ENTERPRISE RESOURCE PLANNING

ENTERPRISE RESOURCE PLANNINGK J SOMAIYA INSTITUTE OF MANGEMENT STUDIES & RESEARCHPranav Anand 03Partha Sarathi Banerjee 09Sankalpa Mohapatra 40Palash Linge 51Group 10 11INTRODUCTIONEnterprise resource planning (ERP) is an integrated set of software modules linked to a centralized database and handling basic corporate functions. It helps to integrate all the departments and functions of an organization and hence helps in ease of business, better analysis and providing quick and optimal solutions

2MOTIVATIONS UNDERLYING ADOPTION OF ERP

33TYPES OF BENEFIT REALISED

4MOTIVATIONS UNDERLYING ADOPTION OF ERP IN HEALTH CARE SYSTEMSTechnological motivations Clinicaloperational motivations Clinicalstrategic motivationsFinancial motivations. Improve administrative process effectiveness Improve the effectiveness and efficiency of care provided to patientsMonitor cost trendsLeverage the ERP system to enhance compliance with applicable laws and regulations5SUCCESS FACTORS OF ERP IMPLEMENTATIONSFactors are broadly classified into 5 sections which are further classified as given below: Factors related to Implementation Participants:Project ManagerTeam CompositionTeam InvolvementMotivation Systems:Cooperation with Suppliers: Top Management InvolvementTop Management SupportTop Management AwarenessTop Management Participation

6SUCCESS FACTORS OF ERP IMPLEMENTATIONS (CONTINUED)C. Project Definition and Organization:Linking with StrategyImplementation GoalsDetailed SchedulePre-implementation analysisOrganizational ChangeMonitoring and FeedbackImplementations and PromotionsFast EffectsAppropriate Training7SUCCESS FACTORS OF ERP IMPLEMENTATIONS (CONTINUED)D. Project Status Investment PlanProject Team EmpowermentFinancial BudgetWork Time ScheduleIT infrastructureE. Information SystemsSystem ReliabilityMinimal CustomizationLegacy SystemsImplementation Experience

8RESEARCH METHODOLOGYThe research questionnaire was conducted It included respondents of 228 various ERP project users and 68 answers were obtained (30 %) from various industriesThis questionnaire was also floated with the specialists with experience in ERP implementationsThe list of success factors given above were presented and were asked to express their opinions about the importance of each factor on the scale of 0-5 (Likert scale)0 extremely low 1 very low 2 low 3 average 4 high 5 very high

9ANALYSIS OF THE RESEARCHOn Factor Analysis, it was found that the responses of the respondents and the specialists were in agreement with each other with a degree of convergence of 77% Both groups indicated Team composition, team Involvement and Detailed Schedule are most important and necessary elements for a project successExperts suggest factors Project Manager, Financial Budget, Top Management Support and Project Team Empowerment to be of paramount importance whereas Respondents indicate the importance of factors Co-Operation with Supplier, Top Management Awareness and System Reliability of higher importance.

1010CONCLUSION FOR SUCCESSFUL IMPLEMENTATION IN OVERALL INDUSTRIESThe study (Soja, 2006) helps us to determine the influence of various factors involved in the ERP projects success in overall industries where the application can be put to useAlso helps us to determine the key factors that can be taken into consideration during an ERP implementationAs the research is based on a multiple industry responses, factors for a particular industry may be different from those obtained here11CRITICAL SUCCESS FACTOR FOR ERP IMPLEMENTATION IN HEALTHCARETop Management Commitment:

User Involvement

Business Process Reengineering

Project Management

ERP Teamwork & Composition

12CRITICAL SUCCESS FACTORS FOR ERP IMPLEMENTATION IN A FORTIS HOSPITALWe narrow down our scope of research to target one specific hospital.The Fortis Hospital of Bangalore and discuss about the factors which have led to the successful implementation of ERP in that hospital.Aim : To identify the key factors and examine the relationships between them and the success of ERP implementation.20 percent of key items that contribute to 80 percent of ERP implementation success were noted down as critical factors.

13RESEARCH FRAMEWORK AND HYPOTHESES DEVELOPMENTThe five critical factors under study were as follows :Top Management Commitment : Top management must be involved and devote appropriate time to finish and allocate valuable resources to the implementation effort. Hypothesis defined was H1: Top Management Commitment is positively related with ERP implementation successUser Involvement : The more the users are familiar with the new ERP methodologies, greater is the chance for its success. H2: User Involvement is positively related with ERP implementation success

14Business Process Reengineering : Re-engineering has continually reduced workforce size and other short-term cost saving, with less impact on developing computer-based automation. H3: Business Process Reengineering is positively related with ERP implementation successProject Management : Healthcare projects need excellent management for the diverse contributions from the business units, customers and suppliers, vendors and consultants involved in the project. H4: Project Management is positively related with ERP implementation successERP Teamwork & Composition : In a strategic business unit such as a hospital, building a cross-functional team is essential, which must be a judicious combination of consultants and internal staff, so the internal staff can develop the necessary technical skills for design and implementation. H5: ERP Teamwork & Composition is positively related with ERP implementation success

