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信用管理与催收属性 (19) 信用管理与催收活动 (12) 提取指南 (4)

您的信用管理与收账数据模板

此模板为您收集分析和优化信用管理与收账流程所需的数据提供了清晰的指南。它概述了要收集的关键属性、要追踪的核心活动以及来自 SAP S/4HANA 系统的实际提取指导。请利用此资源确保您捕获了所有关键信息，以进行稳健的流程分析。

建议在事件日志中收集的属性
要在发票全生命周期中追踪的关键流程活动
SAP S/4HANA 的具体提取指南

不熟悉事件日志？了解如何创建流程挖掘事件日志.

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信用管理与催收属性

这些是建议包含在事件日志中的数据字段，用于对信用管理与收账流程进行全面分析。

3 必填 5 推荐 11 可选

	名称	描述
	Event 时间 EventTime	活动发生的时间戳。
描述该属性为每个记录的活动提供精确的日期和时间。它对于确定事件顺序和计算各步骤之间的时长至关重要。事件时间（Event Time）用于按时间先后对活动进行排序、构建流程图并计算性能指标。例如，通过测量“争议已登记”和“争议已解决”时间戳之间的时间间隔，来计算“平均争议解决时间”。为何重要它提供了 event 的时间顺序，这对于计算周期时间、分析流程绩效和发现瓶颈是必需的。获取方式源自 SAP 各类表中的日期和时间字段，例如 BKPF 中的 BUDAT（过账日期），或不同表中的 CPUDT/CPUTM（输入日期/时间）。更改日志表 CDHDR/CDPOS 也包含时间戳。示例 2023-04-15T10:00:00Z2023-05-01T14:30:00Z2023-05-10T09:15:00Z
	发票编号 InvoiceNumber	客户发票的唯一标识符，作为信用管理与收账流程的主要 case ID。
描述发票编号（通常体现为会计凭证编号）是每笔应收账款交易的唯一标识。它是连接所有流程事件的核心线索，涵盖了从发票创建、催款通知到争议管理，直至最终付款或核销的全过程。在流程挖掘中，分析每个发票编号的流转路径可以实现端到端流程的全景视图。这有助于识别常见路径、付款处理中的瓶颈以及处理不同发票时的偏差，这对于“发票流程变体分析”和“逾期发票账龄与状态”等仪表板至关重要。为何重要它是关键的 case 标识符，连接了所有相关的信用和催收活动，从而实现每笔应收账款的全生命周期分析。获取方式通常在表 BKPF（会计凭证抬头）中体现为字段 BELNR，或在 VBRK（开票凭证：抬头数据）中体现为字段 VBELN。示例 190000012319000004561900000789
	活动名称 ActivityName	信用管理与收账流程中发生的特定业务事件名称。
描述该属性描述了流程中的单个步骤或任务，例如“发票已生成”、“催款程序已启动”或“收到付款”。这些活动的顺序构成了每个案例的流程流。分析活动名称（Activity Name）是流程挖掘的基础，因为它能帮助发现流程图、识别变体并衡量不同步骤之间的转换。它是几乎所有流程分析的基础，包括计算“催款成功率”等 KPI。为何重要它定义了流程的步骤，这对于可视化流程图、分析变体和理解流程流至关重要。获取方式通过组合事务代码 (TCODE)、表更改日志 (CDHDR/CDPOS) 或 SAP 凭证中的状态字段生成。示例发票已发送给客户催收程序已启动已收到付款争议 case 已登记
	付款到期日 PaymentDueDate	发票的付款到期日。
描述付款截止日期是根据发票日期和与客户约定的付款条件计算得出的。它是衡量付款及时性的基准。该日期是所有逾期分析的基础。它是计算“逾期天数”和触发催收程序的起点。诸如“逾期发票账龄与状态”仪表板以及“平均应收账款周转天数 (DSO)”等 KPI 均高度依赖此属性。为何重要它是确定发票是否逾期的关键日期，用于触发催收活动并计算关键 KPI。获取方式位于会计凭证的客户行项目中，表 BSEG（字段 ZFBDT）。示例 2023-05-302023-06-152023-07-01
	发票金额 InvoiceAmount	以凭证货币计的发票总金额。
描述该属性代表发票所载商品或服务的总货币价值。它是衡量每个案例财务影响的关键指标。分析发票金额是优化催收优先级的基础（如“催收组合优先级”仪表板所示）。它还用于评估流程效率低下带来的财务影响，例如争议发票的总额或逾期应收账款中占用的资金量。它通过提供价值基准，直接支持“发票核销比例”等 KPI。为何重要它量化了每个 case 的财务价值，这对于优先级排序、风险评估和绩效衡量至关重要。获取方式源自表 BSEG 中的会计凭证行项目（字段 DMBTR 为本币金额，WRBTR 为凭证货币金额）。示例 1500.0025000.50750.75
	客户编号 CustomerNumber	客户账户的唯一标识符。
描述客户编号是收到发票的业务伙伴的唯一标识，它将财务交易与客户的主数据记录关联起来。该属性对于以客户为中心的分析至关重要，例如识别特定客户或客群的付款行为。它在“客户付款行为趋势”等仪表板中被用于追踪哪些客户经常逾期付款，并通过按客户对发票进行分组，为“高优先级账户覆盖率”等 KPI 提供数据支持。为何重要它将交易与特定客户联系起来，从而实现对付款行为、细分和关系管理的分析。获取方式位于表如 BSEG（字段 KUNNR）的会计凭证行项目中，或客户主数据表 KNA1 中。示例 CUST100234CUST200567CUST300890
	用户名称 UserName	执行该活动的用户ID。
描述该属性用于识别负责特定流程步骤的特定用户，例如过账付款或启动催款运行。在 SAP 中，这通常存储在“用户名”(UNAME) 或“输入者”字段中。按用户分析有助于识别表现优秀的个人或团队，以及需要额外培训的领域和工作量分配模式。它还可以用于调查合规问题或未经授权的操作。例如，它通过追踪每个催收员的成果来支持“催收沟通有效性”仪表板。为何重要它将流程活动与特定个人联系起来，从而实现对资源绩效、工作负载和合规性的分析。获取方式通常位于抬头表如 BKPF（字段 USNAM）或更改日志表如 CDHDR（字段 USERNAME）中。示例 JSMITHRROEBATCH_USER
	逾期天数 DaysOverdue	发票超过其付款截止日期的天数。
描述这是一个计算出的指标，用于衡量“付款截止日期”与当前日期（针对未结发票）或“付款日期”（针对已结发票）之间经过的时间。正值表示付款逾期。逾期天数（Days Overdue）是收账流程的核心 KPI。它是“逾期发票账龄与状态”仪表板中的主要指标，用于确定催收工作的优先级。分析该指标的分布情况有助于了解应收账款投资组合的整体健康状况。为何重要它是衡量催收效果的关键绩效指标，用于账龄分析、工作优先级排序和衡量付款延迟。获取方式在 data 转换期间计算：（当前日期或清账日期）- 付款到期日 (BSEG-ZFBDT)。示例 1530920
	争议原因 DisputeReason	客户对发票提出争议的原因代码。
描述当客户对发票提出争议时，通常会分配一个原因来对问题的性质进行分类，如“定价错误”、“货物损坏”或“重复发票”。这在 SAP 争议管理模块中进行管理。分析争议原因（Dispute Reasons）是识别客户不满和付款延迟根本原因的关键。可以在“发票争议量与解决”仪表板中按此属性进行维度分析，以查明上游订单到现金流程中需要解决的周期性问题。为何重要它提供了关于发票争议根本原因的关键洞察，有助于识别并解决潜在的业务运营问题。获取方式源自 SAP 争议管理（Dispute Management）模块，通常根据争议案例属性从 UDM_SCASE_ATTR 等类似表中获取。示例 PRC_ERR - 定价错误QTY_DIF - 数量差异SHIP_DMG - 货物受损
	信用额度 CreditLimit	给予客户的最高信用限额。
描述信用额度是存储在客户信用主数据中的一个数值，定义了公司愿意承担的最高信用敞口。诸如“已申请信用额度”和“已批准信用额度”等活动直接与此属性相关。该属性为信用风险分析提供了背景。“信用审批周期分析”仪表板用于追踪设置或更改此限额的过程。将其与逾期金额结合分析，有助于评估整体投资组合风险。为何重要它定义了客户获批的信用风险，是分析信用审批流程和整体信用敞口的核心。获取方式存储在 SAP 信用管理 (FSCM) 模块中，例如表 UKM_BP_CMS_SGMT（字段 CREDIT_LIMIT）。示例 50000.00100000.00250000.00
	催款等级 DunningLevel	指示逾期发票催收流程的当前阶段。
描述催款级别代表催收工作的力度，通常从简单的提醒升级到正式的法律通知。每个级别对应催款程序中定义的特定催收活动。追踪此属性对于监控催收流程的有效性和合规性至关重要。“催收流程有效性”仪表板利用此属性分析不同级别的回款率，而“催收流程合规性”仪表板则检查催款级别的执行顺序是否正确。为何重要它追踪催收工作的进展，从而实现对催收效果和流程合规性的分析。获取方式此信息存储在催款数据表（如 MHND）中。某项的最后催款级别可在 BSEG（字段 MANST）中找到。示例 123 - 最后通知法律诉讼
	公司代码 CompanyCode	代表独立法人公司的组织单位，用于创建财务报表。
描述公司代码是 SAP 财务系统中的基本组织实体。所有的财务交易（包括发票和付款）都会过账到特定的公司代码下。在流程挖掘中，通过公司代码进行过滤或维度分析，对于比较集团内不同法人实体的流程表现至关重要。这有助于识别某个实体的最佳实践并推广，或查明影响特定公司的系统性问题。它是几乎所有财务流程分析的核心过滤维度。为何重要它允许在组织内的不同法律实体之间进行流程绩效和合规性的比较。获取方式位于大多数财务表中，如 BKPF 和 BSEG（字段 BUKRS）。示例 10002000US01DE01
	最后数据更新 LastDataUpdate	此属性指示data最后一次从Salesforce Financial Services Cloud提取的日期和时间，为分析数据“新鲜度”提供背景。这对于dashboard用户理解分析时效性至关重要，有助管理数据及时性预期，并验证data pipelines是否按计划运行。
描述该属性指示数据集的最后更新时间，让用户了解所分析数据的时效性。对于任何仪表板或分析来说，这都是至关元的数据。它告知用户分析所涵盖的时间段，防止基于过时信息产生误读。例如，只有在用户知道数据最后提取时间的情况下，对逾期发票的分析才有意义。为何重要它确保用户了解 data 的时效性，这对于做出准确的、由 data 驱动的决策至关重要。获取方式此值在数据提取、转换和加载 (ETL) 过程中生成并存储。示例 2023-10-27T02:00:00Z2023-10-26T02:00:00Z
	发票币种 InvoiceCurrency	开具发票的货币。
描述该属性指定了发票金额的货币代码（如 CNY, USD）。它为解读货币价值提供了必要的背景，尤其是在跨国企业中。虽然大多数分析是以标准化的本位币进行的，但凭证货币对于理解原始交易以及任何与汇率影响相关的分析都非常重要。它为 InvoiceAmount 属性提供了补充背景。为何重要它为发票金额提供了必要的背景信息，从而实现在多货币环境下的准确财务分析。获取方式通常可在抬头表如 BKPF（字段 WAERS）或行项目表如 BSEG（字段 PSWSL）中找到。示例美元EURGBP
	处理时间 ProcessingTime	特定活动的持续时长。
描述该属性衡量完成一项活动所需的时间，计算为活动结束时间与开始时间之差。这对于非即时完成的活动最为相关。对于 SAP 中的许多财务交易，开始和结束时间是相同的。然而，对于争议解决等流程，此指标可以衡量案例处于特定状态的时长。它通过测量过账活动的持续时间，直接支持“付款过账周期”等 KPI。为何重要它有助于识别流程中可能成为瓶颈的耗时活动。获取方式根据 event data 计算为（结束时间 - 开始时间）。每个活动都需要开始和结束 timestamp。示例 P1DPT2H30MP3DT5H
	客户细分 CustomerSegment	客户的一种分类方式，例如根据规模、行业或战略重要性进行划分。
描述客户群是一种营销或销售分类，用于将具有相似特征的客户归组。这可以基于年度收入、行业、地理位置或关系状态（如金牌、银牌、铜牌客户）等因素。在催收分析中，按此属性进行细分有助于发现特定群体的模式。例如，“发票核销分析”Dashboard 可以揭示某个特定细分群体是否产生了不成比例的核销金额，从而指导该细分群体信用政策的战略决策。为何重要它使分析不同客户群的流程绩效和客户行为成为可能，从而揭示宝贵的战略洞察。获取方式通常源自客户主数据（表 KNA1），通常位于分类或属性字段中，如 KDKG1-KDKG5（客户组 1-5）。示例大型企业中小企业政府战略账户
	是否已自动化 IsAutomated	一个标志位，指示活动是由系统用户还是人工用户执行的。
描述此布尔属性用于区分系统自动执行的活动（如预定的催款运行、自动付款过账）和用户手动执行的活动（如催收电话）。分析此属性有助于衡量流程的自动化水平。它可以比较自动步骤与手动步骤的效率和一致性，识别进一步自动化的机会，并了解收账流程中真实的纯手工成本。为何重要它有助于量化流程的自动化程度，从而分析自动化对效率和成本的影响。获取方式这是一个衍生属性，通常基于“用户名”。如果用户 ID 与预定义的系统或批处理用户列表（如 'BATCH_USER'）匹配，则该标志设为 true。示例 truefalse
	核销原因 WriteOffReason	解释发票为何被视为无法收回并进行核销的逻辑代码。
描述当一笔应收账款被认定为无法收回时，它将从账面上核销，并分配一个原因代码来对原因进行分类，如“破产”、“小额核销”或“未解决的争议”。该属性对于“发票核销分析”仪表板至关重要。通过按原因分析核销的频率和价值，公司可以识别其信用政策或催收策略中的薄弱环节，并采取纠正措施以最大程度减少未来的损失。为何重要它解释了因坏账带来的财务损失的根本原因，为改进信用和催收政策提供信息。获取方式这通常在用于应收账款核销的特定财务过账事务（如 F-30）期间，通过原因代码字段 (BSEG-RSTGR) 捕获。示例破产小额余额争议损失
	源系统 SourceSystem	用于标识数据来源的系统。
描述该属性指定了源信息系统，在本例中为 SAP S/4HANA。在需要整合多个系统数据（如不同 ERP 实例或独立的 CRM）的环境中，这一点尤为重要。在流程分析中，这有助于区分可能跨越多个系统的流程，或允许将分析过滤到特定的系统实例。它确保了数据血缘，并在数据验证和故障排除期间提供背景信息。为何重要它提供了有关 data 来源的关键背景信息，确保多系统环境下的清晰度并辅助 data 治理。获取方式这通常是在数据提取过程中添加的静态值，用于标识特定的 SAP S/4HANA 实例（例如通过系统 ID 或 SID）。示例 S4H_PROD_100S4HANA_FINANCE_EUSAP_ECC_US

