Carolin Romeser
email: carolin.romeser@gmail.com

Christoph Roser
email: christoph.roser@hochschule-karlsruhe.de

Direction of the Bottleneck in Dependence on Inventory Levels

Keywords: Inventory, FiFo, Bottleneck direction, Bottleneck detection

Buffers decouple fluctuations in the material flow. It is common wisdom in industry that a full buffer indicates a downstream bottleneck and an empty buffer indicates an upstream bottleneck. Numerous different bottleneck detection methods use this approach to detect the bottlenecks. However, so far this common wisdom on the shop floor has not yet been verified academically. The authors tested this hypothesis using a bottleneck detection method that was able to detect the bottleneck in a system at any given time. The bottleneck direction can reasonably be determined based on the inventory levels of the buffer only for symmetrical systems. In asymmetrical systems, the likelihood of the bottleneck direction is biased toward the bottleneck.

Introduction

Bottleneck detection is the key to improving capacity in any production system. Only the improvement of the throughput of a bottleneck process will lead to an improvement of the throughput of the overall system. This is complicated by the tendency of bottlenecks in industry to shift between different processes. We define the bottleneck as follows: "Bottlenecks are processes that influence the throughput of the entire system. The larger the influence, the more significant the bottleneck" [START_REF] Roser | Reliable Shop Floor Bottleneck Detection for Flow Lines through Process and Inventory Observations: The Bottleneck Walk[END_REF].

In many bottleneck detection methods, both in academic publications as well as in industrial practice, the buffer inventory between two processes is investigated. The hypothesis is usually not explicitly stated but is often implicitly indicated to be as follows: "If the buffer between two processes is full or rather full, the bottleneck is probably downstream [. . . ]. If the buffer is empty or rather empty, the bottleneck is probably upstream [. . . ]. If the inventory is half full, the bottleneck may be in either direction" [START_REF] Roser | Reliable Shop Floor Bottleneck Detection for Flow Lines through Process and Inventory Observations: The Bottleneck Walk[END_REF].

However, while in compliance with conventional wisdom and logical deduction, to the best of our knowledge this assumption has never before been analyzed in detail even though it is the basis of several bottleneck detection methods. This is probably due to the fact that until recently there was no reliable method available to follow the shifting of bottlenecks.

Literature Review

Despite this, there are many different bottleneck detection methods that use inventory levels or the closely related waiting times as an integral part of their method. Law and Kelton base their method on the average waiting time or queue length [START_REF] Law | Simulation Modeling & Analysis[END_REF]. Elmasry and Hon measure the average waiting time and average queue length [START_REF] Elmasry | Bottleneck Discovery in Large-scale Networks Based on the Expected Value of Per-hop Delay[END_REF]. Roser et. al. use the inventory level to determine the bottleneck direction [START_REF] Roser | Reliable Shop Floor Bottleneck Detection for Flow Lines through Process and Inventory Observations: The Bottleneck Walk[END_REF][START_REF] Roser | Reliable Shop Floor Bottleneck Detection for Flow Lines through Process and Inventory Observations[END_REF]. Li et. al. use the largest inventory to detect the bottleneck [START_REF] Li | Bottleneck Detection of Manufacturing Systems Using Data Driven Method[END_REF]. Lawrence and Buss look at the greatest number of waiting jobs in the queue [START_REF] Lawrence | Shifting Production Bottlenecks: Causes, Cures, and Conundrums[END_REF]. Also in industry, the inventory size is commonly used to determine bottleneck locations. Most of the above methods also include the flaw to use averages in bottleneck detection, and hence they are unable to follow shifting bottlenecks.

Logical Deduction

Using logical reasoning, it can be deduced that the commonly used hypothesis is approximately correct. Fig. 1 shows an example material flow with four processes and five inventories. If the situation shown remains stable, it can be assumed that process P3 is the bottleneck, as material is accumulating upstream of P3 and there is a lack of material downstream of P3. Yet, this is valid only for a stable system. It becomes more complex for an unstable system. Fig. 2 shows an example of an unstable system, where it is much less clear how the inventories influence the bottleneck. For easier understanding, Fig. 2. Example of unstable material flow with four processes and five inventories we narrow it down to an example of two processes with a buffer inventory with a maximum capacity of three parts. All possible inventory levels are shown in Fig. 3. It is commonly assumed that with a completely empty buffer as in a), Fig. 3. All combinations of two processes with a buffer inventory capacity of three parts the bottleneck must be upstream, and with a completely full buffer as in d), the bottleneck must be downstream. However, this is not certain. Assume in Fig. 3 a) that process P2 would normally be the bottleneck. Due to a breakdown in process P1, the buffer between P1 and P2 has emptied. Process P2 is currently still processing its last part. Despite the buffer being empty, process P2 has yet to wait on process P1. Only if P2 finishes its part, process P2 would have to wait on process P1, and P1 would definitely be the bottleneck. If the problem in P1 is fixed and P1 supplies a part before P2 needs it, P1 was not the bottleneck, despite the empty buffer.

Similar is true for Fig. 3 d) if P1 is still working on a part, and the buffer opens up one space before the part in P1 is completed and has to be added to the buffer. In both cases it cannot be said for certain if the bottleneck is upstream for a) or downstream for d) until process P2 and P1 respectively have to wait for the other process. Hence, for a completely empty buffer as in a), there is still a small chance that the bottleneck is NOT upstream. Similarly, for a completely full buffer as in d), there is still a small chance that the bottleneck is NOT downstream.

The situation becomes even more complicated for Fig. 3 b) and c). As the inventory levels are only the result of the past behavior of P1 and P2, however, it can reasonably be assumed that these inventory levels have a likely bottleneck direction between the situations a) and d). Hence, the more material an inventory contains, the more likely the bottleneck is downstream. The less material an inventory contains, the more likely the bottleneck is upstream.

Manufacturing is usually seen as handing parts downstream. However, it is equally valid to see it as handing free slots upstream. Hence, we have a symmetric behavior, and for this reason of symmetry, it can be expected that the influence by the preceding process and the succeeding process be of similar magnitude. Therefore, for an inventory level of 50%, it is equally likely that the bottleneck is upstream or downstream.

Hence, the likelihood of the bottleneck direction can be deducted as shown in Fig. 4, with the caveat that a momentary observation of a completely full inventory is not a 100% likelihood of the bottleneck being downstream, and a

Simulated System

For the experimental analysis, a simple system with two processes and one buffer inventory, as shown in Fig. 5, has been analyzed. These two processes can also stand for several processes in a system. The system has been analyzed for a buffer capacity of 10 pieces. The reason for choosing an even amount of pieces as buffer was that the filling level can be precisely 50% by having a filling level of 5 pieces. The random distribution of the cycle times has been varied both in distribution type and width to understand the bottleneck behavior for different situations. An Exponential Distribution was tested as well as two Erlang Distributions with the Standard Deviations of 10% and 100%. The benefit of all of these distributions is that at no time will they be negative. This is important for the simulated system because cycle times can never be negative. Finally, the mean cycle times have been changed so that the mean cycle time of P1 was 80% of the mean cycle time of P2. Additional simulations can be found in the underlying master's thesis [START_REF]Richtung des Engpasses in Abhängigkeit vom Füllstand eines Bestandes[END_REF]. The systems have been simulated using the commercial Simul8 software package.

