strategies for making data driven decisions to keep your operations afloat during tough economic times

Presenters Laurie Radke, Dean Corporate Training & Economic Development Northeast Wisconsin Technical College 920-498-6995 [email_address] Charlene Templeton, Executive Director Community and Professional Programs Anne Arundel Community College 410-777-2662 [email_address]

Laurie Radke, Dean

Corporate Training & Economic Development

Northeast Wisconsin Technical College

920-498-6995

[email_address]

Charlene Templeton, Executive Director

Community and Professional Programs

Anne Arundel Community College

410-777-2662

[email_address]

Presenter Charlene Templeton Executive Director Community and Professional Programs Anne Arundel Community College

Charlene Templeton

Executive Director

Community and Professional Programs

Anne Arundel Community College

What is Data-Driven Decision-Making? Use of data and relevant background information, to inform decisions related to planning and implementing program strategies at all levels of the institution. “ Achieving the Dream”

Use of data and relevant background information, to inform decisions related to planning and implementing program strategies at all levels of the institution.

“ Achieving the Dream”

Why is Data-Driven Decision-Making Important? Research shows that if planning is based on assessment information relevant to the desired courses/programs you want to offer, the probability is increased that they will meet financial and FTE goals. Meet student needs

Research shows that if planning is based on assessment information relevant to the desired courses/programs you want to offer, the probability is increased that they will meet financial and FTE goals.

Meet student needs

Going From “if you build it they will come” to Making Informed Decisions Data-driven decision making is a relatively recent idea that has emerged in the last 10-15 years in response to the perceived lack of informed decisions due to: Most institutions rely on a transaction processing system as the primary platform to support their needs for information and analysis Many institutions use advanced applications of academic analytics most frequently in student services and least frequently in grants and continuing education management Use of analytics varies in functional area Data was experiential

Data-driven decision making is a relatively recent idea that has emerged in the last 10-15 years in response to the perceived lack of informed decisions due to:

Most institutions rely on a transaction processing system as the primary platform to support their needs for information and analysis

Many institutions use advanced applications of academic analytics most frequently in student services and least frequently in grants and continuing education management

Use of analytics varies in functional area

Data was experiential

Reasons to Implement Data-Driven Decision-Making College administrators and legislators demand for evidence based results Quality improvements in all current reporting information Increased awareness of financial/programming information Staff is being held more accountable for making sound business decisions. Consider information about the demographic and instructional variables that influence programs Identifying trends, cycles and seasonability in time Ability to understand the economic/business landscape and respond to it

College administrators and legislators demand for evidence based results

Quality improvements in all current reporting information

Increased awareness of financial/programming information

Staff is being held more accountable for making sound business decisions.

Consider information about the demographic and instructional variables that influence programs

Identifying trends, cycles and seasonability in time

Ability to understand the economic/business landscape and respond to it

Choices of Technology Platforms Level 1 – Transactional system Level 2 – Operational data storage in conjunction with an extract, transform and load tool – queries Level 3 – Enterprise data warehouse and/or multiple data marts used in conjunction with an load tool, online analytical processing tools or executive dashboard.

Level 1 – Transactional system

Level 2 – Operational data storage in conjunction with an extract, transform and load tool – queries

Level 3 – Enterprise data warehouse and/or multiple data marts used in conjunction with an load tool, online analytical processing tools or executive dashboard.

