Demand planning on small and medium-sized enterprises in Mexico: A case study of a confectionery firm

*Corresponding Author DEMAND PLANNING ON SMALL AND MEDIUM-SIZED ENTERPRISES IN MEXICO: A CASE STUDY OF A CONFECTIONERY FIRM Miguel Gil* Tecnologico de Monterrey, Mexico [email protected] Mauro Rodriguez-Marin Tecnologico de Monterrey, Mexico [email protected] Miguel A. Montoya Tecnologico de Monterrey, Mexico [email protected] Abstract Organizations that efficiently complete a demand planning process gain a competitive advantage. The current demand planning literature mostly studies relatively large organizations. However, SMEs invest a significant amount of resources into improving demand planning practices. Moreover, the context of SMEs in Latin America, and specifically Mexico, has not been explored sufficiently by the current literature. Thus, the purpose of this paper is to understand demand planning in a Mexican SME. The paper involves a case study of a confectionery firm based in Jalisco, Mexico. To make sense of the empirical findings, the Kilger and Wagner (2008) theoretical framework of demand planning was utilized. This paper concludes that Mexican SMEs have a different context compared to larger firms in developed countries. Thus, how Mexican SMEs envision and implement demand planning is unique, specifically in demand planning structures and controlling. Key Words Demand Planning; manufacturing, small and medium enterprises, Mexico. Advances in Business-Related Scientific Research Journal, Volume 11, No. 2, 2020 57 INTRODUCTION Small and medium-sized enterprises (SME´s) play a vital role in the economy of emerging markets. Therefore, it is important to implement processes, such as demand planning, for the optimization of resources, and economic growth. Demand planning helps businesses remain in the market and increase competitiveness by reducing uncertainty, increasing revenues, and adapting to favorable environmental conditions. In this sense, demand planning represents a model of uncertainty reduction. In recent years, demand planning has been recognized as the first link in the supply chain. However, its use can vary slightly between developed and emerging countries. This suggests that there are processes or mechanisms involved that have not been considered predominant or that are not necessarily homogeneous among all countries. The case of demand planning in emerging countries is interesting because it provides information about variables that were not generally considered in current theories of demand planning; thus, it will be the focus of this study. Furthermore, this research aims to demonstrate the impact of demand planning on SMEs, specifically in emerging markets. Finally, this document provides an approximation of what the optimal conditions, models, and rules for its operation are. These factors contribute to delivering positive results such as high levels of customer service, optimal inventory levels, minimal waste of materials and reduced risk of obsolescence which, at the end of the day, resulting in reduced costs and hence, profitability; variables that determine growth in companies in the current environment. This is indisputably necessary to understand the past and present new scientific knowledge on the subject and make an original contribution. BACKGROUND When firms sell their products, their goal is to provide customers with the exact amount of demanded goods (Mentzer et al., 2001). Providing fewer products would result in less income, while an oversupply might incur extra costs in sales expenses. Thus, companies intend to forecast the exact amount of sale goods. However, such a task is a complicated challenge (Lambert and Cooper, 2000). Furthermore, without financial support, firms can rarely complete any organizational process. As stated by Kaufman and Covaleski, “Activity can only occur through financial support for staff and related expenses, and a significant indicator of activity deemed legitimate is its priority for resource allocation” (2010, p. 54). Forecasting demand is a complex activity because it involves a large number of variables that are usually exogenous to the firm. For instance, customers might change their desire to acquire goods from the company without giving previous notice (David, 1993). Additionally, customers might drastically change their previous consumption behavior, making it impossible to forecast future trends with historical data. Furthermore, the demand for goods is affected by Advances in Business-Related Scientific Research Journal, Volume 11, No. 2, 2020 58 macroeconomic variables that are sometimes impossible to foresee (Hugos, 2018). However, as difficult as the task seems, demand planning is a crucial activity in Supply Chain Management (SCM) due to its impact on income and expenses (Tayur et al., 2012). It is also important to notice that demand planning structures and strategies are designed and implemented depending on the market of the goods being produced (Hugos, 2018). On the one hand, regarding to business-tobusiness (B2B) business models, demand must be planned in parallel with the requirements of the buyers (David, 1993). This means that demand planning needs to be coherent throughout both organizations to eventually fulfill the demand requirements in terms of time and quality from the clients. On the other hand, business models with a business-to-customer (B2C) fashion, must anticipate their demand based on trends of final clients (Ramus, et al., 2017). Such a difference becomes relevant when demand planning structures and designs are implemented in the organizations. In this sense, marketing theories suggest that demand planning is intrinsically related