The Active Period Method

The challenge is to verify the above assumptions through experiments. While the inventory level can easily be measured, the bottleneck direction is more complex, especially since we cannot use the inventory levels to avoid circular reasoning. However, the active period bottleneck detection method is able to determine the location of the bottleneck at any given time based solely on the duration a process was active without interruption [START_REF] Roser | Single Simulation Buffer Optimization[END_REF][START_REF] Roser | Tracking Shifting Bottlenecks[END_REF]. This method is highly accurate and can determine the influence of a process on the entire system with a very high degree of accuracy [START_REF] Roser | A Quantitative Comparison of Bottleneck Detection Methods in Manufacturing Systems with Particular Consideration for Shifting Bottlenecks[END_REF]. The method was also verified by independent researchers who compared this method to other bottleneck detection methods and found it to be superior [START_REF] Lima | Metodology for selecting the best suitable bottleneck detection method[END_REF].

The active period method looks at the durations a process is active without interruptions by being blocked or starved. This is called the active period. At any given time, the process with the longest active period is the bottleneck. If the longest active periods of the processes overlap, the bottleneck is shifting between the two processes as shown in Fig. 6. If there is no overlap, then the process is the sole bottleneck. This method has been used in the simulated system to determine the bottleneck for any given time. At any given time, there are three possible outcomes: The bottleneck is in the first process (P1); the bottleneck is in the second process (P2); or the bottleneck is unknown (shifting).

6 Simulation Results

Symmetric System, Exponential Distributions

The first experiment analyzed a system with a buffer capacity of 10 pieces and exponentially distributed cycle times, where the cycle times of process P1 and P2 had identical distribution. Fig. 7 shows the results of these simulations, including the confidence intervals based on multiple repetitions of the simulation and the theoretically expected perfect result as a dashed line.

Due to the occurrence of shifting bottlenecks, there is a gap between the two bottleneck directions where the direction of the bottleneck is not known because of shifting bottlenecks. Yet, these curves are symmetrical within the limits of the confidence intervals. Neither a completely empty nor a completely Fig. 7. Bottleneck location for a system with identical exponential distributed cycle times full buffer had certainty with its respective bottleneck direction. For example, a completely full buffer had an 86.4% likelihood of the downstream process being the bottleneck but also a slim but real 0.32% likelihood of the upstream process being the bottleneck. Similarly, a completely empty buffer had an 88.7% chance of an upstream bottleneck but also a 0.35% chance of a downstream bottleneck.

Symmetric System, Erlang Distributions, Standard Deviation 10%

In another experiment, the same system was tested using an Erlang distribution, where the standard deviation was 10% of the cycle time for each process. The results are shown in Fig. 8. The system behaved very symmetrically and similarly to Fig. 7. This experiment was repeated with a much higher standard deviation equal to 100% of the cycle time as shown in Fig. 9. Again, there was no practical difference from the previous results. Finally, the average cycle time of process P1 has been reduced to 80% of the previous value, and hence to 80% of P2. In effect, P1 is now much faster than P2, and P2 is much more likely to be the bottleneck. Both cycle times are still exponentially distributed. The result of this experiment is shown in Fig. 10 . Now the bottleneck locations are no longer symmetrical to the inventory levels. For example, for an inventory level of three, the bottleneck is still with a 40.0% likelihood of being downstream, and with only a 17.1% likelihood of being upstream. The theoretical ideal value is expected to be only around 30%. For any inventory level, it is much more likely that the bottleneck is in P2 than expected theoretically (Fig. 4) or analyzed for symmetrical systems experimentally (Fig. 7, 8,9).

Conclusion

We experimentally analyzed the direction of the bottleneck based on the inventory levels and compared it to the theoretically expected results. The type of distribution and the width of the standard deviation made no difference to the outcomes. For systems with (near) identical cycle times, it is valid to assume that the buffer inventory is a good indicator of the bottleneck direction.

However, if the cycle times are different, this assumption no longer holds true. As the differences between the cycle times increase, so does the likelihood of the bottleneck direction getting skewed toward the slower processes.

Naturally, having a more pronounced bottleneck downstream creates inventory levels that are more often full. If, due to random fluctuations, the inventory empties, it is much more likely to recover to its full state due to a strong downstream bottleneck than to turn empty due to a temporary upstream bottleneck. This explains the skewedness toward the strong bottleneck. Similar but symmetrical behavior occurs in case of an upstream bottleneck [START_REF]Richtung des Engpasses in Abhängigkeit vom Füllstand eines Bestandes[END_REF].

Overall, a linear relation between inventory level and bottleneck direction can be assumed only for systems with similar cycle times. The more pronounced the difference in cycle times, the less valid is this assumption. Further research is needed to analyze the relation between inventory levels and the bottleneck direction for asymmetric systems.

Fig. 1 .

 1 Fig. 1. Example of stable material flow with four processes and five inventories

Fig. 4 .

 4 Fig. 4. Theoretical likelihood of bottleneck direction based on inventory levels

Fig. 5 .

 5 Fig. 5. Experimental system

Fig. 6 .

 6 Fig. 6. Experimental system

Fig. 8 .

 8 Fig. 8. Bottleneck location for Erlang distributions with 10% standard deviation

Fig. 9 .

 9 Fig. 9. Bottleneck location for Erlang distributions with 100% standard deviation

Fig. 10 .

 10 Fig. 10. Bottleneck location for unequal cycle times with P1 at 80% of P2


Farhad Ameri

Ramin Sabbagh

Matheus Cardoso Pires
email: matheus.pires@grad.ufsc.br

Enzo Morosini Frazzon
email: enzo.frazzon@ufsc.br

Ann-Kristin Cordes
email: cordes@ercis.uni-muenster.de

Bernd Hellin- Grath
email: bernd.hellingrath@wi.uni-muenster.de

Digital Factories for Capability Modeling and Visualization

Keywords: Supply chain, Planning, Management, Integrated planning, Operations research

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

A Supply Chain (SC) can be defined as a network of organizations, flows, and processes where companies work to transform raw material in final products delivered to a customer. [START_REF] Ivanov | An Adaptive Framework for Aligning (re) Planning Ddecisions on Supply Chain Strategy, Design, Tactics, and Operations[END_REF] Presents Supply Chain Management (SCM) as the study of resources of enterprises and human decisions in relation to cross-enterprise collaboration processes to transform and use these resources in the most rational way along the entire value chain, from customers up to raw material suppliers, based on functional and structural integration, cooperation, and coordination throughout. The author classifies SCM as the most popular strategy for improving organizational competitiveness in the twenty-first century. Supply Chain planning can be seen as a set of goals, performance indicators and decisions to be taken in order to optimize the SC performance. The Supply Chain Planning comes in different levels of application, each one focusing in actions that fit its time horizon and goals. The Strategic Planning is on the top of the pyramid, and consists in long-term decision and goals, as desired service level and facilities location. In the middle of the pyramid is placed the Tactical Planning, working on midterm decisions what includes the allocation of production and transports capacities, for example. At the bottom of the pyramid, the Operational Planning takes care of the daily decisions, as transport strategies and production scheduling.

All the levels of planning are necessary in SCs planning. However, these planning are usually built without communicating with the other, in despite of the fact that the efficiency and applicability of the output of each plan can decrease if the different levels of planning are considered in isolation of each other [START_REF] Ivanov | A Multi-structural Framework for Adaptive Supply Chain Planning and Operations Control with Structure Dynamics Considerations[END_REF].

This research paper aims to develop a communication procedure between the operational planning and tactical planning of a spare parts supply chain. To reach this objective, a flowchart comprising the planning steps of each level as well as mutual feedbacks between the decision-support models will be proposed.

