Are forest sector firms maximizing the economic

Are forest sector firms maximizing the economic returns from their timber? Evidence from British Columbia by Harry Nelson1, David Cohen2 and William Nikolakis3

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ABSTRACT

Understanding the components of the forest value chain and linkages is essential in designing a system that will maximize the economic value of Canadian fibre. A key part of the system is how firms incorporate the fibre quality and attributes of their timber supply into the decision over what kinds of products to manufacture. The linkage between timber supply and how firms decide to utilize fibre is critically important, especially in Canada, where government policy plays a key role in governing access to fibre. We explore this question by looking at whether firms try to maximize the economic return from their fibre, or instead focus on other objectives such as maximizing the production volume they can generate from their timber supply. We surveyed sawmills and woodland managers in British Columbia in the Fall of 2006 and focused on a particular characteristic—the extent to which sawmills and operations are responding to value-based signals rather than to other kinds of signals. We found that the majority of BC forest sector firms we interviewed are emphasizing volume-based measures on a daily basis, whether they are in sawmill or woodlands operations, and while economic measures become more important as the period lengthens, it is unclear as to how firms reconcile these 2 different types of measures. Key words: organizational behaviour, firm operations, Canadian forest industry, value chain optimization RÉSUMÉ

La compréhension des composantes de la chaîne de valeur du milieu forestier et des liens qui les unissent est essentielle pour pouvoir concevoir un système qui maximisera la valeur économique de la fibre de bois du Canada. Un élément déterminant de ce système est constitué de la façon selon laquelle les entreprises incorporent la qualité de la fibre et les caractéristiques de leur approvisionnement en matière ligneuse dans leur décision du genre de produits qu’elles produiront. La relation entre l’approvisionnement en bois et la décision d’une entreprise d’utiliser ces fibres constitue un élément de prime importance, surtout au Canada, où les politiques gouvernementales jouent un rôle déterminant au niveau de l’accès à ces fibres. Nous explorons cette question en examinant si les entreprises cherchent à maximiser le rendement économique de leurs fibres ou si elles se concentrent plutôt sur d’autres objectifs comme la maximisation du volume de production qu’elles peuvent générer à partir de leur approvisionnement en bois. Nous avons effectué des sondages dans des scieries et auprès des gestionnaires du domaine forestier en Colombie-Britannique au cours de l’automne 2006, pour nous concentrer sur une caractéristique déterminante—jusqu’à quel point les scieries et les opérations forestières répondent aux signaux reposant sur la valeur par rapport à tout autre signal. Nous avons relevé que la plupart des entreprises du secteur forestier que nous avons interviewées mettent l’emphase sur les données quotidiennes reposant sur le volume, que ce soit pour les scieries ou pour les opérations forestières et, même si les données économiques deviennent plus importantes lorsque les périodes de temps s’allongent, la méthode de réconciliation de ces deux types de données par les entreprises demeure obscure. Mots clés : comportement organisationnel, gestion des opérations, industrie forestière canadienne, optimisation de la chaîne de valeur

1Assistant

Professor, Forest Resources Management, University of British Columbia, 2045–2424 Main Mall, Vancouver, British Columbia V6T 1Z4. E-mail: [email protected] 2Wood Science, Faculty of Forestry, UBC 3Research Associate, Faculty of Forestry, UBC MAY/JUNE 2009, VOL. 85, NO. 3 — THE FORESTRY CHRONICLE

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Harry Nelson

David Cohen

Introduction The idea of the forest value chain recognizes that there is an underlying system that determines the economic value of Canadian wood fibre. Under this system, there are a number of factors that influence the value of wood fibre, some of which are economic and others which are not. Non-economic factors include the underlying quality of the fibre itself and the relationship between the characteristics of that fibre and what may be possible to technologically manufacture from that fibre. Economic factors include the cost of accessing the fibre, the effect of existing infrastructure on the costs of manufacturing the product, and access to markets, among others. A key linkage in the system is how the forest resource is utilized; yet at the same time, this is an area that is not well understood nor that has been examined. This is also an area where provincial policies can play a critical role. Many aspects of provincial forest policies are organized around maximizing the yield of timber on Crown lands (subject to environmental targets and other regulatory requirements). This timber volume is then made available to firms through long-term tenure agreements that process the timber, providing employment and other economic benefits to the communities in which they operate. There are a number of policies that specifically link individual timber volumes to firms, including policies that not only emphasize achieving the Annual Allowable Cut and maintaining an even flow of timber, but that also tie timber to mills.4 At the same time, a common observation of the behaviour of the softwood lumber industry in Canada is that, at a strategic level, the industry emphasizes maintaining production levels and increasing physical productivity in order to remain cost-competitive in the global forest product markets in which the industry participates. This emphasis on physical productivity and cost reduction has been criticized by several authors as being too narrow since it does not take into account opportunities to enhance firm profitability through value-enhancing activities (Porter 1991, Kozak and Cohen 2001, Martin and Porter 2001). This in turn contributes to the financial plight of the firms. However, the evidence that firms behave in this cost-focused way is anecdotal, and to our 4These

