Supply chain challenges of North-European paper industry

The Authors

Pekka Koskinen, Oy Confidea Business Consulting Ltd, Espoo, Finland

Olli-Pekka Hilmola, Kouvola Research Unit, Lappeenranta University of Technology, Lappeenranta, Finland

Abstract

Purpose – Owing to the consolidation and globalization of the paper industry, manufacturing units have keen interest to focus on particular product groups. While this specialization will create opportunities for scale economics in production, management of supply chains becomes increasingly challenging, as one particular manufacturing unit serves a number of different sales locations. The aim of this paper is to identify improvement areas in the new supply chain context of paper production, and possibly give further support for the general discipline development.

Design/methodology/approach – Research work is based on two different case studies completed for one major North-European paper manufacturer, which is mostly serving its customers in Europe and the USA. The first case study (a preliminary one) started when supply chain challenges were recognized at the end of the 1990s, and a manufacturing unit was seeking managerial remedies – this investigation only concerned one manufacturing unit, while not singling cut any particular supply chain in the analysis. During the most recent years a more detailed case-study was conducted with this paper manufacturer, which concerned lead time performance of four different strategically important supply chains. These supply chains were championed by two different large manufacturing units (the preliminary analysis concerned one of these two paper mills). The objective of this research work is to identify whether general lead time and response studies, mostly completed in the automotive industry, are applicable to paper production.

Findings – According to the analysis North-European paper manufacturers hold approximately 45 days of distribution inventory. Interestingly, in the case study it was found that in distribution this does not result in high efficiency–on the contrary different parties involved (railway, port operations and vessels) need to have a considerable amount of free and unused capacity in their operations to ensure the smooth flow of materials.

Research limitations/implications – The case studies were conducted in the factories of one large North-European multinational. Therefore, the observations are limited to this company. However, in order to generalize the results further, the authors have analysed North-European paper producers through macro data and financial reports in any research environment. To cover a mismatch between company level quantitative analysis and macro data, the authors consulted several key persons in the case company concerning the research results. Therefore, triangulation in the empirical data was achieved.

Practical implications – It is argued that four reasons, namely: scale emphasis in production, IT systems to support supply chains, sea shipment, and outsourced distribution, play a vital role in the forthcoming performance improvement initiatives. At the moment this results in long supply chain lead times, whatever the distance to the actual market. Decision makers in practice need to find solutions for these in order to improve performance further.

Originality/value – Supply chains are rarely analyzed in research works through more than one supply chain – here analysis of four different supply chains concerning lead time is provided. The analysis is based on the enterprise resource-planning database, and findings are verified with interviews with the managers and directors of the case company.

Article Type:

Case study

Keyword(s):

Supply chain management; Paper industry; Northern Europe; Case studies.

Journal:

Industrial Management & Data Systems

Volume:

108

Number:

Year:

2008

pp:

208-227

Copyright ©

Emerald Group Publishing Limited

ISSN:

0263-5577

1 Introduction

Logistics and supply chain management (SCM) have gained increasing importance in the strategic planning process of global manufacturing companies, and it considered as contemporary topic of competitiveness (Kannan and Tan, 2005). For example, in automotive industry assembly to order (ATO) strategy has been widely analyzed and discussed recently (Holweg and Pil, 2001, 2004; Holweg et al., 2005). Research topics and approaches range from outsourced logistics/distribution services using soft methodology of behavioural science (Panayides and So, 2005) ending to mathematical analysis (Tyan et al., 2003; Zhang et al., 2006). Interestingly, both dynamic high-tech industries (Heikkilä 2002) as well as in less frequently changing traditional industries (McCarthy and Golicic, 2002; Mowat and Collins, 2000) have been under research interest. As the number of production plants decreases and served market areas grow, so does the number and complexity of supply chains – consolidation has created typical manufacturing vs marketing debate in different industries, and based on literature review of Hsu and Lin (2006) this has only intensified, and appears in tactical and strategic level.

