Modeling Lean, Agile, and Leagile Supply Chain Strategies

Journal of Business Logistics 03/2006; 27(1):57 - 80. DOI: 10.1002/j.2158-1592.2006.tb00241.x


The merits of lean and agile supply chain strategies have been much debated among practitioners and academics. While these strategies are often viewed as opposites, this research supports the view that they must not necessarily compete and can, in fact, be employed simultaneously through a so-called “leagile” approach. Lean, agile, and leagile strategies are illustrated by modeling their respective applications at a tier-1 supplier to the Heating, Ventilating, and Air-Conditioning (HVAC) industry. Simulation analyses indicate that the lean system excels in customer service performance while the leagile system results in lower enterprise-wide inventory levels under modeled circumstances. Subsequent analysis suggests that trade-offs exist among the systems in the base case and under varying cost conditions.

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    • "Some authors defined agility as a 'post-lean paradigm' (Womack and Jones 1996; Jain, Benyoucef, and Deshmukh 2008), which incorporates lean principles to cope with a turbulent environment. Other researchers stressed the difference between agility and leanness (Naylor, Naim, and Berry 1997; Goldsby, Griffis, and Roath 2006) where leanness is a philosophy essentially focused on eliminating all waste including time, while agility is a way to use market knowledge to exploit profitable opportunities in a volatile marketplace. "
    International Journal of Logistics 08/2015; DOI:10.1080/13675567.2015.1073234 · 0.48 Impact Factor
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    • "These factors, as outlined by Williams and Waller (2010), can include replenishment and execution processes at the store or operating procedures at the retail DC's, (Kum et al. 2010; Vogt 2010), as well as idiosyncrasies with warehouse management systems (Autry et al. 2005). In addition, supply chain processes can drive complexity, such as postponement (Zinn and Bowersox 1988), inventory centralization (Evers 1995; 1996; 1997; Evers and Beier 1993; 1998; Mahmoud 1992; Ronen 1990; Tallon 1993; Zinn et al. 1989) and lean practices (Goldsby et al. 2006). All of these factors may make DC orders more difficult to predict, than retail sales. "
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    ABSTRACT: Suppliers of consumer packaged goods are facing an increasingly challenging situation as they work to fulfill orders from their retail partners' distribution facilities. Traditionally these suppliers have generated forecasts of a given retailer's orders using records of that retailer's past orders. However, it is becoming increasingly common for retail firms to collect and share large volumes of point-of-sale data, thus presenting an alternative data signal for suppliers to use in generating forecasts. A question then arises as to which data produces the most accurate forecasts. Compounding this question is the fact that forecasters often temporally aggregate data for consolidation or to produce forecasts in larger time buckets. Extant literature prescribes two countervailing statistical effects, information loss and variance reduction, that could play significant roles in determining the impact of temporal aggregation on forecast accuracy. Utilizing a large set of paired order and point-of-sale data, this study examines these relationships.
    Journal of Business Logistics 03/2015; 36(2). DOI:10.1111/jbl.12091 · 2.35 Impact Factor
    • "There are divergent perspectives across operations and supply chain management researchers regarding the relationship between agility and efficiency. Some have considered agility to be significantly different from lean, which has been linked to COST (e.g., Goldsby et al., 2006). Supply chain researchers characterize lean management as concerning the minimization of waste and liken this to a strategy focused on efficiency (Christopher et al., 2006; Sebastiao and Golicic, 2008). "
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    ABSTRACT: Traditionally, researchers have claimed agility as an attribute closely tied to the effectiveness of strategic supply chain management. Because of its association with customer effectiveness, some researchers have considered agility to be fundamentally different from lean, which has been linked to cost efficiency (Goldsby et al., 2006). Therefore, the relationship between agility and cost efficiency is not clear due to limited empirical scrutiny from researchers. Since elimination of waste is the cornerstone of lean, unravelling the relationship between agility and efficiency can also offer a better perspective on relationship between the fundamental paradigms of agility and lean. The manuscript makes a key contribution to the agility literature by examining the association between supply chain agility (FSCA), cost efficiency and customer effectiveness across various environmental situations. We use archival data to examine the moderating effects of environmental munificence, dynamism, and complexity. It has been argued that firms should embrace agile strategies when operating in highly uncertain environments, and embrace lean strategies when operating in more stable environments (Lee, 2002 and Sebastiao and Golicic, 2008). We empirically question this premise to determine whether supply chain agility can also lead to superior performance for firms operating in stable environments. The study results also provide a better understanding of how FSCA contributes to firm financial performance. We evaluate the impact of FSCA on the firm's Return on Assets using archival data from the Compustat database. Thus, we provide evidence to managers that deploying resource to enhance FSCA can positively impact the firm's bottom line.
    Journal of Operations Management 10/2014; 33-34. DOI:10.1016/j.jom.2014.10.008 · 3.82 Impact Factor
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