are generally called appurtenancy policies, where the timber is made “appurtenant” to the mill. Access to the timber is made conditional on operating a specific processing facility. This has long been a staple of provincial forest policy, although it is increasingly being questioned.

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knowledge, there has not been any effort to actually assess whether this is the case. It is also unclear to what extent such behaviour, if it does exist, may reflect either a strategic approach to cost reduction or, instead, a response to provincial volume-oriented timber policies. In order to explore these questions, we surveyed sawmill and woodlands managers in British Columbia (BC) about how they currently assess their operational performance. We looked not only at their existing operations, but also at the financial criteria that they used to evaluate investments. We chose BC as our case study region because, unlike many of the regions across Canada where policies govern the allocation of wood and restrict harvest levels and wood flows, in 2003, BC adopted a number of policy changes to increase the size of the market for fibre and to allow firms to respond more easily to market forces (Niquidet et al. 2007). Part of these changes involved dropping polices that required firms to maintain harvest levels or process timber through specific mills. This, in turn, gave firms more flexibility in how they could operate and in the strategies they could pursue. This also means that decision-makers in firms, given the desire, have the opportunity to pursue strategies to increase economic value. We then analyzed the results by looking at the responses through 3 filters in regards to the measures they employ: 1) To what extent do firms rely on strictly volume-based or cost-based performance measurements or do they use value-based performance measurements? 2) How consistent are mills in using those measurements over time? 3) How consistent are firms in how they evaluate mill operations and investment opportunities? This was followed by an assessment of the extent that firms are practising volume-based and cost-reducing strategies today, and how coherent those strategies are.

Competitive Strategies and Choosing Performance Measures At its most basic level, businesses choose competitive strategies and then develop functional strategies and organizations to carry out those strategies (Hill and Jones 1992). As part of that process, they develop standards and measures and collect information to assess how well they are achieving those strategies (Garrison 1985). Thus, the articulation of performance measures serves several purposes from a company’s point of view: it provides the means of deciding which types of performance (activities or outcomes) should be evaluated and what activities or outcomes are preferable; how the measures might be explicitly linked to incentives to reward good performance (or at least monitored); and how they can be used to provide feedback into company strategies (i.e., is the approach yielding the desired results?). Oftentimes, performance measures may also be used as benchmarks for comparison with other firms or to track changes over time. Much of the more formal economic theory has specifically examined the design of incentives and their effect on employee performance, both from a transaction costs perspective (Williamson 1985, Milgrom and Roberts 1988, Gibbons 1998) as well as an organizational theory and design perspective (Kaplan and Henderson 2005, Bouwens and van Lent 2006). Much of this work has highlighted the problems of ensuring that compensation practices are aligned with