Pulp and paper production is one part of wood processing industry, where usually is also included mechanical wood processing. In this research, we concentrate only into paper production, which significantly differs from other bulk type of production approaches in this industry. In our paper, we firstly present in a nutshell industrial sector statistics with respect of business and logistical performance measures concerning top five North-European producers. All of these companies have their headquarters and most of the production capacity as well as staff located in this region; this group of five companies play significant role in European, but also in global markets (with respect of capacity ownership and sales, Lee, 2005). Our examination in this paper is not limited to macro level, but also includes detailed examination of operational supply chain challenges of Finnish manufacturing units serving two different continents through strategically important supply chains. We base our main findings in the unique analysis of enterprise resource planning (ERP) database from the period of one year; in total we have 1,000 production lots analyzed throughout the supply chain. Examination scale and scope of one cross-organizational supply chain is still rather rare; according to SCM case study literature research completed by Hilmola et al. (2005) nearly half from the total population of case studies examined supply chains through their own internal perspective. Research validity of completed research work was assured with iterative triangulation; we use previous research work, discussions with case company personnel, macro data and analysis of IT database to draw conclusions (from iterative triangulation and case studies Yin, 1989; Eisenhardt, 1989; Meredith, 1998). Research approach applied in this paper reminds inductive research (Hilmola et al., 2005; Handfield and Melnyk, 1998, pp. 321-39; Eisenhardt, 1989, pp. 532-50); logistics and supply chain paradigms have been well-established in recent years, but our interest is to see how paper industry supply chains work with respect of theory. In empirical data analysis, we try to answer primarily in “how” question, while in discussion thereafter more substance is provided on “why” (case study questions, please Yin, 1989). As generally in inductive research works; our aim is to give further support for supply chain theory development through specific, and still not so well studied global paper production. Our objective in this research work is to use general SCM theory as well as research methodology to identify improvement areas, and suggest managerial remedies for the performance enhancement. Possibly our research results give some sort of SCM-based improvement agenda for North-European paper producers.

The structure of this paper is as follows: literature review in the following Section 2 describes the theoretical evolution from logistics to SCM, and discusses contemporary research findings from the field. Research environment and motivation for the study are described in Section 3; we will briefly present industrial sector statistics and analyze the logistical performance from the top five North-European companies through their financial statement data. After these we will present Section 4, which introduces our case study from supply chain performance of one main paper production unit. This analysis is further enlarged into lead time analysis of four different strategically important supply chains; these concern two different large manufacturing units (inc. manufacturing unit in the earlier case analysis). Our first case analysis was completed in 1999, and second larger case research took place four years later – however, all of these three empirical investigation approaches reveal that distribution, and SCM is a real challenge in the paper industry; inventory investments are high, and have not changed at all in the five year observation period, capacity management is poor in a supply chain, which results in cost inefficiencies, and in the end lead times from the actual production start to the final shipment for the customer are relatively long (on the average, above 90 days, whatever the destination actually is). After empirical data analysis we will discuss in Section 5 about the most important factors, which cause undesired effects on the supply chain performance; these findings are mostly resulting from unstructured interviews with case supply chain's responsible managers and directors. In the end of our paper in Section 6, we will bring together our findings in conclusions part, and sketch some future SCM research directions for this industry.

2 Literature review: logistics and supply chain management

Logistics involves the integration of information, transportation, inventory, warehousing, material handling and packaging. The overall goal of it is to achieve a targeted level of customer service at the lowest possible total cost. Customers of logistics companies are increasingly demanding products with added value, but with a lower cost. According to Bowersox and Closs (1997), a typical enterprise seeks to develop and implement an overall logistical competency that satisfies key customer expectations at realistic total cost expenditure. Very seldom will either the lowest possible total cost or the highest attainable customer service constitute the desirable logistics strategy. A well-designed logistical effort must have high-customer response capability, while controlling operational variance and minimizing inventory commitment (Bowersox and Closs, 1997, p. 12). Thus, currently profit maximization and flexibility have also been associated in the logistics, creating agile and leagile responsive strategies.

Companies have recently recognized the strategic importance of logistics in the new global environment. As Baumgarten and Wolff (1999) argue based on survey research that more than 50 percent of the respondent companies consider logistics to be the first or the second priority in their internal development. All over the world different regions will increasingly involve suppliers and customers into supply chain processes; initiative scope will move away from local and national, to regional and global. This is quite similar, what early authors of SCM argued more than decade before (Houlihan, 1985; Oliver and Webber, 1982; Houlihan, 1987). Oliver and Webber (1982) argued that SCM contained some number of major differences as compared to logistics; SCs are concerning only one large entity, gives new ideas how collaboration and interaction between different partners and inventory holding places should be accomplished, and SCM is dependent on strategic decision making. Houlihan (1985) gave similar argumentation, but emphasized the importance of international competition, and especially distribution. He argued that horizontal integration in the international distribution supported by management information would improve the efficiency considerably. In Houlihan's (1987), second article from SCM he mentions two additional items. Logistical problems have started to be strategic items in a company's development process; rapid changes in the economical environment have caused this. The future role of SCM was defined as a balancing factor between the company's marketing, sales, production and distribution (Houlihan, 1985, 1987). This argued difference has lasted, and logistics is nowadays identified to be a part of SCM (Mentzer et al., 2001; Larson and Halldorsson, 2004).