The paper is organized in three sections. In the Literature Review section, a brief contextualization about the state of the art of the studying will be presented, as well as a contextualization about the emerging concept of integration between spare parts supply chain and intelligent maintenance systems wherein the output of the paper is intended to be used. In the second section, the communication procedure will be proposed by means of a test case. In the last section, the results will be discussed and the work summarized.

2

Literature Review

Supply Chain Management

According to Christopher [START_REF] Christopher | Logistics and Supply Chain Management: Creating Value-added Networks[END_REF] Supply Chain Management (SCM) is the management of upstream and downstream relationships with suppliers and customers to deliver superior customer value as less cost to the supply chain as a whole. Therefore, SCM becomes an interesting object of study, widely addressed by numerous approaches, being needed in any product factoring and flow around the world. Supply Chain Management seeks to link and coordinate processes from different entities (as customers and suppliers) and to organize them [START_REF] Christopher | Logistics and Supply Chain Management: Creating Value-added Networks[END_REF]. This add an enormous level of complexity in decision making, once each action should not just consider each company limitation and goals, but all limitations and requirements from other agents present in the SC.

According to [START_REF] Narasimhan | Decision Models in Global Supply Chain Management[END_REF] considerable work has been invested in developing decision methods for overcoming supply chain issues, which generally adopt conventional approaches as mathematical programming (optimization), simulation and heuristics. These models can be very helpful since they assist managers to overcome the dimensions of the mental models for Supply Chains and provide non-biased results, helping to deal with the high complexity of considering a big number of agents, limitation, goal and variables in the system.

According to [START_REF] Ivanov | An Adaptive Framework for Aligning (re) Planning Ddecisions on Supply Chain Strategy, Design, Tactics, and Operations[END_REF] decision-supporting methods can be divided in optimization, simulation and heuristics, where the optimization has been very visible and influential for the operations management. However, there is a challenge in the optimization development that consists in developed a well detailed model that can represent the reality of the supply chain at the same time it keeps simple enough to be solved with a relative low processing cost. High computational costs could turn the planning, especially on an operational level, impracticable, since it could require too much time to be executed that its results become obsolete. Since the aggregation of both tactical and operational planning levels in a single model would probably require high computational power to be solved, the goal of the present work is to describe a procedure of communication between two models.

Spare Parts Supply Chain

Spare parts need to be available in the right place within the supply chain, to ensure the desired level of service. However, several aspects make this task complicated, such as: the high number of parts to be managed, high responsibility required due to customer downtime costs, and the risk of obsolete inventory. Among these problems, according to [START_REF] Espíndola | Integrating Intelligent Maintenance Systems and Spare Parts Supply Chain[END_REF], "due to the high costs for spare parts and their sporadic demand, keeping inventories of all parts at all warehouses in the spare parts network are not economical". Also, SCs are thus characterized by distinct, yet mutually interdependent decision domains with in-dependent business objectives. This way, the capability of existing models for supporting an intelligent and flexible synchronization and coordination of the involved process is limited. Given this intertwined and complex aspects, management processes of spare parts supply chain (SPSC) cover different areas of knowledge, which, in turn, use various resources, methods, techniques for solving coordination problems. Some features of SPSC can be highlighted in the literature. First, the demand for spare parts usually has an intermittent and/or erratic character, making more difficult the forecasting process by classical statistical methods and inventory control [START_REF] Boylan | Spare Parts Management: A Review of Forecasting Research and Extensions[END_REF]. The second characteristic relates to high levels of required services. Components for maintenance need to be available as soon as a fault occurs, otherwise the productive systems may be unavailable, causing high costs for the production facility [START_REF] Huiskonen | Maintenance Spare Parts Logistics: Special Characteristics and Strategic Choices[END_REF]. Another feature derives from the two previous characteristics, as there is a wide variation in demand and a network of well-lined stocks, distribution costs are high. In periods of low demand, inventories are still needed for high demand periods, implying more expensive distribution process [START_REF] Israel | Planejamento Operacional de Cadeias de Suprimentos de Peças de Reposição Integrado com Sistemas Inteligentes de Manutenção[END_REF].

Having seen these concepts, detailed planning of the spare parts supply chain is necessary in order to meet service levels while minimizing costs. Furthermore, not only the planning but also the coordination between different levels and actors can be seen as a relevant topic, considering the autonomy of the different actors involved in the supply chain coordination. The collaboration can be reached through exchanging relevant data from multiple individual planning domains (e.g. demand planning, master planning, production planning, etc.), aiming to design a collaborative planning concept (CP). But the applicability of existing CP approaches for coordinating the different autonomous actors in heterarchical SPSCs has not yet been investigated [START_REF] Espíndola | Integrating Intelligent Maintenance Systems and Spare Parts Supply Chain[END_REF]. The portability of CP approaches to other scenarios is still an open research issue, especially to a SPSC scenario.

Integrating Intelligent Maintenance Systems and Spare Parts Supply Chain

The Integrating Intelligent Maintenance Systems and Spare Supply Chain (I2MS2C) concept is proposed to approach the challenge of simultaneously coping with the constraints and specificities of Intelligent Maintenance Systems (IMS) and Spare Parts Supply Chain (SPSC). The primary objective of the I2MS2C is the improvement of the effectiveness and efficiency of service management operations for complex technical systems. This will be achieved by integrating information provided by embedded IMS systems with planning and coordination methods and processes in the spare parts supply chain. On the other way around, maintenance operation benefits from an improved planning of the service operation synchronizing service demands with spare parts availability and servicing capacities.

From the technological perspective, the goal is to improve IMS capabilities in order to achieve more reliable estimations of maintenance needs. The use of intelligent maintenance technology will predict future failures in components allowing the operator to react directly on the component degradation. Besides, through techniques of mixed reality integrated into an Intelligent Maintenance System, we intend to bring relevant data about the components and machines aiding thus the provision of information to operators and service personnel.

To achieve these goals, the I2MS2C concept is divided into four main elements of the model. Research on IMS will in the following be related to the first element. Here, the concept aims at developing improved spare parts planning methods integrating IMS information and the coordination of the spare parts supply chain's actors. The focus relies on the extension and development of spare part-specific mid-term forecasting and planning methods in the domain of inventory and transportation planning. The IMS used in this project is based on the Watchdog Agent (WA), developed by the IMS center [START_REF] Djurdjanovic | Watchdog Agent-an Infotronics-based Prognostics Approach for Production Performance Degradation Assessment and Prediction[END_REF].

The second element of the I2MS2C concept aims to integrate the planning domains into a supply chain-wide coordination concept which also includes tactical production and maintenance service planning methods. Methods for planning short-term decisions of the supply chain actors as well as their coordination are developed in third element. Here, the interconnections to the tactical planning layer have to be regarded. The focus relies on short-term inventory planning, transportation and production scheduling. Both layers, tactical as well as operational planning, are restricted to the improvement of pro-active supply chain planning. In other words, this means that supply chain planning not include issues of reacting upon concrete machine break-down alerts, i.e. only failure forecasts of the IMS are included. Also, the integration architecture of the overall research work was built upon a Service Oriented Architecture (SOA), and is a cloud-based system and each entity is built as a device, following the Device Profile for Web Services (DPWS) standard, and exposes a set of services.

