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, DeanCorporate Training & Economic DevelopmentNortheast Wisconsin Technical College [email protected]
Charlene Templeton, Executive DirectorCommunity and Professional ProgramsAnne Arundel Community [email protected]
Presenter
Charlene TempletonExecutive DirectorCommunity and Professional
ProgramsAnne 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”
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
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
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
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.
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
AACC Noncredit Enrollment
FY 2008 FY 2009
AACC Weekly Enrollment Report
0.59180.85
34.73.77
52.5917.77
1140.060.0832.5
417.6524.7918.7120.04
84.821.76010.3600.020
75.4753.68
4.47124.33
66.07115.81
531.6730.9418.89
352.820
158.153573.36
0.37123.8
28.682.5848.27
22.881148.33
090.96
409.5122.5219.4619.58
82.865.240.022.130.100.34
78.259.69
10.86115.44
77.3496.33
604.3223.0517.06
352.540.54
143.433606.43
0.00 500.00 1000.00 1500.00 2000.00 2500.00 3000.00 3500.00 4000.00
Women
TEPD
Technology
Seniors
OCO
NG
LLY
HCAT
FON
EXTL
ESL
CWSO
CCT
Correctional
CNS
Center on Aging
FY08 & FY09 Comparison Totals
AACC CE Eligible FTE - FY2009/2008 Comparison
5/4/2009
5/5/2008
AACC Weekly Dashboard
Indicator FY 2009:Q1 FY 2009:Q2 FY 2009:Q3 FY 2009:Q4 Total2010
BenchmarkFunded Productivity FY 09 to Date Goal
5. Online Class Enrollment Non-Credit Eligible FTE 3606.43 3,819b. Noncredit 387 210 343 218 1,158 1,750 Credit OE FTE (HRM & EDU) 320.33 313
24. Workforce DevelopmentCAPS Contract Credit (HRM & EDU) 16.13 20
a. Headcount 6,366 5,593 5,747 17,706 18,736 Total 3942.89 4,152b. Enrollment 11,079 9,352 10,021 30,452 42,169
25. Licensure or CertificationNon Funded/Funded Elsewhere Productivity
FY 09 to Date Goal
a. Headcount 784 886 507 2,177 4,661 Non-Credit Non-Eligible FTE 357.6 520.0b. Enrollment 920 1,057 618 2,595 6,644 CWS Contract Credit 70 60.0
26. Number of business organizations provided contract training (provided by K. McArthur from FY07 data) CAPS Contract Credit (OCC) 22.96 12.046 27 20 93 98 Total 450.56 592.0
27. Contract Training (Cheryl and IR)a. Headcount 9,981 18,200b. Enrollment 19,785 40,541
28. Employer satisfaction with contract training (%) (provided by CWS)Very satisfied 69% 71.4% 95%
Satisfied 31% 28.6%Neutral 0% 0.0%
Dissatisfied 0% 0.0%Very Dissatisfied 0% 0.0%
29. Noncredit community service and LLL courses (General Education)a. Headcount 4,986 4,990 5,307 15,283 15,632b. Enrollment 8,474 9,545 9,825 27,844 39,075
30. Basic Skillsa. Headcount 1,757 1,134 1,645 4,536 4,960b. Enrollment 2,425 1,134 2,070 5,629 7,993
MHEC Indicators Enrollment Summary
AACC Continuing Education Workforce Development Dashboard Summary FY 2009Week of May 4, 2009
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 Innovationhttp://www.league.org/index.cfm
• Websites - Listings in other community college catalogues
Presenter
Laurie Radke, DeanCorporate Training & Economic
DevelopmentNortheast Wisconsin Technical College [email protected]
Data Beyond Delivery
• 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
Operational Challenges
• 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
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
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
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
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
Questions and Answers
Presenters
Laurie Radke, DeanCorporate Training & Economic DevelopmentNortheast Wisconsin Technical College [email protected]
Charlene Templeton, Executive DirectorCommunity and Professional ProgramsAnne Arundel Community [email protected]
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