Baumgarten and Wolff (1999, p. 15) define both logistics and supply chains in pragmatic manner. Classic logistics contains traditional functions of logistics, like warehousing, shipping, external transport and materials management. Total logistics management has been developed from the classic logistics management by adding new functions to the classic logistics management. Internal transportation, order processing, procurement and production planning are the key elements in the total logistics management. SCM includes product development, management of information systems, production control, quality control, customer service and recycling and waste management.

Coyle et al. (1996, pp. 9-11) have identified seven different characteristics of traditional logistics and modern SCM. The observations show that in most cases the focus in logistics is towards only to own intra-organizational operations; this concerns inventory management, costing, information systems, risk management, planning and inter-organizational relationships.

Several articles have described the globalization of supply chains (Baumgarten and Wolff, 1999; Drewry, 2000; Hertz, 2002). However, it should be remembered that this all started from Forrester's (1958) research published in the late 1950s, which has increased its popularity with graphical system dynamics simulation tools, and mostly “MIT beergame” is the paradigm in supply chain simulation research (Holweg et al., 2005; Fiala, 2005). SCM has gained increasing interest in the recent years, and we could identify major shift, where articles start to concentrate in topics such as supply chains as a general managerial issue, and about the role of IT to serve objectives of SCM (Saab and Correa, 2005; Olsson, 2000; Lee et al., 1997; Schary and Skjott-Larsen, 1995; Jones and Riley, 1987). An increasing number of companies are implementing modern information technologies in order to facilitate communication between the supply chain partners and at the same time these companies would like to integrate customers into their processes. Sharing information with the customers and suppliers enables companies to know exactly what is happening in the supply chain. Having the right information, in the right place, at the right time makes the logistical decision making more streamlined and ultimately creates competitive advantage.

Among the global climate change, hyper competition among actors in the markets, and increased general uncertainty (e.g. in demand, product mix, etc. or in macro level, like politics and trade areas), research related to supply chain interruptions, risks and business uncertainty has arisen (Finch, 2004; Jin and Wu, 2007; Wilson, 2007; Papadakis, 2003, 2006). For example, Finch (2004) illustrates risk management in supply chain context with flooding of river in York, UK – one pub in the area was designed with modularity and flood avoidance, and it was able to open its doors within 24 hours after flooding, while in some of the rivals outlets waiting time for opening of the doors took several months. From Wilson's (2007) research work we could gain more examples for supply chain context; how prepared your supply chain is for earthquake, blackouts, fires or labour strikes? Papadakis (2003, 2006) has reported from 1999 earthquake effects on manufacturing of personal computers; Dell's ATO strategy was very responsive for memory market shortage from Taiwan (in that time 10 percent from memory production took place over there), and was able to direct its product offerings and deliveries on the areas, where shortage was lower or non-existent. Some of the competitors did not even identify the earthquake effects, and were blaming Y2K problems from the disappointing financial performance.

3 Research methodology and motivation of the study

3.1 Research methodology

Several authors have discussed the question of generalizability in the case study research context (Ellram Lisa, 1996, p. 100; Lukka and Kasanen, 1995; Eisenhardt, 1989). The key question is how many cases are necessary to achieve sufficient level of confidence in how analyzed results do hold validity among variety of different companies and environments. Usually, case studies are carried out within single company, and in single unit of this organization – this is adequate from methodological point of view, if case represents “critical case” that can be tested with a well formulated theory (Ellram Lisa, 1996, p. 100). However, larger amounts of cases are needed (multiple case study), when purpose is to show contrasting results and several explainable reasons. Usually, this multiple case approach belongs into the era of normal science, where current theory needs further support and modification to exist. Therefore, we have used multiple case approach inside of larger company to achieve this objective. Although, multiple case study sounds typical choice, it is rarely used in supply chain research – Hilmola et al. (2005) identified eight research works out of 55 to use three or more cases in their empirical justification. Typically case study research in supply chain area is still having only one case, and it is completed inside of own company (where research deals issues of supply chain, e.g. suppliers, distribution or final consumers). Based on the literature analysis of Häkkinen and Hilmola (2005) quantitative approach used in our study, is rather uncommon for logistics research, but follows more tradition of production/operations management discipline.