to market research and costumer relations (Howard, 1983). As Vlckova and Patak (2010) stated “There is feedback between the marketing and demand planning” (p. 1122). In the context of SMEs, demand planning is even more relevant. Due to their size, SMEs are usually required to minimize selling expenses (Quayle, 2003). SMEs tend to have less liquidity and smaller credit lines than larger organizations, making efficiency a must (Sesar et al., 2018). Successful demand planning for SMEs can give them a competitive advantage as it might help them to reduce their costs and maximize their potential sales (Vaaland and Heide, 2007). In other words, a firm that’s successful at demand planning might be able to have a leaner and cheaper productiondistribution process, allowing them to set competitive prices for their goods. Emerging markets provide an interesting context for the study of demand planning (Cedillo-Campos and Sanchez-Ramirez, 2013). Generally, emerging economies are associated with scarce capital and a shortage of credit lines. Thus, saving on production and sale expenses becomes critical in the survival of a firm (Esfahbodi et al., 2016). Demand planning offers firms in emerging markets an opportunity to create cheaper budgets, allowing organizations to operate at lower costs. With proper demand planning, firms can achieve more efficient inventories, giving them relief in their search for working capital. Furthermore, organizations in emerging markets are exposed to external institutions, which are generally different from developed economies (Omazic et al., 2020). Such institutions affect how the organizations develop their internal practices; “Organizations deal with multiple sociocultural pressures that define appropriate ways of doing things" (Ramus et al., 2017, p. 1253). This study incorporates such contextual influences and acknowledges the specific features of emerging markets. The Mexican market represents one of the most complex economies in the world. Its relationship with foreign markets, the size of the internal market, and the complicated regulatory framework makes the Mexican economy a challenging scenario for demand planning (Van Hoof and Thiell, 2014). Advances in Business-Related Scientific Research Journal, Volume 11, No. 2, 2020 59 Forecasting gets easier as macroeconomic forces tend to be more stable. In the case of Mexico, the macroeconomic landscape is turbulent and, to some degree, unpredictable (Garcia-Reyes and Giachetti, 2010). Regulatory changes, increasing market regulations, and inequality in national wealth make it difficult to forecast the behavior of consumers. This paper argues that, in the end, demand planning activities are “Socially constructed historical patterns of material practices, assumptions, values, beliefs, and rules" (Thornton and Ocasio, 1999, p. 84). Demand planning in the context of SMEs in an emerging economy such as Mexico seems like a huge challenge (Mangan and Lalwani, 2016). However, the outcomes of successful demand planning are exponentially positive for Mexican SMEs. This paper will use Kilger and Wagner’s (2008) framework of demand planning to make sense of the empirical data gathered in the case studies. The following subsection presents the framework and aims to signpost the relevant processes in demand planning. A framework for Demand Planning Demand Planning is a critical activity in SCM as knowing the demand for products is the first step in the production and sales processes. Without a proper forecast of the demand, it is impossible even to prepare an accurate budget. Thus, financing the firm is also dependent on the success of demand planning. However, when organizations intend to plan the demand, it can be extremely chaotic. For instance, some firms might sell too many different products, or even an infinite number of products, if they sell customized goods, such as is the case with Dell. Furthermore, forecasting demand can be complicated if the time frame is not well defined. Sometimes, companies sell products without knowing how long their product is going to be on sale. To clarify how demand planning is carried out in the companies studied in this paper, a demand planning framework will be used. The framework organizes the demand planning process into three features. Through this framework, it is possible to visualize what type of activities are carried out in the organizations and it makes it easier to compare them with different firms. As the purpose of this study is to analyze the demand planning of SMEs from the chocolate industry in Mexico, using this framework of demand planning seems appropriate. Furthermore, the same framework has been used in other studies with similar research objectives. For instance, Kannegiesser et al. (2009) developed a demand planning model for the chemical industry. The authors used the demand planning framework to make sense of the empirical data that they collected and to structure their own. Moreover, Vlckova and Patak (2012) carried out a study to understand the effect of outsourcing on demand planning in Czech firms. The framework of demand planning helped the authors to organize the processes studied. Besides, the framework allowed them to assess the effects of outsourcing in a specific subprocess of demand planning. The framework of demand planning is divided into three features that are subsequently divided into more specific mechanisms, which will be Advances in Business-Related Scientific Research Journal, Volume 11, No. 2, 2020 60 explained in this subsection. The three main features are: structures, processes, and controlling. Demand Planning Structures Demand planning structures are important because these set the basis on