A Forrester Total Economic Impact Study Prepared For Fuzzy Logix The Total Economic Impact Of Fuzzy Logix s DB Lytix

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1 A Frrester Ttal Ecnmic Impact Study Prepared Fr Fuzzy Lgix Prject Directr: Dean Davisn Cntributr: Nrman Frbush Octber 2013

2 TABLE OF CONTENTS Executive Summary... 2 RHcare Uses DB Lytix Fr Real-Time In-Database Analytics On Big Data T Make New Discveries... 2 Disclsures... 3 TEI Framewrk And Methdlgy... 4 Analysis... 5 Interview Highlights... 5 Csts... 7 Benefits... 8 Flexibility Risk Financial Summary Fuzzy Lgix And Sybase: Overview Appendix A: Ttal Ecnmic Impact Overview Appendix B: Glssary , Frrester Research, Inc. All rights reserved. Unauthrized reprductin is strictly prhibited. Infrmatin is based n best available resurces. Opinins reflect judgment at the time and are subject t change. Frrester, Techngraphics, Frrester Wave, RleView, TechRadar, and Ttal Ecnmic Impact are trademarks f Frrester Research, Inc. All ther trademarks are the prperty f their respective cmpanies. Fr additinal infrmatin, g t Abut Frrester Cnsulting Frrester Cnsulting prvides independent and bjective research-based cnsulting t help leaders succeed in their rganizatins. Ranging in scpe frm a shrt strategy sessin t custm prjects, Frrester s Cnsulting services cnnect yu directly with research analysts wh apply expert insight t yur specific business challenges. Fr mre infrmatin, visit Page 1

3 Executive Summary In Octber 2013, Fuzzy Lgix and Sybase cmmissined Frrester Cnsulting t examine the ttal ecnmic impact and ptential return n investment (ROI) that enterprises may realize by deplying Fuzzy Lgix s in-database library DB Lytix. The purpse f this study is t prvide readers with a framewrk t evaluate the ptential financial impact f DB Lytix n their rganizatins. Fuzzy Lgix prvides analytics tls fr big data that reside and execute within the database (r data warehuse), greatly reduce the need t mve the data, are accessible using SQL scripts, and use parallel techniques t significantly reduce analytic prcessing times. RHcare Uses DB Lytix Fr Real-Time In-Database Analytics On Big Data T Make New Discveries Fr this study, Frrester interviewed a reginal healthcare prvider, referred t as RHcare, with mre than 10,000 emplyees and 20 millin patients. Frrester s analysis shws that DB Lytix enabled analysts t make significant discveries frm big data that will enable RHcare t better treat and ptentially prevent disease in patients, thus lwering csts. In additin, DB Lytix lwered RHcare s csts by reducing its need fr standalne analytics servers and by using real-time analytics t imprve business prcesses. DB Lytix resides and executes within the existing data warehuse (r database) and gave RHcare analysts the ability t run tests n big data. DB Lytix uses parallel techniques t imprve perfrmance, enabling RHcare s queries t run in a few hurs when equivalent data mdels nrmally require weeks t run. The value f rapid perfrmance allws experts t test ideas i.e., hyptheses quickly and iterate, purging hyptheses that are nt substantiated by data and fcusing mre time n ideas that have merit based n data results. Fr example, RHcare was able t run tests n data relatinships that resulted in a statistical mdel that predicts which patients will develp a specific chrnic disease. Because treating the specific chrnic disease makes up 10% f RHcare s cst f services, the impact f preventing the disease is significant. In fact, RHcare estimates that preventing the disease in nly 0.5% f patients will reduce the cst f treatment by several millin dllars. Frrester s interview with RHcare and subsequent financial analysis fund that RHcare experienced the risk-adjusted ROI, csts, and benefits shwn in Table 1. Table 1 RHcare Three-Year Risk-Adjusted ROI ROI Ttal benefits (present value) Ttal csts (present value) Net present value 337% $3,275,635 ($749,105) $2,526,529 Surce: Frrester Research, Inc. Page 2

