In today's globalized business environment, marked by growing market uncertainties and increasing supply chain complexity, Sales and Operations Planning (S&OP) has emerged as a critical practice to balance demand and supply. As industries evolve in volatile and competitive landscapes, the rapid advancements of business analytics and its integration into S&OP gains prominence; they offer promising avenues to leverage data-driven insights that enable agile decision-making and swift adaptation to market fluctuations. Yet, despite its widespread adoption, the integration of business analytics into S&OP remains insufficiently understood, exposing a gap between theory and practical application. This thesis explores the gap at the intersection of S&OP and business analytics. It highlights the potential of integrating business analytics capabilities into S&OP frameworks through a socio-technical approach that addresses both technological and organizational challenges. It provides a comprehensive S&OP taxonomy, a performance framework, and a dedicated Business Analytics-S&OP Framework, culminating in a systematic method for designing and implementing a data-driven S&OP process that aligns capabilities, business objectives, processes, and analytics applications. Demonstrated through a series of case studies, these findings offer actionable insights for transforming supply chain management in today's dynamic market.
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Paperback. Condition: new. Paperback. In today's globalized business environment, marked by growing market uncertainties and increasing supply chain complexity, Sales and Operations Planning (S&OP) has emerged as a critical practice to balance demand and supply. As industries evolve in volatile and competitive landscapes, the rapid advancements of business analytics and its integration into S&OP gains prominence; they offer promising avenues to leverage data-driven insights that enable agile decision-making and swift adaptation to market fluctuations. Yet, despite its widespread adoption, the integration of business analytics into S&OP remains insufficiently understood, exposing a gap between theory and practical application. This thesis explores the gap at the intersection of S&OP and business analytics. It highlights the potential of integrating business analytics capabilities into S&OP frameworks through a socio-technical approach that addresses both technological and organizational challenges. It provides a comprehensive S&OP taxonomy, a performance framework, and a dedicated Business Analytics-S&OP Framework, culminating in a systematic method for designing and implementing a data-driven S&OP process that aligns capabilities, business objectives, processes, and analytics applications. Demonstrated through a series of case studies, these findings offer actionable insights for transforming supply chain management in today's dynamic market. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9783832557973
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Paperback. Condition: new. Paperback. In today's globalized business environment, marked by growing market uncertainties and increasing supply chain complexity, Sales and Operations Planning (S&OP) has emerged as a critical practice to balance demand and supply. As industries evolve in volatile and competitive landscapes, the rapid advancements of business analytics and its integration into S&OP gains prominence; they offer promising avenues to leverage data-driven insights that enable agile decision-making and swift adaptation to market fluctuations. Yet, despite its widespread adoption, the integration of business analytics into S&OP remains insufficiently understood, exposing a gap between theory and practical application. This thesis explores the gap at the intersection of S&OP and business analytics. It highlights the potential of integrating business analytics capabilities into S&OP frameworks through a socio-technical approach that addresses both technological and organizational challenges. It provides a comprehensive S&OP taxonomy, a performance framework, and a dedicated Business Analytics-S&OP Framework, culminating in a systematic method for designing and implementing a data-driven S&OP process that aligns capabilities, business objectives, processes, and analytics applications. Demonstrated through a series of case studies, these findings offer actionable insights for transforming supply chain management in today's dynamic market. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9783832557973
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Paperback. Condition: new. Paperback. In today's globalized business environment, marked by growing market uncertainties and increasing supply chain complexity, Sales and Operations Planning (S&OP) has emerged as a critical practice to balance demand and supply. As industries evolve in volatile and competitive landscapes, the rapid advancements of business analytics and its integration into S&OP gains prominence; they offer promising avenues to leverage data-driven insights that enable agile decision-making and swift adaptation to market fluctuations. Yet, despite its widespread adoption, the integration of business analytics into S&OP remains insufficiently understood, exposing a gap between theory and practical application. This thesis explores the gap at the intersection of S&OP and business analytics. It highlights the potential of integrating business analytics capabilities into S&OP frameworks through a socio-technical approach that addresses both technological and organizational challenges. It provides a comprehensive S&OP taxonomy, a performance framework, and a dedicated Business Analytics-S&OP Framework, culminating in a systematic method for designing and implementing a data-driven S&OP process that aligns capabilities, business objectives, processes, and analytics applications. Demonstrated through a series of case studies, these findings offer actionable insights for transforming supply chain management in today's dynamic market. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9783832557973
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