APICS CTSC - Certified in Transformation for Supply Chain (CTSC)

According to the ASCM, a RACI analysis is a tool that clarifies the roles and responsibilities of different stakeholders in a business process or activity1.RACI is an acronym for Responsible, Accountable, Consulted, and Informed, which are the four types of participation that a stakeholder can have in a task2.A RACI analysis can help identify the gaps and overlaps in the assignment of tasks, and ensure that everyone knows what they are expected to do and who they need to communicate with1. In the case of the company that receives customer complaints, a RACI analysis can help them understand why their inquiries are being forwarded multiple times to different departments, and who is the right person or department to resolve them.A RACI analysis can also help them improve their customer service process and avoid confusion and frustration among customers and employees1. Therefore, performing a RACI analysis is the most appropriate activity to identify the gap.

According to the ASCM CTSC Exam Content Manual, a data steward is a key role within a digital supply chain transformation team that is responsible for the quality and accuracy of the data feeds.A data steward is defined as "an oversight or data governance role within an organization, and is responsible for ensuring the quality and fitness for purpose of the organization’s data assets, including the metadata for those data assets"1.A data steward may share some responsibilities with a data custodian, such as the awareness, accessibility, release, appropriate use, security and management of data1. A data steward would also participate in the development and implementation of data assets.A data steward may seek to improve the quality and fitness for purpose of other data assets their organization depends upon but is not responsible for1.Data stewards have a specialist role that utilizes an organization’s data governance processes, policies, guidelines and responsibilities for administering an organizations’ entire data in compliance with policy and/or regulatory obligations1.The overall objective of a data steward is the data quality of the data assets, datasets, data records and data elements1.This includes documenting metainformation for the data, such as definitions, related rules/governance, physical manifestation, and related data models (most of these properties being specific to an attribute/concept relationship), identifying owners/custodian’s various responsibilities, relations insight [definition needed] pertaining to attribute quality, aiding with project requirement data facilitation and documentation of capture rules1.Data stewards begin the stewarding process with the identification of the data assets and elements which they will steward, with the ultimate result being standards, controls and data entry1.The steward works closely with business glossary standards analysts (for standards), with data architect / modelers (for standards), with DQ analysts (for controls) and with operations team members (good-quality data going in per business rules) while entering data1.Data stewardship roles are common when organizations attempt to exchange data precisely and consistently between computer systems and to reuse data-related resources1. Master data management often [quantify] makes references to the need for data stewardship for its implementation to succeed.Data stewardship must have precise purpose, fit for purpose or fitness1.

1:Data steward - Wikipedia

According to the CTSC exam content manual1, the last phase of the transformation project is to analyze performance, which involves measuring and evaluating the outcomes of the transformation, identifying gaps and opportunities for improvement, and communicating the results and lessons learned to stakeholders.

According to the ASCM CTSC Exam Content Manual, one of the factors that influences the risk exposure of a supply chain segment is the availability of alternative sources of supply (p. 20). If there is only one available supplier for an important product, the supply chain segment is more vulnerable to disruptions and uncertainties, such as supplier failure, quality issues, price fluctuations, or geopolitical events. Therefore, this product category should have the most complete and thorough risk mitigation plans, which may include strategies such as developing backup suppliers, increasing inventory buffers, diversifying sourcing locations, or implementing contractual agreements.