4 Benefits. RHcare experienced the fllwing benefits: Reducing the cst f standalne analytics platfrms. DB Lytix resides within the data warehuse, allwing RHcare t eliminate sme f its analytics servers fr a savings f mre than $1.5 millin ver three years. Identifying a predictive mdel fr a chrnic disease. Leveraging the ability f DB Lytix t lk at relatinships in big data, RHcare derived a mdel that predicts which patients will develp an expensive and chrnic cnditin within five years. RHcare estimates that being able t prevent the disease in its patients will reduce the cst f treating thse patients by mre than $3.8 millin ver three years. Using real-time analytics in business prcesses. RHcare imprved its uncllectable accunts by using real-time data frm third-party surces and an internal Sybase data warehuse t reduce RHcare s risk while registering new patients, resulting in financial benefits f mre than $1.1 millin. Csts. RHcare experienced the fllwing csts: Licensing DB Lytix. RHcare paid fr DB Lytix and annual maintenance fees f 20%. RHcare already had the data warehuses where DB Lytix is installed. The cst t license and maintain a cumulative ttal f nine instances f DB Lytix ttals $937,500 ver three years. Disclsures The reader shuld be aware f the fllwing: The study is cmmissined by Fuzzy Lgix and Sybase and delivered by the Frrester Cnsulting grup. Frrester makes n assumptins as t the ptential ROI that ther rganizatins will receive. Frrester strngly advises that readers shuld use their wn estimates within the framewrk prvided in the reprt t determine the apprpriateness f an investment in Fuzzy Lgix DB Lytix. Fuzzy Lgix reviewed and prvided feedback t Frrester, but Frrester maintains editrial cntrl ver the study and its findings and des nt accept changes t the study that cntradict Frrester s findings r bscure the meaning f the study. The custmer names fr the interviews were prvided by Fuzzy Lgix. Page 3

5 TEI Framewrk And Methdlgy Intrductin Frm the infrmatin prvided in the interview, Frrester cnstructed a Ttal Ecnmic Impact framewrk fr thse rganizatins cnsidering implementing Fuzzy Lgix DB Lytix. The bjective f the framewrk is t identify the cst, benefit, flexibility, and risk factrs that affect the investment decisin. Apprach And Methdlgy Frrester tk a multistep apprach t evaluate the impact that Fuzzy Lgix DB Lytix can have n an rganizatin (see Figure 1). Specifically, we: Interviewed Fuzzy Lgix marketing/sales/cnsultants persnnel and Frrester analysts t gather data relative t in-database analytics and the marketplace fr DB Lytix. Interviewed an rganizatin using DB Lytix with Sybase t btain data with respect t csts, benefits, and risks. Cnstructed a financial mdel representative f the interviews using the TEI methdlgy. The financial mdel is ppulated with the cst and benefit data btained frm the interviews as applied t the cmpsite rganizatin. Figure 1 TEI Apprach Perfrm due diligence Cnduct custmer interviews Cnstruct financial mdel using TEI framewrk Write case study Surce: Frrester Research, Inc. Frrester emplyed fur fundamental elements f TEI in mdeling fr Fuzzy Lgix DB Lytix: 1. Csts. 2. Benefits t the entire rganizatin. 3. Flexibility. 4. Risk. Given the increasing sphisticatin that enterprises have regarding ROI analyses related t IT investments, Frrester s TEI methdlgy serves the purpse f prviding a cmplete picture f the ttal ecnmic impact f purchase decisins. Please see Appendix A fr additinal infrmatin n the TEI methdlgy. Page 4