必填推荐可选

信用管理与催收活动

这些是需要在事件日志中捕获的关键流程步骤和里程碑，旨在帮助您准确发现并优化催收工作流。

6 推荐 6 可选

	活动	描述
	争议 case 已登记	此活动表示客户已正式对发票提出争议，且在 SAP 争议管理中创建了案例。当新案例创建并关联到发票凭证时，系统会捕获此事件。
为何重要登记争议是理解流程异常的关键步骤。分析争议的数量、原因和解决时间有助于识别根本原因，如定价错误或运输失误。获取方式这是 SAP 争议管理表中记录的一个明确事件。关联到发票的 UKM_CASE 或 FDM_DCOBJ 等表中案例的创建日期可作为时间戳。捕获使用 UKM_CASE 表中争议案例的创建时间戳，并按争议的案例类型进行过滤。事件类型 explicit
	发票已核销	此活动代表决定将未付发票吸收为损失，归类为坏账。当过账了特定类型的清算凭证（通常带有唯一的原因为代码）时，该事件会被捕获。
为何重要核销代表直接的财务损失。分析其频率、价值及前置活动有助于识别风险客户和收账流程中的失效点。获取方式这可以通过分析结算发票的清算凭证来推断。清算凭证中使用的特定总账科目或原因代码 (BSEG-RSTGR) 通常表示进行了核销。捕获识别清账凭证，并检查特定的原因代码或是否过账到坏账科目。事件类型 inferred
	发票已结清	这是发票的最终圆满结果，表示款项已全额支付并已从待结项中清除。当发票具有相应的清算凭证和日期时，即可认定为该状态。
为何重要作为流程的主要成功终点，此活动标志着发票生命周期的结束。分析达到此状态的路径和所需时间是流程优化的基础。获取方式这并非一个离散事件，而是从财务表中推断出的状态。当发票出现在客户已结清项表 BSAD 中且具有有效的清算日期 (AUGDT) 时，即视为已结算。捕获使用 BSAD 表中的清算日期 (AUGDT) 作为此结束活动的时间戳。事件类型 inferred
	已收到付款	此活动代表收到客户资金并用于冲抵未结发票。它是通过创建结算发票金额的清算凭证来捕获的。
为何重要这是一个直接影响现金流和 DSO 的关键里程碑。分析回款时间及其前置活动可以揭示整个收账流程的有效性。获取方式这可以从针对该发票过账的清算凭证中推断。已结清项表 BSAD 中该特定发票的清算日期 (AUGDT) 提供了时间戳。捕获从表 BSAD 中为对应的发票凭证编号 (BELNR) 识别清账日期 (AUGDT)。事件类型 inferred
	已生成发票	此活动标志着客户发票的生成，也是收账流程的起点。当 SAP S/4HANA 系统中过账了发票类型的会计凭证时，该事件即被捕获。
为何重要这是“发票到现金”流程的主要起始事件。分析从这一刻到回款的时间，对于衡量应收账款周转天数 (DSO) 和整体流程效率至关重要。获取方式此事件有明确记录。可在会计凭证抬头表 BKPF 中根据相关凭证编号 (BELNR) 查找创建日期和时间。凭证类型如“RV”通常表示客户发票。捕获使用 BKPF 表中发票凭证的凭证创建时间戳 (CPUDT, CPUTM)。事件类型 explicit
	已过付款截止日期	一个计算出的 event，当当前日期超过发票的净到期日且未过账清账付款时发生。它标志着发票从“当前”状态转为“逾期”状态。
为何重要此活动是所有催收和催款任务的触发点。对于分析付款行为、逾期原因以及主动提醒的有效性至关重要。获取方式这不是一个显式日志。它是通过将净到期日（来自 BSID 表字段 ZFBDT 等）与分析的时间戳或后续活动的时间戳进行对比计算得出的。捕获通过比较发票净到期日 (BSID-ZFBDT) 与当前 timestamp 或后续 event 的 timestamp 来得出。事件类型 calculated
	争议已解决	此活动标志着争议案例的结束，无论是因为客户的主张获得认可还是被驳回。当争议案例的状态更新为“已关闭”或“已解决”时，系统会捕获此事件。
为何重要解决争议所需的时间是衡量客户满意度和运营效率的关键指标。解决时间过长会推迟回款，并使客户关系紧张。获取方式这可以从争议案例的状态更改中推断。UKM_CASE 表中状态更改为“已关闭”或“已确认”的相关时间戳表示争议解决的时间。捕获在表 UKM_CASE 或相关的状态更改日志表中，识别状态更改为最终解决状态的 timestamp。事件类型 inferred
	付款已过账	代表付款记入总账的会计分录。通常这与收到付款同步发生，但也可能是一个独立的步骤，并存在延迟。
为何重要收到现金到过账之间的延迟会扭曲财务报告。衡量这一周期时间有助于确保会计流程的高效和准确。获取方式此事件可以从 BKPF 表中清算凭证的过账日期 (BUDAT) 或创建日期 (CPUDT) 推断。清算凭证编号可在 BSAD-AUGBL 中找到。捕获使用 BKPF 表中结算该发票的清算凭证的过账日期 (BUDAT)。事件类型 inferred
	催收程序已启动	此活动代表正式启动针对逾期发票的自动催款程序。当催款运行处理了该发票并分配了催款级别时，该事件即被捕获。
为何重要这标志着自动催款的开始。追踪催款活动是评估催款策略有效性以及确保符合内部政策的关键。获取方式这是催款数据表中记录的一个明确事件。来自催款抬头表 MHNK 且与发票关联的运行日期 (LAUFD) 表示程序的执行时间。捕获提取特定发票的催收运行日期 (MHNK-LAUFD) 和催收级别 (MHNK-MAHNS)。事件类型 explicit
	发票已发送给客户	代表发票通过打印、电子邮件或 EDI 等方式发送给客户的时刻。这通常通过 SAP 的输出确定日志捕获，记录输出消息的处理时间。
为何重要发票生成和发送之间的延迟会延长整个付款周期。追踪这一过程有助于识别客户沟通和单据分发中的瓶颈。获取方式这可以从消息状态表 NAST 中的处理日期和时间推断，其中输出类型对应客户发票。这需要预先正确配置输出确定。捕获在与发票开票凭证编号关联的 NAST 表中查找处理成功的记录。事件类型 inferred
	已创建付款承诺	当催收人员记录客户承诺在特定日期支付逾期款项时，会发生此事件。这是 SAP 催收管理模块中的一个明确操作。
为何重要付款承诺是催收活动的重要产出。分析其频率、履行率以及对回款时间的影响，有助于进一步完善催收策略。获取方式这是 SAP 催收管理中记录的一个明确事件。付款承诺的创建日期可以从 UDM_P2P_ATTR 等表中获取。捕获使用付款承诺表（如 UDM_P2P_ATTR）中关联到该发票的创建日期。事件类型 explicit
	已拨打催收电话	代表催收人员就逾期发票与客户进行的人工联系。这通常不是标准的 SAP 事件，需要依靠自定义日志或 CRM 系统集成。
为何重要人工干预是收账流程中成本最高的部分。追踪这些沟通记录有助于衡量催收人员的效率，并明确哪些账户需要重点人工跟进。获取方式此信息在标准 S/4HANA 配置中通常不可用。它可能存储在自定义表中、收账工作列表的备注中，或存储在需要集成的外部 CRM 系统中。捕获需要分析系统增强功能、备注或记录了催收活动的外部系统数据。事件类型 explicit

