流程探勘與它在評估流程 成本及分析流程上之應用 徐立群 成功大學會計學系 長榮大學資訊暨工程學院 Outline Introduction to Process Mining Data explosion challenge ; exploit the value of ever increasing business data Process mining The three main purposes of process mining: discovery, conformance, and enhancement Estimating process costs w/ process mining Analyzing processes w/ process mining An example taken from BPIC 2012 challenge Physical universe vs. digital universe “The state of a bank” is mainly determined by the data stored in the bank’s information system. Money has become a predominantly digital entity . Nowadays, when the booking of an HSR seat is successful, the customer can receive an e-ticket that can be carried by a smart phone. Page 4 Physical universe vs. digital universe (cont) When the ERP system of a manufacturer indicates that a particular product is out of stock, it is impossible to sell or ship the product even when it is available in physical form. Technologies such as RFID, GPS, and sensor networks will stimulate a further alignment of the digital universe and the physical universe. Page 5 Exploiting the value of ever increasing business data One of the main challenges of today’s organizations is to extract information and value from data stored in their information systems. The importance of information systems is not only reflected by the spectacular growth of data, but also by the role that these systems play in today’s business processes as the digital universe and the physical universe are becoming more and more aligned. Page 6 Exploiting the value of ever increasing business data(cont) The growth of a digital universe that is well-aligned with processes in organizations makes it possible to record and analyze events. The challenge is to exploit event data in a meaningful way, for example, to provide insights, identify bottlenecks, anticipate problems, record policy violations, recommend countermeasures, and streamline processes. That is what process mining is all about. Page 7 Process mining vs BPM vs WFM Process mining, i.e., extracting valuable, process-related information from event logs, complements existing approaches to Business Process Management (BPM). BPM is the discipline that combines knowledge from information technology and knowledge from management sciences and applies this to operational business processes. BPM can be seen as an extension of Workflow Management (WFM). Page 8 Process mining vs BPM vs WFM (cont) WFM primarily focuses on the automation of business processes, whereas BPM has a broader scope: from process automation and process analysis to process management and the organization of work. BPM aims to improve operational business processes; for example, by modeling a business process and analyzing it using simulation, management may get ideas on how to reduce costs while improving service levels. Page 9 Example process model A Petri net modeling the handling of compensation request (taken from van der Aalst Process Mining text) Page 10 Process Models --- Informal and Formal Process models play important role in larger organizations. Typically, two types of models are used: (a) informal models and (b) formal models (also referred to as “executable models”). Informal models are used for discussion and documentation whereas formal models are used for analysis or enactment (i.e., the actual execution of process). Process Models --- Informal and Formal (cont) The value of models is limited if too little attention is paid to the alignment of model and reality. For example, it makes no sense to conduct simulation experiments while using a model that assumes an idealized model---incorrect redesign decisions are made. It is also precarious to start a new implementation project guided by process models that hide reality. Limitations Executable models may be used to force people to work in a particular manner. However, most models are not well-aligned with reality. Most hand-made models are disconnected from reality and provide only an idealized view on the processes at hand: “paper tigers”. Given (a) the interest in process models, (b) the abundance of event data, and (c) the limited quality of hand-made models, it seems worthwhile to relate event data to process models: process mining! Process Mining The idea of process mining is to discover, monitor and improve real processes (i.e., not assumed processes) by extracting knowledge from event logs readily available