Lastly, the fourth element of the I2MS2C concept works with solutions to integrate the results of the previously described elements and furthermore provided a simulation environment for the evaluation of the overall I2MS2C concept. Here, the challenge of integrating IMS with SPSC are analyzed using simulation-based computational experiments and is intended to be evaluated in real-world case studies. Also, in order to achieve a proof-of-concept and an evaluation of the proposed concept, regarding to necessity to align the extended/developed intra-organizational planning methods as well as the coordination process, this element deals with the integration by aligning and fixing the interfaces between the developed concepts of the other thematic areas. Finally, the last part of this area relies on the validate of I2MS2C concept applying the methods proposed in cases studies, especially from the domain of ship building and the oil industry which both show the characteristics of slow moving and expensive components.

The main contribution of the I2MS2C concept is the integration of three different sub-systems: a distributed and networked embedded diagnostic system able to assess the error degradation of machinery/equipment and forecast the need for spare parts. A distributed decision-making sub-system for spare parts supply chain planning and coordination, responsible for tactical spare parts inventory and distribution planning as well as maintenance service planning concepts. An operational planning and scheduling system that is based on the information provided by the other sub-systems optimizes the operational production, transportation and inventory processes. Therefore, two decision-support models are need for the optimization of the systems. In the present paper, a supply chain with the I2MS2C concept fully implemented will be considered as the test case, which implies great data exchange among supply chain participants and deterministic demand of spare parts for maintenance in industries as the final clients.

Communication Procedure Proposal

The study developed in this paper is based on the study of a real case of a reference company in the production and distribution of spare parts for electric actuators in Brazil, which will be described hereafter in this work. The supply chain in which the communication procedure will be based was first presented in [START_REF] Israel | Planejamento Operacional de Cadeias de Suprimentos de Peças de Reposição Integrado com Sistemas Inteligentes de Manutenção[END_REF], and consists of a simplified spare parts supply chain having a production facility that produces three types of products and has to attend, as final destination, the five biggest markets. The final clients of this supply chain are industries that buy these products as spare parts for maintenance on their production machines. In this supply chain, intelligent maintenance systems are used, that makes the demand visible for each one of the fifteen following days. The supply chain scheme is represented in Figure 1. The communication procedure is shown on Figure 2 and it was modeled base on the model proposed in [START_REF] Ivanov | Applicability of Optimal Control Theory to Adaptive Supply Chain Planning and Scheduling[END_REF]. In the first step, the tactical optimization model is solved, using as input the predefined service level (defined in a previous strategic plan), minimum and maximum capacities per transportation mode and the demand per region (deterministic in this case). As outcome, the support-decision model will provide the inventory level desired per item per facility location, the service level in each region, the transport capacities required per transport mode and region, the emergency shipments capacities per region, the service personnel capacities required per service center and the production capacities required per item. Based on this outputs, tactical strategies will be studied and implemented in order to attend the settled goals. An analysis of the result of the plan shall be done to verify its feasibility and applicability. Otherwise, a feedback shall be given to the model to implement an internal adaptation and the model solved again. Then, the results of the tactical model will be used as boundaries and limitations for the operational planning. The operational plan will consider the allocated capacities and demands and will optimize the scheduling of the production and distribution throughout the supply chain on a daily basis. The results must be analyzed, and in case of unfeasibility or improvement opportunity, the feedback must be given to the model for an internal adaptation and the planning process re-executed. Otherwise, the result can be used to feedback the tactical plan, to verify its feasibility. If the operational plan is unfeasible, the desired standards are too high, and the boundaries given by the plan are too demanding to be achieved, and the tactical plan must be reviewed. Otherwise, the plan must be executed, and the supply chain monitored in other to verify if the results of the plans are being achieved. Otherwise, a feedback must be given to the decision-support models, to implement an external adaptation. The communication procedure is guided to synchronize the execution of two mixed-integer linear problem (MILP) models developed in order to manage the already introduced spare parts supply chain. Summarizing, the tactical decision-support model will provided the objectives to be reach by the operational level, which will be executed and analyzed its feasibility by simulation in order to forecast the behavior of the results implemented with stochastic characteristics. The last result will feedback the tactical planning. When both plans converge, the output can be implemented on the real case, which will be also analyzed in order to feedback both support-decision models.

Conclusion

In the present work it was elucidated the importance and necessity of decision-support models in decision taking in supply chains. These models are designed in three different levels of wideness. These models generally do not consider the other levels decision, concluding that there is a lack in today's approaches concerning in communication between planning levels. The work also introduces the concept about integrating intelligent maintenance systems and spare parts supply chain. A concept that can be shortly summarized being the use of electronic sensors in order to predict spare parts demands in industries combined with mathematical optimization models, both for tactical and operational levels, in order to provide lower costs on the supply chain while delivering higher service level.

It was, as main objective of the paper, proposed a communication procedure between tactical and operational support-decision models in order to align different levels of planning. The procedure is recommended because no alignment between planning levels can reduce the efficiency and feasibility of the outcome plan, as well as a unique plan for more than one level could result in high computational cost. Using this procedure, it is possible to use more detailed optimization models in each planning level. As future work directions it is recommended to develop support-decision models for each level in order to run a test application of the communication procedure. As well as an in-depth study about the possibility of including the strategic level in the procedure.

Fig. 1 .

 1 Fig. 1. Supply Chain Structure from a Spare Parts Supply Chain (Source: [8]) .

Fig. 2 .

 2 Fig. 2. Proposed communication procedure between tactical and operational decision-support models. (Source: author)

Acknowledgements This research was supported by the German Research Foundation (DFG) and the Brazilian Federal Agency for the Support and Evaluation of Graduate Education (CAPES) as part of the BRAGECRIM project "Integrating Intelligent Maintenance Systems and Spare Parts Supply Chains (I2MS2C)" (BRAGECRIM 022/2012).


Simone Beux
email: beuxsimone@gmail.com

Arcione Viagi

Roberto Panizzolo

Martino Cassandro

Food Supply Chain -Sustainability in Small Milk Industry

Keywords: Sustainability, Production, Milk, Supply Chain

Farming is very important for the development of a country economy and, in Brazil, cattle (meat and milk) is one of the most important sectors of this segment. This paper aims to develop a conceptual framework to identify the key characteristics of the Short Food Supply Chain and, moreover, propose a model for the implementation of sustainability in the sector of small milk producers and dairy products. The research presents data from small producers located in Paraná, Brazil and utilizes the better condition of Italian producers in the Veneto region as a benchmarking to identify opportunities for improvement by adopting the concept of Short Food Supply Chain. The conclusion of the analysis showed that there are significant gains for small farmers with the adoption of the proposed model because it solves several issues that currently hinder the development of the sector.

Introduction

Brazil is among the largest producers of milk in the world, ranks sixth, according to data from the United States Department of Agriculture in the year 2014. It produced 35.2 billion liters, increased by 2.7% compared to 2013 [START_REF]IBGE: Projeção da População do Brasil por Sexo e Idade para o Período 2000/2060[END_REF]. Milk production in the country is growing, but the challenge will be hard in the coming years in relation to: adequate food for the herds in terms of quantity and quality, improving product quality indicators, business management for efficient use of resources and improving competitiveness for the world market competition. Another major challenge is to resolve issues such as low professionalization of the sector; it is characterized by many small and medium producers in a state of insolvency.

According to data from the last Census of Agriculture in 2006, it was observed that most producers have low production and they are responsible for the majority of national production (80% of farmers produce up to 50 liters/day and account for 26% of Brazil's milk production). In Paraná, 55.3% of farmers produce up to 50 liters/day, representing 14.7% of total production of the state, about 60% of Paraná's production comes from small family farms. For these reasons, the Federal University of Technology-Paraná (Brazil) and University of Padova (Italy), has ongoing projects to technology transfer to improve the performance of producers of milk and dairy products.