推荐可选

提取指南

如何从 SAP S/4HANA 获取您的数据

步骤

验证 CDS 视图可访问性：登录您的 SAP S/4HANA 系统并使用“视图浏览器”Fiori 应用。搜索查询中提到的关键 CDS 视图（如 I_OperationalAcctgDocItemCube 和 I_DisputeCase），确保它们处于激活状态并包含 data。这能确认必要组件是否可用。
公开 OData 服务：使用事务 /IWFND/MAINT_SERVICE 验证相关的 CDS 视图是否已作为 OData 服务发布。如果尚未发布，您需要发布它们以便外部工具访问。
建立客户端连接：使用您的 data 提取工具（如 Microsoft Power BI、SAP Analytics Cloud、Python 等）创建与 SAP S/4HANA 系统 OData 端点的新连接。
身份验证：提供连接详情，并使用拥有足够权限读取财务会计、催收管理和争议管理 data 的用户 ID 进行身份验证。
准备查询：复制本文档“查询”部分提供的完整 SQL 查询。
自定义参数：在查询文本中，将所有占位符值替换为特定于您的系统和分析范围的值。这包括 [Your Company Code]、[Start Date]、[End Date]、[Your Invoice Doc Type]、[Your Write-off Reason Code] 和 [Your Dispute Case Closed Status]。
调整自定义日志：“已拨打催收电话”活动依赖于占位符视图 [Your Custom Contact Log View]。您必须将其替换为您组织记录催收专员联系情况的实际表或视图。如果此 data 不可用，请从查询中删除整个 UNION ALL 代码块。
执行查询：从连接的客户端工具运行自定义查询。根据工具的不同，您可能需要将 SQL 语法调整为其特定的 OData 查询语言，例如将 WHERE 子句转换为 $filter 参数。
审核与验证：查询完成后，对返回的 data 进行初步审核。检查行数是否合理，并确保包含各种活动。
导出为 CSV：将完整的结果集导出为 CSV 文件。确保文件采用 UTF-8 编码以防止字符问题。
确认列标题：打开 CSV 文件并确认列标题与所需和推荐的属性完全匹配：InvoiceNumber、ActivityName、EventTime、UserName、CustomerNumber、InvoiceAmount、PaymentDueDate 和 DaysOverdue。
上传到 Process Mining 工具：完成的 CSV 文件现在可以上传到 ProcessMind 或您选择的 Process Mining 平台。

配置

日期范围：我们建议提取 3 到 6 个月的 data 切片，以平衡数据集的代表性与系统性能。查询中的占位符 [Start Date] 和 [End Date] 必须进行相应设置。
公司代码筛选器：查询设计为按 CompanyCode 进行筛选。一次仅限提取一个或少数几个公司代码，对于管理性能和创建集中分析至关重要。
凭证类型筛选器：必须使用 AccountingDocumentType 字段筛选特定的发票凭证类型（如“RV”）。这可以防止供应商发票或贷记通知单等无关凭证进入 event log。
可定制逻辑：多个活动依赖于特定配置的代码。您必须根据系统设置识别并提供 [Your Write-off Reason Code] 和 [Your Dispute Case Closed Status] 的正确值。
系统前提条件：此方法要求您的 S/4HANA 系统已启用财务供应链管理 (FSCM) 的争议和催收管理模块。如果没有这些模块，则无法提取“争议 case 已登记”和“已创建付款承诺”等相关活动。
授权：执行提取的 SAP 用户需要所有底层 CDS 视图的读取权限。这通常涉及总账会计（如 F_BKPF_BUK）、客户主数据和特定 FSCM 组件的授权对象。

a 查询示例 sql

SELECT
    INV.AccountingDocument AS "InvoiceNumber",
    'Invoice Generated' AS "ActivityName",
    INV.CreationDateTime AS "EventTime",
    INV.CreatedByUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    0 AS "DaysOverdue"
FROM I_OperationalAcctgDocItemCube AS INV
WHERE INV.CompanyCode IN ('[Your Company Code]') AND INV.AccountingDocumentType = '[Your Invoice Doc Type]' AND INV.CreationDate BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

SELECT
    INV.AccountingDocument AS "InvoiceNumber",
    'Invoice Sent To Customer' AS "ActivityName",
    OUTP.OutputRequestDateTime AS "EventTime",
    OUTP.LastChangedByUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < CAST(OUTP.OutputRequestDateTime AS DATE) THEN DATEDIFF(day, INV.NetDueDate, CAST(OUTP.OutputRequestDateTime AS DATE)) ELSE 0 END AS "DaysOverdue"
FROM I_BillingDocumentOutputRequest AS OUTP
JOIN I_OperationalAcctgDocItemCube AS INV ON OUTP.BillingDocument = INV.AccountingDocument AND INV.CompanyCode IN ('[Your Company Code]') AND INV.AccountingDocumentType = '[Your Invoice Doc Type]'
WHERE CAST(OUTP.OutputRequestDateTime AS DATE) BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

SELECT
    INV.AccountingDocument AS "InvoiceNumber",
    'Payment Due Date Passed' AS "ActivityName",
    INV.NetDueDate AS "EventTime",
    'SYSTEM' AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    0 AS "DaysOverdue"
FROM I_OperationalAcctgDocItemCube AS INV
WHERE INV.CompanyCode IN ('[Your Company Code]') AND INV.AccountingDocumentType = '[Your Invoice Doc Type]' AND INV.IsCleared = '' AND INV.NetDueDate BETWEEN '[Start Date]' AND '[End Date]' AND INV.NetDueDate < CURRENT_DATE

UNION ALL

SELECT
    REL.RelatedAccountingDocument AS "InvoiceNumber",
    'Dispute Case Registered' AS "ActivityName",
    DCASE.CreationDateTime AS "EventTime",
    DCASE.CreatedByUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < CAST(DCASE.CreationDateTime AS DATE) THEN DATEDIFF(day, INV.NetDueDate, CAST(DCASE.CreationDateTime AS DATE)) ELSE 0 END AS "DaysOverdue"
FROM I_DisputeCase AS DCASE
JOIN I_DisputeCaseRelatedObject AS REL ON DCASE.DisputeCase = REL.DisputeCase
JOIN I_OperationalAcctgDocItemCube AS INV ON REL.RelatedAccountingDocument = INV.AccountingDocument AND REL.RelatedCompanyCode = INV.CompanyCode AND INV.AccountingDocumentType = '[Your Invoice Doc Type]'
WHERE INV.CompanyCode IN ('[Your Company Code]') AND CAST(DCASE.CreationDateTime AS DATE) BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

SELECT
    DUN.AccountingDocument AS "InvoiceNumber",
    'Dunning Procedure Initiated' AS "ActivityName",
    DUN.DunningDate AS "EventTime",
    DUN.DunningRunUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < DUN.DunningDate THEN DATEDIFF(day, INV.NetDueDate, DUN.DunningDate) ELSE 0 END AS "DaysOverdue"
FROM I_DunningHistoryItem AS DUN
JOIN I_OperationalAcctgDocItemCube AS INV ON DUN.AccountingDocument = INV.AccountingDocument AND DUN.CompanyCode = INV.CompanyCode AND INV.AccountingDocumentType = '[Your Invoice Doc Type]'
WHERE DUN.CompanyCode IN ('[Your Company Code]') AND DUN.DunningDate BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

-- Note: This activity requires a custom view. Replace '[Your Custom Contact Log View]' with your specific implementation.
SELECT
    LOG.InvoiceReference AS "InvoiceNumber",
    'Collection Call Made' AS "ActivityName",
    LOG.CreationDateTime AS "EventTime",
    LOG.CreatedByUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < CAST(LOG.CreationDateTime AS DATE) THEN DATEDIFF(day, INV.NetDueDate, CAST(LOG.CreationDateTime AS DATE)) ELSE 0 END AS "DaysOverdue"
FROM [Your Custom Contact Log View] AS LOG
JOIN I_OperationalAcctgDocItemCube AS INV ON LOG.InvoiceReference = INV.AccountingDocument AND INV.CompanyCode IN ('[Your Company Code]') AND INV.AccountingDocumentType = '[Your Invoice Doc Type]'
WHERE CAST(LOG.CreationDateTime AS DATE) BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

SELECT
    P2P.OriginalReferenceDocument AS "InvoiceNumber",
    'Promise To Pay Created' AS "ActivityName",
    P2P.CreationDateTime AS "EventTime",
    P2P.CreatedByUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < CAST(P2P.CreationDateTime AS DATE) THEN DATEDIFF(day, INV.NetDueDate, CAST(P2P.CreationDateTime AS DATE)) ELSE 0 END AS "DaysOverdue"
FROM I_PromiseToPay AS P2P
JOIN I_OperationalAcctgDocItemCube AS INV ON P2P.OriginalReferenceDocument = INV.AccountingDocument AND P2P.CompanyCode = INV.CompanyCode AND INV.AccountingDocumentType = '[Your Invoice Doc Type]'
WHERE P2P.CompanyCode IN ('[Your Company Code]') AND CAST(P2P.CreationDateTime AS DATE) BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

SELECT
    INV.AccountingDocument AS "InvoiceNumber",
    'Payment Received' AS "ActivityName",
    INV.ClearingDate AS "EventTime",
    INV.ClearingJournalEntryUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < INV.ClearingDate THEN DATEDIFF(day, INV.NetDueDate, INV.ClearingDate) ELSE 0 END AS "DaysOverdue"
FROM I_OperationalAcctgDocItemCube AS INV
WHERE INV.CompanyCode IN ('[Your Company Code]') AND INV.AccountingDocumentType = '[Your Invoice Doc Type]' AND INV.IsCleared = 'X' AND INV.ClearingDate BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

SELECT
    INV.AccountingDocument AS "InvoiceNumber",
    'Payment Posted' AS "ActivityName",
    INV.ClearingDate AS "EventTime", -- Often same as Payment Received timestamp
    INV.ClearingJournalEntryUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < INV.ClearingDate THEN DATEDIFF(day, INV.NetDueDate, INV.ClearingDate) ELSE 0 END AS "DaysOverdue"
FROM I_OperationalAcctgDocItemCube AS INV
WHERE INV.CompanyCode IN ('[Your Company Code]') AND INV.AccountingDocumentType = '[Your Invoice Doc Type]' AND INV.IsCleared = 'X' AND INV.ClearingDate BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

SELECT
    REL.RelatedAccountingDocument AS "InvoiceNumber",
    'Dispute Resolved' AS "ActivityName",
    DCASE.LastChangeDateTime AS "EventTime",
    DCASE.LastChangedByUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < CAST(DCASE.LastChangeDateTime AS DATE) THEN DATEDIFF(day, INV.NetDueDate, CAST(DCASE.LastChangeDateTime AS DATE)) ELSE 0 END AS "DaysOverdue"
FROM I_DisputeCase AS DCASE
JOIN I_DisputeCaseRelatedObject AS REL ON DCASE.DisputeCase = REL.DisputeCase
JOIN I_OperationalAcctgDocItemCube AS INV ON REL.RelatedAccountingDocument = INV.AccountingDocument AND REL.RelatedCompanyCode = INV.CompanyCode AND INV.AccountingDocumentType = '[Your Invoice Doc Type]'
WHERE INV.CompanyCode IN ('[Your Company Code]') AND DCASE.DisputeCaseProcessingStatus = '[Your Dispute Case Closed Status]' AND CAST(DCASE.LastChangeDateTime AS DATE) BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

SELECT
    INV.AccountingDocument AS "InvoiceNumber",
    'Invoice Settled' AS "ActivityName",
    INV.ClearingDate AS "EventTime",
    INV.ClearingJournalEntryUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < INV.ClearingDate THEN DATEDIFF(day, INV.NetDueDate, INV.ClearingDate) ELSE 0 END AS "DaysOverdue"
FROM I_OperationalAcctgDocItemCube AS INV
WHERE INV.CompanyCode IN ('[Your Company Code]') AND INV.AccountingDocumentType = '[Your Invoice Doc Type]' AND INV.IsCleared = 'X' AND INV.ClearingDate BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