6 Analysis Interview Highlights RHcare prvides preventative and emergency medical services t mre than 20 millin patients within a fcused gegraphical area f the US. Because the cst f prviding healthcare services is rising dramatically, RHcare s vice president f business analytics tld Frrester that it leverages patient data t: Develp mdels that predict patient healthcare needs. Identify patterns f high-risk (and expensive) custmers. Recgnize successful treatments by disparate hspital, clinics, and dctrs. Assess risk calculatins that determine underwriting appraches. RHcare puts a great deal f emphasis n imprving business peratins frm patient healthcare t financial management using insights that are derived frm big data. T help fuel cntinuus discvery, RHcare rganized its 250-plus data analysts int a central business unit with prfit and lss gals. As a result, the research grup actively evaluates emerging technlgies that ffer the ptential t imprve the insights frm custmer data. Analysts within the research grup wrk with business experts t gather ideas, test hyptheses, develp statistical mdels, and run queries. Business units use the results fr a wide range f business gals that range frm reducing the cst f healthcare, intrducing new medical treatments, r even negtiating with business partners. Situatin The RHcare executive tld Frrester that nearly all f the analytics wrk that is currently dne by the research grup is using cleansed data. Analysts must hne a hypthesis, extract the data that will prve the hypthesis, cleanse the data t eliminate anmalies, and run the mdel t create statistical results. Frm beginning t end, these steps require an average f tw weeks. Althugh the research grup is already successful (revenue grwth frm analytics is 18% annually), leaders cntinually lk fr innvatin in analytics tls, methds, r capabilities that will prvide significant imprvements in big data analytics. With a grwing understanding f the benefits f analyzing big data, RHcare lked t use new tls that culd increase and sustain revenue grwth. We are always lking fr tls that allw us t lk at data frm different pints f view. DB Lytix gives us an efficient way t lk at big data, which I believe will becme an imprtant tl in ur verall tl set. (Vice president, business analytics) Page 5

7 Slutin Frrester s interview with the RHcare executive uncvered that DB Lytix enabled RHcare t efficiently analyze big data. By installing DB Lytix within the data warehuse, RHcare was able t iterate mre quickly thrugh queries, including: Running a regressin t identify single-variable relevance with mre than 1,300 markers n the recrds f 15 millin patients in less than 1 hur. Testing 17,000 markers n 1 millin patients that ran in 15 minutes. Evaluating 200,000 patients with 300 markers that ran in 6 t 8 hurs. Results RHcare realized the fllwing results using DB Lytix: DB Lytix enabled new discveries, significantly reducing the cst f care. The ability t iterate quickly n sets f data allwed RHcare t make significant discveries. The mst ntable is a mdel with 95% accuracy that predicts which patients will develp a specific chrnic disease. Treating this chrnic disease is apprximately 10% f the cmpany s cst f services. The ability f RHcare t prevent r delay patients frm develping this chrnic disease will imprve the lives f millins f patients and has the ptential t reduce RHcare s csts by millins f dllars annually. The executive frm RHcare tld Frrester: Withut the ability t identify relatinships in big data by DB Lytix, we wuld never have been able t develp this mdel. The relatinships between variables are t intricate fr us t ever develp and test using mst ther analytics methds. DB Lytix significantly reduced the csts f big data analytics. RHcare indicated that using DB Lytix as an indatabase analytics tl helped it: Avid the effrt f mving data between systems. Because DB Lytix resides within the data warehuse, analysts n lnger spend time mving data sets between databases and analytics servers an average f 30 GBs per prject. Reduce its capital investment in standalne analytics systems. Similarly, because DB Lytix resides within the data warehuse, RHcare required fewer standalne servers fr analytics prjects, allwing DB Lytix t eliminate five standalne servers ver three years. Allw business experts t test ideas n their wn using SQL queries. Users run queries in DB Lytix using SQL cmmands rather than cmplex prprietary languages, creating a shrter learning curve that allws business users t begin testing ideas withut analyst supprt. Imprve RHcare s negtiating leverage with partners especially healthcare payers. RHcare has greater leverage in negtiatins with insurance cmpanies when it can refer t the detailed insights abut patient treatments and csts that cme frm analytics prjects. Page 6