which demand planning will operate. Structures set the assumptions that the firm will use to forecast the demand for the goods that they sell. Demand planning structures are important because failure in setting the appropriate assumptions can lead to a wrong forecast. Min and Yu (2008) did a study of supply chain partners and concluded that a key factor in the success of chain value management was correctly setting the structure in which they operate. According to the authors of the framework, a demand planning structure is divided into three mechanisms: (i) time, (ii) products, and (iii) aggregation/disaggregation. The time frame is very important when planning the demand. Firms need to think carefully about what time frame they will use. The time frame should allow firms to include seasonal changes in demand and supplier availability. For instance, a fast-food restaurant might set its time frame daily since fast food restaurants usually supply their raw materials every day. In contrast, a cloth retailer might resupply their inventories weekly; thus, it makes sense if the cloth retailer sets the time frame of their demand planning to a weekly basis. The product feature is critical when firms set the structure on how they will do the demand planning process. Product refers to the unit of analysis that the firm will use to forecast the demand. Firms can forecast specific products using the SKU (stock-keeping units). For instance, a beverage firm can forecast the demand specifically for its cola soda of 500 ml presentation and independently forecast the cola soda of 750 ml. Furthermore, firms can choose to forecast a family of products. For example, the same company can choose to forecast using a family of products and they will forecast cola sodas regardless of the presentation. Firms should also set if they want to aggregate or disaggregate their demand planning. Aggregating means that the firm starts from the smallest unit of analysis related to the products and from there they plan the demand to higher levels. For instance, if the beverage firm from the previous example decides to apply an aggregate perspective, they should plan first their demand using specific products and then add all the products of each family to calculate the total. In contrast, a disaggregating perspective suggests that the firm will do the demand planning based on the family of products, and from that, they can state the specific demand for each product. In the end, regardless of the perspective the firm chooses, their numbers at the family or product level should match. For instance, if the firm decided to disaggregate and they planned demand of 100 cola sodas, the sum of the 500 ml and 750 ml of soda colas should be 100 in total. Demand Planning Processes Once the structures are set, firms also need to establish the phases of demand planning. Defining the phases is a critical part of demand planning Advances in Business-Related Scientific Research Journal, Volume 11, No. 2, 2020 61 as it allows the organization to schedule the activities involved in demand planning. The core of this stage is to generate an outcome that would permit the firm to foresee the future demand for their products. It is also important to mention that this stage needs to be coherent with what was established in the structures of the demand planning, otherwise the disconnection between the stages might produce mistakes in the way in which the firm forecasts demand. Demand planning processes consist of three mechanisms that organizations should clarify: (i) phases, (ii) participants, and (iii) forecast. The phases in the demand planning process might differ in different organizations. For instance, some firms might consider fewer phases than other firms. Usually, the level of complexity in the supply chain decides the number of phases identified by each organization. Examples of phases include gathering data, computations of statistics, judgmental forecasting, and the release of forecasts. It is important to note that each of these phases needs to be based on the structures that were previously set by the organization. Defining the participants of the demand planning process is another crucial procedure that firms should complete. It is impossible to invite everyone in the organization to participate in demand planning. Thus, it is an operational need to define who will participate and who will not. In some organizations, senior managers carry out the demand planning process alone. In such cases, organizations believe that senior managers hold all the information required to complete the demand planning process. In other organizations, mid-tier managers are also invited to participate in the demand planning process. Such organizations are usually large and complex, so they require the participation of more members. Finally, some firms decide to invite external members to participate in the demand planning process. These organizations intend to extract information from outside of the firm and include it in their demand planning process. The core of the demand planning process is the forecast. During the forecast, the firm uses a previously established methodology to forecast the expected demand for their products. As the current literature states, there are three main ways an organization can forecast the demand: qualitative, quantitative, and mixed methods. Qualitative focuses on the subjective opinion of individuals in the organization to forecast the expected demand for a product. An organization might find it easier to rely on the experience and knowledge of their managers to establish the expected demand, whilst other firms rely on complex mathematical and statistical methods to forecast