Active Governance of Customer Data with Forms and Workflow Solutions Inderaj Sehmi Winshuttle



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Active Governance of Customer Data with Forms and Workflow Solutions Inderaj Sehmi Winshuttle

Agenda 1. Introduction 2. Customer Master - Governance Workflow Demo 1. Questions and Open Discussion

Everything depends on Master Data Master Data is the strength of the data foundation that runs the enterprise Costing millions in both lost opportunities and having to rectify mistakes Reporting Suboptimal decision-making Transactional Data Operational problems Master Data Errors and omissions in master data

Active Governance of Customer Data - Master Data Governance is. - Defined as the people, policies and processes that control the creation and maintenance of master data ( e.g. material, vendor, customer, financial) and ensure that it is accurate, consistent, and up to date - Active Data Governance v Passive Data Governance - Passive data governance is the process of reactively addressing data quality issues that have already arisen within the master data. - Active data governance is the application of governance for data quality at the point of consumption or creation by the users of the data

Active Data Governance v Passive Data Governance

Active Governance of Customer Data - Active Data Governance turns master data management into a business process to include dynamic, web-enabled applications that empower business users to collaboratively author, review and approve changes to ERP master data - Reduces the possibility of business-process interruptions due to omissions, duplicates, consistency and content errors, or a lack of standards

Active Governance Elements A typical active data governance process consists of two key elements: Quality: Data entry forms with role-specific views that have built-in validation rules, ensuring only valid data can be entered for the various attributes. Time: Workflows that streamline processes by automatically routing forms to all data contributors and approvers. An effective workflow also includes reminders, escalations and a comprehensive audit trail.

Data never sleeps Unstructured and Structured business critical data changes all the time, for example : - a customer s address changes, new contact details, purchasing habits change, bank details; - a suppliers moves, goes bankrupt or acquires a competitor; - you discontinue a product or launch a new one; - you on-board a new asset or retire an old one.

Impact of poor quality customer data.. - Poor customer onboarding experience when first orders cannot be delivered in good time - Wrong delivery addresses leading to customer frustration, redelivery costs, negative social media attention. - Customer s not visible as a credit risk - lack of consistent information needed to make critical decisions - Invoicing and debiting the right customer accounts. - Customer service levels are unsatisfactory and often lead to customers switching to competitors

Achieving active data governance via.. - Validation of data - SAP Rules - External - mandatory fields, drop down fields, prepopulated entries. - 3 rd party web services- Address Doctor validation - Duplication checks Search in SAP - Role specific form views - Auditability and the support of a role based, traceable processes - Dynamic workflow which allows reviews of data and rule driven actions

Achieving active data governance via.. Active Governance Customer Master Data Data Validation Duplication Checks Role Specific Form Views Traceability and Audit Rule Driven Workflow

Achieving active data governance via.. Active Governance Customer Master Data Data Validation Duplication Checks Using existing SAP rules External rules mandatory fields, drop down limited fields, prepopulate entries 3 rd party web services Address Doctor Validation Live search in SAP Results visible to Approvers in the workflow Search in external sources apart from SAP

Demo

Questions and Open Discussion