8 Use real-time analytics t adjust patient billing chices during registratin. RHcare significantly lwered the cst f cllecting payments within ne business unit by tailring financial agreements t the patient s circumstances and histry. Framewrk Assumptins The discunt rate used in the present value (PV) and net present value (NPV) calculatins is 10%, and the time hrizn used fr the financial mdeling is three years. Organizatins typically use discunt rates between 8% and 16% based n their current envirnment. Readers are urged t cnsult with their respective cmpany s finance department t determine the mst apprpriate discunt rate t use within their wn rganizatins. Csts Based n Frrester s interview f the RHcare executive, cmpanies that use DB Lytix will incur csts fr licensing and maintaining DB Lytix. The cst f the platfrm includes paying fr DB Lytix and assumes that cmpanies have an existing data warehuse fr installing an in-database analytics tl. The executive at RHcare tld Frrester that the implementatin f DB Lytix tk fewer than 15 minutes. Because DB Lytix uses SQL cmmands and R as the query language, the learning curve fr analysts is shrt. RHcare purchased an initial license in Year 1. Based n results, it buys eight mre instances fr a ttal f nine ver the three years; based n Frrester s three-year ROI mdel, the cst fr an enterprise license and annual maintenance fees fr DB Lytix ttal $937,500 ver three years (see Table 2). Table 2 Licensing And Maintenance Fees Fr DB Lytix Ref Cst Calculatin Year 1 Year 2 Year 3 Ttal A1 Licenses purchased A2 Fees fr licenses purchased A1*$87,500 $93,750 $281,250 $468,750 A3 Maintenance fee (18%) 20% f previus year s license fees $18,750 $75,000 At Ttal cst A2+A3 $87,500 $300,000 $543,750 $937,500 Surce: Frrester Research, Inc. Page 7

9 Benefits Based n Frrester s interview f the RHcare executive, cmpanies that use DB Lytix are likely t realize financial benefits in the frm f: Reducing the cst f standalne analytics platfrms. Identifying a predictive mdel fr a chrnic disease. Leveraging real-time analytics in business prcesses. Reducing The Cst Of Standalne Analytics Platfrms RHcare lwered its verall cst fr mdeling prfessinals, hardware platfrms, and sftware tls t run standalne analytics platfrms. Because RHcare has a large analytics grup, the five servers are a small percentage f its verall standalne analytics servers. RHcare retired five f its standalne analytics servers ver three years, reducing csts in analytics servers by mre than $1.5 millin ver three years (see Table 3). Cst savings are als cumulative since a cst avided in the first year is a cst avided in subsequent years. Table 3 Reducing The Cst Of Standalne Analytics Platfrms Ref. Benefit Calculatin Year 1 Year 2 Year 3 Ttal B1 Number f analytics servers retired B2 Hardware csts B1*$50,000 $50,000 $100,000 $100,000 B3 Sftware csts B1*$80,000 $80,000 $160,000 $160,000 B4 Maintenance csts B3*18% $14,400 $28,800 $28,800 B5 System admin csts B1*12.5%*$123,000 $15,375 $46,125 $76,875 Bt Cumulative csts avided by retiring analytics platfrms B2+B3+B4+B5 +Year 1 csts +Year 2 csts $159,775 $494,700 $860,375 $1,514,850 Surce: Frrester Research, Inc. Page 8

