Proposal of a model for sales and operations planning (S&OP) maturity evaluation

Abstract

A successful S&OP implementation can bring many benefits to organizations, and after its implementation, the S&OP process can evolve and reach higher levels of maturity. Considering that, only through a measurement system, goals and benefits can be achieved, thus, it is essential to assess S&OP maturity level. Many papers on literature adopt a quantitative perspective on S&OP, but just few of them deal with uncertainty present in S&OP decision-making, such as maturity model assessment process that carries subjectivity and uncertainty. Thus, this study proposes a decision making model based on fuzzy theory to evaluate and to categorize S&OP maturity levels and to suggest strategies to increase S&OP maturity. A pilot application was conducted in two manufacturing organizations that have implemented the S&OP process. The results, according to the performance presented, suggest different actions must be taken in terms of ensuring enablers to S&OP implementation. KeywordsSales and operations planning. Maturity model. Fuzzy inference. Fuzzy set theory.

SALES & OPERATIONS PLANNING: Case study on the Engineer-To-Order production model in the entertainment industry

“…This structure captures the main elements of S&OP (Kjellsdotter Ivert et al, 2015a) and is considered generic, as it offers a complete overview of the process (Noroozi and Wikner, 2017). This study was later referred to by several authors, such as Danese et al (2017), who evaluated the managing evolutionary paths in S&OP, Goh and Eldridge (2015), who analyzed new product introduction and supplier integration in the S&OP of two companies in Asia, Kristensen and Jonsson (2018), who did a systematic literature review on context-based S&OP, Pedroso et al (2016), who developed a multiple case study, Pedroso et al (2017), who offers a model for S&OP maturity, Seeling et al (2019) and Seeling et al (2020), who presents a case studies in Latin America, and Vereecke et al (2018), who assesses maturity in demand planning. There was also the influence of the different frameworks developed, such as those by Tuomikangas and Kaipia (2014), which assesses the coordination of S&OP, by Hulthén et al (2016) looking at the effectiveness and efficiency of S&OP, by Thomé et al (2012) and Hollmann et al (2015) with a focus on collaborative planning, forecasting and replenishment, by Kjellsdotter Ivert et al (2015a) who analyzes the complexity of the planning environment, by Noroozi and Wikner (2017) with a focus on supply chain integration, and Kristensen and Jonsson (2018) analyzing context-based S&OP.…”

“…The maturity model of Grimson and Pyke (2007) was adopted for this research, as it evaluates, with clear and objective parameters, the relevant dimensions for the implementation of the process in the analyzed company. Besides that, several authors have referred to this study over the past few years as Wagner et al (2014), Goh and Eldridge (2015), Kristensen and Jonsson (2018), Pedroso et al (2016), Pedroso et al (2017) and Vereecke et al (2018), all of these references are related to maturity analysis and assessment regarding S&OP. Danese et al (2017) used this model to study the key dimensions and the sequence of implementation of S&OP in companies.…”

Proposta de um modelo híbrido de tomada de decisão em grupo baseado na teoria >i<dual hesitant fuzzy>/i< e algoritmo genético

“…combinado com Fuzzy Technique for Order of Preference by Similarity to Ideal Solution -TOPSIS(BOUTKHOUMet al, 2016;DARBARI et al, 2015); AHP combinada com o método de organização por ordem de preferência para o enriquecimento das avaliações -Deve-se observar que mais da metade dos estudos com abordagens multicritérios utilizam a teoria da lógica fuzzy como representação da informação. O amplo uso da teoria dos conjuntosfuzzy para representar informações de avaliação nos processos de tomada de decisão se deve à sua capacidade de representar informações subjetivas, imprecisas e vagas(PEDROSO et al, 2017). Entretanto, nenhum dos modelos propostos apresentados nos estudos trata de informações hesitantes, que podem ser tratadas através de outras generalizações fuzzy, tais como hesitant fuzzy, intuitionistic fuzzy e dual fuzzy hesitante(CALACHE et al, 2021c).…”