Decision Support System Dr. William Scroggins President Dr. Irene Malmgren Vice President of Instruction Bob Hughes Director, Enterprise Applications Systems Daniel Lamoree Sr. Systems Analyst/Programmer RP Group Conference 2014 April 10 th, 2014

The Role of Executive Leadership President’s Cabinet President’s Cabinet Decision Support System given high priority Decision Support System given high priority Regular updates to Cabinet Regular updates to Cabinet Instruction Team Instruction Team Demonstration of application to Deans Demonstration of application to Deans Gather Feedback Gather Feedback

IT and Research Collaboration Information Technology staff goal – protect the data; restrict access Information Technology staff goal – protect the data; restrict access Researchers goal – more data leads to better decision- making Researchers goal – more data leads to better decision- making When these units are in different divisions, the need for cooperation and collaboration is critical When these units are in different divisions, the need for cooperation and collaboration is critical

The approach at Mt. SAC Data Users Group (DUG) meeting – every 2 weeks Data Users Group (DUG) meeting – every 2 weeks Researchers Data Warehouse (RDW) instance of the Banner Database Researchers Data Warehouse (RDW) instance of the Banner Database Report Designer access to Argos DEV Report Designer access to Argos DEV SQL training of Researchers by IT Staff SQL training of Researchers by IT Staff

Leveraging Talent Director of RIE recognized a team member with a unique aptitude for programming Director of RIE recognized a team member with a unique aptitude for programming Director of EAS (Enterprise Resource Applications) responded to a need for a Decision Support System Director of EAS (Enterprise Resource Applications) responded to a need for a Decision Support System Best solution – temporary reassignment of a researcher to IT as a programmer Best solution – temporary reassignment of a researcher to IT as a programmer Located in IT Located in IT Build trust with other IT staff Build trust with other IT staff Improved access to data Improved access to data

Learning Objectives 1.How Mt. SAC calculates FTES Targets 2.How Mt. SAC decides sections to add or cut 3.How Mt. SAC Deans develop prospective schedules

Mt. SAC Story: Lost FTES

Scheduling Overview Top-Down Approach Top-Down Approach Get Annual FTES Target Get Annual FTES Target Distribute Annual Target between CR, ENHC_NC, NC Distribute Annual Target between CR, ENHC_NC, NC Grow only Credit? Distribute as before? Grow only Credit? Distribute as before? Distribute CR, ENHC_NC, NC among Terms Distribute CR, ENHC_NC, NC among Terms Grow Summer (yes, please)? Fall? Winter? Spring? Grow Summer (yes, please)? Fall? Winter? Spring? Distribute FTES among Divisions... Distribute FTES among Divisions...

Annual Targeting Example Example Funded FTES for Prior Year = Funded FTES for Prior Year = Growth = 3.5% Growth = 3.5% Unfunded FTES for Prior Year = 400 Unfunded FTES for Prior Year = 400 (( * 1.035) – 400) = (( * 1.035) – 400) = CR: (90%), 2400 ENHC_NC (8%), 600 NC (2%) CR: (90%), 2400 ENHC_NC (8%), 600 NC (2%) 10% Summer; 42% Fall; 8% Winter; 40% Spring 10% Summer; 42% Fall; 8% Winter; 40% Spring Of 10% Summer: 36.22% HSS;... Of 10% Summer: 36.22% HSS;...

Annual Targeting

Just one catch... Just one catch...

Moving Target

Minimizing Spring Uncertainty Knowns Knowns Sections Scheduled for Spring Sections Scheduled for Spring Scheduled Hours per Section for Spring Scheduled Hours per Section for Spring Historical Fill Rate for Spring Historical Fill Rate for Spring Unknowns Unknowns Future Contact Hours (Fill Rate for WSCH/DSCH or PACH) Future Contact Hours (Fill Rate for WSCH/DSCH or PACH) Mt. SAC Decision Mt. SAC Decision Projection Projection

Projection: Weighted Averages

Does the projection work? Spring 2012 AcctPotentialProjectedActualError #Error % W % IW % ID % D % LD % LW % TOTAL %

Does the projection work? Fall 2012 AcctPotentialProjectedActualError #Error % W % IW % ID % D % LD % LW % TOTAL %

Does the projection work? Spring 2013 AcctPotentialProjectedActualError #Error % W % IW % ID % D % LD % LW % TOTAL %

Does the projection work? Fall 2013 AcctPotentialProjectedActualError #Error % W % IW % ID % D % LW % TOTAL %

What happened? No variance in pervious years; easy to project when fill rates hover around 100% (after drops and adds) No variance in pervious years; easy to project when fill rates hover around 100% (after drops and adds) What now? What now? More robust model, an actual predictive model More robust model, an actual predictive model Will that help given downward trends? Always 1 year or term behind? Will that help given downward trends? Always 1 year or term behind? Maintain Agility Maintain Agility Reporting via Argos and APEX Reporting via Argos and APEX Sandboxing via APEX Sandboxing via APEX

APEX Highlights Highlights Oracle’s primary tool for developing Web applications using SQL and PL/SQL Oracle’s primary tool for developing Web applications using SQL and PL/SQL Only requires web browser to develop Only requires web browser to develop No cost option of the Oracle Database No cost option of the Oracle Database

Reports What sections should we add? What sections should we add? Demand Demand 90%+ Fill 90%+ Fill Waitlists Waitlists Registration Acceleration Registration Acceleration What sections should we cut? What sections should we cut? Lagging Sections Lagging Sections Registration Acceleration Registration Acceleration What else? What else? Room Usage Room Usage Excluded CRNs Excluded CRNs

Demand 90%+ Fill

Response?

Waitlists

Registration Acceleration

Lagging Courses

Room Usage

Excluded CRNs From 320

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Future Building Predictive Model Building Predictive Model Room/Space Efficiency Room/Space Efficiency Reporting Off Sandboxes Reporting Off Sandboxes Task/Directive Assignment Task/Directive Assignment