10 Reductin In Disease Management Csts By Identifying A Predictive Mdel Fr A Chrnic Disease RHcare used DB Lytix during early pilt testing t identify a mdel that predicts with 95% accuracy the patients that will develp a specific chrnic disease. Because RHcare currently spends abut 10% f its cst f services treating this disease, preventing r delaying nset f the disease in patients has a significant impact n RHcare s csts. Because RHcare can cnfidently predict which patients will develp the disease, RHcare expects t prevent the disease in 0.5% f patients. In Table 4, Frrester prvides a cnservative estimate f the financial benefits that RHcare will realize frm this ne discvery, which is equal t $1.8 millin at the end f three years based n an investment f $131,250, giving RHcare a return f 13.7 times its investment fr its initial DB Lytix license. Table 4 Reductin In Disease Management Csts By Identifying A Predictive Mdel Fr A Chrnic Disease Ref. Benefit Calculatin Year 1 Year 2 Year 3 Ttal C1 Annual cst f treating disease fr RHcare $180,000,000 $180,000,000 C2 Reduced cst f treating patients that avid disease C1*0.5% $900,000 $900,000 Ct Ttal cst savings f predicting disease C2 $900,000 $900,000 $1,800,000 Surce: Frrester Research, Inc. This benefit is a specific example f the ptential f using DB Lytix t tap int big data. RHcare tld Frrester that althugh it desn t expect all discveries t have the same financial benefit, RHcare expects t realize nging benefits and discveries frm analytics f the data. Page 9

11 Leveraging Real-Time Analytics T Reduce Uncllectable Accunts RHcare was able t use real-time analytics n a high-perfrmance Sybase database t identify patients and suggest alternate financial appraches r adjust payment ptins based n a patient s risk. RHcare s auditrs required that the business unit keep a cash reserve f $525,000 as a safeguard t the financial risk psed by patients. By using real-time analytics alng with sme third-party infrmatin services RHcare was able t assess a patient s ability t pay, arrange fr alternate payment methds, and make additinal changes that eliminated the need fr the cash reserve and reduced the cmpany s challenges with uncllectable accunts. The financial impact is that RHcare reduced the number f high-risk patients (i.e., patients that default n payments) by 15% annually, resulting in an increase in cash flw f mre than $1.1 millin ver three years (see Table 5). Table 5 Leveraging Real-Time Analytics In Business Prcesses Ref. Benefit Calculatin Year 1 Year 2 Year 3 Ttal D1 Reduced cst f uncllectable accunts Previus year *85%; riginal value=$525,000 $446,250 $379,313 $322,416 Dt Ttal savings frm reduced reserves $446,250 $379,313 $322,416 $1,147,979 Surce: Frrester Research, Inc. Page 10

12 Ttal Benefits As shwn in Table 6, the benefits t RHcare are valued at mre than $4.4 millin. The benefits include reducing the cst f standalne analytics platfrms, increasing the impact frm nging analytics, ttal cst savings f predicting disease, and Ttal savings frm reduced reserves (see Table 6). Table 6 Ttal Benefits Ref. Benefit Calculatin Year 1 Year 2 Year 3 Ttal Bt Cumulative csts avided by retiring analytics platfrms $159,775 $494,700 $860,375 Ct Ttal cst savings f predicting disease $900,000 $900,000 Dt Ttal savings frm reduced reserves $446,250 $379,313 $322,416 Ttal cst savings Bt+Ct+Dt $606,025 $1,774,013 $2,082,791 $4,462,829 Surce: Frrester Research, Inc. Page 11