Process For Making Data-Driven Decisions

Anne Arundel Community College’s Operations Staff Processed 62,000 + registrations Section maintenance of 12,000 + sections 5,000 + room assignments Generated 7,500 + student evaluation packets Generated 4,500 + faculty contracts Responded to over 35,000 telephone calls

Processed 62,000 + registrations

Section maintenance of 12,000 + sections

5,000 + room assignments

Generated 7,500 + student evaluation packets

Generated 4,500 + faculty contracts

Responded to over 35,000 telephone calls

AACC Noncredit Enrollment FY 2008 FY 2009

FY 2008

FY 2009

AACC Weekly Enrollment Report

AACC Weekly Dashboard

Resources Economic Modeling Specialist Inc. http://www.economicmodeling.com/ Official websites for your state http://www.maryland.gov Data Mining http://www.statisticsjobs.com/ http://www.SASjobs.com NCCET http://www.nccet.org/ League of Innovation http://www.league.org/index.cfm Websites - Listings in other community college catalogues

Economic Modeling Specialist Inc. http://www.economicmodeling.com/

Official websites for your state

http://www.maryland.gov

Data Mining

http://www.statisticsjobs.com/

http://www.SASjobs.com

NCCET

http://www.nccet.org/

League of Innovation

http://www.league.org/index.cfm

Websites - Listings in other community college catalogues

Presenter Laurie Radke, Dean Corporate Training & Economic Development Northeast Wisconsin Technical College 920-498-6995 [email_address]

Laurie Radke, Dean

Corporate Training & Economic Development

Northeast Wisconsin Technical College

920-498-6995

[email_address]

Data Beyond Delivery Data is critical when making decisions related to infrastructure and process Growth and sustainability is expected

Data is critical when making decisions related to infrastructure and process

Growth and sustainability is expected

But We Are In A Recession Did you know historically the most innovative time for the United States was during the Great Depression Think, create and innovate

Did you know historically the most innovative time for the United States was during the Great Depression

Think, create and innovate

Operational Challenges Decreased Budget Reduced Staffing Increased demand for services Skilled worker shortage Decrease in traditional revenue streams

Decreased Budget

Reduced Staffing

Increased demand for services

Skilled worker shortage

Decrease in traditional revenue streams

When the data tells you to build capacity and you don’t have $$$ Become “Lean” – to increase capacity to serve more with the same Lean Office Maintain a continuous improvement model Build Strategic partnerships

Become “Lean” – to increase capacity to serve more with the same

Lean Office

Maintain a continuous improvement model

Build Strategic partnerships

Continuous Improvement Three Key Objectives 1. Identify waste and variation in your process 2. Apply tools to reduce and/or eliminate waste and variation 3. Make your process flow

Three Key Objectives

1. Identify waste and variation in your process

2. Apply tools to reduce and/or eliminate waste and variation

3. Make your process flow

Lean/Six Sigma Define Lean- A systematic approach to identify and eliminate waste (non-value added activities) through continuous improvement. Define Six Sigma- is an organized approach to continually improve the performance of a process by discovering the causes of variation

Define Lean- A systematic approach to identify and eliminate waste (non-value added activities) through continuous improvement.

Define Six Sigma- is an organized approach to continually improve the performance of a process by discovering the causes of variation

Characteristics of Six Sigma Data and measurement based Uses wide range of statistical tools and root cause analysis skills Uses wide range of project management skills Follows a disciplined series of steps Team oriented

Data and measurement based

Uses wide range of statistical tools and root cause analysis skills

Uses wide range of project management skills

Follows a disciplined series of steps

Team oriented

Partnerships Data indentifies customer need Required to build content and capacity without budget or staff Partnership and collaborate Develop MOU with outside vendor CrossRoads- simulated driving Optima – Lean consulting Ed2go

Data indentifies customer need

Required to build content and capacity without budget or staff

Partnership and collaborate

Develop MOU with outside vendor

CrossRoads- simulated driving

Optima – Lean consulting

Ed2go

Questions and Answers

Presenters Laurie Radke, Dean Corporate Training & Economic Development Northeast Wisconsin Technical College 920-498-6995 [email_address] Charlene Templeton, Executive Director Community and Professional Programs Anne Arundel Community College 410-777-2662 [email_address]

Laurie Radke, Dean

Corporate Training & Economic Development

Northeast Wisconsin Technical College

920-498-6995

[email_address]

Charlene Templeton, Executive Director

Community and Professional Programs

Anne Arundel Community College

410-777-2662

[email_address]