THE QUEBEC WOOD SUPPLY GAME: AN INNOVATIVE TOOL FOR KNOWLEDGE MANAGEMENT AND TRANSFER

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THE QUEBEC WOOD SUPPLY GAME: AN INNOVATIVE

TOOL FOR KNOWLEDGE MANAGEMENT AND

TRANSFER

Constance VAN HORNE and Philippe MARIER

FOR@C Research Consortium, Pavillon Pouliot, Université Laval, Quebec City, Quebec G1K 7P4, Canada

connie.van-horne@forac.ulaval.ca

This paper presents how a game is used as an innovative tool to manage and transfer the tacit and explicit knowledge of researchers and practitioners to employees working in forest products industry enterprises in the Canadian Province of Quebec. The Quebec Wood Supply Game and workshop present knowledge management problems and possible solutions for commercial logistics activities; i.e. the planning, procurement and collaboration functions of the value creation network of the Quebec forest products industry.

Introduction

The challenges faced by organizations in the 21st century require new methods and mental

models to turn these challenges into opportunities. The looming retirement and knowledge loss of thousands of logistics professionals worldwide comes hand in hand at a time when companies are looking to logistics and the supply chain for cost savings and as sources of value. These challenges require companies to improve the management and transfer of all available knowledge which in turn require innovative solutions. FOR@C, a research consortium based at the Université Laval in Quebec City, Canada, has developed a game and accompanying workshop built on the value creation network of the forest products industry in the Canadian Province of Quebec to help with these knowledge management processes. The Quebec Wood Supply Game (QWSG) was inspired by the Wood Supply Game (Fjeld, 2001), which in turn was inspired by the Beer Game developed at the Massachusetts Institute of Technology in the 1960s (Goodwin and Franklin, 1994). The first section of this paper will outline the context of the forest products industry and its supply chain in the Province of Quebec and introduce the Consortium that developed the game. The second section will focus on Nonaka and Noboru’s (1988) theories for knowledge management and describe how knowledge is created and transferred. The third section will describe the QWSG and how it is used as an innovative tool to manage and transfer the tacit and explicit knowledge of researchers and practitioners to employees working in forestry enterprises in Quebec. The last section will highlight some positive and negative feedback from participants and some lessons that have been learned by the developers of the game.

Forest products industry in Quebec

Logistics planning and operations in the forest products industry in the province of Quebec, Canada, are different from other resource based industries for several reasons: government ownership of the resource and strict control and changing regulations of procurement rights and practices, uncertainty with regards to quantity and quality of raw material, transformation process is stochastic (due to the very nature of fiber) and both

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divergent (trees are processed into various wood and fiber products such as lumber, chips, wood panels, etc.) and convergent (wood products are then reassembled into finished products such as wood structures, beams, doors, windows, furniture, wood floor, paper, etc.) resulting in complicated and specific logistics management methods. (Van Horne et al., 2004).

These industry and supply chain specificities led in 2002 to the creation of the FOR@C Research Consortium in e-Business in the forest products industry. The Consortium conducts research activities in the fields of supply chain management and the use of Internet and communications technologies for the forest products industry in Canada and has four objectives:

1) Improve the competitiveness of forest product companies.

2) Develop skills via graduate student training and continuing education. 3) Develop and disseminate innovative knowledge serving to advance the state

of the art.

4) Maintain the involvement and satisfaction of partners.

As part of its mandate FOR@C developed the QWSG and workshop as a knowledge management and transfer tool to present the supply chain in a tactile way and to create a “laboratory” to study supply chain phenomena such as the bullwhip effect (Lee et al., 1997) and to test hypotheses for solutions to commercial logistics activities; i.e. planning, procurement and collaboration functions (see Moyaux et al., 2003). Such games have been used elsewhere to great success, and are said to balance theory with practice (Hongyi, 1998), aid participants in understanding the key concepts and key problems encountered along a supply chain (Sparling, 2002), and give participants a view of the big picture so that root causes can be seen instead of solutions (Goodwin and Franklin, 1994). It is the goal of this game and workshop to teach the basic dynamics of logistics, i.e. the importance of information sharing, the importance of timely and accurate information, the effect of time delays, the bullwhip effect, etc. and transfer the know-how of researchers and professionals to practitioners working in logistics activities.