The objective of this work is to propose a management model for the supply chain of small farmers and assess their applicability in Brazil. The work has exploratory approach, using case study and benchmarking, with data obtained from available literature and collected through qualitative research with small farmers in the state of Paraná.

This paper is organized into four sections: Section 2 presents the theoretical framework, Section 3 analyze State of Paraná situation and describe the proposed model, and Sections 4 draws the conclusions followed by the references.

Theoretical Framework

Sustainability in Food Industry

The concern with sustainability is recent (1980) and defines which companies are part of a whole and their activities generate impacts throughout society, so they should get reasonable economic results without destroying nature or creates problems for society today and in the future [START_REF] Azapagic | Indicators of Sustainable Development for Industry[END_REF]. In the 1990s, the proposed balance received the designation of triple bottom line (Fig. 1) and advocated that sustainability is achieved when there is a balance between value creation, environmental responsibility and social responsibility [START_REF] Azapagic | Indicators of Sustainable Development for Industry[END_REF][START_REF] Foran | Integrating Sustainable Chain Management with Triple Bottom Line Accounting[END_REF][START_REF] Gimenez | Sustainable Operations: Their Impact on the Triple Bottom Line[END_REF]. The approach for this paper in terms of sustainability is to develop actions that improve the management of small producer of milk and dairy products and increase their profitability.

Supply Chain Management in Food Industry

Growing competition and higher consumer expectations have forced companies to seek alternative forms of management in order to reduce costs and increase the quality and availability of products. As a result of this trend, Supply Chain Management (SCM) has been adopted in order to improve the efficiency of operations through increased collaboration between trading partners and greater proximity to customers [START_REF] Rong | An Optimization Approach for Managing Fresh Food Quality Throughout the Supply Chain[END_REF][START_REF] Vorst | Agro-industrial Supply Chain Management: Concepts and Applications[END_REF]. For the adoption of SCM two major problems have been arisen: the first concerns the need for traceability (Fig. 2) of products due to increased consumer attention for safe and animal-friendly production methods, such as the origin and production techniques used. The second is related to the aspect of providing more speed to the process, reducing losses due to food and agricultural products shelf life constraints, therefore alternatives are: to reduce product crossing time in the agrifood chain or to use preserving agent in order to increase products life. This solution has been questioned and rejected by the most demanding consumers [START_REF] D'alessio | Filiera Latiero-casearia: Caratteri Strutturali e Andamenti Congiunturali[END_REF]. The SCM enables the production and the deliv-Fig. 2. Supply chain network and specific [START_REF] Vorst | Agro-industrial Supply Chain Management: Concepts and Applications[END_REF] ery of food products at competitive prices in all parts of the planet. In a Food Supply Chain (FSC) several companies collaborate strategically in more than one area without losing their own identity and autonomy. In general, the quality assurance of products in the agrifood chain depends on integration, awareness and collaboration of participants in the supply chain because misconduct can compromise the result of all the others [START_REF] Rong | An Optimization Approach for Managing Fresh Food Quality Throughout the Supply Chain[END_REF]. The focus has been produce with sustainable methods and processes, quality products and offers them in the consumption places, at the right time to meet consumer expectations. However, this represents a problem for small producers who not have production volume or financial capacity to be representative in this new competitive regional, national and global market.

Because of the difficulties faced by small producers and their importance in the overall context of the economy, there are a number of actions in several countries, aimed to provide viable alternatives for strengthening the small farmers. One of them is the Short Food Supply Chain (SFSC), (Fig. 3), initially created for the purpose of achieving goals of "sustainable agriculture" by reducing transport costs and, hence, CO 2 emissions and promoting biodiversity by strengthening periurban agriculture.

Currently, interest in this alternative has grown and has been incorporated into the Europe Union (EU) scope and has encouraged states members to use this concept in the local markets to strengthen them. Moreover, the EU has considered the key role of small farmers in the food supply chain and provides a credit line to finance projects aimed at the participation of farmers to a "struc-tured" short food supply chain, where quality products are linked to territory [START_REF] Canfora | Is the Short Food Supply Chain an Efficient Solution for Sustainability in Food Market?[END_REF]. The SFSC can be structured in two basic ways always focusing on marketing in the local market or region, ensuring the reduction of transport costs. The first is the vertical integration of a producer and the second is the integration of various agricultural producers, located within walking distance that can process the products and distribute them in the local market or region.

Food Supply Chain in Italy

Italy has a great tradition in the production of dairy products and, therefore, this activity receives great attention from public and private agencies: largest usage of milk is to cheese making [START_REF] Cassandro | Comparing Local and Cosmopolitan Cattle Breeds on Added Values for Milk and Cheese Production and their Predicted Methane Emissions[END_REF]. Cheeses have one of the greatest values in milk chain, which contributes to the strengthening of the sector in the country.

Even with the strong dairy chain with several positive points, between the small Italian producers, the operating current form is the vertical integration (multifunctional diversification), the milk processing is performed by the producer and marketing through direct sale, in a process known as "short-chain"; it has a direct influence on many weaknesses listed because it strengthens local production and supply chain management (Figure 4). The economic crisis and the growing desire of consumers for fresh and healthy products had boosted the interest and adoption of the concept of "short chains" in Italy and in the European Union as a whole. In fact, the need to support producer organizations and direct sales, to strengthen the activity, led to one of the objectives of the new Common Agricultural Policy (CAP) [START_REF] De Fazio | Agriculture and Sustainability of the Welfare: The Role of the Short Supply Chain[END_REF].

The creation and ongoing operation of SFSC proved to be a highly effective model because farmers or distributors can add value to rural activity by encouraging the production and consumption in the local market. Also, in order to promote local agriculture, the European Union (EU) approved a rule which provides farmers can make the labeling of products for direct sale [START_REF] Canfora | Is the Short Food Supply Chain an Efficient Solution for Sustainability in Food Market?[END_REF]. The young farmers with higher education have better understanding of this market trend, and they recognize that the consumers prefer to buy regional products due to growing concerns about safety and nutrition of food. Another important initiative is the denomination Small Local Production (SLP) by the "Regional Veneto Council" for the recognition of traditions value [START_REF] Morgan | Worlds of Food: Place, Power, and Provenance in the Food Chain. Oxford geographical and environmental studies[END_REF]. The Brazilian reality is different; the small producers are struggling to maintain activity, because they have no bargaining power with dairies and distributors.

In the recent years, public policies stimulate an increasing of milk production and influence the improvement of milk quality, ensuring the standardization of products according to the demand, especially in the dairy industry. But many farmers cannot meet the required standards [START_REF] Schmitz | A Produção de Leite na Agricultura Familiar do Sudoeste do Paraná e a Participação das Mulheres no Processo Produtivo[END_REF], the worst consequence of this situation is that many farmers become bankrupt or they cannot influence the descendants to continue the activity, creating a rural exodus. One of the strong points in Italy is that farmers have high knowledge of management, technology and genetics while in Brazil, mainly in small properties, there is a deficiency in these areas, resulting in low productivity of herd.

In Brazil, the average production is 950 kg/cow/year versus 5.579 kg/cow/year in Italy and in state of Paraná, in 2013 milk, production was 2.533kg/cow/year [START_REF] Deral | Analise da Conjuntura Agropecuária[END_REF][START_REF] Júnior | Evolução da Produção de Leite no Brasil[END_REF].The strengthening of the Italian chain is also associated with typical products, as well as high supply of products with Protected Geographical Identification (PGI) and Protected Designation of Origin (PDO). A survey in Europe showed that more than 50% of consumers recognize the certifications and willing to pay between 10% and 30% more [START_REF] Kakuta | Indicações Geográficas: Guia de Respostas[END_REF], in Brazil it is necessary to consolidate and enhance product with these concepts.