Research work reported in here is based on the inductive approach, where real life data analysis drives the results of a research work. Although, induction quite often supports current paradigm, its theory supporting feature is vital for the existence of normal science (Kuhn, 1996). From Arbnor and Bjerke's (1997) research approach alternatives we selected systematic approach (other two approaches are analytical and actor's approach). Research work conducted in the following could be considered as pragmatic, since it starts from the real-life preliminary analysis, and continues into larger context. By using induction the results from the supply chain process analyzing will be tested with existing theories and then by using deduction the empirical results in combination with existing theories will lead to enhanced form of current theory formation, which later on can be verified with other real life observations from the same industry, and/or other industries.

3.2 Motivation of the study – significance, structure and performance of European production

There exist over 1,100 pulp and paper mills in Europe (CEPI, 2006). However, it should be reminded that in 16 years (1991-2006) number of mills has decreased by nearly 24 percent. The production capacity of these CEPI-member (Confederation of European Paper Industries) mills is 110 million tons of paper and paperboard products and 47 million tons of pulp. The European forest industry cluster and their suppliers generate an annual turnover of more than 400 billion. The forest cluster employs directly 259,100 employees, and indirect employment is approximately 3.5 million persons. In 2001, European market consumed over 100 million tons of paper products, and its average growth is estimated to be 3 percent p.a. European paper and board industry is a net exporter, as 17 percent of the production is being exported. The total export outside Western Europe in 2006 was 17.7 million tons and the import was 4.4 million tons from outside of Western European countries. Within Europe, Germany is the largest paper producer, followed closely by Finland, Sweden and France.

The main pulp-producing countries are Finland and Sweden (CEPI, 2001, 2003, 2006). As could be noticed from Table I, these two latter mentioned countries are well presented in the world capacity ratings. In year 2002 StoraEnso owned largest amount from the total production capacity, while UPM-Kymmene was third, and Norske Skog was in tenth place. Other two rather large North-European manufacturers do not appear in the list, since they are just behind the tenth position. M-Real owns 6,400 million tons of production capacity, and SCA has 5,600.

All of the top five manufacturers located in Northern-Europe are having quite significant inventory investments in their end-item inventory. The general trend has levelled off in recent years, and on the average companies have 45 days of inventory to serve their customers in distribution. This inventory investment for distribution purposes is quite similar with US auto industry, where companies approximately invest 60-70 days to assure availability of different alternatives (quite often without success), and most importantly being able to run assembly plants and factories without interruptions (Holweg and Pil, 2001, 2004). Although, automotive industry in Europe has a bit better performance in this respect, even first tier suppliers carry approx. 20 days of inventory, and have spare capacity in production process available to hedge against supply risks (Holweg, 2005).

During recent decades structural changes have appeared in the sold production grades (product mix change). One exemplary case is the change in the use of Finnish production capacity (Finnish Forest Industry, 2002, 2003): In the early 1980s, newsprint production totalled 26 percent from total capacity use, but in 2002 this had declined to 8 percent. However, fine paper products, as well as printing and writing papers have both nearly doubled their share from capacity use. Only grade, paperboard products, have stayed in the level of 21-24 percent during these two decades.

4 Case study analysis of paper supply chains – production mills in Finland, markets in Europe and the USA

4.1 Research environment of case study

The physical starting point of the analyzed supply chain in the following case studies is the paper mill's production, where the paper reels are produced, and further forwarded into dispatching warehouse. The end point is product's arrival to the customer's facilities (e.g. printing houses). Railway and trucking companies (most often competing with one other) are transporting products to the port of loading, where the port operator is discharging arriving wagons and trucks. Thereafter, port operator loads arrived products into the vessel. There exist several ways for loading the vessel, but in this context this is understood as a generic. The forwarding company prepares the necessary documentation. The shipping company transports the products by sea to the port of discharge, where the port operator takes care of the vessel discharging. The port operator also dispatches, sends the products to the distribution centers or directly to the customers' facilities. Once again railway and trucking companies take care of the transport to the distribution centers and customers. It should be remembered that paper manufacturing is mass production like, and inventories are located in paper mills (dispatching warehouse), in the harbour (located in the port of loading) as well as in the customer side, most often near of the port of discharge. Case company's strategy has emphasised stocking near of customer's facilities (distribution inventory), and avoiding inventory holding in the country of actual production.