Knowledge management and transfer

There are two sides to knowledge management; one involves technology and the other people. The field of logistics has embraced the management of hard knowledge with the use of information technologies; however the soft knowledge of practitioners and experts is often less well managed. The efficiency and effectiveness of all logistics activities requires the creation and management of two kinds of knowledge, explicit and tacit. Tacit knowledge is our hunches, insights, know-how and cognitive knowledge and is based on our beliefs, ideals, values, schemata and mental models. Explicit knowledge can be expressed in words and numbers and shared in the form of data, scientific formulae, specifications, manuals, reports, etc. (Lee and Yang, 2000; Schmoldt and Rauscher, 1994; Nonaka, 1991; Nonaka and Noboru, 1988).

Nonaka and Noboru (1988) explain that knowledge creation is the spiralling process of interactions between explicit and tacit knowledge and that there are four types of knowledge innovation: socialization, externalization, combination and internalization. Socialization is the transfer of tacit knowledge to tacit knowledge between individuals and can be done through joint activity, apprenticeship and the capturing of knowledge through physical proximity (watching and learning). Externalization is the transfer of tacit

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knowledge to explicit knowledge so that tacit knowledge can be diffused and used by others. It is done by the conversion of tacit knowledge into metaphors, narratives, analogies, visuals and through dialogue. Combination is the transfer of explicit knowledge to explicit knowledge and involves the conversion of explicit knowledge into more complex sets of explicit knowledge. Finally, internalization is the transfer of explicit knowledge to tacit knowledge and is accomplished with training, exercises and learning by doing (Nonaka and Noboru, 1988; Nonaka, 1991). Knowledge management therefore can be seen as the management of this knowledge creation process.

This framework for knowledge management, which uses the interactions between hard science (explicit knowledge) and art (tacit knowledge) compliments the definition of logistics by SOLE France (2004) as the art and science of management, engineering and technical activities concerned with requirements, design, and supplying and maintaining resources needed to support objectives, plans and operations. This definition of logistics lends itself to the use of innovative “soft” tools for the management and transfer of knowledge of supply chain management. The QWSG is an example of an innovative tool that uses the four types of knowledge innovation.

The QWSG and workshop

As previously mentioned, the QWSG is based on the Wood Supply Game (Fjeld, 2001), which is itself an adaptation of the Beer Game that is used to teach supply chain dynamics (Goodwin and Franklin, 1994). The Wood Supply Game was adapted to the North European forest sector with the use of divergent flows, i.e. lumber and paper. The greatest differences between the two games adapted to the forestry supply chains is that the QWSG assumes that the raw material for the pulp mill is supplied entirely by the sawmill and not the forest as with the Wood Supply Game. In addition, in the QWSG the forest has a limited capacity and as such only a maximum number of logs are available each week/turn. This is a better reflection of the situation in the Quebec forest products industry.

The workshop begins with an introduction to current supply chain management problems faced by the industry. The need for change in current practices, in order to remain competitive in an increasingly competitive industry is also addressed and some concrete examples are given for reinforcement. This is an example of externalization. The tacit knowledge of the seminar presenters was collected into a presentation, and experts in this way are able to share their know-how to participants. This is generally popular with people in the industry as most of their knowledge is tacit (learned on the job) rather than explicit (theories and case studies) in nature. Discussion of personal experiences is encouraged and this is another example of externalization, only this time on the part of the participants.

Following the introduction into the theory of logistics and supply chain management, the game is explained to participants. Figure 1 (Moyaux, 2003) illustrates how the game is set up. Between seven and fourteen participants take the role of the different positions (i.e. one or two players in each of the seven positions). This hands-on role playing allows participants to internalize the explicit knowledge of the game, and in fact make it a part of their own personal, tacit knowledge.

The basic goal of the game is simple, minimize total supply chain costs. Items in backorder cost twice as much as items in inventories, so players try to avoid backorder situations. Participants are not allowed to communicate between positions, and final

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customer demand is known only to the retailer. The game is a series of turns, each turn representing one week and split into five parts. Each position plays the turn at the same time. Goods, which were shipped by suppliers two weeks previously (due to a two week shipping delay), arrive in the first step and filled orders are shipped to clients in the second step. Next, current orders are checked and then filled, if there are back-orders these are filled first. The fourth step involves participants recording their orders and backorders. Orders are decided on and placed with suppliers in the fifth step. The game lasts between 20 and 25 weeks or turns.

Each position is played in the same way, except for the sawmill which receives two orders (one from the pulp mill and one from the lumber wholesaler) and must aggregate the two orders before it places an order with the forest (each item received from the forest by the sawmill is split into two parts).

Figure 1: Model of the QWSG

Ordering policies remain similar to those of the Beer Game (Goodwin and Franklin, 1994). That is orders are constant, and around the fifth week there is a one time increase in demand, and then demand rests at this increased level for the remainder of the game. Even given these simple rules the bullwhip effect occurs, to lesser and greater degrees, each time the game is played. Frustration is always apparent at the inability to communicate between positions. Participants see upstream orders being placed that seem to have no relation to the actual orders that they placed with their supplier.

