Rensselaer Data Warehouse Project. Financial Analysis Requirements Findings. Last saved on 1/25/02 Page 1

Transcription

1 Rensselaer Data Warehuse Prject Financial Analysis Requirements Findings Last saved n 1/25/02 Page 1

2 OVERVIEW... 3 BACKGROUND... 3 PROCESS AND PARTICIPANTS... 3 Finance... 3 Administratin... 3 Schls... 4 Prvst... 4 DOT CIO... 4 Student Life... 4 KEY OPERATIONAL REPORTS... 4 BUSINESS REQUIREMENTS SUMMARY... 5 HIGH LEVEL OBJECTIVES... 5 INFORMATION AND ANALYTIC REQUIREMENTS... 6 FINANCIAL ANALYSIS SUCCESS CRITERIA... 8 DATA WAREHOUSE RECOMMENDATIONS... 9 Last saved n 1/25/02 Page 2

3 Overview Backgrund The Rensselaer Data Warehuse prject will enable management t better leverage infrmatin cllected within current peratinal systems t help in their decisin making prcess. Thrugh a frmal priritizatin effrt, Rensselaer identified key analytical subject areas and selected Financial Analysis as the infrmatin required in fr phase I. T ensure all requirements were clearly understd and t help define the financial analysis scpe, a detailed requirements prcess was cnducted. The prcess cnsisted f tw primary effrts, analyzing existing mnth-end financial reprts and cnducting detailed requirements meetings with business representatives thrughut the institute. The key bjectives f this effrt were t: Identify detailed financial reprting and analytical requirements. Develp an understanding f surce systems and identify data issues. Ensure the academic and administrative requirements thrughut the institute are fully understd. Finalize the scpe f the Financial Analysis subject area. Prcess and Participants Ten interviews were cnducted with twenty individuals representing bth the administrative and academic rganizatins f the institute. The interviews cncentrated n the financial analysis area, reviewing specific reprts, shadw systems, spreadsheets and Banner frms t understand the detailed analytical requirements. The fllwing lists the interview participants. Department Participant Psitin Finance Cntrller s Office Jackie Ellswrth Assciate Directr Cntrller s Office Jeraldine Lake Assciate Cntrller Cntrllers Office Jin Wang Assciate Directr Cntrller s ffice Diane Vers Directr Financial Planning & Budgeting Eileen McGlaughlin Directr Financial Planning & Budgeting Helen Grzymala Assciate Directr Financial Planning & Budgeting Gina Ricci Budget Analyst Administratin Prcurement & Administrative Services Steve Schwan Manager f Financial Operatins Prcurement & Administrative Services Clleen Serr Financial Services Crdinatr Auxilary Services Kathy Edick Directr Last saved n 1/25/02 Page 3

4 Schls Engineering Dnna Tmlinsn Manager f Financial Ops MS&E Lri Rbichaud Financial Manager MANE Rse Bshff Financial Manager Chemistry Anne Marie Strack Asst. Directr Science Sam Wait Assciate Dean Prvst Prvst Trish Lyns Directr Prfessinal & Distance Kim Scalz Directr Educatin DOT CIO DOT CIO Sandy Butcher Financial Manager Student Life RU Fitness Center Steve Allard Crdinatr f Mueller Center, Prgrams and Club Sprts RUO Martha McElligtt Crdinatr f Finance & Office Ops. Key Operatinal Reprts The data warehuse team inventried key mnthly reprts and perfrmed an analysis f each reprt t identify key clumns used, cnditins applied, calculatins derived, cmmn grupings f data and key measures. The detailed inventry f reprts is lcated in the fllwing directry. V:\Data_Warehuse\1-Financial DW\Requirements\reprt analysis V:\Data_Warehuse\1-Financial DW\Requirements\reprts used fr fin statements Last saved n 1/25/02 Page 4

