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Design of Risk Management Strategies in Business Process Information Flow Xue Bai Operations and Information Management School of Business University of.

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Presentation on theme: "Design of Risk Management Strategies in Business Process Information Flow Xue Bai Operations and Information Management School of Business University of."— Presentation transcript:

1 Design of Risk Management Strategies in Business Process Information Flow Xue Bai Operations and Information Management School of Business University of Connecticut

2 Risk Workshop SAMSI2 Outline Motivation and problem definition Methodology Experimental study Real world application Future research

3 Risk Workshop SAMSI3 Motivation Impact of errors in corporate business processes –10 percent to 30 percent of the data flowing through corporate systems is bad… (CFO magazine 2003) Impact of errors in healthcare processes –More than 8.8 million ADEs occur each year in ambulatory care, cost at least $5,000 per ADE. Medication errors account for 1 out of 131 ambulatory care deaths (Washington: eHealth Initiative 2004). –Health care data quality: accuracy 67%, completeness: 30.7% (Stein et al. 2000) Legal mandates –Sarbanes Oxley Act (2002) –HIPAA (1996), Medical malpractice laws

4 Risk Workshop SAMSI4 Physician Patient Pharmacist Insurer Prescription Bill Medication Bill An Example of BP with Errors and Risks Call back and complain Formulary mismatch Wrong dosage Adverse Drug Event Call back efforts; Administrative cost; Patient satisfaction & loyalty & litigation issues. Patient ends up in ER. An example: a medication process Bills for ER visit. Manual check E-prescribing systems Performance review E-order systems

5 Risk Workshop SAMSI5 Physician Patient Pharmacy Insurer Prescription Bill Medication Bill An Example of BP with Errors and Risks A medication process

6 Risk Workshop SAMSI6 A Business Process (BP) –Tasks –Information flow –Errors Accuracy Completeness Occurrence –Risk exposure –Design of Control structure for risk management enter order info. check alert info. update medication info. order database inaccurate dosage missing information The order management process at the pharmacy Manual check E-order mgt. check alert info. update medication info. database enter order info. Elements of the Model

7 Risk Workshop SAMSI7 Outline Motivation and problem definition Methodology Experimental study Real world application Future research

8 Risk Workshop SAMSI8 Check alert info. Update medication information Enter order information Database Check alert info. Update medication information Enter order information Database wrong dosage A Simple Sequential Process Process Structure Affects Error Impact

9 Risk Workshop SAMSI9 A Simple Parallel Process Order of medication Shipping invoice Payment voucher Preparing voucher package control Process Structure Affects Control Function

10 Risk Workshop SAMSI10 BP as a Graph t1t1 t2t2 t3t3 The precedence matrix:

11 Risk Workshop SAMSI11 t1t1 t2t2 t3t3 The volume transition matrix: p(T): the ratio between the volume output by task i and the volume fed to task j, given t ij =1. t 1: Non-Condition node: t 1: Condition node: BP as a Graph

12 Risk Workshop SAMSI12 The propagation impact (PI) matrix: –K: the length of the longest path in a process. –p(T): the volume transition matrix The propagation potential: t 1: Non-condition node:t 1 :Condition node: Impact of Error

13 Risk Workshop SAMSI13 Error Generation Error correlation structure Models for error generation processes – hierarchical sampling schema Controlling for dependence/independence due to the homogeneity/ heterogeneity of operations and resources involved –Within a task –Across tasks

14 Risk Workshop SAMSI14 The number of errors of type m at task i: – : number of errors of type m that show up at task i – : number of errors of type m that arrive at task i – : occurrence of errors of type m generated by task i – : average number of e im Error Propagation

15 Risk Workshop SAMSI15 Loss and Risk Measurement Loss: c im : cost of an error of type m at task i. Risk Measures –Expected Loss (EL), Value-at-Risk (VaR), Conditional Value-at- Risk (CVaR) ELCVaRVaR loss β

16 Risk Workshop SAMSI16 Risk Measures –Expected Loss –Value-at-Risk –Conditional Value-at-Risk ELCVaRVaR loss β

17 Risk Workshop SAMSI17 Control allocation factor Effectiveness of control –the probability of a control catching an error: Deterministic control Stochastic control Cost of control (per period) Risk Management: Control Model