the demand. By using such methods, the organization analyses the gathered data and forecasts the possible demand. Finally, it is also possible to mix qualitative and quantitative methods. In this case, organizations might use a quantitative approach to set an objective baseline for the forecast, then they might use a subjective judgment by senior managers to polish the forecast. Demand Planning Controlling Once the organizations have finished with the forecast, it is necessary to supervise the real outcomes of the firm. This stage is critical in every organization, but the context of SMEs highlights its importance. Davila and Advances in Business-Related Scientific Research Journal, Volume 11, No. 2, 2020 62 Foster (2009) found that startup firms that monitored the expected demand had a better performance than organizations that only focused on forecasting demand but never documenting what happened. Similarly, Shi et al. (2011) concluded that controlling demand planning is a critical stage that allows organizations to improve their production processes. Demand planning controlling is divided into two mechanisms: (i) incentivesresponsibilities and (ii) Key Performance Indicators (KPIs). Setting incentives and responsibilities is critical when firms carry out the demand planning process. Organizations might focus on how they can foster the successful implementation of demand planning without harming the production process of the firm. In this sense, senior managers might focus on stimulating individuals in the organization to accomplish the forecast. Once senior managers realize that the demand forecast has been accomplished, they can provide organizational members with bonuses as a reward for their effectiveness. On the contrary, when the forecast is not met, senior managers should be able to identify the organizational members responsible for such a variance and act accordingly. However, when the senior managers contrast what happened with the forecast, they usually find it hard to judge if the outcome was positive or negative. Furthermore, even if managers can determine whether the outcome was positive or negative, it is difficult to assess the degree of success or failure. Due to these difficulties, senior managers develop KPIs that allow them to evaluate, as objectively as possible, if the outcomes of the process were positive or negative. There are different KPIs that are used worldwide, but in this paper, three will be explored during the case study: accuracy, inventory, and field rate. Accuracy KPIs relate to how well the firm accomplished the stated forecast, inventory KPIs focus on the efficiency of inventory management and, finally, field rate KPIs focus on fulfilling the demands of the firm’s clients. METHODOLOGY Demand planning has been studied using different methodologies. Authors have used quantitative (Peidro et al., 2009), qualitative (Akillioglu et al., 2013), or mixed methods (Okurut et al., 2015). Each researcher chose a methodology based on his abilities and the research question that he or she previously stated. In the case of this research, the most suitable methodology is qualitative (Apaiah et al., 2005). A qualitative methodology permits a deeper understanding of the case context (Goffin et al., 2012). Additionally, the qualitative methodology considers the individual interpretations of relevant participants (Mangan et al., 2004). These two features of the qualitative methodology are coherent with the research objectives of this paper. This paper will use a case study to capture and analyze empirical data. A case study permits a deeper understanding of a phenomenon in a determined context (Yin, 2011). Since the purpose of this study is to Advances in Business-Related Scientific Research Journal, Volume 11, No. 2, 2020 63 understand how a company carries out a demand planning process, the case study method becomes the most suitable alternative (Scapens, 2004). For this study, different types of empirical data were collected. Firstly, the researchers gathered external reports such as press releases from the company studied, where the firm explained to outsiders some of their production innovations (Merriam, 1998). Secondly, the researchers carried out interviews with organizational members of the firm. The researchers completed six semi-structured interviews, which allowed them to ask for critical information related to demand planning (Bromley and Bromley, 1986; Whiting, 2008). The interviewees were mid and senior managers from the firm studied. During the interviews, managers asked not to include the name of the company in the case study. Thus, the studied company will be called Confectionery Inc. Changing the name of the company is only to fulfill the ethical agreements of the case study, the findings and conclusion of this paper are not affected by the change (Tellis, 1997; Street and Ward, 2012). The Kilger and Wagner framework of demand planning (2008) was used throughout the whole data analysis period. CASE STUDY Confectionery Inc is a Mexican confectionary firm that was founded in 1942, one of the most important sweet companies in the country. Confectionery Inc’s headquarters is located in Guadalajara, Jalisco México. The plants of Confectionery Inc currently are located in Tlaquepaque and Tlajomulco, where 350 products are made. Confectionery Inc continues to grow thanks to the fact that it continues to develop new flavors, formulas, and attractive presentations, using the best technology in the confectionery sector and moving its products throughout the country. The confectionery industry was selected for its importance in the local economy and for its complicated demand planning procedures. Firstly, the