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either the incentives or the desired outcomes of the firm. This literature has shown how poorly designed schemes or poorly chosen indicators may lead to undesirable outcomes, contrasting it with examples where more appropriate measures have contributed to better outcomes (Kerr 1975).5 In our study, we do not specifically examine individual compensation; instead, we focus on the information the firms are collecting, and the importance placed upon this information by firm officials. We chose this as a way to increase the response rate and to standardize across the different companies and mills that we were examining.6 We also chose to interview mill and woodlands managers directly, rather than relying on annual reports or other public statements made by the firms surveyed. As these managers are in charge of carrying out operations on a daily basis (and indeed their job security is ultimately linked to how well they perform), we anticipated that they would be well qualified to not only identify the salient measures important to senior decision-makers at the firm, but also to provide a relative ranking of these measures. The choice of performance measures offers insight into not only the decision-making criteria a firm uses, but also the strategies they are actually implementing (which can be different from those publicly stated). We also expected to find more than one measure associated with the firm’s operations, since companies will have a number of different objectives, some of which may be in support of their primary strategy, and others that may be in support or response to other requirements such as regulatory obligations. In this case, we simply looked to identify what other measures they might use, and whether they could be considered to be in support of their main strategy. Following the interviews, we grouped the measures into 3 types: volume and cost-based; value-based; and other. We considered the time frame over which each measure was employed, and whether the type of measure ranked most important by respondents was consistent across different time periods. We also investigated what criteria managers are currently using to assess investment decisions. This offers insight into 2 areas. First, the criteria reported can be compared to the operational performance to see whether or not there is consistency in the strategic focus (e.g., operational and investment decisions are directed towards the same goals). Second, given that there are a number of different rules that can be used to eval5The

literature focusing on the effects of incentives on employee performance can be split into 2 areas, one examining effort (is the effort of the employees consistent with the objectives of the firms), and the second selection (is the system designed so that more productive employees self-select to the firm) (Bouwens and van Lent 2006). Most of the examples of how poorly designed measures lead to inappropriate outcomes focus on their effect on employee performance, underscoring the fact that company signals affect how the firm operates. 6Given the confidential nature of the industry, we were unsure if we could obtain more detailed information related to pay structure, individual compensation, or even the performance of the establishment. Therefore, we decided to focus on collecting more general information on how the firm carried out its operations. We did find that, once we were able to reach the appropriate manager, while there was reluctance in divulging more specific or detailed information, there was less hesitation in discussing the type of measure.

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uate investment decisions, with some preferred over others in terms of offering a more comprehensive view on the overall benefits to the company, which rules are being utilized? Do these rules reveal anything more about the firm orientation? Finally, do the rules show whether the firm is following a coherent, well-integrated strategy around all aspects of its operations, including how it links manufacturing decisions, fibre sourcing, and the allocation of investment? This paper seeks to answer these questions by first describing the methodology we used. We then report the survey results for sawmills and then for woodlands operations, and finally we conclude with a discussion of the results.

Methodology The sample frame for this project was all sawmills and woodlands departments that supplied these sawmills in British Columbia. We had responses from 28 sawmills and 37 woodlands departments in October and November of 2006. Respondents, who were the managers of the operations, completed different but related survey instruments shown in Appendix 1. Additional effort, such as multiple contacts, was made to ensure that responses were received from woodlands and mill managers working in the same division for the same company to facilitate meaningful results. Information was collected using telephone interviews. This was preferable to other methods such as a mail survey for several reasons. A telephone interview made it easier to obtain results from sawmill and woodlands managers from the same company in the same division. Dillman (1978, p. 45) refers to this as controlling the selection of respondents within sample units. Telephone contact also facilitated the expansion of the sample as interviewees often provided additional current contact information for other managers within the sample frame. As well, the ability to gather more qualitative information and be exposed to the nuances of answers to open-ended questions was the primary reason a telephone interview was selected (Dillman 1978). Each survey collected information on how operational performance was measured based on common industry standards for sawmills or woodland operations. Respondents were encouraged to add any additional measure not covered by the list generated and reviewed by industry experts (see Appendix 1). Respondents were also asked the frequency of performance measures and if the measures changed based on this frequency. Further, respondents provided information on transfer pricing enabling a comparison between the supplier (woodlands) and the buyer (the mill) on how prices were determined. The final category of questions addressed how investment decisions were evaluated. Analysis was restricted to descriptive analysis due to the mix of qualitative and quantitative information and incomplete information on the population size.