5 BUSINESS REQUIREMENTS SUMMARY High Level Objectives The financial departments thrughut the institute cnsistently discuss the need fr a mechanism, which ffers imprved access t bth summarized and detailed financial infrmatin. Many cmmn themes were expressed while discussing requirements with department financial managers and directrs. The fllwing summarizes key bjectives described during the requirements gathering prcess. The finance department needs t simplify and reduce the time it takes t prduce and distribute quarterly management reprts and annual financial statements. Currently, a large number f queries are executed t extract data frm the Banner business systems t integrate int lcal spreadsheets and Micrsft Access database tables. This time cnsuming prcess requires many steps t manually integrate and regrup data frm varius surces int meaningful financial infrmatin. Thse respnsible fr the preparatin f this infrmatin are requesting a single surce f integrated, reliable and timely financial infrmatin that is interfaced with an easy t use and flexible reprting tl. Nte: Currently the data as it is cllected in Banner des nt crrespnd t the frmal presentatin categries utilized in the annual financial statements. The finance ffice must first take the necessary steps t setup the categrizatins in Banner befre the data warehuse can incrprate the frmal prductin f financial statements. Each f the departmental representatives indicated that they needed a simplified methd f integrating financial infrmatin with data maintained lcally. In many cases, departments maintain a shadw system t track all fund activity, including thse items, which haven t hit the Banner system. This enables them t understand their true available budget. Currently, much f the infrmatin cllected frm Banner riginates frm mnthly static reprts and/r dwnlads. In many cases, this data is re-entered int lcal spreadsheets and/r Access applicatins. A cmmn difficulty expressed by mst individuals was the difficulty in sharing infrmatin. Many system generated reprts need t be shared with individuals respnsible fr departmental spending. A mechanism is needed that will enable dynamic viewing f infrmatin relevant t an individual. In additin, many adhc requests frm faculty members are currently distributed in paper frm. It wuld be extremely helpful t have this infrmatin distributed in electrnic frm via r website. The ability t access histrical data is very imprtant when analyzing past spending activity in preparatin f annual budgets. This type f infrmatin is very difficult t retrieve and in many cases is maintained lcally in shadw systems. Many business representatives expressed frustratin with the perfrmance f current Micrsft Access queries they run against Oracle database views. Althugh they culd nt characterize adequate respnse time in minutes and secnds, the cmmn theme was reasnable respnse time. They d nt want t wait fr data dwnlads that in sme cases take mre than an hur t run. The budget ffice and individual financial departments are in need f an imprved methd f preparing quarterly frecasts and annual budgets. Althugh a data warehuses typically des nt enable write-back functinality t supprt frecasting and annual budget preparatin, the data assciated with this prcess must be Last saved n 1/25/02 Page 5

6 analyzed and reprted n in supprt f the prcess. The data warehuse shuld integrate with the verall budget prcess t prvide a cnsistent and integrated envirnment, serving as it s data surce, reprting and analytical mechanism. Many f the financial managers indicated that is very difficult t see all activity assciated with their individual funds. In many cases activity assciated with anther rganizatin may hit their fund. Due t current Banner security, activity n the fund utside their authrized rganizatin is nt be available, leading t misleading and inaccurate reprting. The data warehuse needs t reslve this issue t ensure all activity assciated with specific funds can be mnitred. Many indicated that a graphical representatin f key perfrmance indicatrs is very imprtant fr senir and executive level management. The data warehuse team needs t prvide an executive management dashbard f key perfrmance indicatrs as a cmpnent f the phase I rllut. Infrmatin and Analytic Requirements Thrughut the requirements gathering prcess, it became clear that a definitin between what is and is nt cnsidered financial analysis was difficult t define. In many cases, this was dependent upn the individuals we discussed requirements with. The fllwing summarizes key infrmatin and analytical requirements rganized int functinal business grupings and thse that are cmmn t all dcumented areas. Financial Infrmatin T prduce quarterly and annual financial statements, infrmatin frm bth the perating ledger and general ledger must be incrprated int the data warehuse. Operatinal data fr the RPI and Hartfrd campuses must be integrated int the data warehuse frm the Banner system. Currently, the RPI Technlgy Park data resides in a lcal business system and is manually integrated int the annual financial statements. The data warehuse must incrprate a mechanism t integrate RPI Technlgy Park year-end financial data fr the prductin f annual financial statements. Typical financial data necessary fr reprting and analysis includes budget, expenditure, encumbrance and reservatins. Standard calculatins used in reprting include fund balance, variance f budget t actual, percent f budget used and fiscal year t date and inceptin t date summaries. The primary attributes used t reprt and analyze financial data include fiscal and calendar perids f time, rganizatinal structure, fund structure, perating and general ledger accunt structures, prgram and activity. Each f the primary analytical attributes used in reprting cntain natural data hierarchies maintained within the Banner business systems. The data warehuse needs t incrprate the standard hierarchical structures within the rganizatin, fund and accunt structures. Additinally, each f the reprting hierarchical structures is unique t the RPI, Hartfrd and RPI Technlgy Park lcatins. T supprt the prductin f quarterly and annual financial statements, the data warehuse must incrprate the accunting framewrk used. Currently, Last saved n 1/25/02 Page 6