Case study presented in this paper concerns SCM of a major North-European paper manufacturer, which is mostly serving its customers in Europe and the USA; represented case study results are taken from year 1999 as well as 2003. First and preliminary case was started when supply chain challenges were recognized, and manufacturing unit was seeking managerial remedies – this investigation only concerned one manufacturing unit, while not separating any particular supply chain in the analysis. This first preliminary case analysis illustrates in a good manner, how different logistics operators are involved in the supply activity, and how difficult management of outsourced logistics is (our investigation is limited from paper mill to the port of loading, and actual sea delivery). This first step in the research process convinced company management to give larger database for the further analysis, and this data gathering concerned numerous different parties in the corporation. As our preliminary investigation dealt with efficiency and capacity management issues (through real numbers), while the latter one, more detailed case-study, analyzed lead time performance in four different strategically important supply chains, which were championed by two different large manufacturing units (the preliminary analysis concerned one of these two paper mills). Latter case analysis provides more in-depth to the causing factors of long lead times, and suggests remedies. Analyses concern entire supply chains, starting from paper mills and ending up to customer delivery (based on Figure 1).

4.2 Preliminary case-study, identifying disturbance areas in the supply chain

4.2.1 Disturbance area no. 1: booking of paper products to shipping line

Centralized logistics function takes care of cargo bookings towards shipping lines. Needed impulse for booking is generated through order management system. The production planning system firstly confirms to order management system that ordered quantity will be produced and cargo space onboard of vessels can be booked. However, in real life this causes numerous disturbances for vessel capacity need. Our case supply chain could hardly fulfill 10 percent out of its bookings for one particular vessel leaving in the end of October 1999. However, vessel bookings are general problem among number of different manufacturers and their respective manufacturing units, and deviation exist in large extend, mostly causing lower use than expected. In the case supply chain the main reasons for booking vs actual use difference were identified as follows:

changes in ordered quantities of customers;
changes in production planning; and
slow information transfer to the shipping line and port operator.

4.2.2 Disturbance area no. 2: ordering of railway wagons for transport from the mill to the port of loading

As vessel capacity bookings are more long-term oriented (low frequency, only once or twice in a week), and critical with respect of total logistics costs, the railway wagon order process should show ratios near to 1 (or 100 percent) between bookings and use. In the case supply chain ordering of wagons happens with one day lead time, meaning that railway company owns flexibility to serve its customer. However, analyzed results from case supply chain share similarities with vessel bookings – during the first day of observation period mill had ordered 80 wagons and the railway company delivered 78 wagons, but in the end mill used for dispatching/loading only 40 wagons. Remaining 38 wagons were simply left waiting in the yard for future use. Thus, inconsistencies and disturbances continued as we moved in the second day of our observation period; mill ordered 40 wagons and the railway company delivered 57 wagons, and only 30 wagons were eventually loaded! This kind of development continues throughout the whole half-month observation period in October 1999. There simply exist two reasons for unused and waiting wagons:

mill is incapable to order needed amounts of wagons, which leads to booking vs loaded difference; and
for one reason or other railway company is delivering now and then more wagons than what was in the first place needed.

So, in this case it could be argued that railway company simply would like to assure the availability of wagons in the yard, and also booking of mill is over ordering wagons. These two causes together will result on undesired situation of low-capacity usage.

4.2.3 Disturbance area no. 3: arrival of trucks to the port of loading

Among railway transportation concurrently is being used road transportation, trucks. This has appeared as very popular mode of transportation, e.g. in Finland (also in Europe generally), since trucks offer needed flexibility and plenty of spare capacity exist among road transportation companies (most often these companies are small or medium sized, and subcontracting is the norm in this industry). So, paper producers will gain flexibility in terms of service, and quite often lower prices than before. However, still in the case company supply chains 70-90 percent of transports from manufacturing unit to the harbour are completed with frequent rail connections (typically 2-3 connections per a day), which of course, increases the sustainability of transportation mode selection in the eyes of different stakeholders.

Flexibility indeed seems to be in need, as truck arrivals are being further observed in the port of loading (Figure 2). As all the arrivals from different companies were taken together, port was informed to receive 850 tons of paper products in the morning shift. However, only just above 500 appeared to the loading terminal. Of course, these trucks arrived during evening and night shift. However, in the end of one 24-hour shift, actual arrivals to the port of loading were above 600 tons more than planned, and this information just appears to be invaluable for managerial purposes. The port operator has just been used to keep additional resources in the evening and night shift. This additional resource availability can only be explained by lacking of joint planning processes and the level of accuracy in planning information. Thus, this results on less optimal overall costs in the supply chain.