Results Operational measures

Mills use a number of different measures, of which the most frequently reported measures were production-related measures (volume, machine downtime) followed by safety (injury free). The least-frequently reported measures were the economic measures that focused on different measures of value (value of production, falldown, grade recovery). If a measure

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was used, it was most likely to be reported on a shift basis. The only exception was for value produced, which was measured most frequently on a daily basis. Others included feed speed (feet per minute), piece counts through trimmer, log count and cost. We did not attempt to examine whether managers saw any relationship or trade-off between safety and other measures (i.e., was safety driven by concerns over how injuries might affect production?), or if the focus reflected the stringency of provincial regulations, the increasing cost of insurance costs due to injuries, or simply part of how business is carried out in the industry.7 Economic measures (e.g., net profit, comparison to budget) were used more frequently on a monthly basis. However, value-based measures were still lower than volumebased measures in evaluating monthly performance. Other monthly measures reported included LRF (5 respondents), costs (3), grade recovery (3), and safety (2). It is interesting to note that “value produced” was used to measure performance on a daily basis by less than 10% of the respondents, but by over 50% of the respondents for monthly performance evaluation. In other words, short-term measures were focused more on production and volume, while longer-term measures increasingly included value-based measures. This is illustrated in Fig. 3, which shows the most important measures used in evaluating firm performance. The most important operational performance indicators—production measures—decrease in importance over time while economic measures (e.g., operating earnings, margin, financial statements, profitability, ROCE and cash flows) increase over time. The category, Other, most typically included safety (recorded as the primary measure, rather than “volume and safety” reported by a number of mills), but also included measures such as log count. Indeed, if we assume that safety reflects other (non-economic) performance measures, then some kind of volume-based measure (including volume and volume plus safety) accounts for 60% of the daily measures, versus 12% on a daily basis for economic measures. On a monthly basis by the same criteria, volume measures still dominate slightly; it is only on a quarterly basis that economic measures become more important with just over 40% of mills reporting it as their most important measurement. Volumebased indicators are reported by only 5% of the mills. This also points out a major inconsistency (whether measures are evaluated either on a volume only or volume and safety versus an economic measure). The preferred measure changes over time in these cases, yet it is the accumulation of daily decisions and activities that determine daily outcomes that then consequently generate monthly and quarterly results. Finally, it is important to note that 5 companies were represented by 2 or more mills. Generally, there was no consistent reporting across the mills when it came to identifying the most important performance measures; instead mills owned by the same company oftentimes identified different criteria, especially as the time period lengthened. There are 2 possibil-

72005 had seen a number of deaths and injuries in the industry, and

there had subsequently been some initiatives to highlight the importance of worker safety in 2006, including the development of a safety council bringing together government, industry and unions (Stirling 2006).

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ities: either this reflects incoherence in the strategies (where the overall company’s strategy has not been successfully translated into carrying out day-to-day operations at each mill), or this may reflect a strategic approach by the company to decentralize, giving some scope to the managers to select their specific mill-level strategy.8 A puzzle

There is a key anomaly in how mills assess performance: results indicate that production measures (e.g., volume produced, machine downtime, injury free operations) dominate short-term performance evaluation (daily or weekly), while economic measures (net profit, comparison to budget) dominate longer-term measures. While this may indicate a close connection between production and economic performance (due to the commodity emphasis of the BC industry where production levels have an influence on the cost of manufacturing), it may also indicate a lack of cohesiveness in overall performance objectives. These long-term economic objectives may reflect either firm strategies or recognition that generated economic value is the key objective of the firm. Nevertheless, these have not been internalized into daily decision-making. Perhaps an indication of that is to note that, for the few firms that did report an economic measure as their single most important measure on a daily basis, they were consistent (i.e., their measure did not switch to a volumebased or production measure over the different time periods). Instead, it was firms that either reported volume or production-based measures as the most important measure that then indicated a switch to economic measures. Woodland operations

We also interviewed woodlands managers (of which the majority were associated with a mill in our sample). Again, our focus was in determining to what extent economic criteria entered into their decision-making process, although the circumstances were slightly different, as woodlands managers were producing both a different type of product (logs for the mill) and drawing from different sources, including their own timberlands, as well as in many cases, purchasing on behalf of the mill. In this case, we were interested in 2 aspects of the decision-making: first, to what extent decisions were economic ones; second, to what extent firms were gathering or providing information that could then be used in evaluating economic performance (in particular we were interested in learning to what extent they would differentiate fibre on either a species or quality basis as a critical step in any kind of subsequent determination of economic value that fibre was generating).

8Even allowing for decentralized decision-making, this poses somewhat of a question as to why one manager might focus on generating value and another on volume, given that there should be a consistent strategic direction at the firm level unless there are other constraints affecting their decisions (e.g., one particular mill within the company operations might be responsible for ensuring production volumes are maintained for a specific customer, or there may be some unique characteristics of the operation of which we are unaware).