confectionery industry in Jalisco is of critical importance in terms of jobs created and private investment (Contreras-Escareño, 2016). Secondly, the confectionery industry represents important challenges on regards of demand planning (Reddy et al, 2011). Confectionery firms tend to have a complex network of suppliers, which require advanced planning and proper forecasting. Additionally, the demand for confectionery products vary significantly, as customers change their consumption patterns due to holidays, weather or specific events (Reddy et al, 2012). The structure of Confectionery Inc’s 3 plants and a distribution system helps to deliver all products across Mexico. The single large-scale distribution center and great labor management system prove Confectionery Inc’s commitment to innovation. Research and development are also a core element of their business strategy. The brands mentioned are quite popular among Confectionery Inc’s consumers and in markets the company operates. Additionally, corporate social responsibility is a priority for Confectionery Inc. Since 2007, the company Confectionery Inc have helped their employees to finish primary and middle education. Furthermore, the Advances in Business-Related Scientific Research Journal, Volume 11, No. 2, 2020 64 firm applies for health and addiction support programs periodically, the combination of which has allowed the majority of their staff to achieve professional growth. Demand Planning Structures For Confectionery Inc, the task for demand planning is to predict future customer demand at different levels: by-product, set of products, category, total product, and region. The demand pattern for a particular product can be considered as a time series of separate values. For each product, there may be multiple time series representing, for example, historic data, forecast data, or computed data, like the accuracy of the forecast. The selection of the right time series and the planning horizon of the forecast (time frame) to be used in the demand planning process depends on the answer to the question: What is being forecast? In the case of Confectionery Inc, a mid-term master planning process requires a forecast for each product monthly (in cases, or production units, known as DFU - Demand Forecast Units). A long-term capacity planning process requires a forecast for each family monthly to meet the demand according to capacity. Finally, a long-term strategic planning process requires projections on each total product quarterly. See Figure number 1. Figure 1: Demand Planning Structure Source: Rodríguez Mauro, adapted with information from Confectionery Inc, 2020. Currently, Confectionery Inc has a catalog of 300 SKU´s which are divided into 11 large families (see Figure 2). Time-series statistical forecasting is also a necessity when a company produces hundreds of end items. It is inefficient to develop a demand plan for just a few major product lines. The turmoil caused by not planning for the demand for the other products disrupts production. Unplanned demand competes against planned demand for raw materials and production capacity (Crum and Palmatier, 2009). Customer service inevitably suffers, as do sales revenues and profit margins. Consequently, developing demand plans for all products is the best practice Advances in Business-Related Scientific Research Journal, Volume 11, No. 2, 2020 71 regularly and if the firm identifies a fluctuation, then adjustments are made. This is consistent with the existing systems mentioned in the current literature. The similarities between the case study and Confectionery Inc might be since, as organizations become larger, they rely more on formal systems of control (Gil, 2019). CONCLUSION This paper contributes to the existing literature on demand planning practices. In particular, this research highlights the particular features of SMEs in an emerging market. By incorporating the features of an emerging market, it is possible to identify and explain patterns. The conclusions of this paper are congruent with the suggestion of Ryan et al., “It is more appropriate to apply the logic of replication and extension, rather than a sampling logic, to case study research” (2002, p. 269). Demand planning is a relevant stream in the current managerial and accounting literature. Furthermore, the context of SMEs in emerging markets permits us to observe new practices and novel interpretations of already institutionalized procedures. Thus, future research calls for more explanatory case studies on the subject. The findings from such studies might benefit the current state of literature in demand planning. In particular, incorporating other industries into academic studies will enrich the understanding of demand planning practices and systems. Apart from the possible theoretical contributions that the proposed future research proposes, practical contributions are also relevant in the development of knowledge; “Just contributing to theory without any application of that theory should not be fulfilling to researchers in a professional school” (Merchant, 2012, p. 339). It is also relevant to acknowledge the limitations of this study. First, while measures have been taken to prevent response bias, it is not possible to eliminate this in qualitative research (Mehra, 2002). Although the organization in this case study was selected due to its interesting context and innovative practices on demand planning, it would be interesting to incorporate a second organization to compare its demand planning practices. Second, due to legal bylaws of the firm studied, only one researcher could complete the semi-structured interviews. 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