4.3 Case-study from the responsiveness of a supply chain, lead time analysis

After completing previous analysis, case company got interested about supply chain issues, and enlarged the examination into four different supply chains, which includes two large factories (also the factory of previous analysis, total annual production capacity in these two factories is above 1.3 million tons p.a.), two different harbours in the port of loading (Finland), four different ports of dispatching (Europe and the USA), and their respective warehousing places. Aim was to utilize lead time analysis for paper industry's supply chain, in order to identify whether long lead time of automotive industry is apparent in here as well. Figure 3 shows main process steps in a supply chain, and their sequential and concurrent nature. As could be noticed, three first process steps are completed concurrently, namely production lots in mills are larger than dispatching lots from the mill's own warehouse, as well as transportation lots to the port of loading. This kind of practice enables smoothed production (for different end products, as production proceeds in cycles), and gives lead time as well as responsiveness advantage, as demand and requirements change. It should be remembered that in the following analysis, we have calculated together the lead times in these three first phases, which leads too pessimistic results; four latter steps are completed in sequential manner, so results are entirely valid with that respect (preliminarily we could estimate that concurrent three process phases contribute approx. 5-15 percent reduction in total lead time). Actually, the final supply chain process phase, customer delivery, is completed also with more convenient smaller lot sizes, but its previous phases are needed to be completed before it can start. However, this practice also enables some lead time advantage for case company.

Case company tries to operate its large factories through make to order principle; as customer has given indication from the aggregate need for the next couple of months, this amount is thereafter converted in the master production schedule on the actual production orders. Production orders are typically produced within different smaller batches (due to different paper grades, and “rotating” production schedule from thicker to thinner and vice versa), due to technical constraints, as well as other competing orders. We utilized case company's extensive ERP system to gather information regarding to lead time analysis; we traced, e.g. the first dispatching date as well as the last one through production order numbers, which are used among in all of the process steps in the case company's supply chain. In total, four different supply chains together amounted 1,000 observations, taking into account one whole year in each supply chain; this analysis should provide valid lead time analysis for decision making as well as research purposes. Analysis results could be found from Figures 4 and 5.

Even though our lead time analysis is limited with respect of three first process steps, results in total were shocking news for the company's directors; on the average lead time concerning all supply chains (two European and two US) was nearly above 90 days. As could be noticed, most of the time produced items wait in the warehouses, either in the port of discharge or the port of loading. Also local distribution in Europe and America takes long time (Figure 5). In our further analysis, we found great differences between median and average values (median values of lead times are much lower than the averages), and this only reveals that analysed data contains some observations, which have very long lead times as being compared to the rest of the data – this development is driven due to the reason of large customer/production lot sizes, and in the supply chain process consisting sequential steps, this results on long lead time in total. Figures 6 and 7 show the production, dispatching, sea shipping and final mile customer delivery lots further; interestingly we found in the deeper supply chain analysis that large production order is divided in the paper mill as well as in the customer interface into similar manner, to the smaller lots (in these we have analyzed further SC: Europe I and SC: America II from Figure 4). However, the situation with sea delivery is having scale emphasis; above 90 percent from production orders are delivered within one or two sea shipments! So, if the transfer lot size increases during the supply process so significantly, it means high inventories before and after the sea shipment (in the port of loading or discharge). Our lead time analysis supports this argument; considerable amount from total lead time paper reels just spend in the warehouses for waiting. Although situation with average lead time values was alerting, median values were more satisfying for the case company, since they were only some percentage above best business practice identified internally. Interestingly, it takes same amount of time to supply paper products from Finland to Europe or USA; even though the sea transportation is longer. This just illustrates in a good manner, why lead time performance in supply chain is not individual task issue, but rather the issue of lot sizing (orders and production) and capacity control.

In discussions with case company personnel, there were identified several different factors, which cause long lead time in their respective supply chain. One of the most important issue is organization and outsourcing related; all of the steps after mill's warehouse are operated by other organizations, and outsourced. It is evident that outsourcing leads to sub-optimization of the entire chain, as actors try to enhance own efficiency and results. So, in discussions it was identified that fourth party is needed to control the entire chain of actors, or own logistics organization is needed to be changed to complete this task. Another issue in supply chain control was the dominating role of manufacturing unit; it creates, similarly with automotive industry, own smoothed production programs, and tries to enhance and ensure own efficiency. Therefore, linking this behaviour into supply chain becomes troublesome. Centralization of manufacturing planning and control might be good implementation issue in the future. Third identified cause for long lead times was information system capability, and production lot sizing and discharging from the port of loading. In the current system, entire production lot is needed to be gathered into warehouse of the port of loading. This is simply due to the reason of inadequate of tracking and tracing; individual reels cannot be scanned in real-time to the system, so these are all first gathered together into warehouse from where these will proceed towards Europe or USA by sea transportation. If tracking and tracing could be improved, concurrent processes could be developed further to concern the whole supply chain (process steps from four to seven). This would clearly be an advantage, but large information system investments are needed, and most probably it would mean to utilize bar coding systems instead of RFID (it is not sufficiently accurate with paper reels, since tag would be located inside of the paper reel, making it hard to be accurately recognized). Hou and Huang (2006) showed in their research from printing industry that RFID implementation plans started from publisher's sales tracking process, not from purchasing inventory or raw material supplier(s) – this gives some support for our case-study findings. Implementation of this kind of large system is problematic, since different actors in supply chain have own information system in use, and enterprise application integration is the issue to be taken into account.