As mentioned above the game lasts between 20 and 25 weeks or turns. At the end of the game, results are entered into Excel (combination of the explicit results of the game) and a period of discussion follows. What went wrong? How can we improve the efficiency of the supply chain? It is in these discussions that the tacit knowledge of participants and presenters is shared with the group and socialization occurs. The most common suggestion is that if we could share information it would be much easier to make better decisions and the total costs of the supply chain would decrease. Participants are then asked if they share information with their suppliers. This is often a moment of profound realization for participants. Customer Customer Lumber Paper Lumber Paper Paper Forest Retailer Retailer Wholesaler

Wholesaler Pulp mill

Sawmill

Product stream Order stream

1 week shipping delay 1 week order delay

Player 1 Player 3

Player 2 Player 4 Player 5

Player 6

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The QWSG allows participants to experience first hand common supply chain problems such as the bullwhip effect and a lack of communication between supply chain partners. This tacit knowledge gained by playing the game is supplemented with explicit knowledge presented by the Consortium concerning the supply chain and some methods that can be used to improve communication and reduce the bullwhip effect. This mix of explicit and tacit knowledge is exactly what Nonaka (1991) tells us is necessary for a knowledge-creating company. Logistics is not an easy field to understand with only tacit or explicit knowledge, a mix is necessary to have a better understanding of the dynamics of the supply chain and this in turn we hope will lead to better decision making.

Lessons and conclusion

It is sometimes difficult to convince decision makers that an afternoon spent playing a game will be a profitable use of time. However, comments received after the workshop have been for the most part positive. Comments include: “The activity is based on what actually happens each day and shows that there are many areas where we can make improvements”; “This allowed me to realise the combined effects of each player’s estimations on the final demand to the sawmill”; “The workshop allowed me to learn about the new trends in logistics to better manage our production” and “A very interesting workshop that provides good management tools on how to react to demand”. The negative comments include: “It is difficult to see how to apply this to forest management” and “The workshop is based on customer demand and in the forestry context the accent should be placed on the production capacity of the forest in terms of product, quality and quantity”. All these comments have been used to improve the workshop, but the challenge remains in convincing companies of the utility of game-playing.

Knowledge management is not just about teaching and building knowledge repertoires using information technologies, it is about capturing undocumented tacit knowledge and creating new explicit and tacit knowledge. Logistics is not just getting the right goods to the right people at the right time for the lowest possible costs. The QWSG is a knowledge management tool to transfer and share the tacit and explicit knowledge of all participants to hopefully improve supply chain performance in the Quebec forest products industry.

References

Fjeld, D., 2001. The Wood Supply Game as an educational application for simulating industrial dynamics in the forest sector. in Sjostrom, K., and Rask, L., editors, Supply Chain Management For Paper and Timber Industries, pages 242-251, Vaxjo, Sweden. Goodwin, J., and Franklin, S., The beer distribution game: using simulation to teach systems thinking. Journal of Management Development, 13 (8), 7-15.

Hongyi, S., 1998. A game for the education and training of productions/operations management. Education + Training, 40 (9), 411-416.

Lee, C. and Yang, J., 2000. Knowledge value chain. Journal of Management Development 19 (9), 783-793.

Lee, H., Padmanabhan V. and Whang S., 1997. The bullwhip effect in the supply chain. Sloan Management Review, 38(3), pages 93-102.

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Moyaux, T., Chaib-draa, B., and D'Amours, S., 2003. Agent-based simulation of the amplification of demand variability in a supply chain. Conference for Agent-Based Simulation ABS 4 (CIRAD, Montpellier, France), 28-30 April.

Nonaka, I., and Noboru, K., 1988. The Concept of “Ba”: Building a Foundation for Knowledge Creation. California Management Review, 40 (3), 40-54.

Nonaka, I., 1991. The Knowledge-Creating Company. Harvard Business Review, 69 November-December, 96-104.

Schmoldt, D. and Rauscher, M., 1994. A knowledge management imperative and six supporting technologies, Computers and Electronics in Agriculture 10 (1), 11-30.

Société des Ingénieurs Logisticiens (SOLE France). www.soleurope.org/france

Sparling, D., Simulations and supply chains: strategies for teaching supply chain management. Supply Chain Management: An International Journal, 7 (5), 334-342.

Van Horne, C., Frayret, J.-M. and Poulin, D., submitted. Knowledge Management in the Forest Products Industry: the Role of Centres of Expertise. Computers and Electronics in Agriculture.

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