SELECT
    INV.AccountingDocument AS "InvoiceNumber",
    'Invoice Written Off' AS "ActivityName",
    INV.ClearingDate AS "EventTime",
    INV.ClearingJournalEntryUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < INV.ClearingDate THEN DATEDIFF(day, INV.NetDueDate, INV.ClearingDate) ELSE 0 END AS "DaysOverdue"
FROM I_OperationalAcctgDocItemCube AS INV
WHERE INV.CompanyCode IN ('[Your Company Code]') AND INV.AccountingDocumentType = '[Your Invoice Doc Type]' AND INV.IsCleared = 'X' AND INV.ClearingReason = '[Your Write-off Reason Code]' AND INV.ClearingDate BETWEEN '[Start Date]' AND '[End Date]'

步骤

验证 CDS 视图可访问性：登录您的 SAP S/4HANA 系统并使用“视图浏览器”Fiori 应用。搜索查询中提到的关键 CDS 视图（如 I_OperationalAcctgDocItemCube 和 I_DisputeCase），确保它们处于激活状态并包含 data。这能确认必要组件是否可用。
公开 OData 服务：使用事务 /IWFND/MAINT_SERVICE 验证相关的 CDS 视图是否已作为 OData 服务发布。如果尚未发布，您需要发布它们以便外部工具访问。
建立客户端连接：使用您的 data 提取工具（如 Microsoft Power BI、SAP Analytics Cloud、Python 等）创建与 SAP S/4HANA 系统 OData 端点的新连接。
身份验证：提供连接详情，并使用拥有足够权限读取财务会计、催收管理和争议管理 data 的用户 ID 进行身份验证。
准备查询：复制本文档“查询”部分提供的完整 SQL 查询。
自定义参数：在查询文本中，将所有占位符值替换为特定于您的系统和分析范围的值。这包括 [Your Company Code]、[Start Date]、[End Date]、[Your Invoice Doc Type]、[Your Write-off Reason Code] 和 [Your Dispute Case Closed Status]。
调整自定义日志：“已拨打催收电话”活动依赖于占位符视图 [Your Custom Contact Log View]。您必须将其替换为您组织记录催收专员联系情况的实际表或视图。如果此 data 不可用，请从查询中删除整个 UNION ALL 代码块。
执行查询：从连接的客户端工具运行自定义查询。根据工具的不同，您可能需要将 SQL 语法调整为其特定的 OData 查询语言，例如将 WHERE 子句转换为 $filter 参数。
审核与验证：查询完成后，对返回的 data 进行初步审核。检查行数是否合理，并确保包含各种活动。
导出为 CSV：将完整的结果集导出为 CSV 文件。确保文件采用 UTF-8 编码以防止字符问题。
确认列标题：打开 CSV 文件并确认列标题与所需和推荐的属性完全匹配：InvoiceNumber、ActivityName、EventTime、UserName、CustomerNumber、InvoiceAmount、PaymentDueDate 和 DaysOverdue。
上传到 Process Mining 工具：完成的 CSV 文件现在可以上传到 ProcessMind 或您选择的 Process Mining 平台。

配置

日期范围：我们建议提取 3 到 6 个月的 data 切片，以平衡数据集的代表性与系统性能。查询中的占位符 [Start Date] 和 [End Date] 必须进行相应设置。
公司代码筛选器：查询设计为按 CompanyCode 进行筛选。一次仅限提取一个或少数几个公司代码，对于管理性能和创建集中分析至关重要。
凭证类型筛选器：必须使用 AccountingDocumentType 字段筛选特定的发票凭证类型（如“RV”）。这可以防止供应商发票或贷记通知单等无关凭证进入 event log。
可定制逻辑：多个活动依赖于特定配置的代码。您必须根据系统设置识别并提供 [Your Write-off Reason Code] 和 [Your Dispute Case Closed Status] 的正确值。
系统前提条件：此方法要求您的 S/4HANA 系统已启用财务供应链管理 (FSCM) 的争议和催收管理模块。如果没有这些模块，则无法提取“争议 case 已登记”和“已创建付款承诺”等相关活动。
授权：执行提取的 SAP 用户需要所有底层 CDS 视图的读取权限。这通常涉及总账会计（如 F_BKPF_BUK）、客户主数据和特定 FSCM 组件的授权对象。

a 查询示例 sql

SELECT
    INV.AccountingDocument AS "InvoiceNumber",
    'Invoice Generated' AS "ActivityName",
    INV.CreationDateTime AS "EventTime",
    INV.CreatedByUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    0 AS "DaysOverdue"
FROM I_OperationalAcctgDocItemCube AS INV
WHERE INV.CompanyCode IN ('[Your Company Code]') AND INV.AccountingDocumentType = '[Your Invoice Doc Type]' AND INV.CreationDate BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

SELECT
    INV.AccountingDocument AS "InvoiceNumber",
    'Invoice Sent To Customer' AS "ActivityName",
    OUTP.OutputRequestDateTime AS "EventTime",
    OUTP.LastChangedByUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < CAST(OUTP.OutputRequestDateTime AS DATE) THEN DATEDIFF(day, INV.NetDueDate, CAST(OUTP.OutputRequestDateTime AS DATE)) ELSE 0 END AS "DaysOverdue"
FROM I_BillingDocumentOutputRequest AS OUTP
JOIN I_OperationalAcctgDocItemCube AS INV ON OUTP.BillingDocument = INV.AccountingDocument AND INV.CompanyCode IN ('[Your Company Code]') AND INV.AccountingDocumentType = '[Your Invoice Doc Type]'
WHERE CAST(OUTP.OutputRequestDateTime AS DATE) BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

SELECT
    INV.AccountingDocument AS "InvoiceNumber",
    'Payment Due Date Passed' AS "ActivityName",
    INV.NetDueDate AS "EventTime",
    'SYSTEM' AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    0 AS "DaysOverdue"
FROM I_OperationalAcctgDocItemCube AS INV
WHERE INV.CompanyCode IN ('[Your Company Code]') AND INV.AccountingDocumentType = '[Your Invoice Doc Type]' AND INV.IsCleared = '' AND INV.NetDueDate BETWEEN '[Start Date]' AND '[End Date]' AND INV.NetDueDate < CURRENT_DATE

UNION ALL

SELECT
    REL.RelatedAccountingDocument AS "InvoiceNumber",
    'Dispute Case Registered' AS "ActivityName",
    DCASE.CreationDateTime AS "EventTime",
    DCASE.CreatedByUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < CAST(DCASE.CreationDateTime AS DATE) THEN DATEDIFF(day, INV.NetDueDate, CAST(DCASE.CreationDateTime AS DATE)) ELSE 0 END AS "DaysOverdue"
FROM I_DisputeCase AS DCASE
JOIN I_DisputeCaseRelatedObject AS REL ON DCASE.DisputeCase = REL.DisputeCase
JOIN I_OperationalAcctgDocItemCube AS INV ON REL.RelatedAccountingDocument = INV.AccountingDocument AND REL.RelatedCompanyCode = INV.CompanyCode AND INV.AccountingDocumentType = '[Your Invoice Doc Type]'
WHERE INV.CompanyCode IN ('[Your Company Code]') AND CAST(DCASE.CreationDateTime AS DATE) BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

SELECT
    DUN.AccountingDocument AS "InvoiceNumber",
    'Dunning Procedure Initiated' AS "ActivityName",
    DUN.DunningDate AS "EventTime",
    DUN.DunningRunUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < DUN.DunningDate THEN DATEDIFF(day, INV.NetDueDate, DUN.DunningDate) ELSE 0 END AS "DaysOverdue"
FROM I_DunningHistoryItem AS DUN
JOIN I_OperationalAcctgDocItemCube AS INV ON DUN.AccountingDocument = INV.AccountingDocument AND DUN.CompanyCode = INV.CompanyCode AND INV.AccountingDocumentType = '[Your Invoice Doc Type]'
WHERE DUN.CompanyCode IN ('[Your Company Code]') AND DUN.DunningDate BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

-- Note: This activity requires a custom view. Replace '[Your Custom Contact Log View]' with your specific implementation.
SELECT
    LOG.InvoiceReference AS "InvoiceNumber",
    'Collection Call Made' AS "ActivityName",
    LOG.CreationDateTime AS "EventTime",
    LOG.CreatedByUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < CAST(LOG.CreationDateTime AS DATE) THEN DATEDIFF(day, INV.NetDueDate, CAST(LOG.CreationDateTime AS DATE)) ELSE 0 END AS "DaysOverdue"
FROM [Your Custom Contact Log View] AS LOG
JOIN I_OperationalAcctgDocItemCube AS INV ON LOG.InvoiceReference = INV.AccountingDocument AND INV.CompanyCode IN ('[Your Company Code]') AND INV.AccountingDocumentType = '[Your Invoice Doc Type]'
WHERE CAST(LOG.CreationDateTime AS DATE) BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

SELECT
    P2P.OriginalReferenceDocument AS "InvoiceNumber",
    'Promise To Pay Created' AS "ActivityName",
    P2P.CreationDateTime AS "EventTime",
    P2P.CreatedByUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < CAST(P2P.CreationDateTime AS DATE) THEN DATEDIFF(day, INV.NetDueDate, CAST(P2P.CreationDateTime AS DATE)) ELSE 0 END AS "DaysOverdue"
FROM I_PromiseToPay AS P2P
JOIN I_OperationalAcctgDocItemCube AS INV ON P2P.OriginalReferenceDocument = INV.AccountingDocument AND P2P.CompanyCode = INV.CompanyCode AND INV.AccountingDocumentType = '[Your Invoice Doc Type]'
WHERE P2P.CompanyCode IN ('[Your Company Code]') AND CAST(P2P.CreationDateTime AS DATE) BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

SELECT
    INV.AccountingDocument AS "InvoiceNumber",
    'Payment Received' AS "ActivityName",
    INV.ClearingDate AS "EventTime",
    INV.ClearingJournalEntryUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < INV.ClearingDate THEN DATEDIFF(day, INV.NetDueDate, INV.ClearingDate) ELSE 0 END AS "DaysOverdue"
FROM I_OperationalAcctgDocItemCube AS INV
WHERE INV.CompanyCode IN ('[Your Company Code]') AND INV.AccountingDocumentType = '[Your Invoice Doc Type]' AND INV.IsCleared = 'X' AND INV.ClearingDate BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

SELECT
    INV.AccountingDocument AS "InvoiceNumber",
    'Payment Posted' AS "ActivityName",
    INV.ClearingDate AS "EventTime", -- Often same as Payment Received timestamp
    INV.ClearingJournalEntryUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < INV.ClearingDate THEN DATEDIFF(day, INV.NetDueDate, INV.ClearingDate) ELSE 0 END AS "DaysOverdue"
FROM I_OperationalAcctgDocItemCube AS INV
WHERE INV.CompanyCode IN ('[Your Company Code]') AND INV.AccountingDocumentType = '[Your Invoice Doc Type]' AND INV.IsCleared = 'X' AND INV.ClearingDate BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

SELECT
    REL.RelatedAccountingDocument AS "InvoiceNumber",
    'Dispute Resolved' AS "ActivityName",
    DCASE.LastChangeDateTime AS "EventTime",
    DCASE.LastChangedByUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < CAST(DCASE.LastChangeDateTime AS DATE) THEN DATEDIFF(day, INV.NetDueDate, CAST(DCASE.LastChangeDateTime AS DATE)) ELSE 0 END AS "DaysOverdue"
FROM I_DisputeCase AS DCASE
JOIN I_DisputeCaseRelatedObject AS REL ON DCASE.DisputeCase = REL.DisputeCase
JOIN I_OperationalAcctgDocItemCube AS INV ON REL.RelatedAccountingDocument = INV.AccountingDocument AND REL.RelatedCompanyCode = INV.CompanyCode AND INV.AccountingDocumentType = '[Your Invoice Doc Type]'
WHERE INV.CompanyCode IN ('[Your Company Code]') AND DCASE.DisputeCaseProcessingStatus = '[Your Dispute Case Closed Status]' AND CAST(DCASE.LastChangeDateTime AS DATE) BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

