b'ManagementDr. David Preston is a Professor of Information Systems at Texas Christian University, Fort Worth, Texas. Dr. Daniel Chen is a Professor in the Department of Information Systems and Supply Chain Management of the M.J. Neeley School of Business at Texas Christian University, U.S.A. Dr. Morgan Swink teaches and leads research in areas of supply chain management, innovation management, project management, and operations strategy.improve SC practices has become essential for governmentalFramework I: The first framework examines the key drivers organizations. This study examines the role that organizationalof analytics usage for SC practice which consists of the use of technology innovation plays in improving SCMfollowing contexts: 1) Technical; 2) Organizational; 3) activities for public organizations. Environmental. Specifically, this framework examines how the mechanisms within each context either directly or Technology innovation is imperative to SCM success sinceindirectly influence analytics usage.organizations along the value chain require information flows and knowledge creation. Technology innovation hasThe technological context is comprised of both the key organizational implications to the domain of SCM. SCMorganizations expected benefits and its technological activities are boundary-spanning by their nature since theycapability. Such technological concerns are relevant to both often most involve other organizational partners across thepublic and private organizations. To adopt a technology to value chain. an appreciable and useful degree, an organization must expect to benefit from such technology. For an organization However, public entities often lag in technological innovationto adopt analytics for SCM, it should expect a series of and as such their supply chain (SC) practices are affectedoperational and strategic benefits will arise: cost savings, accordingly.inventory reduction, reduced cycle times, better product/service delivery rates, improved customer service, improved Three Frameworks for Analytics Usage knowledge sharing, and increased confidence levels in Government organizations should look to industry practice todecision-making, etc. Therefore, key decision-makers will model how technology innovation can improve SCM. In thisneed to assess if analytics use as a technology is truly study, technology innovation is examined via the potentialcompatible with the values and SCM work practices ofuse of analytics, blockchain, and artificial intelligence (AI) asthe organization.they apply to SCM practice. In this report, we first examine analytics usage for SC impacts since analytics currently hasThe organizational context is considered in terms of wider rates of adoption in industry. Through an empiricalorganizational readiness, which is the degree to which analysis of industry survey data, the research design developsan entity has the required organizational resources to three frameworks for analytics usage. effectively implement analytics. Such resources include financial capital available for allocation and technical infrastructure as needed. Top management is key in assessing the external landscape and how the industry is engaging with from technology standpoint. Findings indicate that the organizational and environmental factors alone are not sufficient to influence analytics adoption and usage directly and adequately, rather managerial leadership is needed as a mediating effect. Hence, top management is likely to sponsor analytics ubiquitously for organizational functions if it views that the entity has proper resources in place and there are salient competitive pressures.2022 IBM Center for The Business of Government 93'