15FORMULATION OF MULTIPLE REGRESSION MODEL

The above mentioned factors are independent variables which we name as X1, X2, X3, X4 and X5 respectively, on which the dependent variable which we define as Y (respondents perception of the Success of ERP implementation) depends upon.Thus, the multiple regression model can be formulated as followsY = 0 + 1 X1 + 2X2 + 3X3 + 4X4 + 5X5 + eObjective is to test our hypothesis on our selected sample (namely, Fortis Hospital) to get an overview of the population as a whole which is the healthcare industry

16RESEARCH METHODOLOGYThis study was based on empirical data collected through an interview with Managers, key users of Fortis hospital who had an important role during ERP implementation and consultants who participated in the project.An initial draft questionnaire was developed containing the five factors, for each, questions were provided to tap the elements of the factor. The study employed a five-point Likert scale ranging 1 (not important for success) to 5 (extremely important for success) to measure above-mentioned items.Next, statistical methods were used in the research which comprised factor analysis, descriptive statistics, correlation analysis and multiple regression analysis in order to examine and validate the relationship between critical factors and success of ERP implementation at Fortis hospital.17RESULTSSample was adequateAll items were deemed reliableAll the independent variables were positively related to success of ERP implementationThere is a positive relation between each of the factor and the success of ERP implementationCoefficient of Determination R2 = 0.877 indicated that 87.7 percent of the variation in success of ERP implementation could be explained by that of the five independent variables.18ANALYTICSHuge volumes of Data

Skyrocketing costs

Improve operations and patient outcomes

Data sharing and collaboration across value chain

Stiff Competition19Healthcare Analytics Adoption ModelProvide a roadmap for organizations to measure their own progress towards analytic adoption

Provide a framework for evaluating the industrys adoption of analytics

Provide a framework for evaluating vendor products

Healthcare Analytics Adoption ModelLevel 8Personalized Medicine& Prescriptive AnalyticsTailoring patient care based on population outcomes and genetic data. Fee-for-quality rewards health maintenance.Level 7Clinical Risk Intervention& Predictive Analytics Organizational processes for intervention are supported with predictive risk models. Fee-for-quality includes fixed per capita payment.Level 6Population Health Management & Suggestive AnalyticsTailoring patient care based upon population metrics. Fee-for-quality includes bundled per case payment.Level 5Waste & Care Variability ReductionReducing variability in care processes. Focusing on internal optimization and waste reduction.Level 4Automated External ReportingEfficient, consistent production of reports & adaptability to changing requirements.Level 3Automated Internal ReportingEfficient, consistent production of reports & widespread availability in the organization.Level 2Standardized Vocabulary & Patient RegistriesRelating and organizing the core data content.Level 1Enterprise Data WarehouseCollecting and integrating the core data content.Level 0Fragmented Point SolutionsInefficient, inconsistent versions of the truth. Cumbersome internal and external reporting.Progression in the ModelThe patterns at each levelData content expandsAdding new sources of data to expand our understanding of care delivery and the patientData timeliness increasesTo support faster decision cycles and lower Mean Time To ImprovementData governance expandsAdvocating greater data access, utilization, and qualityThe complexity of data binding and algorithms increasesFrom descriptive to prescriptive analyticsFrom What happened? to What should we do?The Expanding Ecosystem of Data ContentReal time 7x24 biometric monitoring data for all patients in the ACOGenomic dataLong term care facility dataPatient reported outcomes data*Home monitoring dataFamilial dataExternal pharmacy dataBedside monitoring dataDetailed cost accounting data*HIE dataClaims dataOutpatient EMR dataInpatient EMR dataImaging dataLab dataBilling data

3-12 months1-2 years2-4 years* - Not currently being addressed by vendor products

Six Phases of Data GovernanceYou need to move through these phases in no more than two years243-12 months1-2 years2-4 years

Phase 6: Acquisition of DataPhase 5: Utilization of DataPhase 4: Quality of Data Phase 3: Stewardship of Data Phase 2: Access to DataPhase 1: Cultural Tone of Data Driven

ArchitectureTimelines and CostsCan the solution offer business value in less than 3 months, in constant increments?Does the solution cost less than $7M over three years for a $1B - 2B organization (scale up and down accordingly)?26Vendors in the Crowded Market4medicaAnalytics8AscenderCernerCitiusTechCognizantCrimsonEpicExplorysHealth Care DataworksHealth CatalystHealthBridgeHumedicaIBMMedeAnalyticsMEDecisionOraclePerficientPredixionRecombinantPSCISajixSpectraMDStrata Decision TechnologyWhite Cloud AnalyticsZirMed

27SummaryThe analytic environment in healthcare is rapidly changing, and thats not going to stopAdaptability of the technology is crucialTechnology is only 1/3 of the solutionCultural willingness to embrace analytics is crucialCultural processes for sustained implementation are crucialLook for a vendor that offers a total solution closed loop analytics28Thank You29