Other problems are these collection system due to the distance of the property and aggravated due to the precariousness of the roads [START_REF] Paixão | Carretagem de Leite a Granel: Um Estudo de Caso[END_REF][START_REF] Zoccal | Modelo Ideal para Produção de Leite no Brasil[END_REF] and small number of laboratories accredited in Paraná, about 18 laboratories [START_REF] Inmetro | Inmetro -Consulta ao Catálogo da RBLE[END_REF]. In Italy, considering only the region of Veneto, which has less than 10% of Paraná size, there are 61 laboratories. Regarding the hygienic-sanitary quality, the Brazil-ian normative requires quality standard, but without presenting alternatives to solve the problems, it results in a greater impact on small producers. An alternative to the small farmer is the agribusiness with production of cheeses, yoghurts and others dairy products, adding value to raw materials and providing relative autonomy, however, these several factors hinder this initiative. In this context, after reviewing the data on the current conditions of small farmers agricultural and compare with data considered as benchmark in the industry, it became clear that the evolution of the recent years does not eliminate the gaps between policies and effective practices to ensure the sustainability of Brazilian agribusiness. Figure 5 shows the strengths and weaknesses identified in the exploratory survey answered by farmers in the southwestern state of Paraná region in conjunction with information obtained from related industry literature review. As can be seen, it is already evident big difference in terms of strengths and weaknesses, demonstrating that a few factors have been crucial in maintaining the sector's competitiveness. However, according to Cassandro [START_REF] Cassandro | Sustainable Milk Production in Different Dairy Cattle Systems and Valorisation of Environmental Chain on the Basis of Added Value[END_REF] the add value (AV) for cheese in the southwest of Paraná is satisfying, the production cost (per liter) of milk is around $0.207 and the value of cheese produced is $0.443, with these values AV generated is positive, $0.235, this demonstrates a good opportunity for producers. 6 shows the steps to implementation SFSC in the approved and promoted manner by the EU and observed operating in Italy. The proposed change is not easy and requires the assessment of priorities before you start it, because the distrust of the entrepreneur disturbs the identification of potential business partners. In Italy, the economic crisis and the lack of jobs for young people have generated the return of many to the agricultural activities of the family. They return with training and willingness to take an innovative approach and this has been a success factor and facilitator for the implementation of some public policies to encourage the creation of local SFSC. The activities to structure a SFSC are: Choosing the right business partners; Make a logistic map, role of each player and the flow of market information; Define the capacity and bottlenecks; Define service model (push or pull); Define the joint logistics to support the process; Implement an information system and Define how the profits will be shared. As in Italy it is possible applied this systems for small producers in Paraná, and create a structured of the milk SFSC as a sustainable alternative for them.

Conclusions and Outlook

This work confirmed the problems identified in the literature review as the situation of the Brazilian milk production and the State of Paraná and identified other factors that have contributed negatively to the development of rural family farms in milk production and dairy products sector. It was found that there were significant structural problems whose solution will not be achieved in the short term; in this sense the SFSC for dairy chain can represent a viable alternative for sustainability of small and medium milk producers.

The growing concern about the future of small farmers and the alternatives to become more competitive are considered important to motivate them to accept the proposal. To enable the pilot deployment, the team should be composed of universities (researchers), rural service, trade associations, and industry regulators to give agility, support and structuring. Since this work is just an early effort in the pursuit of competitive advantages for small farmers, new scientific studies could open new opportunities of application of the model through process simulations and case studies.

Fig. 1 .

 1 Fig.1. Triple Bottom Line[START_REF] Azapagic | Indicators of Sustainable Development for Industry[END_REF]

Fig. 3 .

 3 Fig. 3. Single and Multiple players SFSC

Fig. 4 .

 4 Fig.4. Strong and weak points of the phase[START_REF] D'alessio | Filiera Latiero-casearia: Caratteri Strutturali e Andamenti Congiunturali[END_REF]

Fig. 5 .

 5 Fig. 5. Strong and weak points: Agriculture, Industry and Product/Supply Chain

Figure

  Figure6shows the steps to implementation SFSC in the approved and promoted manner by the EU and observed operating in Italy. The proposed change is not easy and requires the assessment of priorities before you start it, because the distrust of the entrepreneur disturbs the identification of potential business partners. In Italy, the economic crisis and the lack of jobs for young people have generated the return of many to the agricultural activities of the family. They return with training and willingness to take an innovative approach and this

Fig. 6 .

 6 Fig. 6. Main Steps to Implement SFSC


Heidi Dreyer
email: heidi.c.dreyer@ntnu.no

Iskra Dukovska-Popovska

Kasper Kiil

Riikka Kaipia

Retail Tactical Planning: An Aligned Process?

Keywords: Grocery retailing, Planning processes, Tactical planning

This paper addresses tactical planning in retailing through a case study approach in one grocery retailing company. The issues are how tactical planning is conducted and how the different plans are connected. The study complements earlier retail planning studies by showing the sequence of planning phases and by studying the fragmented plans as a process. The master category planning is important and sets borders for the other planning phases. This stabilizes overall planning. However, the retailer loses responsiveness to demand. The study proposes better integration among planning phases.

Introduction

Efficient supply and demand planning is an appropriate solution to ensure product availability in stores at lower costs [START_REF] Kuhn | Integrative Retail Logistics: An Exploratory Study[END_REF][START_REF] Ettouzani | Examining Retail on Shelf Availability[END_REF]. Retailers fix some important variables, such as store product segmentation, category management, planograms and delivery patterns and replenishment lead times, at a tactical level and pass the decisions to the execution level as parameters [START_REF] Kuhn | Integrative Retail Logistics: An Exploratory Study[END_REF]. How the different tactical planning issues affect the retail operations (stores, transportation and distribution) and responds to demand has been treated to a limited extent [START_REF] Kuhn | Integrative Retail Logistics: An Exploratory Study[END_REF][START_REF] Ettouzani | Examining Retail on Shelf Availability[END_REF]. Even though the basic structure of a coordinated planning framework in the grocery retail industry has been proposed [START_REF] Hübner | Demand and Supply Chain Planning in Grocery Retail[END_REF], the interdependency of the planning decisions requires a good balance between individual planning processes and supply and demand management. The need for more integrative retail logistics and collaborative planning has been identified [START_REF] Hübner | Demand and Supply Chain Planning in Grocery Retail[END_REF][START_REF] Kuhn | Integrative Retail Logistics: An Exploratory Study[END_REF]. This study addresses tactical planning processes in retailing. In particular, the purpose is to analyse the planning processes and their aim, and to what extent these are integrated to serve the need for alignment and demand responsiveness. Consequently, the research questions are: [START_REF] Agrawal | Supply Chain Planning Processes for Two Major Retailers[END_REF] How is tactical planning conducted at a retail company? [START_REF] Chopra | Supply Chain Management: Strategy, Planning and Operation[END_REF] How are the different plans connected and interact?

2

Literature on Retail Planning

The main objective of mid-term, aggregated supply chain (SC) planning is to build a plan that satisfies demand while maximizing profit [START_REF] Chopra | Supply Chain Management: Strategy, Planning and Operation[END_REF] in a timely manner. Mid-term planning often covers multiple SC stages [START_REF] Kreipl | Planning and Scheduling in Supply Chains: Overview on Issues in Practice[END_REF][START_REF] Fleischmann | Advanced Planning[END_REF] is based on aggregate demands for entire product families and covers a medium-term horizon. Creating such a collaborative plan could be challenging since different functions may achieve profitability in conflicting ways. Coordination between stages and functions becomes the core element in SC mid-term planning.

