Before the firm can negotiate or discuss data exchanges with the retailers, it should first review its own data needs and potential trading options. This means that the firm should identify what kind of retail sales data it requires, how frequently, and for what purpose. It should also assess the value and quality of the data, and the costs and benefits of obtaining it. Moreover, the firm should explore what kind of data it can offer in return to the retailers, and how it can create a mutually beneficial data exchange relationship. By reviewing its data needs and potential trading options, the firm can prepare a clear and realistic data exchange proposal that can facilitate the subsequent negotiation or discussion process.

1: Data Processing Agreements: Coordination, Drafting, and Negotiation

According to the ASCM CTSC Exam Content Manual, one of the first steps in developing a transformational supply chain strategy is to ''determine the current and future needs and expectations of the customers, and align the supply chain strategy with the business strategy and customer value proposition'' (p. 16). This helps to ensure that the supply chain transformation is customer-centric and focused on delivering value to the end users. The other options are also important, but they should be done after the initial determination of the customers' needs.

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 ASCM CTSC Exam Content Manual, one of the prerequisites for a supply chain transformation roadmap is to standardize and harmonize processes across the enterprise1. This can help to eliminate waste, reduce complexity, improve efficiency, and enable scalability of the supply chain opera-tions2. The other options are not prerequisites, but rather outcomes or enablers of a supply chain transformation roadmap.1: ASCM CTSC Exam Content Manual, page 10. 2: 1