13 Flexibility Flexibility, as defined by TEI, represents an investment in additinal capacity r capability that culd be turned int business benefit fr sme future additinal investment. This prvides an rganizatin with the right r the ability t engage in future initiatives but nt the bligatin t d s. There are multiple scenaris in which a custmer might chse t implement DB Lytix and later realize additinal uses and business pprtunities. Flexibility wuld als be quantified when evaluated as part f a specific prject (described in mre detail in Appendix A). Because experts acrss RHcare are able t begin lking at relatinships in big data, the executive described the future ptins as nearly infinite and described the pprtunities as: Allwing business experts t test ideas n their wn. By using SQL cmmands, business experts are able t test ideas and iterate quickly frm ne idea t the next withut ging thrugh the lnger prcess f defining a hypthesis, cleansing data, running queries, and validating results. Once an idea is prven, SAS/SPSS experts will cnduct the query with the needed scientific rigr, but early testing f ideas can iterate quickly. Within SAS/SPSS, users frequently extend calls t the riginal DB Lytix mdels. This apprach is hw RHcare was able t test ideas and lk fr relatinships in the data that allwed analysts t create a mdel that predicts the nset f the specific chrnic disease. Prviding dashbards that reprt real-time infrmatin. As executives became aware f the real-time data available using DB Lytix, the request arse fr varius dashbards that prvide insight int patients, dctrs, facilities, and ther aspects f RHcare s peratins. The business unit that used the results t reduce its uncllectable accunts was ultimately able t cnnect advertising campaigns t the surces f varius patients, including the risk prfiles f thse patients. Over time, business executives were able t reduce advertising in channels and lcatins that tended t draw higher-risk patients. Risk Frrester defines tw types f risk assciated with this analysis: implementatin risk and impact risk. Implementatin risk is the risk that a prpsed investment in Fuzzy Lgix DB Lytix may deviate frm the riginal r expected requirements, resulting in higher csts than anticipated. Impact risk refers t the risk that the business r technlgy needs f the rganizatin may nt be met by the investment in Fuzzy Lgix DB Lytix, resulting in lwer verall ttal benefits. The greater the uncertainty, the wider the ptential range f utcmes fr cst and benefit estimates. Quantitatively capturing investment and impact risk by directly adjusting the financial estimates results in mre meaningful and accurate estimates and a mre accurate prjectin f the ROI. In general, risks affect csts by raising the riginal estimates, and they affect benefits by reducing the riginal estimates. The risk-adjusted numbers shuld be taken as realistic expectatins since they represent the expected values cnsidering risk. The fllwing impact risks that affect benefits are identified as part f the analysis: Reducing the cst f standalne analytics platfrms. The amunt that a cmpany might save frm standalne analytics platfrms depends n the efficiency f analytics teams the cmplexity and speed f testing, validatin, and the running f current analysis. RHcare was 100%-fcused n SAS/SPSS befre intrducing DB Lytix. Page 12

14 Increasing the impact frm nging analytics prgrams. RHcare is able t gain nging benefits in prduct mix, custmer services, and related fferings because it has extensive data abut its patients. Cmpanies prviding retail services r similar lw-tuch experiences will lack the level f data used by RHcare. Identifying a predictive mdel fr a chrnic disease. Develping a predictive mdel fr a chrnic disease is described by RHcare as striking gld. Table 7 shws the values used t adjust fr risk and uncertainty in the cst and benefit estimates. The TEI mdel uses a triangular distributin methd t calculate risk-adjusted values. T cnstruct the distributin, it is necessary t first estimate the lw, mst likely, and high values that culd ccur within the current envirnment. The risk-adjusted value is the mean f the distributin f thse pints. Readers are urged t apply their wn risk ranges based n their wn degree f cnfidence in the cst and benefit estimates. As with any analysis, readers are urged t apply their wn risk ranges based n their wn degree f cnfidence in the cst and benefit estimates. Table 7 Cst And Benefit Risk Adjustments Csts Lw Mst likely High Mean Purchasing DB Lytix 98% 100% 105% 101% Benefits Lw Mst likely High Mean Reducing the cst f standalne analytics platfrms 80% 100% 110% 97% Identifying a predictive mdel fr a chrnic disease 40% 100% 110% 83% Leveraging real-time analytics in business prcesses 80% 100% 110% 97% Surce: Frrester Research, Inc. Page 13

