Opus (Faculty Information System) Opus: Project Review. CITI: December 14, 2012

Transcription

1 Opus (Faculty Infrmatin System) Opus: Prject Review CITI: December 14, 2012

2 Agenda 1. Overview & Prject Status 2. Technical verview 3. Plicy verview 4. Resurces verview

3 Purpse Design, build, & release a faculty infrmatin system f recrd fr UCLA.

4 High Level Design

5 Csts f Paper-based Systems Typical ffice wrkers spend: 40% f their time lking fr infrmatin 500 hurs annually reviewing and ruting files 150 hurs lking fr incrrectly filed dcuments The average dcument is cpied 9 times (Gartner, 2007) The main csts f paper dcumentatin fall int cpying, delivery, handling, strage, and retrieval f that paper, with cpying csts at 33% and distributin csts at 56%, accrding t ne study. The average rganizatin spends abut: $20 in labr t file each paper dcument $120 in labr searching fr each misfiled dcument $220 in re-creatin f a dcument (PWC, 2009)

6 Existing Systems at UCLA DAT Dssier Actin Tracking (Academic Persnnel Office) RevSec Review Sectin system (Academic Persnnel Office) LS Dssier (Life Sciences, Schl f Engineering) SSC Recruit System Recruitment system (Scial Sci, Andersn) Recruit system Recruitment system (Cmputer Science) LS Suth Recruit System Recruitment system (Life Sciences) Applicant Tracking Database Demgraphic survey fr academic jb applicants (Cllege) HeadHunter Recruitment sftware (Ecnmics) VITAE Hmegrwn faculty prfile system (LONI, Schl f Medicine) Faculty DB Hmegrwn faculty data prfile system (Schl f Medicine) LEAD Lngitudinal electrnic academic database (Academic Persnnel, APB) FAST Faculty salary tracking database (Academic Persnnel, APB) Five years ag, estimates put the cst f AP prcessing at UCLA at 10.3 millin per year

7 Opus: Wrk t Date CITI: December 14, 2012

8 Executive Steering Cmmittee Endrsed general design cncept and scpe Cnducted brad survey f campus needs Cnducted interviews at each schl Priritized list f system features Dcumented and framed plicy cncerns Drafted Terms f Use Created high level business requirements Defined data utline/categries fr a standardized dssier (with examples) Recmmended a standard data utline t CAP, and circulated it t faculty

9 Opus Team Established prject charter, gvernance, initial staffing, and crss-rganizatinal resurces Cnducted feasibility studies n existing campus and UC systems Created high level architecture, design and baseline business requirements Launched and supprted all wrk grup and cmmittee activity (privacy, external surces, bk f recrd) Cmpleted cmprehensive technical analysis f UCD system My Inf Vault Wrked with campus UC PATH team n interdependencies (e.g., data warehuse) Crdinated business prcess mapping fr APO Cnducted survey and analysis f campus faculty recruiting practices Deplyed and supprted UCLA Academic Recruit

10 Opus: Technical Overview CITI: December 14, 2012

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12 Gap Analysis N Architecture Gap Ptential Slutin Dependencies 1 Business System fr string and managing faculty infrmatin Electrnic academic tracking and review Standard electrnic data utline Autmatic ppulatin f dssier data fields where available Academic Persnnel decisin supprt and business intelligence Data prtectin and integrity Build Opus t incrprate data frm existing electrnic systems as well as paper recrds. Build Opus t leverage DAT and/r MIV wrkflw and audit functins Define and implement a standard data utline fr data cllectin and reprting. Tl/wrkflw t pass data between Opus and UC Path Leverage existing enterprise reprting tls as apprpriate Create ad hc transactinal reprts in Opus where necessary Cnsistent data Recmmendatin f Bk f Recrd wrkgrup Viability f data surces Outcme f DAT feasibility study Apprval f Senate Inventry f reprting needs Ability fr existing enterprise reprting tl t supprt the reprting requirements Identify transactinal reprting need Maintain data cnsistency Resurce availability 2 Infrmatin A system t aggregate and present faculty data in a meaningful way Cmmn definitin f data elements Authritative and cnsistent data acrss HR and APO and frm department t central administratin Opus Standard data dictinary Create prcess t imprt authritative faculty data frm internal and external surces Declare authritative data surces Disallw mdificatin f authritative data in dwnstream systems Data crrectin takes place in system f recrd Adequate funding fr infrastructure and staffing Data gvernance, plicy, and prcess Identificatin and viability f authritative data surces Exercising and enfrcing data gvernance Scpe f functinality in the UC Path case mgmt tl 3 Applicatin Repsitry fr faculty infrmatin Business lgic engine fr academic wrkflw Data aggregatrs and translatrs Granular permissins management Create central Opus repsitry Aggregate data frm data surces Leverage DAT, MIV and r pen surce BPM / BPEL slutins VIVO, KM Data, bibligraphic database APIs r custm slutin Gruper-DACSS r custm access management Technlgy selectin Feasibility studies Availability f rich and flexible wrkflw engine Terms f SLA Availability f interperable service APIs Clear dcumentatin and supprt Capability and maturity f existing slutin

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15 Opus: Plicy Overview CITI: December 14, 2012

16 High Pririty Requests frm Campus Standard dssier utline. Clear definitins fr schlarly activities. Specific guidance n reprting Service. Criteria t be included in the self-statement. Best practices student & peer teaching evaluatins.

17 Plicy Effrts Privacy, Public Access & Apprpriate Use Create a jint wrkgrup between Privacy Bard, Steering Cmmittee and campus cunsel t create educatinal recmmendatins, identify plicy gaps. Cllect use cases r user stries f challenging scenaris t understand campus cncerns. Dialgued with Privacy Bard, Opus Executive Steering, and campus cunsel t discuss access t and uses f faculty prductivity data. Reviewed applicable plicies and standards acrss UCLA, the UC system and ther tier ne research institutins. Understand UCLA s current reprting requirements, needs and challenges s that we have a clear picture f the present envirnment. Drafted Terms f Access and Apprpriate Usage language with Campus Cunsel, Privacy Bard, and Steering Cmmittee.

18 Plicy Effrts Bk f Recrd & Master Data Management Cnvened diverse interview team that will initiate deep-dive interviews with campus data stewards t cllect details n faculty infrmatin residing in systems. Wrk with campus data warehuse grup and UCLA PATH prject team t understand the future technical landscape. Held brad discussins with crss-campus data stewards regarding enterprise data challenges and gals. Reviewed best practices and prcesses fr master data management initiatives and created methdlgy fr carrying ut the interviews. Identify and recmmend ways t recncile disparate data and create paths t crrect errneus data. Determine the effective Bk f Recrd fr each faculty data type (e.g., curse enrllment wuld reside in Registrar system).

19 Opus: Resurces Overview CITI: December 14, 2012

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21 Team Rster / Cntact inf Meg Buzzi: Prject Directr mbuzzi@cnet.ucla.edu Shan Kandaswamy: Directr, IT Architecture skandaswamy@it.ucla.edu Heather Small: Prject Crdinatr hsmall@it.ucla.edu Ying Ma: Technical Prject Manager yma@it.ucla.edu Jhn Abbtt: Business Analyst jabbtt@cnet.ucla.edu