SELECT
    INV.AccountingDocument AS "InvoiceNumber",
    'Invoice Settled' AS "ActivityName",
    INV.ClearingDate AS "EventTime",
    INV.ClearingJournalEntryUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < INV.ClearingDate THEN DATEDIFF(day, INV.NetDueDate, INV.ClearingDate) ELSE 0 END AS "DaysOverdue"
FROM I_OperationalAcctgDocItemCube AS INV
WHERE INV.CompanyCode IN ('[Your Company Code]') AND INV.AccountingDocumentType = '[Your Invoice Doc Type]' AND INV.IsCleared = 'X' AND INV.ClearingDate BETWEEN '[Start Date]' AND '[End Date]'

UNION ALL

SELECT
    INV.AccountingDocument AS "InvoiceNumber",
    'Invoice Written Off' AS "ActivityName",
    INV.ClearingDate AS "EventTime",
    INV.ClearingJournalEntryUser AS "UserName",
    INV.Customer AS "CustomerNumber",
    INV.AmountInTransactionCurrency AS "InvoiceAmount",
    INV.NetDueDate AS "PaymentDueDate",
    CASE WHEN INV.NetDueDate < INV.ClearingDate THEN DATEDIFF(day, INV.NetDueDate, INV.ClearingDate) ELSE 0 END AS "DaysOverdue"
FROM I_OperationalAcctgDocItemCube AS INV
WHERE INV.CompanyCode IN ('[Your Company Code]') AND INV.AccountingDocumentType = '[Your Invoice Doc Type]' AND INV.IsCleared = 'X' AND INV.ClearingReason = '[Your Write-off Reason Code]' AND INV.ClearingDate BETWEEN '[Start Date]' AND '[End Date]'

步骤

安装前提条件：在运行脚本之前，请确保已安装 Python 3.6 或更高版本。使用 pip 安装必要的 Python 库 PyRFC：pip install pyrfc。此外，从 SAP 支持门户下载 SAP NWRFC SDK，并将其 lib 文件夹放置在系统路径可访问的位置。
SAP 用户与授权：运行提取需要专用的 SAP 用户账户。该用户必须拥有通过 S_RFC 授权对象进行的远程函数调用 (RFC) 授权。用户还需要执行 RFC_READ_TABLE 函数模块的特定权限，以及对脚本中引用的底层表（如 BKPF、BSEG、BSID、BSAD、NAST、UDM_SPS_CASE_ATTR、MHNK 和 UDM_P2P_ATTR）的读取权限。
配置连接详情：打开 Python 脚本并定位 sap_config 字典。在该字典中填入目标 SAP S/4HANA 系统的正确连接参数，包括应用服务器主机、系统编号、客户端以及专用 SAP 用户的用户名和密码。
设置提取参数：在脚本的主部分定义关键提取参数。设置 company_codes 列表以包含您要分析的 SAP 公司代码。以 'YYYYMMDD' 格式指定 start_date 和 end_date 以定义提取的时间窗口。此日期范围对于控制 data 量至关重要。
执行 Python 脚本：从命令行或终端使用命令 python your_script_name.py 运行脚本。脚本将连接到 SAP 并执行一系列函数调用（针对定义的每个活动）。提取每种活动类型的 data 时，控制台将打印进度消息。
data 聚合与转换：脚本会自动将 12 个活动的 data 收集到不同的 data 结构中。然后，它使用 pandas 库将它们合并为一个统一的 event log。在此步骤中，它会标准化列名并正确格式化 data。
计算属性：聚合后，脚本会进行必要的计算。例如，它通过比较相关活动的 event 日期与 PaymentDueDate 来计算 DaysOverdue 属性，为流程分析提供有价值的背景信息。
导出为 CSV：data 完成处理和转换后，脚本会将最终的 event log 保存为名为 collections_event_log.csv 的 CSV 文件（位于脚本所在目录）。该文件格式已针对直接上传到 Process Mining 软件进行了优化。

配置

SAP 连接参数：该脚本需要一个包含目标 SAP 系统连接详情的字典：ashost（应用服务器主机）、sysnr（系统编号）、client（客户端 ID）、user（SAP 用户 ID）和 passwd（密码）。
SAP 授权：确保 SAP 用户拥有 RFC 权限以及对所有所需财务和催收管理表的读取权限。关键授权对象包括用于远程调用的 S_RFC 和用于表显示访问的 S_TABU_DIS。
日期范围：设置 start_date 和 end_date 以限制提取范围至关重要。对于初步分析，建议选择 3 到 6 个月的时间范围，以确保 data 量和脚本执行时间在可控范围内。
公司代码筛选器：company_codes 参数是选择特定法律实体 data 的必选筛选器。强烈建议一次仅提取一个或少数几个公司代码，以获得更好的性能。
凭证类型筛选器：在脚本逻辑中，通过发票凭证类型（例如“RV”或“RE”）进行筛选，以确保数据集中仅包含相关的客户发票。这应根据您系统的特定凭证类型使用情况进行配置。
性能注意事项：通过 RFC_READ_TABLE 直接读取 BSEG 或 BSAD 等大表可能会消耗大量资源。请在非高峰时段运行脚本，并始终对公司代码、会计年度和凭证过账日期等索引字段使用选择性筛选器。

a 查询示例 python

import pandas as pd
from pyrfc import Connection
from datetime import datetime, timedelta

class=class="hl-string">"hl-comment"># --- SAP Connection Configuration ---
class=class="hl-string">"hl-comment"># Replace with your SAP system's connection details
sap_config = {
    class="hl-string">'ashost': class="hl-string">'[Your SAP Application Server Host]',
    class="hl-string">'sysnr': class="hl-string">'[Your System Number]',
    class="hl-string">'client': class="hl-string">'[Your Client ID]',
    class="hl-string">'user': class="hl-string">'[Your SAP User]',
    class="hl-string">'passwd': class="hl-string">'[Your SAP Password]'
}

class=class="hl-string">"hl-comment"># --- Helper Functions ---
def rfc_read_to_df(conn, table_name, fields, options):
    class="hl-string">"""Generic function to read an SAP table and return a pandas DataFrame."""
    result = conn.call(class="hl-string">'RFC_READ_TABLE',
                       QUERY_TABLE=table_name,
                       DELIMITER=class="hl-string">',',
                       FIELDS=fields,
                       OPTIONS=options)
    data = result[class="hl-string">'DATA']
    if not data:
        return pd.DataFrame(columns=[f[class="hl-string">'FIELDNAME'] for f in fields])
    
    records = [dict(zip([f[class="hl-string">'FIELDNAME'] for f in fields], row[class="hl-string">'WA'].strip().split(class="hl-string">','))) for row in data]
    return pd.DataFrame(records)

def format_sap_date(date_str):
    class="hl-string">"""Converts SAP date string (YYYYMMDD) to datetime object."""
    if date_str and date_str != class="hl-string">'00000000':
        return datetime.strptime(date_str, class="hl-string">'%Y%m%d')
    return None

def format_sap_time(time_str):
    class="hl-string">"""Converts SAP time string (HHMMSS) to timedelta object."""
    if time_str and len(time_str) == 6:
        return timedelta(hours=int(time_str[0:2]), minutes=int(time_str[2:4]), seconds=int(time_str[4:6]))
    return timedelta(0)

class=class="hl-string">"hl-comment"># --- Activity Extraction Functions ---

def get_invoices_generated(conn, company_codes, start_date, end_date):
    options = [fclass="hl-string">"(BUKRS IN ('{','.join(company_codes)}') AND BUDAT >= '{start_date}' AND BUDAT <= '{end_date}' AND BLART IN ('RV', 'RE'))"] class=class="hl-string">"hl-comment"># Filter for customer invoices
    bkpf_fields = [{class="hl-string">'FIELDNAME': class="hl-string">'BELNR'}, {class="hl-string">'FIELDNAME': class="hl-string">'GJAHR'}, {class="hl-string">'FIELDNAME': class="hl-string">'BUKRS'}, {class="hl-string">'FIELDNAME': class="hl-string">'BUDAT'}, {class="hl-string">'FIELDNAME': class="hl-string">'CPUDT'}, {class="hl-string">'FIELDNAME': class="hl-string">'CPUTM'}, {class="hl-string">'FIELDNAME': class="hl-string">'USNAM'}]
    bseg_fields = [{class="hl-string">'FIELDNAME': class="hl-string">'BELNR'}, {class="hl-string">'FIELDNAME': class="hl-string">'GJAHR'}, {class="hl-string">'FIELDNAME': class="hl-string">'BUKRS'}, {class="hl-string">'FIELDNAME': class="hl-string">'KUNNR'}, {class="hl-string">'FIELDNAME': class="hl-string">'WRBTR'}, {class="hl-string">'FIELDNAME': class="hl-string">'ZFBDT'}]
    
    df_bkpf = rfc_read_to_df(conn, class="hl-string">'BKPF', bkpf_fields, options)
    if df_bkpf.empty: return pd.DataFrame()

    class=class="hl-string">"hl-comment"># Fetch line item details
    invoice_keys = [fclass="hl-string">"(BELNR = '{row.BELNR}' AND GJAHR = '{row.GJAHR}' AND BUKRS = '{row.BUKRS}')" for index, row in df_bkpf.iterrows()]
    bseg_options = [class="hl-string">" OR ".join(invoice_keys[i:i+50]) for i in range(0, len(invoice_keys), 50)] class=class="hl-string">"hl-comment"># Batch options
    df_bseg_list = [rfc_read_to_df(conn, class="hl-string">'BSEG', bseg_fields, [opt]) for opt in bseg_options]
    df_bseg = pd.concat(df_bseg_list)
    df_bseg = df_bseg[df_bseg[class="hl-string">'KUNNR'] != class="hl-string">''].drop_duplicates([class="hl-string">'BELNR', class="hl-string">'GJAHR', class="hl-string">'BUKRS'])
    
    df = pd.merge(df_bkpf, df_bseg, on=[class="hl-string">'BELNR', class="hl-string">'GJAHR', class="hl-string">'BUKRS'])

    df[class="hl-string">'ActivityName'] = class="hl-string">'Invoice Generated'
    df[class="hl-string">'EventTime'] = df.apply(lambda row: format_sap_date(row[class="hl-string">'CPUDT']) + format_sap_time(row[class="hl-string">'CPUTM']), axis=1)
    df.rename(columns={class="hl-string">'BELNR': class="hl-string">'InvoiceNumber', class="hl-string">'USNAM': class="hl-string">'UserName', class="hl-string">'KUNNR': class="hl-string">'CustomerNumber', class="hl-string">'WRBTR': class="hl-string">'InvoiceAmount', class="hl-string">'ZFBDT': class="hl-string">'PaymentDueDate'}, inplace=True)
    df[class="hl-string">'PaymentDueDate'] = df[class="hl-string">'PaymentDueDate'].apply(format_sap_date)
    return df[[class="hl-string">'InvoiceNumber', class="hl-string">'ActivityName', class="hl-string">'EventTime', class="hl-string">'UserName', class="hl-string">'CustomerNumber', class="hl-string">'InvoiceAmount', class="hl-string">'PaymentDueDate']]