As was the case for sawmills, volume-based operational measures are the ones most frequently employed at the woodland level on a daily basis. However, unlike sawmill managers, woodland managers also use cost-based operational measures on a daily basis, and indeed, on a monthly basis, costbased measures exceeded the individual volume-based measures. Log quality was the most frequent individual daily measure, reported on a daily basis by almost half (48%) of the respondents surveyed. Volume produced and volume shipped to mill were reported on a daily basis by 30% to 38% of the respondents. Cost per cubic meter was recorded daily by 24% of the respondents, and all other measures were reported daily by less than 10% of the respondents. Except for value produced, all measures were reported monthly by more than 45% of the respondents and very little was reported on a quarterly basis. Most firms reported multiple criteria on a monthly basis. The volumes to mill and log quality were the most frequently used daily measures. Some respondents indicated that both production and safety measures, such as injury-free days, were important. As in the case of sawmills, concern for safety could either be considered a cost reduction measure or a public relations measure reflecting increased public attention. Fig. 5 shows the most important measures used to evaluate performance. Here, production measures predominate on a daily basis, although cost-based measures emerge as a significant indicator, as do quality-based measures. Yet again, value measures were the least used measures on a daily basis. In terms of other measures, 17% of the respondents mentioned safety and 11% environment. However, when we move to monthly based indicators, cost-based measures are by far the most commonly employed, a pattern that persists at the quarterly interval. A similar puzzle is presented by the results from the sawmills. First, while volume-based measures are the most important on a daily basis, these become far less important on a monthly or quarterly basis, and another indicator—cost— becomes the most important. This may reflect the priority of ensuring that the mill “gets its volume,” whereby managers are expected to make volume a priority with the secondary objective of ensuring that they control costs (i.e., given that managers secured the necessary volume, did they do it in a costeffective manner?) Yet this still poses the problem of how they reconcile competing objectives, especially where the possibility exists that marginal or incremental volumes are likely to be more costly. Further, value-based measures remain an infrequent measure, used by only a few mills, and in this case the frequency does not increase even as the interval over which it is measured increases. For the woodland managers, quality was nearly as important as volume, and it may be the case that this attribute influences production. The subsequent relegation of log quality as an operational measure on a monthly or quarterly basis, along with production measures, may reflect the belief that the effect of quality has been incorporated in costs on a daily basis. Yet in this case, it is not clear as to whether or not that information is explicitly utilized by woodlands managers to evaluate the effect on costs, and whether or not individual log information (or on classes of logs) is retained for subsequent evaluation on performance by the mill.


Investment criteria

Another critical way in which firms implement strategies is through the kinds of investments they make. Indeed, a firm’s investment decision-making processes can reveal not only the basis for which they form their strategies, but also to what extent they are properly evaluating their alternatives. It is not uncommon to observe the use of inappropriate tools and myopic horizons in evaluating investment decisions (Klemperer 2003). Internal budgeting procedures may restrict the scope of what can be considered eligible for investment by focusing primarily on incremental investments or only considering one element of the production process (or one part of the value chain). While consistent with company strategy these procedures may be focused on the wrong criteria (e.g., they may look only at investments that reduce costs) or utilize discount rates that are too high, thereby precluding otherwise profitable investments. When asked what criteria they used to evaluate investment decision, 21% of respondents reported that they used more than one method, indicating the high level of concern regarding investment expenditures. Given the slump in prices and profits for many lumber producers at the time (which has only worsened), most mills indicated a rather stringent set of criteria to support capital investments. The most common method reported was payback period, with the average period to recoup investment being less than 22 months (the time span ranged from 12 to 36 months). While payback period is the best evaluation tool for shortterm cash flow, it is not the preferred measure for evaluating investment decisions since, given a choice of several different investments, it does not take into account the net economic value generated over the period of the investment. When asked what attracted investment from the Head Office, many indicated that there were many results that could attract investment. Mill respondents indicated that there was a somewhat different set of criteria for attracting investment from Head Office than for evaluating their performance. By grouping responses it became clear that most (61%) indicated that various forms of cost reduction or volume increases to reduce costs attracted investment from Head Office. Only 25% indicated improving economic measures attracted this investment, while14% indicated a mixed set of variables that included both cost and economic performance. There is a further anomaly in the fact that while mill respondents consider economic measures to be the most important for long-term performance evaluation, they perceive investment decisions from Head Office to be based on purely cost reduction and not economic performance. Fig. 7 illustrates the investment methods used to evaluate woodlands investment. As was the case for sawmills, we see that payback period was the most commonly cited method with 25 months reported as the average period (the time span ranged from 18 to 30 months). Nine percent of respondents used more than one method including ROCE (return on capital expenditure) and EBITA (earnings before interest, taxes, depreciation and amortization), which are consistent with the payback strategy and required rate of return.