in today’s systems. Page 14 The three main uses of process mining: discovery, conformance, and enhancement Page 15 Estimating process costs w/ process mining 16 Event logs (taken from van der Aalst Process Mining text) 航空公司賠償流程 以代號表示 Petri Net Annotated transition system Case 1 Case 5 Case 3 Case 6 Case 4 Case 2 Case id Trace 1 abdeh 2 adceg 3 acdefbdeg 4 adbeh 5 acdefdcefcdeh 6 acdeg Decide the probabilities 1/6 1 1 Case id Trace 1 abdeh 2 adceg 3 acdefbdeg 4 adbeh 5 acdefdcefcdeh 6 acdeg 1 1/2 1 1 1 1 1 1 1 2/3 1/2 1 3/6 1 1 1 1 1 Activity 1/3 1/2 1 1 2/6 1/2 1 1 a register request b examine throughly c examine casually d check ticket e decide f reinitiate request g pay compensation h reject request Observations 1/6的Case會先 詳細的檢查(b) , 但最後被拒絕 重新申請的Case 有1/2會被接受, 有1/ 2會被拒絕 3/6的Case會大 略的檢查(c) -> 1/3接受,2/3再 重新申請 ✔ ✔ 2/6會先驗票(d), 最後有1/2會被接受, 有1/2會被拒絕 流程拖的較長的 case都牽涉到 「大略檢查」 (activity c) ✔ 整體來看,六個Case 的求償成功率為1/2。 (h = reject request) Process cost 利用Event log 所留下的Cost,計算流程成本 Activity Cost a register request 50 examine throughly 400 c examine casually 400 d check ticket 100 e decide 200 Case id Trace Cost 1 2 3 4 abdeh adceg acdefbdeg adbeh acdefdcefcde h acdeg SUM AVG 950 950 1850 950 b f reinitiate request 200 2750 g pay compensation 200 h reject request 200 5 6 950 8400 1400 50+400+100+200+200 = 950 流程成本 $950 $2750 2300×⅔+950×⅓≅1850 $1850 $950 950×⅙+1850×½+950 ×⅓≅1400 950×½+950×½≅950 $950 $950 在發生了acdef流程時,預 期此處流程的成本為$2300 2750×½+1850×½=2300 流程成本-決策樹 用決策樹的方式,不止可以得到平均成本$1400,也可以得到 各個決策點的總流程成本。管理者可以思考如何改進流程以降 低總成本。 $950 $950 $2750 $2300 $1400 $1850 $2750 $1850 $950 $950 $1850 在發生了acdef流程後,預期整 $950 個流程的成本為$2300,高於 $950 $950 原來預期的1400 $950 $950 Analyzing processes w/ process mining BPIC 2012 on the loan and overdraft approvals process of a real-world financial institution in the Netherlands. Attempted to investigate following areas in detail: Develop thorough understanding of the data Develop a detailed understanding of the underlying process Understand critical activities and decision points Understand and map life cycle of a loan application from start to eventual disposition as approved, declined or cancelled Identify any resource level differences in performance one can discern based on available data Identify opportunities for “process interventions”:places in the process based on likelihood of success 27 Materials and Methods The data captures process events for 13,087 loan / overdraft applications over a roughly six month period from October 2011 to March 2012. The event log is comprised of a total of 262,200 events within these 13,087 cases. Starting with a customer submitting an application and ending with eventual conclusion of that application into an Approval, Cancellation or Rejection 28 (Delined). Log Description An application is submitted through a webpage. Then, some automatic checks are performed, after which the application is complemented with additional information. This information is obtained through contacting the customer by phone. If an applicant is eligible, an offer is sent to the client by mail. After this offer is received back, it is assessed. When it is incomplete, missing information is added by again contacting the customer. Then a final assessment is done, after which the application is approved and activated. 29 Developing Thorough Understanding of the data 30 Determining Standard Case Flow 31 Determining Standard Case Flow Original Explanation afhandelen leads Following up on incomplete initial submissions completeren aanvraag Completing pre-accepted applications nabellen offertes Follow up after transmitting offers to qualified applicants nabellen incomplete Seeking additional information during assessment phase valideren aanvraag Assessing the application 32 Understanding Eventual Outcomes for Each Application 33 Understanding Eventual Outcomes for Each Application 1/4立即被拒絕 開始到後續大約剩下 1/4被拒絕 34 Case-Level Analysis 35 Case-Level Analysis 分965或966個 case為一個區 段來看 36 Case-Level Analysis 拒絕 取消 核准 37 Performance of the Top 5 Resources based on Time Spent 最有經驗的人所花的 時間>全體平均 38 Conclusions Process mining is a new technique that allows one to zoom into the details of actual business processes --- X ray for business processes. More applications are needed to show its usefulness. 39 Thank you for your listening! Department of Accountancy National Cheng Kung University Chang Jung Christian University College of Information & Engineering 40