def get_invoices_sent(conn, company_codes, start_date, end_date):
    options = [fclass="hl-string">"KAPPL = 'V3' AND DATUM >= '{start_date}' AND DATUM <= '{end_date}'"] class=class="hl-string">"hl-comment"># V3 is for Billing
    nkey_prefix = [fclass="hl-string">"{client}{cc}" for client in [sap_config[class="hl-string">'client']] for cc in company_codes]
    options[0] += fclass="hl-string">" AND (LEFT(OBJKY, 5) IN ('{','.join(nkey_prefix)}'))"

    fields = [{class="hl-string">'FIELDNAME': class="hl-string">'OBJKY'}, {class="hl-string">'FIELDNAME': class="hl-string">'DATUM'}, {class="hl-string">'FIELDNAME': class="hl-string">'UZEIT'}, {class="hl-string">'FIELDNAME': class="hl-string">'USNAM'}]
    df = rfc_read_to_df(conn, class="hl-string">'NAST', fields, options)
    if df.empty: return pd.DataFrame()

    df[class="hl-string">'InvoiceNumber'] = df[class="hl-string">'OBJKY'].str[5:15].str.lstrip(class="hl-string">'0')
    df[class="hl-string">'ActivityName'] = class="hl-string">'Invoice Sent To Customer'
    df[class="hl-string">'EventTime'] = df.apply(lambda row: format_sap_date(row[class="hl-string">'DATUM']) + format_sap_time(row[class="hl-string">'UZEIT']), axis=1)
    df.rename(columns={class="hl-string">'USNAM': class="hl-string">'UserName'}, inplace=True)
    return df[[class="hl-string">'InvoiceNumber', class="hl-string">'ActivityName', class="hl-string">'EventTime', class="hl-string">'UserName']]

def get_payment_due_passed(conn, company_codes):
    options = [fclass="hl-string">"BUKRS IN ('{','.join(company_codes)}') AND BLART IN ('RV', 'RE') AND ZFBDT < '{datetime.now().strftime('%Y%m%d')}'"]
    fields = [{class="hl-string">'FIELDNAME': class="hl-string">'BELNR'}, {class="hl-string">'FIELDNAME': class="hl-string">'KUNNR'}, {class="hl-string">'FIELDNAME': class="hl-string">'ZFBDT'}]
    df = rfc_read_to_df(conn, class="hl-string">'BSID', fields, options)
    if df.empty: return pd.DataFrame()

    df[class="hl-string">'ActivityName'] = class="hl-string">'Payment Due Date Passed'
    df[class="hl-string">'EventTime'] = df[class="hl-string">'ZFBDT'].apply(lambda x: format_sap_date(x) + timedelta(days=1))
    df.rename(columns={class="hl-string">'BELNR': class="hl-string">'InvoiceNumber', class="hl-string">'KUNNR': class="hl-string">'CustomerNumber'}, inplace=True)
    return df[[class="hl-string">'InvoiceNumber', class="hl-string">'ActivityName', class="hl-string">'EventTime', class="hl-string">'CustomerNumber']]

def get_dispute_cases(conn, company_codes, start_date, end_date):
    options = [fclass="hl-string">"COMPANY_CODE IN ('{','.join(company_codes)}') AND CREATED_AT >= '{start_date}'"]
    fields = [{class="hl-string">'FIELDNAME': class="hl-string">'CASE_GUID'}, {class="hl-string">'FIELDNAME': class="hl-string">'CREATED_AT'}, {class="hl-string">'FIELDNAME': class="hl-string">'CREATED_BY'}, {class="hl-string">'FIELDNAME': class="hl-string">'CLOSING_DATE'}, {class="hl-string">'FIELDNAME': class="hl-string">'PROCESSOR'}]
    df_case = rfc_read_to_df(conn, class="hl-string">'UDM_SPS_CASE_ATTR', fields, options)
    if df_case.empty: return pd.DataFrame()

    case_guids = df_case[class="hl-string">'CASE_GUID'].unique().tolist()
    obj_options = [fclass="hl-string">"CASE_GUID IN ('{','.join(case_guids)}')"]
    obj_fields = [{class="hl-string">'FIELDNAME': class="hl-string">'CASE_GUID'}, {class="hl-string">'FIELDNAME': class="hl-string">'OBJECT_ID'}]
    df_obj = rfc_read_to_df(conn, class="hl-string">'UDM_SPS_OBJECT', obj_fields, obj_options)

    df = pd.merge(df_case, df_obj, on=class="hl-string">'CASE_GUID')
    df[class="hl-string">'InvoiceNumber'] = df[class="hl-string">'OBJECT_ID'].str[7:17].str.lstrip(class="hl-string">'0')

    df_registered = df.copy()
    df_registered[class="hl-string">'ActivityName'] = class="hl-string">'Dispute Case Registered'
    df_registered[class="hl-string">'EventTime'] = df_registered[class="hl-string">'CREATED_AT'].apply(format_sap_date)
    df_registered.rename(columns={class="hl-string">'CREATED_BY': class="hl-string">'UserName'}, inplace=True)
    
    df_resolved = df[df[class="hl-string">'CLOSING_DATE'].notna() & (df[class="hl-string">'CLOSING_DATE'] != class="hl-string">'00000000')].copy()
    df_resolved[class="hl-string">'ActivityName'] = class="hl-string">'Dispute Resolved'
    df_resolved[class="hl-string">'EventTime'] = df_resolved[class="hl-string">'CLOSING_DATE'].apply(format_sap_date)
    df_resolved.rename(columns={class="hl-string">'PROCESSOR': class="hl-string">'UserName'}, inplace=True)

    return pd.concat([df_registered[[class="hl-string">'InvoiceNumber', class="hl-string">'ActivityName', class="hl-string">'EventTime', class="hl-string">'UserName']], 
                      df_resolved[[class="hl-string">'InvoiceNumber', class="hl-string">'ActivityName', class="hl-string">'EventTime', class="hl-string">'UserName']]])

def get_dunning(conn, company_codes, start_date, end_date):
    options = [fclass="hl-string">"BUKRS IN ('{','.join(company_codes)}') AND LAUFD >= '{start_date}'"]
    h_fields = [{class="hl-string">'FIELDNAME': class="hl-string">'LAUFD'}, {class="hl-string">'FIELDNAME': class="hl-string">'LAUFI'}, {class="hl-string">'FIELDNAME': class="hl-string">'KOART'}]
    df_h = rfc_read_to_df(conn, class="hl-string">'MHNK', h_fields, options)
    df_h = df_h[df_h[class="hl-string">'KOART'] == class="hl-string">'D'] class=class="hl-string">"hl-comment"># Only customers
    if df_h.empty: return pd.DataFrame()

    d_fields = [{class="hl-string">'FIELDNAME': class="hl-string">'LAUFD'}, {class="hl-string">'FIELDNAME': class="hl-string">'LAUFI'}, {class="hl-string">'FIELDNAME': class="hl-string">'BELNR'}]
    dunning_keys = [fclass="hl-string">"(LAUFD = '{row.LAUFD}' AND LAUFI = '{row.LAUFI}')" for index, row in df_h.iterrows()]
    d_options = [class="hl-string">" OR ".join(dunning_keys[i:i+50]) for i in range(0, len(dunning_keys), 50)]
    df_d_list = [rfc_read_to_df(conn, class="hl-string">'MHND', d_fields, [opt]) for opt in d_options]
    df_d = pd.concat(df_d_list).drop_duplicates()

    df = pd.merge(df_h, df_d, on=[class="hl-string">'LAUFD', class="hl-string">'LAUFI'])
    df[class="hl-string">'ActivityName'] = class="hl-string">'Dunning Procedure Initiated'
    df[class="hl-string">'EventTime'] = df[class="hl-string">'LAUFD'].apply(format_sap_date)
    df.rename(columns={class="hl-string">'BELNR': class="hl-string">'InvoiceNumber'}, inplace=True)
    return df[[class="hl-string">'InvoiceNumber', class="hl-string">'ActivityName', class="hl-string">'EventTime']]

def get_promise_to_pay(conn, company_codes, start_date, end_date):
    options = [fclass="hl-string">"COMPANY_CODE IN ('{','.join(company_codes)}') AND CREATION_DATE >= '{start_date}'"]
    fields = [{class="hl-string">'FIELDNAME': class="hl-string">'INVOICE_REF'}, {class="hl-string">'FIELDNAME': class="hl-string">'CREATION_DATE'}, {class="hl-string">'FIELDNAME': class="hl-string">'CREATION_TIME'}, {class="hl-string">'FIELDNAME': class="hl-string">'CREATED_BY'}]
    df = rfc_read_to_df(conn, class="hl-string">'UDM_P2P_ATTR', fields, options)
    if df.empty: return pd.DataFrame()
    
    df[class="hl-string">'InvoiceNumber'] = df[class="hl-string">'INVOICE_REF'].str[7:17].str.lstrip(class="hl-string">'0')
    df[class="hl-string">'ActivityName'] = class="hl-string">'Promise To Pay Created'
    df[class="hl-string">'EventTime'] = df.apply(lambda row: format_sap_date(row[class="hl-string">'CREATION_DATE']) + format_sap_time(row[class="hl-string">'CREATION_TIME']), axis=1)
    df.rename(columns={class="hl-string">'CREATED_BY': class="hl-string">'UserName'}, inplace=True)
    return df[[class="hl-string">'InvoiceNumber', class="hl-string">'ActivityName', class="hl-string">'EventTime', class="hl-string">'UserName']]

def get_cleared_items(conn, company_codes, start_date, end_date):
    options = [fclass="hl-string">"BUKRS IN ('{','.join(company_codes)}') AND AUGDT >= '{start_date}' AND AUGDT <= '{end_date}' AND BLART IN ('RV', 'RE')"]
    fields = [{class="hl-string">'FIELDNAME': class="hl-string">'BELNR'}, {class="hl-string">'FIELDNAME': class="hl-string">'AUGDT'}, {class="hl-string">'FIELDNAME': class="hl-string">'AUGBL'}, {class="hl-string">'FIELDNAME': class="hl-string">'RSTGR'}, {class="hl-string">'FIELDNAME': class="hl-string">'USNAM'}, {class="hl-string">'FIELDNAME': class="hl-string">'KUNNR'}]
    df = rfc_read_to_df(conn, class="hl-string">'BSAD', fields, options)
    if df.empty: return pd.DataFrame()
    df.rename(columns={class="hl-string">'BELNR': class="hl-string">'InvoiceNumber', class="hl-string">'KUNNR': class="hl-string">'CustomerNumber', class="hl-string">'USNAM': class="hl-string">'UserName'}, inplace=True)
    df[class="hl-string">'EventTime'] = df[class="hl-string">'AUGDT'].apply(format_sap_date)

    class=class="hl-string">"hl-comment"># Write-offs (Reason Code for write-off needs configuration)
    df_woff = df[df[class="hl-string">'RSTGR'].isin([class="hl-string">'[Your Write-Off Reason Code]'])].copy()
    df_woff[class="hl-string">'ActivityName'] = class="hl-string">'Invoice Written Off'

    class=class="hl-string">"hl-comment"># Normal Payments
    df_paid = df[~df[class="hl-string">'RSTGR'].isin([class="hl-string">'[Your Write-Off Reason Code]'])].copy()
    
    df_received = df_paid.copy()
    df_received[class="hl-string">'ActivityName'] = class="hl-string">'Payment Received'

    df_posted = df_paid.copy()
    df_posted[class="hl-string">'ActivityName'] = class="hl-string">'Payment Posted'
    df_posted[class="hl-string">'EventTime'] = df_posted[class="hl-string">'EventTime'] + timedelta(seconds=1) class=class="hl-string">"hl-comment"># Small offset for ordering