Retail operations and SC management in the retailing context have been largely studied [START_REF] Fernie | Retail Logistics in The UK: Past, Present and Future[END_REF]. Most studies focus on some aspect of planning, like delivery patterns [START_REF] Kuhn | Integrative Retail Logistics: An Exploratory Study[END_REF], in-store operations [START_REF] Van Donselaar | Ordering Behavior in Retail Stores and Implications for Automated Replenishment[END_REF], retail store replenishments or reducing waste in fresh food SCs [START_REF] Kaipia | Creating Sustainable Fresh Food Supply Chains[END_REF]. An overall understanding or syntheses of retail planning are rarely presented, with an exception being the grocery retail planning framework by [START_REF] Hübner | Demand and Supply Chain Planning in Grocery Retail[END_REF]. Mid-term planning comprises several planning phases conducted by and related to one or more functions. First, mid-term planning deals with category and product-related aspects that are grouped as product segmentation and allocation (covering issues related to procurement, warehousing and distribution) and master category planning, related to sales. Second, mid-term planning covers plans for managing the product flow (inbound planning, production planning and distribution planning) and in-store planning, including capacity and personnel planning. Agrawal and Smith (2009) [START_REF] Agrawal | Supply Chain Planning Processes for Two Major Retailers[END_REF] describe a more process-oriented SC planning framework at a (furniture) retailer covering the planning steps, their succession and interrelation. Based on combining the two SC planning overviews, the different planning activities are discussed below. Following the planning process design [START_REF] Kjellsdotter | Contingency Between S&OP Design and Planning Environment[END_REF], we identified, based on theory, design parameters (planning horizon and aggregation level), inputs, outputs, objectives and functions involved in each planning phase.

In grocery retail, selection of vendors is more a strategic decision [START_REF] Hübner | Demand and Supply Chain Planning in Grocery Retail[END_REF]. For products that are carried over multiple seasons, contracts may allow for modifications in order quantities within certain ranges, depending on the observed demand for the product. In addition, retailers can evaluate vendors based on past performance and can be involved in the vendors' production planning more actively or by sharing forecasts and placing purchase orders [START_REF] Agrawal | Supply Chain Planning Processes for Two Major Retailers[END_REF].

The planning of product logistics deals with coordination of flow of products from suppliers to warehousing and to retail stores. These decisions are made on different planning objects, product-specific and product segment-specific decisions. For inbound logistics, the following planning issues are done at different levels of aggregation: supplier-specific level (related to product ordering) and supplier-segment level (related to transportation issues). Distribution planning deals with decisions to fulfill customer service targets at minimum costs as a trade-off between inventory management policies for each store and delivery policies from the central warehouse. As in inbound planning, the decisions are done at different aggregation levels, some are store (concept) related and others focus on delivery regions.

To summarize, master category planning and sourcing are driven more by the demand and product segmentation and allocation are aimed at balancing demand and supply (and are performed by including several functions); the other mid-term planning decisions are aimed at ensuring supply is driven by lowering costs.

Methodology

The aim of the study is to understand the tactical planning processes in grocery retailing. The methodology we chose is a single exploratory case study since this allowed us to gain the needed in-depth insight into the planning process and to enable us to study the planning process in its natural environment [START_REF] Eisenhardt | Building Theories from Case Study Research[END_REF]. A single case was selected in the grocery sector because of the novel nature of the retail planning process and the wide product range and the mix of product types (fresh, frozen and dry food), which make it relevant from a planning perspective. Data were collected in two steps. First, site visits and workshops focusing on describing processes and operations, and observations at warehouses and stores were the main means to understand the planning environment. Second, the data about the tactical planning process were collected in structured interviews following a case study protocol [START_REF] Yin | Case Study Research[END_REF]. The protocol was designed to cover four topics: the objective and content of the tactical planning process, the structure of the planning processes, planning interconnectedness and performance.

The interviews took place at three levels: retail chain, procurement and suppliers and logistics and it involved key managers with responsibility for tactical planning. The field notes from the interviews were converted to a description of the tactical planning and structured according to the literature in section 2. We asked the key interviewees to review the case description to ensure its validity [START_REF] Yin | Case Study Research[END_REF].

Results

The case is a Nordic grocery retailer offering a full-range grocery assortment. The organization is structured into three main functions: retail chain (stores), procurement and assortment, and logistics. Altogether, the retailer runs hundreds of stores divided in different store concepts ranging from discount stores and supermarkets to premium stores. Centralised planning tasks include the development of the different store concepts, their assortments, marketing, sales and promotions and various purchasing and supplier network decisions. Managing the logistics consists of the inbound logistics from suppliers to the warehouses, warehouse operations and outbound logistics to the stores. The main physical operations are the pick-and-pack process at the warehouses together with inbound and outbound transport. All the stores are supplied from the central warehouse, regional warehouses or a combination of the two.

Figure 2 illustrates the tactical planning process, while Table 1 includes a more detailed description of each activity. The tactical planning process takes place at all three functions (Figure 2), but contrary to what is illustrated in the framework presented by [START_REF] Hübner | Demand and Supply Chain Planning in Grocery Retail[END_REF], the process begins at the retail chain. The tactical planning process can be described as follows: [START_REF] Agrawal | Supply Chain Planning Processes for Two Major Retailers[END_REF] The retail chain decides the main profile of the chain concept and the product categories (category, profile, depth, price, etc.) and promotions for each concept. The decisions are made at an aggregated level covering a time horizon of 12 months, with two main objectives: revenue and profit per chain concept. (2) This plan is afterwards disaggregated into specific products, volumes and time periods for the promotions. (3) Additionally, the specifications of each profile act as an input to the procurement and assortment function, which disaggregates the master category plan into specific products and suppliers while (4) negotiating and making the final contract with the suppliers. The suppliers' contracts regulate the terms and conditions for the purchase and deliveries (price and discounts, volume, frequency, promotions, packaging size) for a 12-month period, while the planograms for each store or store concept are updated every 4 months. Planograms define where specific products are placed on shelves and the stock level. ( 5) Based on the volumes specified in the contracts and the expected sales in each area (can be derived from the sizes of the shelf in the planograms), the inventory structure is decided upon. This may be adjusted during the year. Hereafter, [START_REF] Fleischmann | Advanced Planning[END_REF] to ease inventory management decisions, all products are divided into different logistical product groups, which should share the same service level before [START_REF] Hübner | Demand and Supply Chain Planning in Grocery Retail[END_REF] the final inventory policy and delivery plan is finalized. By grouping the suppliers into smaller regions, the inventory and delivery plan specifies when and how much to collect from each supplier. Lastly, the plan for outbound deliveries from warehouse to stores is made on two hierarchical levels, also with a varying time horizon. Based on the profile of each concept or the store revenue and the inventory structure, (8) guidelines are provided for the number of weekly deliveries for three high-level product groups: a) frozen/dry/fresh food, b) fruits and vegetables and c) products from the central warehouse. Large stores get more frequent deliveries than smaller stores. Finally, (9) the individual routes from the warehouse to the stores are calculated by balancing the delivery plan with the utilization of each truck. Figure 2 shows that planning is top-down oriented by starting at an aggregated level and letting the aggregated decisions be the premises for lower level planning. We observed two layers in the tactical planning: one that focuses on a 12 months horizon and is aggregated (store concept and product category) and the second that focuses on product family and individual products and has a 4-month time horizon.