18 Risk Workshop SAMSI18 Model Formulation I, II, and III –Design problem: Given a budget B, –Model I: Expected-Loss-Optimal Control Structure –Model II: β-VaR-Optimal Control Structure –Model III: β-CVaR-Optimal Control Structure

19 Risk Workshop SAMSI19 Outline Motivation and problem definition Methodology Experimental study Real world application Future research

20 Risk Workshop SAMSI20 Experimental Study Experimental design –Topological variation Sequential, parallel, arbitrary –Process size Small (4 tasks), medium (10 tasks), large (25 tasks) –Cost of control vs. Loss per error ( ) Expensive: (500, 1000, 2000, 4000, 10000), inexpensive: (25, 50, 100) –Tolerance level of risks (β) β = 0.90, 0.95, 0.99 –Error correlation Independent, dependent

21 Risk Workshop SAMSI21 Experimental Results As the process size increases, (Table 113, 115, 117, 119, 121, and 123) –The optimal amount of control allocation in total increases –The optimal amount of control allocation at each task decreases –For sequential structure, the objective function value increases exponentially; for parallel structure, the magnitude remains the same. As the tolerance level of risks (β) changes (Table 2 and 10; Table 22 and 30), –The optimal amount of control allocation in total increases –The impact of β at the task level depends on characteristics of the loss distributions In the range of β value and loss distributions tested, the impact is insignificant. As the ratio cost of control / loss per error ( ) increases (Table ) –The optimal amount of control allocation at each task decreases –The optimal amount of control allocation in total decreases

22 Risk Workshop SAMSI22 Experimental Results (continue) Optimal control allocations depend on risk objectives. –The relative importance of each task location changes accordingly –Tradeoffs when consider multi-risk objectives For processes with sequential structure, holding other factors constant, –The highest control allocations occur at tasks towards the center of the process. For processes with parallel structure, holding other factors constant, –The highest control allocations occur at the merging tasks of the process.

23 Risk Workshop SAMSI23 Outline Motivation and problem definition Methodology Experimental study Real world application Future research

24 Risk Workshop SAMSI24 An Order Fulfillment Process The Data: 15 tasks, 13 internal tasks, 46 errors that occur in different tasks, costs per error per type, frequencies of error occurrences, cost factors of controls, based 1200 orders per month. Case Study

25 Risk Workshop SAMSI25 The tasks: 0) Clients place order, 1) Enter order information, 2) Check payer and insurance info. 3) Create/update contracts, 4) Prove prescription, 5) Prepare prescribed items, 6) Dispense from alternative source, 7) Submit drug orders to wholesaler, 8) Deliver medication, 9) Prepare and send claims to an insurance company or 10) to the responsible party, 11) Collect payments, 12) Post payments and prepare vouchers, 13) Update ledgers, 14) insurer/clients pay bills. Results: Optimal Allocation of Control Resource

26 Risk Workshop SAMSI26 The tasks: 0) Clients place order, 1) Enter order information, 2) Check payer and insurance info. 3) Create/update contracts, 4) Prove prescription, 5) Prepare prescribed items, 6) Dispense from alternative source, 7) Submit drug orders to wholesaler, 8) Deliver medication, 9) Prepare and send claims to an insurance company or 10) to the responsible party, 11) Collect payments, 12) Post payments and prepare vouchers, 13) Update ledgers, 14) insurer/clients pay bills. Results: Optimal Objective Function Values

27 Risk Workshop SAMSI27 Outline Motivation and problem definition Methodology Experimental study Real world application Future research

28 Risk Workshop SAMSI28 Summary –Risk management models for error associated risks in business process information flow Future research –Sensitivity analysis of the effect of other factors on optimal control allocations and risk objectives Loss per error, Control effectiveness, Cost structure of controls, Topological redesign, Analytic solution for CVaR –Managerial problems Multi-Objective Optimization Find the maximum confidence level β for a given value-at-risk Given the output errors, identify the most probable error sources Many others. Future research


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