Consolidated Faculty Analysis and Reporting (CFA) Decision Support

Transcription

1 Consolidated Faculty Analysis and Reporting (CFA) Decision Support

2 Presentation Outline Background Challenges Products Demo Timeline Fine Print what problem are we solving? why is it hard now? what is our solution? how does it work in action? when can we get it? what are the limitations? Q&A

3 What s the problem? Slide 3 Common challenge: understanding range of activities faculty are involved in Evaluating research productivity Making promotion and tenure decisions Determining where to best allocate scarce resources Responding to surveys Common needs identified by Colleges Integrated info on Faculty activity Better tools for analysis and decision making

4 Why is this so hard now? Slide 4 Very difficult to pull faculty info together Data resides in multiple subject areas Employee Payroll Grants Proposals Employee Position/Job Student Registration Many different grains and time periods Complex business rules to connect pieces Reports aren t very good for analysis Reports are the hammer, but this isn t a nail Creating more reports isn t the answer Analysis (not just creating lists) requires new approach

5 Analysis vs. Reporting Faculty Activity Analysis: Example Use Case Research Productivity Report mode Dynamic exploration and analysis I act I learn I get data So I ask I want to know Research Productivity How much grant $ are we spending? Inception to Data Grant Expenses How much by Department? ITD Grant Expenses by Department There is a wide disparity between departments (e.g. Dept A has 10x Dept B) Why? Volume of proposals? Dept C had almost as many proposals as Dept D, but a lower hit rate (<½) and requested much less $ (~25%) Schedule review meeting with Dept head Proposals and $ requested for top and bottom depts Dept E was lowest because had fewer proposals, even through more $ proposed than Dept F, also very low hit rate Schedule review meeting with Dept head Dept A was highest not because highest hit rate, but because far more proposals for far more $ (4x as much as next highest) Disclaimer: this is a contrived and greatly oversimplified example for illustration and discussion purposes only and does not reflect actual analysis based on a complete set of data. Where are these coming from? Share stats with Departments and encourage more higher $ proposals By Tenure Description As expected, tenured faculty are producing the vast majority of research activity Few key individuals? A number of faculty members are highly active, not just a few Faculty recognition program By Name Several non-tenured faculty members are also fairly active Review tenure status

6 Analysis vs. Reporting Dynamic Analysis (OLAP * ) is about exploring data Slice and dice on the fly Look for patterns and trends Identify for outliers and exceptions Find relationships Answer questions, develop insights, etc. Analysis is iterative: one question leads to another For analysis, OLAP is much better than Reports Analysis doesn t replace Reporting needs either *On-line Analytical Processing

7 Analysis vs. Reporting Traditional Reports Mostly static Specific questions Tech expertise to create Business expertise Dynamic Analysis (OLAP)* Dynamic Exploration No programming Business expertise *On-line Analytical Processing

8 Products What is the solution DS built?

9 Product Roadmap: in the beginning BI Products Grants Pre- Award Grants Streamlined HR Position/ Job BOS Expenses Grant ICR Employee Admin Registration Complete EDW Position/Job Rank/Tenure Proposals Grants Payroll Employee Course/Section Registration

10 Product Roadmap Several different kinds of needs Easy-to-use faculty data spanning subject areas Dynamic exploration, slice and dicing Create lists of faculty with summary data The right tool for the right job Consolidated faculty data: data mart Custom Reporting: Business Objects Universe Analysis: OLAP Cube Comprehensive solution with several connected parts

11 Product Roadmap Product Planning: Faculty Workload BI Products Create lists or summaries of faculty activity Evaluate research & teaching productivity Promotion and tenure Analyze resource allocation Respond to surveys Pre-packaged analysis CFR Universe CFA Cube Faculty Analysis Templates Data Presentation Layer Consolidated Faculty Info EDW Foundation / Source Layer Proposals Grants Position/Job Rank/Tenure Payroll Employee Course/Section Registration DMI Student Flat Files

12 The Products: Consolidated Data 50+ columns of integrated data Finance: proposals, grants, ICR, grant employees HR: jobs, college, depts, FTE, headcount, payroll, tenure Student: courses, credit hours, contact hours, students One row per faculty member (per fiscal year) Resolves rules for aggregation Defines faculty for analysis purposes Includes totals for faculty across all colleges (e.g. grant expenses) and totals for just my college Job College concept ensures each college sees the correct info for the my college totals Includes fiscal year totals starting from FY05

13 The Products: Reporting Business Objects Universe Same underlying data Custom reports Ad-hoc queries Easier to use than many other BO Universes