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Fig. 1. Performance measures at the sawmill.

Fig. 4. How woodlands measure their performance.

Fig. 2. Monthly performance measures at the sawmill.

Fig. 5. Most important measures used to evaluate woodlands performance.

Fig. 3. Most important measures used in evaluating the mills performance

Fig. 6. Investment methods used by sawmill managers to evaluate investment decisions.

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We earlier noted in our discussion of woodlands managers that we were interested in the kind of information firms use in making their decisions (in some cases, lack of economic decision-making may also be reflected in the fact that they are not collecting appropriate information). Therefore, different sets of questions asked about the kind of information firms gathered and used as input for business decisions. In the case of sawmills, we asked about a particular piece of equipment (an optimizer) that is standard in the majority of most sawmills and that uses current prices as its input information. Sawmill managers were asked whether or not they used optimizers and computer software to identify the most valuable products that can be produced from a log given a set of prices, and if they did, how current the information that they used was. For both woodlands and sawmills, managers were also asked to what extent firms differentiated their fibre input, either by species, quality, or size (as these can all affect the value of products the firm can make for a given unit of fibre input). For sawmills, non-profit-maximizing behaviour was observed that cannot be easily explained with regard to the frequency of optimization. Most of our respondents did have optimizers9 (23 had optimizers and 5 did not, which means that 82% of respondents use optimizers). Of those, the pricing in their optimizers was updated more frequently than monthly (it ranged up to yearly), with over 55% of respondents updating their pricing tables for the optimizers every 2 weeks or less. This is surprising due to the volatility of lumber prices on a daily basis. One explanation may be that often there is a substantial time delay between the time lumber is

produced, and when it is sold at market prices. Keeping an updated optimizing program may only be relevant if there is only a short delay between production and sales. However, it also may be due to the focus on reducing cost and not enhancing revenue that is apparent from our other results. Here, the optimizer may be treated as a cost centre, much like woodlands, thereby reducing the opportunity to add value to the operation. In terms of evaluating fibre inputs, only the fibre purchased either directly by the sawmills or on behalf of the sawmills by the woodland operations was taken into consideration. In this case, we were primarily interested to what extent there was information generated in the marketplace (i.e., differentiation on the basis of fibre attributes) that could subsequently be utilized in deciding how the fibre is utilized and (potentially) evaluating its effect on generating value for that fibre.10 More than ? of all sawmill and woodland firms established prices for the timber they purchased based on species and quality. In the case of sawmills, 65% of the respondents paid a set price for logs based on both species and quality. This is the economic approach to pricing a good. Fourteen percent of mills paid a set price based either on species or on quality, which could be a result of receiving only a single species (which may reflect the characteristics of the fibre basket from which they are drawing, such as areas where lodgepole pine predominates due to the response in the interior of BC to utilize beetle-attacked pine before excessive degradation occurs), and then differentiating price based only on quality. Alternatively, mills may receive logs of only a certain quality, and price the product based on species. In the case of woodlands, 55% of the firms placed an emphasis on both quality and species in setting prices when purchasing wood, compared to the 65% of sawmills that did so. A slightly greater proportion of the woodland firms did focus more on a set price for quality classes (24%) than in the sawmills (with 14%). In both cases, 14% of sawmills and 14% of woodlands paid a set price based on species. Interestingly, 7% of both sawmill and woodland firms paid a set price for logs regardless of species and/or quality. In the case of the latter 2 types (21% in which there is either no differentiation or only on the basis of species), this may reflect the circumstances of the firm’s operation where they have a homogeneous resource, or it may reflect company practice. When it comes to their own fibre, ? of sawmills and ? of woodland firms base transfer prices on the actual cost delivered to the mill, but no clear pattern emerged in these cases. Woodland managers were further asked whether transfer prices were treated as a cost centre or a profit centre. Of the 37 interviewees, 32 (86%) reported they were only treated as a cost centre. This provides little incentive to increase the value of the logs if there is any additional cost to doing so.