    df_settled = df_paid.copy()
    df_settled[class="hl-string">'ActivityName'] = class="hl-string">'Invoice Settled'
    df_settled[class="hl-string">'EventTime'] = df_settled[class="hl-string">'EventTime'] + timedelta(seconds=2)

    return pd.concat([df_received[[class="hl-string">'InvoiceNumber', class="hl-string">'ActivityName', class="hl-string">'EventTime', class="hl-string">'UserName', class="hl-string">'CustomerNumber']], 
                      df_posted[[class="hl-string">'InvoiceNumber', class="hl-string">'ActivityName', class="hl-string">'EventTime', class="hl-string">'UserName', class="hl-string">'CustomerNumber']], 
                      df_settled[[class="hl-string">'InvoiceNumber', class="hl-string">'ActivityName', class="hl-string">'EventTime', class="hl-string">'UserName', class="hl-string">'CustomerNumber']],
                      df_woff[[class="hl-string">'InvoiceNumber', class="hl-string">'ActivityName', class="hl-string">'EventTime', class="hl-string">'UserName', class="hl-string">'CustomerNumber']]])

def get_collection_calls(conn, company_codes, start_date, end_date):
    class=class="hl-string">"hl-comment"># This is a placeholder for a custom activity. 
    class=class="hl-string">"hl-comment"># Assumes a custom Z-table class="hl-string">'ZCOLL_CALLS' exists.
    class=class="hl-string">"hl-comment"># Fields: BELNR, CALL_DATE, CALL_TIME, UNAME, KUNNR
    class=class="hl-string">"hl-comment"># Please adapt table and field names to your specific implementation.
    try:
        options = [fclass="hl-string">"LEFT(BELNR, 4) IN ('{','.join(company_codes)}') AND CALL_DATE >= '{start_date}'"]
        fields = [{class="hl-string">'FIELDNAME': class="hl-string">'BELNR'}, {class="hl-string">'FIELDNAME': class="hl-string">'CALL_DATE'}, {class="hl-string">'FIELDNAME': class="hl-string">'CALL_TIME'}, {class="hl-string">'FIELDNAME': class="hl-string">'UNAME'}]
        df = rfc_read_to_df(conn, class="hl-string">'[Your Custom Table for Call Logs]', fields, options)
        if df.empty: return pd.DataFrame()

        df[class="hl-string">'ActivityName'] = class="hl-string">'Collection Call Made'
        df[class="hl-string">'EventTime'] = df.apply(lambda row: format_sap_date(row[class="hl-string">'CALL_DATE']) + format_sap_time(row[class="hl-string">'CALL_TIME']), axis=1)
        df.rename(columns={class="hl-string">'BELNR': class="hl-string">'InvoiceNumber', class="hl-string">'UNAME': class="hl-string">'UserName'}, inplace=True)
        return df[[class="hl-string">'InvoiceNumber', class="hl-string">'ActivityName', class="hl-string">'EventTime', class="hl-string">'UserName']]
    except Exception as e:
        print(fclass="hl-string">"Could not extract 'Collection Call Made'. This is expected if a custom log table is not used. Error: {e}")
        return pd.DataFrame()

class=class="hl-string">"hl-comment"># --- Main Execution Logic ---
if __name__ == class="hl-string">"__main__":
    class=class="hl-string">"hl-comment"># --- Main Parameters ---
    company_codes = [class="hl-string">'[Your Company Code]'] class=class="hl-string">"hl-comment"># e.g., [class="hl-string">'1000', class="hl-string">'1010']
    start_date = class="hl-string">'[Start Date YYYYMMDD]' class=class="hl-string">"hl-comment"># e.g., class="hl-string">'20230101'
    end_date = class="hl-string">'[End Date YYYYMMDD]' class=class="hl-string">"hl-comment"># e.g., class="hl-string">'20231231'

    all_events = []
    try:
        with Connection(**sap_config) as conn:
            print(class="hl-string">"Connection successful. Starting extraction...")
            
            print(class="hl-string">"1/8: Extracting 'Invoice Generated'...")
            all_events.append(get_invoices_generated(conn, company_codes, start_date, end_date))
            
            print(class="hl-string">"2/8: Extracting 'Invoice Sent To Customer'...")
            all_events.append(get_invoices_sent(conn, company_codes, start_date, end_date))

            print(class="hl-string">"3/8: Extracting 'Payment Due Date Passed'...")
            all_events.append(get_payment_due_passed(conn, company_codes))

            print(class="hl-string">"4/8: Extracting Dispute Cases ('Registered', 'Resolved')...")
            all_events.append(get_dispute_cases(conn, company_codes, start_date, end_date))

            print(class="hl-string">"5/8: Extracting 'Dunning Procedure Initiated'...")
            all_events.append(get_dunning(conn, company_codes, start_date, end_date))

            print(class="hl-string">"6/8: Extracting 'Promise To Pay Created'...")
            all_events.append(get_promise_to_pay(conn, company_codes, start_date, end_date))
            
            print(class="hl-string">"7/8: Extracting Cleared Items ('Payment Received', 'Posted', 'Settled', 'Written Off')...")
            all_events.append(get_cleared_items(conn, company_codes, start_date, end_date))

            print(class="hl-string">"8/8: Extracting 'Collection Call Made' (custom)...")
            all_events.append(get_collection_calls(conn, company_codes, start_date, end_date))

    except Exception as e:
        print(fclass="hl-string">"An error occurred during RFC call: {e}")

    print(class="hl-string">"\nCombining all data...")
    final_df = pd.concat([df for df in all_events if not df.empty])

    if not final_df.empty:
        class=class="hl-string">"hl-comment"># Post-processing
        final_df = final_df.sort_values(by=[class="hl-string">'InvoiceNumber', class="hl-string">'EventTime']).reset_index(drop=True)
        final_df[class="hl-string">'InvoiceAmount'] = pd.to_numeric(final_df[class="hl-string">'InvoiceAmount'], errors=class="hl-string">'coerce')
        final_df[class="hl-string">'PaymentDueDate'] = pd.to_datetime(final_df[class="hl-string">'PaymentDueDate'], errors=class="hl-string">'coerce')

        class=class="hl-string">"hl-comment"># Fill forward attributes for a complete event log
        final_df[class="hl-string">'CustomerNumber'] = final_df.groupby(class="hl-string">'InvoiceNumber')[class="hl-string">'CustomerNumber'].ffill().bfill()
        final_df[class="hl-string">'InvoiceAmount'] = final_df.groupby(class="hl-string">'InvoiceNumber')[class="hl-string">'InvoiceAmount'].ffill().bfill()
        final_df[class="hl-string">'PaymentDueDate'] = final_df.groupby(class="hl-string">'InvoiceNumber')[class="hl-string">'PaymentDueDate'].ffill().bfill()
        
        class=class="hl-string">"hl-comment"># Calculate DaysOverdue
        final_df[class="hl-string">'DaysOverdue'] = (final_df[class="hl-string">'EventTime'].dt.date - final_df[class="hl-string">'PaymentDueDate'].dt.date).apply(lambda x: x.days if pd.notnull(x) and x.days > 0 else 0)

        class=class="hl-string">"hl-comment"># Save to CSV
        output_file = class="hl-string">'collections_event_log.csv'
        final_df.to_csv(output_file, index=False, date_format=class="hl-string">'%Y-%m-%d %H:%M:%S')
        print(fclass="hl-string">"Extraction complete. Event log saved to {output_file}")
    else:
        print(class="hl-string">"Extraction resulted in no data. Please check your parameters and SAP system.")

步骤

创建 ABAP 程序：使用事务代码 SE38 打开 ABAP 编辑器。输入新程序的名称，例如 Z_PM_CREDIT_COLLECTIONS_EXTRACT，然后点击“创建”。提供合适的标题，并将程序类型设置为“可执行程序”。
定义选择屏幕：在程序中定义一个选择屏幕以允许用户筛选 data。关键参数应包括公司代码 (S_BUKRS)、凭证过账日期 (S_BLDAT) 和客户编号 (S_KUNNR)。这有助于进行有针对性且易于管理的提取。
定义输出结构：创建一个本地 data 类型来定义最终 event log 的结构。此结构必须包含 InvoiceNumber、ActivityName、EventTime 以及其他推荐属性，如 UserName、CustomerNumber、InvoiceAmount、PaymentDueDate 和 DaysOverdue。
实现 data 选择逻辑：编写 ABAP 逻辑以选择 12 个所需活动的 data。这涉及查询多个 SAP 表，如 BKPF、BSEG、BSAD、UDM_DISPUTE、MHNK、FDM_P2P_ATTR 和 NAST。使用带有 UNION ALL 的 SELECT 语句，或将结果附加到对应于您定义的输出结构的单个内表中。
处理计算出的 event：对于像“已过付款到期日”这样在表中没有直接条目的活动，需实现特定逻辑。这包括选择未清发票并计算到期日是否早于提取运行日期。此活动的 event timestamp 应设置为到期日的次日。
整合 data：确保为每个活动选择的 data 被正确转换并移动到最终内表的字段中。例如，将“已生成发票”活动的 BKPF-BLDAT 映射到 EventTime。
执行程序：保存并激活您的 ABAP 程序。通过事务 SE38 执行或为其创建新的事务代码。填写选择标准（如日期范围和公司代码）并运行程序。
生成输出文件：程序应设计为将最终内表的内容写入平面文件。使用 OPEN DATASET、LOOP AT... TRANSFER... 和 CLOSE DATASET 等 ABAP 语句在 SAP 应用服务器上创建 CSV 或以制表符分隔的文件。
下载文件：使用事务 AL11 浏览应用服务器目录并定位生成的文件。或者，使用事务 CG3Y 直接将文件从应用服务器下载到本地计算机。
准备上传：确保下载的文件格式为正确的 CSV，且标题行与所需属性匹配。验证日期和时间格式是否一致。现在，文件已准备好上传到 Process Mining 工具。

配置

日期范围 (S_BLDAT)：此参数根据过账日期筛选发票。这对于控制 data 量至关重要。我们建议提取 3 到 6 个月的 data，以在确保数据集大小易于管理的同时，捕获足够的流程变体。
公司代码 (S_BUKRS)：此必选参数将提取范围限制为一个或多个特定的公司代码。这对于将分析重点放在特定的法律实体上以及出于性能考虑都至关重要。
客户编号 (S_KUNNR)：可选参数，用于按特定客户或客户范围筛选提取内容。适用于详细分析或在小规模 data 样本上进行测试。
凭证类型 (S_BLART)：可选筛选器，仅包含代表客户发票的特定凭证类型，如“RV”或自定义发票类型。这有助于在提取时排除无关的财务凭证。
输出文件路径：ABAP 程序必须配置 SAP 应用服务器上的有效目录路径，且运行该报表的用户需拥有写入权限。通常使用共享目录，如 /usr/sap/trans/tmp/。
前提条件：执行该程序的内部用户需要访问财务会计表（BKPF、BSEG、BSAD）、信用管理表（UKM_ITEM）、争议管理表（UDM_DISPUTE）和催收表（MHNK）的权限。此外，创建和修改报表还需要 ABAP 开发权限。

a 查询示例 abap

REPORT Z_PM_CREDIT_COLLECTIONS_EXTRACT.

*&---------------------------------------------------------------------*
*& Data Types for Final Event Log
*&---------------------------------------------------------------------*
TYPES: BEGIN OF ty_event_log,
         invoicenumber  TYPE belnr_d,
         activityname   TYPE string,
         eventtime      TYPE timestamp,
         username       TYPE uname,
         customernumber TYPE kunnr,
         invoiceamount  TYPE wrbtr,
         paymentduedate TYPE dats,
         daysoverdue    TYPE int4,
       END OF ty_event_log.