5 Discussion

From the completed research we could conclude that the four following factors play important role in the SCM of paper industry:

scale emphasis in the production;
sea shipment;
outsourced distribution; and
information systems to support supply chain processes.

After discussing with company managers as well as directors, that solutions for improved lead time and supply chain performance could only be gained with the collaboration as well as implementation of management systems through these four factors concurrently or in a manner where three different factors are taken into consideration same time. If these presented factors are compared to previous literature, Holweg and Pil (2004) identified scale-based thinking to be major reason for long lead times, and high-inventory investment in automotives (similarities for integrated and mini-mills discussion, Denton et al., 2003; Schorsch, 1996). Thus, in paper production one dissimilarity in scale is the problem of joint-production items, which is discussed in the below. Similarly to scale, sea shipment issues have been discussed in Wilson (2007) and Baker (2006). However, our research work includes additional perspective for sea transportation factor – it is of course, source of delay, as well as always hinders possibility for negative deviation in lead time (depends so much in third parties, e.g. strikes and availability of capacity in harbours), and results on high-inventory holdings. Thus, with the discussion among company personnel, we were able to identify other causes as well. Our findings in terms of outsourcing (Tyan et al., 2003; Panayides and So, 2005) and information systems (Cooper and Tracey, 2005; Fiala, 2005) are similar to previous studies in the field. Of course, the magnitude of outsourcing in the supply chain was interesting practical insight for previous studies, and gives further research issues for distributed information systems development. In the following we will review the current situation, and development initiatives through identified improvement areas.

Production investments have been completed in the case company with strong scale emphasis: Basically this means ever faster paper producing machines, with higher production volumes. However, synchronization with customer's own production machines becomes in this case troublesome; fast and high-volume paper production lines use certain width, but customers might use over ten different widths in their production process. In production process width variation issue is managed technically within cutting and packing, but in the end this results on some amount of “side-run” and low-volume reels. In real-life high-order volume for certain width might therefore result on high amounts of side-run products, which have low demand. So, these products therefore are just sitting in the warehouse, either in the port of loading or nearby of the port of discharge. Customers have been informed about this problem, and bargaining is the norm in order phase; quite frequently customer takes some amount of discounted side-run products among order of high-volume reels, with “proper” width. Customers are also aware of high-volume capability of production machines, and therefore group some orders together, to gain volume discounts. This also increases lead times, since lot sizes become larger, and lead time correspondingly multiply in the chain.

As was highlighted in the case analysis phase, tracking and tracing is one major problem in the lead time improvement. However, other issues were also found. For example, in the preliminary case analysis of 1999, we identified production order changes as causing factor of disturbances in the capacity as well as vessel bookings in the supply chain. As information systems was examined further, we found that ERP system only stores the most recent customer order, but does not provide historical data from the original order. Thus, logistics planning and bookings are in some of the cases based on the original order (released); this causes numerous disturbances among supply chain(s). The second information system issue was the support of “key performance indicators” measurement; at the moment case company measures with numerous different measures functional performance among the supply chain, but measurement systems have not been adopted to support cross-functional process thinking. For example, lead time analysis completed in this research work is really a time consuming exercise, and needs to be automated. However, information systems do not at the moment support cross-functional measurement.

Sea transportation creates several implications for the managerial processes; for example, some customers have own stocking points, among the case company, in the port of loading. Cancellation of orders happens in most of the occasions, as paper reels have arrived in the port of loading; also possible payment problems from customer side will be revealed during this stage. So, sea transportation itself is not a problem, but different factors make it as a focal point in case company's supply chains. As was identified earlier, transfer lot sizing in a supply chain should be developed with information systems (using bar coding, or RFID) to enable that produced production orders should not be transferred all at the same time, but could be delivered from the port of loading with smaller lots (simplistic form of traceability in a production batch/lot level). However, during the discussions we identified that there exist several other, in the above given behavioural models, which are needed to be changed, if this constraint is desired to be removed. However, it should be noted that sea transportation inside of the Europe (from north to central) and between Europe and the USA is relatively stabile, and safe, and therefore supply interruptions between manufacturing and warehouse are having lower probability. Based on Wilson's (2007) simulation research, this should result in the lower levels of inventory holding; as supply-based transportation risk from the first tier supplier to the warehouse was considered as most damaging to the inventory levels and smooth flow of operations.