7 manual regruping f infrmatin is perfrmed t prvide the frmal appearance f financial statements. The data warehuse must ensure the grupings used t prduce the financial statements are incrprated int the verall design. Transactin detail is critical fr general reprting and analysis. In many cases reprts are prduced by fund and rganizatin shwing year t date activity alng with supprting transactin detail fr the time perid. Key detail elements can be gathered frm TRND. It will be helpful t incrprate a methd f selecting and/r gruping types f transactins such as credit card activity. Business representatives cmmnly discussed reprting and analyzing labr budget and actual data as a pririty. In additin t reprting by fund, rganizatin, accunt, prgram, activity and lcatin (FOAPAL), labr budget and actual data is analyzed by psitin, jb and persn. The academic schls fcus a great deal f their financial analysis n research related activity. Enabling the academic schls t reprt the research fund activity by rganizatin wuld be a helpful. In the future, they wuld like t reprt this activity by rganizatin and faculty member. Specific rganizatins indicated a need t mnitr budget, encumbrance and expenditure activity specifically fr capital prjects. The capital prject infrmatin stred in Banner is nt based upn a fiscal year and therefre requires an inceptin t date ttal. General Requirements Histrical Data Infrmatin required fr Financial reprting and analysis shuld be available fr a perid f three t five years with the ability t access ne t tw years f supprting transactin detail. It s imprtant t nte that research grants are nt based n a fiscal perid and therefre require the availability f inceptin t date figures. Refresh Criteria All business representatives expressed a need t have infrmatin as timely as pssible and indicated that the data warehuse shuld clearly pst the latest date the refresh ccurred. Mst agreed that any refresh mre frequent than mnthly wuld be beneficial and ideally wuld like t see infrmatin refreshed daily. Data Security Infrmatin in the data warehuse shuld be secured by fund and rganizatin. Currently, security in Banner restricts the wner f a fund frm seeing activity n their fund that is assciated with anther rganizatin. The data warehuse shuld imprve n the current security available in Banner, by enabling a fund wner t access all activity assciated with the fund. Additinally, given the sensitive nature f salary infrmatin, access t the labr data must be individually authrized and must be restricted by rganizatin. Tracking Changes t Reprting Attributes Last saved n 1/25/02 Page 7