15 Financial Summary The financial results calculated in the Csts and Benefits sectins can be used t determine the ROI and NPV fr the rganizatin s investment in DB Lytix. These are shwn in Table 8. Table 8 Cash Flw Nn-Risk-Adjusted Cash flw riginal estimates Initial Year 1 Year 2 Year 3 Ttal Present value Csts $0 ($93,750) ($300,000) ($543,750) ($937,500) ($741,689) Benefits $0 $606,025 $1,774,013 $2,082,791 $4,462,829 $3,581,889 Net benefits $0 $512,275 $1,474,013 $1,539,041 $3,525,328 $2,840,201 ROI 383% Surce: Frrester Research, Inc. Table 9 belw shws the risk-adjusted ROI and NPV. These values are determined by applying the risk-adjustment values frm Table 7 in the Risk sectin t the cst and benefits numbers in Tables 2 and 6. Table 9 Cash Flw Risk-Adjusted Cash flw risk-adjusted estimates Initial Year 1 Year 2 Year 3 Ttal Present value Csts $0 ($94,688) ($303,000) ($549,188) ($946,876) ($749,105) Benefits $0 $587,844 $1,594,792 $1,894,307 $4,076,943 $3,275,635 Net benefits $0 $493,156 $1,291,792 $1,345,119 $3,130,068 $2,526,530 ROI 337% Surce: Frrester Research, Inc. Page 14

16 Fuzzy Lgix And Sybase: Overview Accrding t Fuzzy Lgix, DB Lytix is an in-database cmputatin engine that allws yu t perfrm analytics within yur database, which means yu dn t have t mve the data frm strage t anther lcatin fr analysis, and therefre yu dn t have t build large cmputatinal infrastructure with servers, blades, and lad balancing sftware. Just deply DB Lytix n yur database in fewer than 30 minutes, and yu instantly have the ability t perfrm advanced analytics thrugh simple SELECT and EXECUTE statements. Using DB Lytix has multiple advantages: Rich repsitry f functins. DB Lytix cntains a very rich cllectin f functins. Frm simple statistical analysis t Mnte Carl simulatins and pattern recgnitin, DB Lytix prvides the required functins t d it all. The DB Lytix library cnsists f the fllwing: Mathematical and statistical functins. Mnte Carl simulatins univariate and multivariate. Data mining and pattern recgnitin principal cmpnent analysis, linear regressin, lgistic regressin, ther supervised learning methds, classificatin mdels, and clustering. Ease f use. End users and prgrammers can perfrm cmplex data mining and business analytics by using cnventinal SQL statements (SELECT and EXECUTE stred prcedures). The functins can be embedded in ther functins and stred prcedures and can be invked using ODBC calls. The simplicity f use makes DB Lytix very attractive fr the end users. Time-t-actin. The very paradigm f DB Lytix helps yu gain efficiency in analysis, saves time and cst, and enables yu t prvide answers t the decisin-makers in minutes. Benchmarks have shwn times imprvement in perfrmance ver traditinal multitiered analytics slutins. Affrdability. Yu nly need an enterprise license fr DB Lytix instead f seat licenses as with ther analytical sftware prducts. Als, since DB Lytix is deplyable thrugh simple SELECT statements, yu d nt need additinal sftware t leverage the full ptential f the library. Sybase IQ s smart clumn-based architecture, cmbined with Fuzzy Lgix s in-database analytics capabilities, ensures extremely fast prcessing when running analytics and predictive mdels. Sybase IQ and Fuzzy Lgix have created a high-perfrmance clumn-based analytics server that supprts hundreds f statistical and data mining functins, being called using simple SQL statements and running in the database while supprting a large number f cncurrent users at high perfrmance levels. Page 15