The planning is functional, and the output from one function acts as the input and sets the premises for the next function. Limited feedback loops and interaction between the planning steps are apparent. At the tactical level, there is no joint planning team that joins and coordinates the main planning areas to integrate and align between the functional plans. However, the company does apply different types of meetings to discuss cross-functional issues between the plans.

For each tactical plan there are objectives that serve the aim of the function. Revenue and profit are the objectives of the retail chain, and logistics is measured according to the cost and service level. At this level there do not appear to be any cross-functional objectives that align the SC.

Logistics planning is done under the constraints set in former planning steps, and the aim for logistics is to focus on cost and delivery service to stores given the assortment decided on. Similarly, the stores operate on decisions made by the retail chain and procurement and assortment.

Discussion

Content and sequence in a tactical planning process. Planning in the case company has several of the characteristics described in the literature. We observed the functional structure of the planning described by [START_REF] Hübner | Demand and Supply Chain Planning in Grocery Retail[END_REF], but we also found the planning was process oriented, including different steps and sequences as [START_REF] Agrawal | Supply Chain Planning Processes for Two Major Retailers[END_REF] describe. The planning in the case company started in the retail chain, which decided the master plan for the chain and assortment concept, followed by the assortment and sourcing decisions before logistics decided how and when to move products. Additionally, decisions taken on a higher level is the input from lower planning levels, the planning follows a sequence and is repeated every 4 or 12 months. The initial planning phases seem to be driven by demand management objectives [START_REF] Chopra | Supply Chain Management: Strategy, Planning and Operation[END_REF], while the later phases are driven by supply management. The start of the planning process is the master category, store profile and sales and promotion decisions, which set important premises for the rest of the planning. The retailer obeys the practice presented by [START_REF] Kuhn | Integrative Retail Logistics: An Exploratory Study[END_REF] as it fixes some important variables, such as store product segmentation, category management, space management and planograms and delivery patterns and replenishment lead times, on a tactical level and passes the decisions down to the execution level as parameters. The next planning step also focuses on demand management decisions as procurement and assortment decides on the products and suppliers. When logistics is brought into the planning process, then supply management aspects are brought into the planning, e.g. inbound and outbound logistics and transportation and warehouse capacity. The planning process makes the planning inert since the outcome of the higher level planning is fixed for a long time horizon (12 months) and it is top-down oriented. This makes the planning more predictive and less sensitive to disturbance and market changes and makes it easier to focus on resource utilization and efficiency. However,this makes the planning less dynamic and adjustable to the actual demand situation. Long-term assortment planning and promotion planning (12 months) actually stabilise the planning, and other plans are adjusted.

5Interplay between organizational functions. Constraints are decided by the objectives of the retail chain and procurement and assortment function, and the main role of logistics is to make a plan that optimizes cost and service level. The 'what' decisions are managed by the retail chain and assortment and procurement, leaving the 'when' and 'how much' decisions of warehouse, transport capacity and delivery frequency to the inbound and outbound logistics planning. The store profile and assortment planning constrains the following planning phases to an extent that the other plans keep the role of implementing the plan.

The overall tactical planning process is fragmented as it consists of a set of sequential plans that are only loosely integrated. First, coordination is done when needed and there is no common arena for integrating all the functions that are involved in the process in order to have consensus in the planning. When planning is done in quite separated loops that serve different demands, they can easily end up in sub-optimising. Second, the planning objectives are different in the main planning functions; some obey commercial objectives, revenue and profit, and others cost and service level. The planning is driven by several goals, but it remains unclear how the planning quality is defined and measured.

Some improvement proposals emerged. First, the different plans can be better coordinated and integrated in general. Second, there need to be efficient feedback loops from implementing the plan to tactical planning. This is essential for keeping the plan responsive to demand and achieving alignment. The company needs to have a practice to update the plan between planning rounds if needed. Third, the whole process, particularly the operational part, could benefit from adopting more formal practices. Instead of the reactive way of operating, with ad hoc meetings and fire fighting, the company could operate in a more proactive manner. Furthermore, we suggest that differentiated planning [START_REF] Kaipia | Selecting The Right Planning Approach for a Product[END_REF] can be realised to some extent.

Concluding Remarks

The operating environment of retail business increases competitive pressure because of multichannel operations, global sourcing and increasing number of product variants.

To survive in this competitive environment, retailers need to ensure product availability at stores and at the same time operate efficiently. Our study examines how a retail company has implemented these challenges in its planning solution.

The case company uses a solution for defining retail store assortments for a long period of time and ensuring the supply of products by supplier agreements. This prac-tice stabilises the planning and sets targets for the operations. The downside of the practice is the low level of demand responsiveness. In this paper we suggest that the company, if better demand responsiveness is desired, could realise formal feedback loops from operations to assortment planning. This would allow adjusting the assortment. This could be applied when planning the next 4-month assortment but also between the planning rounds. The company could also benefit from more formal planning practices and integration mechanisms in realising integrated planning.

This study reports initial results from an on-going research project concerning one retail company. The next steps are to collect more data, particularly on outbound logistics and store planning in order to look deeper into demand responsiveness.

8.

Reference

Fig. 1 .

 1 Fig. 1. Grocery retail planning framework at the mid-term level [8] (modified).

Fig. 2 .

 2 Fig. 2. The sequence of tactical planning phases in the case company.

Table 1 .

 1 Description of planning process

	Activity	Aggr. / Horizon	Input	Output	Objectives	Functions
	(1) Category and	Store concept	Limited restrictions	Profile of each concept, including	Profit	Retail Chain
	promotion plan	Product family		price range and promotions	Revenue
	(2) Detailed sales	4 months	Input from master	Specify products	Revenue	Retail Chain
	and promotion	Product level	category planning	-Volume, time and period	Profit
	plan	Concept	Demand forecast or	-Price/promotion per product/concept	Waste
			similar promotions	-Input to inbound logistics call-offs
	(3) Assortment	4 months	Profile of the concept	-Specify products		Procurement
	and planograms	Product level		-Shelf allocation (planograms)		Spacing
		Store/concept level
	(4) Contracts	12 months	Assortment	Supplier contract (yearly volumes,		Procurement
		Product/family		delivery frequency, discounts)
	(5) Inventory	12 months/Trigged	Warehouse capacity,	Storage/location plan (where to locate	Warehouse	Logistics
	structure	by season/as needed	Store demand, Seasons,	each product)	capacity
		Product level	Locations of suppliers
	(6) Grouping of	4-12 months	Planograms	Allocation of individual products into		Logistics,
	products	Product level		A,B,C,D,E categories for planning		Procurement
				decisions-service level
	(7) Inventory	4-12 months	Product shelf life	Quantity	Service level	Logistics
	policy and	Product/Category	Balancing transportation	Time/frequency	Warehouse waste
	delivery plan	level	cost and inventory cost	Safety stock	Tied-up capital
			Demand uncertainty	Grouping suppliers into regions and
			Discounts	delivery frequency
	(8) Delivery plan 12 months	Profile of the	Delivery structure for stores	Service level	Logistics
		High product family	concept/Store revenue	-Delivery frequency	Waste & cost
		level	Inventory structure	-Delivery time	Dry, Inv. turnover
					max 12 days
	(9) Route plan	4 -12 months	Delivery plan	Routes for deliveries to stores		Logistics
		Store level	Size of trucks