8 The RPI rganizatinal structure typically changes ver fiscal years. The data warehuse must preserve histrical reprting by ensuring data assciated with an rganizatin is nt changed as the rganizatinal structure changes frm fiscal year t fiscal year. Hwever, many financial managers als indicated that they wuld like the flexibility t reprt n past histrical data using current rganizatinal structures. T ensure flexibility in reprting, the rganizatinal structure frm each fiscal year end must be preserved in the data warehuse. Reprting Time Perids Financial infrmatin is mst cmmnly reprted and analyzed by fiscal year, quarter and mnth. Transactin details must be available fr a given day. Reprting and analyzing research data requires that cntract and grant infrmatin be available fr the entire grant perid. Financial Analysis Success Criteria All business representatives indicated that they need a slutin that is easy t use, cnsistent, reliable and integrated. Many business users require the ability t slice and dice budget, expense and encumbrance data by fiscal perids f time, fund, rganizatin, prgram, accunt and activity with access t transactin detail. Having the ability t create individual reprts that can easily be exprted r shared with ther members within the rganizatin. Perfrmance f queries was cntinually mentined as being very imprtant. Althugh n qualificatins fr hw lng a query shuld take were identified, it is clear that fast respnse times are expected. The data warehuse shuld be the tl by which quarterly and annual financial statements are generated. Althugh the finance department will cntinue t cmplete prtins f the financial statements manually, there shuld be little need t rerganize data manually when preparing these reprts. Althugh labr budget and actual infrmatin assciated with psitin, jb and persn are nt necessary in phase I, this infrmatin is vital t all rganizatins fr budget preparatins, frecasting and nging analysis and shuld be available shrtly after the phase I rllut. Last saved n 1/25/02 Page 8

9 Data Warehuse Recmmendatins T prvide an enterprise data warehuse slutin, it is imprtant t recgnize the need fr phased implementatins that build upn and integrate with previus phases. Identifying scpe is critical t defining the subject areas that will be addressed within each phase. During the requirements gathering prcess fr the financial analysis subject area, key requirements were identified as ptential requirements utside the parameters f this phase, (I.E. the need fr labr and research related activity). The requirements team recmmends that the first phase f the data warehuse implementatin fcus n analysis f budget and expenditure activity assciated with the FOAPAL structures. In phases II and III, the data warehuse shuld address the need t integrate psitin cntrl data alng with research infrmatin characterized by cntracts and Grants and Spnsr Agencies. The fllwing describes the primary characteristics f phases I III f the data warehuse: Phase I Financial Analysis (January 2002 June 2002) The financial data frm the peratinal ledger must include budget, expenditure, encumbrance and reservatin, while the general ledger data must include debits and credits. Key reprting attributes will include Fund, Organizatin, Accunt, Prgram and Activity. The structured hierarchies within Banner will be incrprated int each data warehuse dimensin. Since transactin data is required, attributes such as dcument type will be included t help end users categrize transactin activity. The data warehuse will cntain three years f histrical data crrespnding t the FOAPAL structures summarized by mnth, fiscal quarter and fiscal perid. The summarized data will be supprted with the current tw fiscal years f transactin detail. The data warehuse will begin t address fundamental reprting aspects f research related activity by incrprating key Grant attributes such as grant cde, descriptin, ttal amunt, grant perids, grant status and spnsr agency. A detailed analysis f Grant tables in the Banner system will be cnducted t identify additinal high value reprting attributes. The data warehuse will incrprate key transactin related infrmatin such as transactin amunt, dcument cde, dcument type, transactin descriptin. Additinal items assciated with transactins will be identified and incrprated during the design phase. Infrmatin in the data warehuse will be secured by fund and rganizatin, enabling a fund wner t access all activity assciated with the fund regardless f the rganizatin. Additinally, phase II will enfrce security n labr data. Data will be refreshed n a daily basis. The data warehuse will be designed in manner that enables the finance department t prduce quarterly and annual financial statements with minimal rerganizatin f the data. Last saved n 1/25/02 Page 9

10 The data warehuse must preserve histrical reprting by ensuring data assciated with a fund r rganizatin is nt changed as these structures change frm fiscal year t fiscal year. Additinally, the flexibility t reprt n past histrical data using current and fiscal year end structures will be incrprated. Phase II Labr Budget and Actual (July 2002 September 2002) The data warehuse will be expanded t incrprate psitin, jb, persn and distributin data. The data warehuse will wrk clsely with the budget ffice t integrate infrmatin with the quarterly frecasting and annual budgeting prcess. Phase III Research Analysis (Octber 2002 December202) The data warehuse will be expanded t incrprate spnsred research infrmatin. Key areas addressed during this phase will enable analysis f research data by spnsr, time, FOAPAL and Grant PIs. Last saved n 1/25/02 Page 10