DATA: lt_event_log TYPE TABLE OF ty_event_log.

*&---------------------------------------------------------------------*
*& Selection Screen
*&---------------------------------------------------------------------*
SELECT-OPTIONS: s_bukrs FOR bkpf-bukrs OBLIGATORY,
                s_bldat FOR bkpf-bldat OBLIGATORY,
                s_kunnr FOR bseg-kunnr,
                s_blart FOR bkpf-blart.

PARAMETERS: p_fpath TYPE string DEFAULT '/usr/sap/trans/tmp/collections_log.csv'.

*&---------------------------------------------------------------------*
*& Main Processing Block
*&---------------------------------------------------------------------*
START-OF-SELECTION.

  " 1. Invoice Generated
  SELECT
    b~belnr AS invoicenumber,
    'Invoice Generated' AS activityname,
    CAST( CONCAT( h~bldat, h~cpuzt ) AS p DECIMALS 0 ) AS eventtime,
    h~usnam AS username,
    b~kunnr AS customernumber,
    b~wrbtr AS invoiceamount,
    b~netdt AS paymentduedate,
    0       AS daysoverdue
  FROM bkpf AS h
  INNER JOIN bseg AS b ON h~bukrs = b~bukrs AND h~belnr = b~belnr AND h~gjahr = b~gjahr
  WHERE h~bukrs IN @s_bukrs
    AND h~bldat IN @s_bldat
    AND b~kunnr IN @s_kunnr
    AND h~blart IN @s_blart
    AND b~koart = 'D' " Customer items
    AND b~shkzg = 'S' " Debit
  INTO CORRESPONDING FIELDS OF TABLE @lt_event_log.

  " 2. Invoice Sent To Customer (Example from NAST)
  SELECT
    a~belnr AS invoicenumber,
    'Invoice Sent To Customer' AS activityname,
    CAST( CONCAT( n~datvr, n~uhrvr ) AS p DECIMALS 0 ) AS eventtime,
    n~usnam AS username,
    a~kunnr AS customernumber,
    a~wrbtr AS invoiceamount,
    a~netdt AS paymentduedate,
    0       AS daysoverdue
  FROM nast AS n
  INNER JOIN vbrk AS v ON n~objky = v~vbeln
  INNER JOIN bseg AS a ON v~xblnr = a~belnr
  WHERE n~kschl = '[Your Output Type]' " e.g., 'RD00'
    AND n~vstat = '1' " Processed successfully
    AND a~bukrs IN @s_bukrs
    AND a~gjahr = SUBSTRING( CONV string( n~datvr ), 0, 4 )
    AND a~kunnr IN @s_kunnr
  APPENDING CORRESPONDING FIELDS OF TABLE @lt_event_log.

  " 3. Payment Due Date Passed (Calculated Event)
  SELECT
    belnr AS invoicenumber,
    'Payment Due Date Passed' AS activityname,
    CAST( CONCAT( netdt + 1, '000000' ) AS p DECIMALS 0 ) AS eventtime,
    ''    AS username, " System event, no user
    kunnr AS customernumber,
    wrbtr AS invoiceamount,
    netdt AS paymentduedate,
    1     AS daysoverdue
  FROM bsid " Open customer items
  WHERE bukrs IN @s_bukrs
    AND bldat IN @s_bldat
    AND kunnr IN @s_kunnr
    AND netdt < sy-datum
  APPENDING CORRESPONDING FIELDS OF TABLE @lt_event_log.

  " 4. Dispute Case Registered
  SELECT
    l~ref_doc_nr AS invoicenumber,
    'Dispute Case Registered' AS activityname,
    CAST( CONCAT( h~created_at_date, h~created_at_time ) AS p DECIMALS 0 ) AS eventtime,
    h~created_by AS username,
    i~kunnr AS customernumber,
    i~wrbtr AS invoiceamount,
    i~netdt AS paymentduedate,
    0       AS daysoverdue
  FROM udm_dispute AS h
  INNER JOIN udm_dispute_link AS l ON h~case_guid = l~case_guid
  INNER JOIN bseg AS i ON l~ref_doc_nr = i~belnr AND l~ref_bukrs = i~bukrs AND l~ref_gjahr = i~gjahr
  WHERE l~ref_bukrs IN @s_bukrs
    AND i~bldat IN @s_bldat
    AND i~kunnr IN @s_kunnr
  APPENDING CORRESPONDING FIELDS OF TABLE @lt_event_log.

  " 5. Dunning Procedure Initiated
  SELECT
    d~belnr AS invoicenumber,
    'Dunning Procedure Initiated' AS activityname,
    CAST( CONCAT( h~laufd, '000000' ) AS p DECIMALS 0 ) AS eventtime,
    h~usnam AS username,
    d~kunnr AS customernumber,
    d~swnet AS invoiceamount, " Dunning amount
    b~netdt AS paymentduedate,
    d~vzsk1 AS daysoverdue
  FROM mhnk AS h
  INNER JOIN mhnd AS d ON h~laufd = d~laufd AND h~laufi = d~laufi
  INNER JOIN bseg AS b ON d~belnr = b~belnr AND d~bukrs = b~bukrs AND d~gjahr = b~gjahr
  WHERE d~bukrs IN @s_bukrs
    AND b~bldat IN @s_bldat
    AND d~kunnr IN @s_kunnr
    AND d~mslev = '1' " First dunning level
  APPENDING CORRESPONDING FIELDS OF TABLE @lt_event_log.

  " 6. Collection Call Made (Assuming logged in FDM_COLL_IN contact history)
  SELECT
    i~belnr AS invoicenumber,
    'Collection Call Made' AS activityname,
    CAST( CONCAT( c~contact_date, c~contact_time ) AS p DECIMALS 0 ) AS eventtime,
    c~processor AS username,
    c~kunnr AS customernumber,
    i~wrbtr AS invoiceamount,
    i~netdt AS paymentduedate,
    0 AS daysoverdue
  FROM fdm_coll_in AS c
  INNER JOIN bseg AS i ON c~kunnr = i~kunnr AND c~bukrs = i~bukrs
  WHERE c~bukrs IN @s_bukrs
    AND i~bldat IN @s_bldat
    AND c~kunnr IN @s_kunnr
    AND c~result = '[Your Call Result Code]'
  APPENDING CORRESPONDING FIELDS OF TABLE @lt_event_log.

  " 7. Promise To Pay Created
  SELECT
    s~belnr AS invoicenumber,
    'Promise To Pay Created' AS activityname,
    CAST( CONCAT( h~creation_date, h~creation_time ) AS p DECIMALS 0 ) AS eventtime,
    h~created_by AS username,
    s~kunnr AS customernumber,
    s~dmbtr AS invoiceamount,
    s~netdt AS paymentduedate,
    0 AS daysoverdue
  FROM fdm_p2p_attr AS h
  INNER JOIN bseg AS s ON h~opbel = s~belnr AND h~opbuk = s~bukrs AND h~opgjr = s~gjahr
  WHERE h~opbuk IN @s_bukrs
    AND s~bldat IN @s_bldat
    AND s~kunnr IN @s_kunnr
  APPENDING CORRESPONDING FIELDS OF TABLE @lt_event_log.

  " 8. Payment Received, 9. Payment Posted, 11. Invoice Settled
  SELECT
    belnr AS invoicenumber,
    'Invoice Settled' AS activityname,
    CAST( CONCAT( augdt, '000000' ) AS p DECIMALS 0 ) AS eventtime,
    augbl AS username, " Often batch user ID in clearing doc header
    kunnr AS customernumber,
    wrbtr AS invoiceamount,
    netdt AS paymentduedate,
    augdt - netdt AS daysoverdue
  FROM bsad " Cleared customer items
  WHERE bukrs IN @s_bukrs
    AND bldat IN @s_bldat
    AND kunnr IN @s_kunnr
    AND augdt <> '00000000'
    AND rstgr = '' " Exclude write-offs
  APPENDING CORRESPONDING FIELDS OF TABLE @lt_event_log.

  " 10. Dispute Resolved
  SELECT
    l~ref_doc_nr AS invoicenumber,
    'Dispute Resolved' AS activityname,
    CAST( CONCAT( h~closing_date, h~closing_time ) AS p DECIMALS 0 ) AS eventtime,
    h~closed_by AS username,
    i~kunnr AS customernumber,
    i~wrbtr AS invoiceamount,
    i~netdt AS paymentduedate,
    0 AS daysoverdue
  FROM udm_dispute AS h
  INNER JOIN udm_dispute_link AS l ON h~case_guid = l~case_guid
  INNER JOIN bseg AS i ON l~ref_doc_nr = i~belnr AND l~ref_bukrs = i~bukrs AND l~ref_gjahr = i~gjahr
  WHERE l~ref_bukrs IN @s_bukrs
    AND i~bldat IN @s_bldat
    AND i~kunnr IN @s_kunnr
    AND h~closing_date <> '00000000'
  APPENDING CORRESPONDING FIELDS OF TABLE @lt_event_log.

  " 12. Invoice Written Off
  SELECT
    belnr AS invoicenumber,
    'Invoice Written Off' AS activityname,
    CAST( CONCAT( augdt, '000000' ) AS p DECIMALS 0 ) AS eventtime,
    augbl AS username,
    kunnr AS customernumber,
    wrbtr AS invoiceamount,
    netdt AS paymentduedate,
    augdt - netdt AS daysoverdue
  FROM bsad " Cleared customer items
  WHERE bukrs IN @s_bukrs
    AND bldat IN @s_bldat
    AND kunnr IN @s_kunnr
    AND rstgr <> '' " Reason code exists for write-off
  APPENDING CORRESPONDING FIELDS OF TABLE @lt_event_log.

  " Output to file
  DATA: lv_string TYPE string.
  OPEN DATASET p_fpath FOR OUTPUT IN TEXT MODE ENCODING UTF-8.
  IF sy-subrc = 0.
    " Header
    lv_string = 'InvoiceNumber,ActivityName,EventTime,UserName,CustomerNumber,InvoiceAmount,PaymentDueDate,DaysOverdue'.
    TRANSFER lv_string TO p_fpath.
    " Data
    LOOP AT lt_event_log ASSIGNING FIELD-SYMBOL(<fs_event>).
      CONCATENATE <fs_event>-invoicenumber
                  <fs_event>-activityname
                  <fs_event>-eventtime
                  <fs_event>-username
                  <fs_event>-customernumber
                  <fs_event>-invoiceamount
                  <fs_event>-paymentduedate
                  <fs_event>-daysoverdue
      INTO lv_string SEPARATED BY ','.
      TRANSFER lv_string TO p_fpath.
    ENDLOOP.
    CLOSE DATASET p_fpath.
  ELSE.
    MESSAGE 'Error opening file.' TYPE 'E'.
  ENDIF.

  WRITE: 'Extraction complete. File created at:', p_fpath.

您的信用管理与收账数据模板

您的信用管理与收账数据模板

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通过 SAP RFC 和 BAPI 的 Python 脚本提取

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用于信用与催收 data 的自定义 ABAP 报表

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a 查询示例 abap

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您的信用管理与收账数据模板

您的信用管理与收账数据模板

信用管理与催收属性

信用管理与催收活动

提取指南

SAP S/4HANA 信用管理 CDS 视图提取

步骤

配置

a 查询示例 sql

对信用管理表的直接 SAP HANA 数据库查询

步骤

配置

a 查询示例 sql

通过 SAP RFC 和 BAPI 的 Python 脚本提取

步骤

配置

a 查询示例 python

用于信用与催收 data 的自定义 ABAP 报表

步骤

配置

a 查询示例 abap

我们重视您的隐私

准备好开始了吗？

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