14 The Products: Analysis OLAP* Cube SQL Server/MS Analysis Services 2005 Data sourced from EDW and IR Monthly refresh (3 rd Saturday) Excel 2007 as the front end Familiar Fairly easy to use, but still powerful Connected to the data in the cube *On-line Analytical Processing

15 Demonstration Let s see what this looks like in action!

16 CFR (Reporting) Product Demo Example Scenario Create recognition and reward mechanisms that enhance productivity and achieve balance between teaching, research, and community service What can the available data tell us about our balance between teaching and research? Traditional approach is to look at a report List of all faculty by department, with lots of columns of data Note: take this example with a grain of salt

17 CFR Product Demo

18 CFA (Analysis) Product Demo Reports are great for defined answers Generating lists Looking up specific values Recall the scenario: what can the available data tell us about our balance between teaching and research? We don t know exactly what we re looking for Ask questions and see where the data takes us This is an exploration, i.e. analysis not reporting

19 CFA Product Demo

20 CFA Product Demo Data Home Dept Name Grant Expense Amt FTE Fall - Number of Contact Hours $/FTE Contact Hr/FTE Electrical & Computer Eng $ 29,882, ,459 $ 303, Physics $ 18,148, ,939 $ 251, Civil & Environmental Eng $ 17,054, ,208 $ 309, Computer Science $ 16,329, ,667 $ 262, Mechanical Science & Engineering $ 16,239, ,770 $ 291, Materials Science & Engineerng $ 13,186, ,961 $ 517, Engineering Administration $ 5,906, ,040 $ 633, Aerospace Engineering $ 4,099, ,480 $ 204, Nuclear Plasma & Rad Engr $ 2,560, ,365 $ 241, Bioengineering $ 1,799, $ 257, Industrial&Enterprise Sys Eng $ 1,207, ,323 $ 48, Materials Research Lab $ 534, $ 267, Computational Science & Engr $ 361, $ 90, Technology Entrepreneur Ctr $ $ Micro and Nanotechnology Lab $ $ Coordinated Science Lab $ $ $ 127,309, ,754 $ 283, Average $ 127,309, ,754 $ 127,309, ,754

21 CFA Analysis Templates Analysis challenges Different way of thinking than reports Many paths to explore, where to start? Coming soon: pre-authored analytic dashboards Pre-defined views of the data are already provided to jump start the analysis Place to start Advanced visualizations make it easier to see patterns and relationships in the data

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23 CFA Product Demo Explore areas of interest in more depth Pick one of the outliers (e.g. a dept that s more research intensive) Dig into that department, and look at individual faculty

24 CFR (Reporting) Product Reprise Same Example Scenario Create recognition and reward mechanisms that enhance productivity and achieve balance between teaching, research, and community service We ve done the analysis, now we know what report we want: a listing of total Contact Hours, Research $, and FTE per Faculty member by Tenure and Department

25 Timeline So when can we get our hands on this?

26 Timeline Initial deployment mid-april Consolidated Data CFA OLAP Cube CFR Business Objects Universe Analysis Templates coming in May Getting access Your USC will be able to request access Getting help Beth Ladd

27 Fine Print What are the limitations and other considerations about these products?

28 Fine Print Business context vital to understanding the story behind the numbers Business rules used to combine and simplify data Worked out with reps from 8 different colleges across the 3 campuses plus each campus IR office Complex, but provide important info Only as good as the source data Often a starting point, not an ending point

29 Fine Print Several key aspects of faculty activity not included, e.g. service, scholarship You can t boil faculty contribution down to just a row of numbers Promotion and Tenure process relies heavily on qualitative evaluation

30 Sample Tenure Review Process No No Inform. End. Inform. End. No Exec Officer* Review Case, ask for CV Proceed? Yes Create Ad-Hoc, compile institutional data Proceed? Yes Get reviewer names, Contact for letters Proceed? Yes P To Coll Review Case Quantitative Data Exec/Advisory Committee P&T Committee + Review Case Provide External Reviewer Names Evaluate, Request Clarification** Y/N Y/N Updated CV, create statements PO Provide External Reviewer Names Update and Revise PO Ad-Hoc Committee Provide External Reviewer Names Candidate External Reviewer note: + in some cases, the full P&T Committee includes all full professors. A smaller subset, the P&T Review Committee, then oversees the Ad-Hoc and provides feedback to the full Committee. The basic process remains the same, with the full P&T providing the votes. note: * in the case of a Dept Chair, the Executive Committee actually makes the decisions to proceed or not ** the P&T committee may interact w/exec Officer rather than directly with the Ad-Hoc

31 How does this fit in with P&T? High level summaries and analysis Comparative Patterns and insight Quantitative College FAA Department In depth review 1 at a time Evaluation Qualitative

32 Q&A You ve got questions Also, please take a moment to fill out your surveys!