Sales and Operations Planning for Profitability Improvement through Analytics: A Systematic Literature Review

Paper Title: Sales and Operations Planning for profitability Improvement through Analytics: A Systematic Literature Review.

Background & Aims: Sales and Operations Planning (S&OP) is a business process for aligning operations with the strategic business goals, planning with execution, and supply with demand. The aim of this paper is to study the S&OP processes, benefits, enablers and barriers for maximising profitability, with the applicable data analytic (DA) techniques for prediction, modelling, optimisation and simulation, that support achieving a successful S&OP, and ultimately a profitable and sustainable business. The paper also provides an introduction about Smart S&OP, which means adding smart capabilities to the standard S&OP process, for improving the integration of systems and processes, information sharing in real-time, demand forecasts, inventory control, among others. The smart capabilities include big data analytics, Internet of Things (IoT), Artificial Intelligence (AI) and machine learning.

Design/methodology/approach: The method used is a systematic literature review (SLR), through secondary data from peer-reviewed journal articles type of literature. The SLR identified 31 papers from 25 journals, with year coverage from 2007 to 2021.

Findings: The SLR results show that S&OP is a fundamental business process to improve profitability, customer satisfaction, sustainability and competitiveness. Therefore, it is advisable that organisations understand its enablers and barriers to ensure successful implementation. IT and DA are important enablers and indicate a mature S&OP process. DA support S&OP in several ways. For example, prediction of raw materials or operations price increases, supply risk mitigation, operational cost optimisation, profitability maximisation, developing what-if scenarios for demand and supply, optimising the suppliers’ network to ensure having alternatives and avoid any supply disruptions, optimising the mix of customers, products and prices to achieve maximum profits, developing trade-offs between cost and volume combinations, prediction of

customers’ future needs and industry trends, and simulating delivery options for selection of optimum solutions.

Smart S&OP is an advanced form of S&OP and provides further support to achieve its objectives including cross-functional integration and profitability. Smart S&OP is considered the future of S&OP that integrates with the smart production planning and Supply Chain (SC). It improves the S&OP performance through data sharing, analytics and automation. By applying the smart capabilities into the S&OP processes, businesses can achieve up to 50% lower development cost, 25% lower operational cost and 30% increased gross margin.

Contributions/Implications: This research contributes to literature by focusing on the S&OP for profitability improvement using DA, by summarising 19 S&OP frameworks from literature focusing on profitability, and presents the smart S&OP concept. The research is beneficial for practitioners since different S&OP frameworks, DA techniques, benefits, maturity levels, enablers are barriers are provided for them to study and apply the most relevant aspects to their businesses. Academics also can use it as a reference for the existing literature on the topic, and the possible future research areas. The SLR results are limited to 31 research papers from 25 journals in English. No academic papers dedicated to smart S&OP were identified through the SLR research criteria. To address this gap, other resources mainly about SC digitisation and smart production planning were used to introduce the smart S&OP.