17 Appendix A: Ttal Ecnmic Impact Overview Ttal Ecnmic Impact is a methdlgy develped by Frrester Research that enhances a cmpany s technlgy decisin-making prcesses and assists vendrs in cmmunicating the value prpsitin f their prducts and services t clients. The TEI methdlgy helps cmpanies demnstrate, justify, and realize the tangible value f IT initiatives t bth senir management and ther key business stakehlders. The TEI methdlgy cnsists f fur cmpnents t evaluate investment value: benefits, csts, risks, and flexibility. Benefits Benefits represent the value delivered t the user rganizatin IT and/r business units by the prpsed prduct r prject. Often prduct r prject justificatin exercises fcus just n IT cst and cst reductin, leaving little rm t analyze the effect f the technlgy n the entire rganizatin. The TEI methdlgy and the resulting financial mdel place equal weight n the measure f benefits and the measure f csts, allwing fr a full examinatin f the effect f the technlgy n the entire rganizatin. Calculatin f benefit estimates invlves a clear dialgue with the user rganizatin t understand the specific value that is created. In additin, Frrester als requires that there be a clear line f accuntability established between the measurement and justificatin f benefit estimates after the prject has been cmpleted. This ensures that benefit estimates tie back directly t the bttm line. Csts Csts represent the investment necessary t capture the value, r benefits, f the prpsed prject. IT r the business units may incur csts in the frm f fully burdened labr, subcntractrs, r materials. Csts cnsider all f the investments and expenses necessary t deliver the prpsed value. In additin, the cst categry within TEI captures any incremental csts ver the existing envirnment fr nging csts assciated with the slutin. All csts must be tied t the benefits that are created. Risk Risk measures the uncertainty f benefit and cst estimates cntained within the investment. Uncertainty is measured in tw ways: 1) the likelihd that the cst and benefit estimates will meet the riginal prjectins, and 2) the likelihd that the estimates will be measured and tracked ver time. TEI applies a prbability density functin knwn as triangular distributin t the values entered. At a minimum, three values are calculated t estimate the underlying range arund each cst and benefit. Flexibility Within the TEI methdlgy, direct benefits represent ne part f the investment value. While direct benefits can typically be the primary way t justify a prject, Frrester believes that rganizatins shuld be able t measure the strategic value f an investment. Flexibility represents the value that can be btained fr sme future additinal investment building n tp f the initial investment already made. Fr instance, an investment in an enterprisewide upgrade f an ffice prductivity suite can ptentially increase standardizatin (t increase efficiency) and reduce licensing csts. Hwever, an embedded cllabratin feature may translate t greater wrker prductivity if activated. The cllabratin can nly be used with additinal investment in training at sme future pint in time. Hwever, having the ability t capture that benefit has a present value that can be estimated. The flexibility cmpnent f TEI captures that value. Page 16

18 Appendix B: Glssary Discunt rate: The interest rate used in cash flw analysis t take int accunt the time value f mney. Althugh the Federal Reserve Bank sets a discunt rate, cmpanies ften set a discunt rate based n their business and investment envirnment. Frrester assumes a yearly discunt rate f 10% fr this analysis. Organizatins typically use discunt rates between 8% and 16% based n their current envirnment. Readers are urged t cnsult their respective rganizatin t determine the mst apprpriate discunt rate t use in their wn envirnment. Net present value (NPV): The present r current value f (discunted) future net cash flws given an interest rate (the discunt rate). A psitive prject NPV nrmally indicates that the investment shuld be made, unless ther prjects have higher NPVs. Present value (PV): The present r current value f (discunted) cst and benefit estimates given at an interest rate (the discunt rate). The PV f csts and benefits feed int the ttal NPV f cash flws. Payback perid: The breakeven pint fr an investment. This is the pint in time at which net benefits (benefits minus csts) equal initial investment r cst. Return n investment (ROI): A measure f a prject s expected return in percentage terms. ROI is calculated by dividing net benefits (benefits minus csts) by csts. A Nte On Cash Flw Tables The fllwing is a nte n the cash flw tables used in this study (see the example table belw). The initial investment clumn cntains csts incurred at time 0 r at the beginning f Year 1. Thse csts are nt discunted. All ther cash flws in Years 1 thrugh 3 are discunted using the discunt rate (shwn in Framewrk Assumptins sectin) at the end f the year. PV calculatins are calculated fr each ttal cst and benefit estimate. NPV calculatins are nt calculated until the summary tables and are the sum f the initial investment and the discunted cash flws in each year. Table [Example] Example Table Ref. Categry Calculatin Initial cst Year 1 Year 2 Year 3 Ttal Surce: Frrester Research, Inc. Page 17