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Decision Support System Dr. William Scroggins President Dr. Irene Malmgren Vice President of Instruction Bob Hughes Director, Enterprise Applications Systems.

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Presentation on theme: "Decision Support System Dr. William Scroggins President Dr. Irene Malmgren Vice President of Instruction Bob Hughes Director, Enterprise Applications Systems."— Presentation transcript:

1 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

2 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

3 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

4 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

5 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

6 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

7 Mt. SAC Story: Lost FTES

8 Scheduling 2014-2015 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...

9 Annual Targeting Example Example Funded FTES for Prior Year = 29371.99 Funded FTES for Prior Year = 29371.99 Growth = 3.5% Growth = 3.5% Unfunded FTES for Prior Year = 400 Unfunded FTES for Prior Year = 400 ((29371.99 * 1.035) – 400) = 30000 ((29371.99 * 1.035) – 400) = 30000 CR: 27000 (90%), 2400 ENHC_NC (8%), 600 NC (2%) CR: 27000 (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;...

10 Annual Targeting

11

12

13

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

15 Moving Target

16 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

17 Projection: Weighted Averages

18 Does the projection work? Spring 2012 AcctPotentialProjectedActualError #Error % W 8432.91928312.958381.98869.0380.824% IW 289.5956311.02266.01945.00116.916% ID 117.6122110.8297.940612.879413.150% D 374.2581395.12340.65154.46915.990% LD 33.202725.8728.37512.50518.829% LW 256.2772236.96224.405312.55475.595% TOTAL 9503.8659392.749339.37953.3610.571%

19 Does the projection work? Fall 2012 AcctPotentialProjectedActualError #Error % W 8980.06588939.189004.844565.66450.729% IW 294.9029323.12268.302754.817320.431% ID 146.9111148.73123.459625.270420.469% D 393.9151385.57337.166448.403614.356% LD 29.333327.4929.02631.53635.293% LW 234.8028208.51228.189819.67988.624% TOTAL 10079.93110032.69990.989341.61070.416%

20 Does the projection work? Spring 2013 AcctPotentialProjectedActualError #Error % W 9147.37028924.058839.006985.04310.962% IW 320.2368337.38290.774646.605416.028% ID 141.3104131.81116.716815.093212.931% D 426.6003445.74359.18986.55124.096% LD 27.805323.826.23122.43129.268% LW 271.2639245.29231.692813.59725.869% TOTAL 10334.586910108.079863.6113244.45872.478%

21 Does the projection work? Fall 2013 AcctPotentialProjectedActualError #Error % W 9444.01419523.719263.0738260.63622.814% IW 350.3353418.18314.465103.71532.981% ID 189.386215.32162.354552.965532.623% D 369.7928397.66317.520380.139725.239% LW 93.0252124.583.073641.426449.867% TOTAL 10446.553410679.3710140.487538.88285.314%

22 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

23 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

24 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

25 Demand 90%+ Fill

26 Response?

27 Waitlists

28 Registration Acceleration

29 Lagging Courses

30

31 Room Usage

32 Excluded CRNs From 320

33 Sandbox

34 Sandbox

35 Sandbox

36 Sandbox

37 Sandbox

38 Sandbox

39 Sandbox

40 Sandbox

41 Sandbox

42 Sandbox

43 Sandbox

44 Sandbox

45 Sandbox

46 Sandbox

47 Sandbox

48 Sandbox

49 Sandbox

50 Sandbox

51 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

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