As was concluded in the research environment, there exist number of different actors in paper production supply chain, and most often supply chain operations are outsourced. Not only number of actors is high, but as well transportation modes being used. In inland transportation, for example in Finland as well as in USA, road and rail transportation are used side by side. In most of the situations rail offers low-cost alternative, but road transportation mode is more flexible, and is able to provide transportation service with short time windows. These factors altogether create uncertainty for the distribution operations, and variations in a lead time. Most often sales offices just hedge this uncertainty by adding more safety stocks, and favoring ever larger customer order lot sizes.

6 Conclusions

As this paper has shown, North-European paper industry faces severe improvement challenges in its supply chain distribution process. In the same time distribution process is full of inventory, having long lead times, and transportation machinery is operating on the average with low-utilization levels. Thus, current management mode in distribution causes every now and then sudden demand spikes. As our argumentation is based on large sample of observations from four supply chains and long-term as well as detailed case-study, these mentioned points represent main contributions of our research work. However, as a secondary contribution we have represented four factors, which are main causes for undesirable effects in the paper industry supply chains; these are related to own internal processes, like scale economics emphasis in production, and long time delays in production as well as in information exchange. Also transfer lot sizes in sea shipment, current information systems, and outsourced operations (among high number of different actors) foster undesired effects. As we add disturbances caused by the customers in the equation, it is evident that distribution performance is lower than expected. Maybe production systems should be developed more flexible, and quite probably minimill concepts will appear in this industry as well (although industrial long-term statistics suggest in paper production opposite, however, recycled paper has showed different development). This flexible, high-labour productivity, near-by-markets and responsive factory concept changed metal industry forever, and some of the large-scale-manufacturing units just disappeared due to their low competitiveness (Denton et al., 2003; Schorsch, 1996). Cost efficiency might be high in the large units, but other sides of performance are far from optimal.

As our two case studies revealed, performance improvement initiatives should also be addressed for the information flow between different parties, but also considerable part of the improvement efforts should be directed to build trust between different parties (Denton et al., 2003). Paper industry's supply chains are typically fragmented, and in the distribution side only we could easily find from seven to nine different parties involved in the transportation activity, before delivery reaches final customer. Different parties might have high competence in their own parts of the transportation work, and cost efficient in theory, but high number of different parties causes the lack of strategic commitment and understanding. However, we identify that IT systems play important part in the future to tie these different parties together. New enhancements in bar coding technology and still developing RFID among efficient database structures are key enablers in improvement initiatives (Cooper and Tracey, 2005). These have direct effect on the shorter response in a supply chain level as well, thus favoring lower inventory levels, and higher adaptability for uncertain business environment.

Our research opens new interesting avenues for the further research in paper industry supply chains. As a short-term interest, it would be extremely interesting to complete analysis concerning the accumulation of inventories in distribution:

are sales units in abroad carrying unnecessary amounts of inventory; and
if so, what is the reason for this behavior.

Large inventory holdings near to markets might also cause effects in the paper grade pricing, and this is in our interest as well. Sales offices eventually represent supply chain champions in this industry, and have the customer interface as well as order lot sizes at their disposal. Generally in supply chain research, we would like to apply our sub-process classification (shown in Figure 3) in this industry as well as in other similar type of industries (like car manufacturing). Based on US Federal Reserve's (2007) long-term statistics, utilization levels in both US paper and car production are approx. 80 percent. However, in capacity addition situation is different, as in car production it has somewhat increased, while in paper production been in constant decline for last seven years. Thus, benchmarking these two industries would clearly add value for car production dominated supply chain research. The value of this benchmarking has been identified in case company level as well, since developed framework has been used to measure performance in numerous other supply chains.

Figure 1Illustration of functionality and scope of the case supply chain

Figure 2Truck arrivals to the port of loading, middle of November 1999

Figure 3Case supply chain classification in sub-process steps, and their relations (in the above) as well as the most typical lengths of the classification steps (in the below)

Figure 4Lead time performance of two supply chains to America and Europe

Figure 5Time being spent in different phases of a supply chain (most typical one)

Figure 6Production, shipping and customer delivery lots in “Supply Chain: Europe I”

Figure 7Production, shipping and customer delivery lots in “Supply Chain: US II”

Table IProduction capacity of world's ten largest pulp and paper manufacturers (million tons) in year 2002

References

Arbnor, I., Bjerke, B. (1997), Methodology for Creating Business Knowledge, Sage, Thousand Oaks, CA, .