9Optimizers

10Where operations do carry out this kind of calculation, it is com-

Fig. 7. Investment methods used by woodlands managers to evaluate investment decisions Valuing outputs and inputs

are computer-controlled systems that maximize yield and grade at specific workstations in sawmills such as bucking operations, at the first sawing station (called a head rig), at edgers, and planers. Based on price lists and/or order files these optimizers determine exactly what products will be produced to maximize value return for each log. Different workstations can be linked together to create an optimized sawmill based on current prices.


monly known as a return to log, where the firms evaluate the net profitability of different kind of products manufactured from that fibre. In this case, firms can more accurately assess when they are making profitable decisions, as a higher log cost might be more than offset by the higher value products that can be generated from it (where all other costs are also taken into account).

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Discussion Our survey results show that there is an emphasis on production-based measures both on the manufacturing side and on the woodland side among the forest product firms surveyed. This is perhaps not too surprising given the commoditybased business within which many of these mills are operating, where the scale of production can have a strong influence on costs, and cost-based reduction strategies can be a successful short-term strategy. Indeed, the short-term focus of the industry, and emphasis on production, is apparent in the investment rules used, where relatively short payback periods are the primary method to evaluate investments, regardless of whether they are at the sawmill or in the woodlands. There also appears to be a number of inconsistencies in what measures are employed and how they are used (aside from the question of what strategies firms are pursuing). These include inconsistencies and differences in: (1) the measure that is used to evaluate mill performance (the measure varies based on the time period); (2) how investments are evaluated at the mill level versus the company level; and, (3) how operational measures are employed across mills by the same companies. In the case of both sawmills and woodlands, we found that either economic measures became more important as the interval lengthened (as in the case of sawmills) or that the relative importance of the productionbased measure switched (as in the case of woodlands), although it is not clear how the 2 different objectives are reconciled in operations. Finally, within our sample there is a smaller set of mills that use economic guidelines to evaluate performance decisions, and they do it on a consistent basis. At this time, we cannot identify what it is about these specific firms that leads to these differences, although they are associated with smaller firms that also produce more specialized products.11

Conclusion Our results show that the majority of BC forest sector firms interviewed are emphasizing volume-based measures on a daily basis, whether they are sawmills or woodlands operations. While firms do broaden their perspective as the time period lengthens to include more economic performance assessment, this raises questions as to how these longer-term assessments influence daily decisions. Potentially compounding the problem is that prevailing investment rules employed by the industry emphasize a short-term focus that is also weighted towards incremental modification, rather than towards considering larger-scale changes. There are also the exceptions to these rules; for example, some sawmills have a consistent focus on value-based measures. However, these sawmills were few in number, and our sample (which did represent the top 6 lumber-producing firms in Canada at the time) consisted largely of firms pursuing a volume-based or cost-oriented strategy. We are left with several unanswered questions. We do not know whether the discrepancy we observe in terms of what is emphasized in daily operations versus longer-term performance reflects firms still in the process of adapting to new pol11

In this case our sample size is too small to draw any definitive conclusions on the basis of our survey results, although these firms do stand in contrast to the larger sample size. 368

icy changes, or whether, despite developing new strategies, there are difficulties in turning strategic level decisions into operational ones where long-engrained attitudes and practices can persist. Kaplan and Henderson (2005) have noted that the adaptation of organizations to new circumstances (including the cognitive frames as to how people evaluate decisions) can be a lengthy and complex process.12 It may be the case that we will continue to observe the practices of the past until they are slowly supplanted by new practices, as firms adjust to the latest policy environment. An assessment of how forest product firms in other jurisdictions adapt to their policy environment, both in Canada and the US, may offer insight into this question, especially where firms elsewhere in Canada may face more constraining timber policies. Finally, we do not know the extent to which the emphasis on cost reduction is an outcome of a cost leadership strategy, nor how successful that strategy has been for the mills in our sample. We also do not know how firms may reconcile the temporal discrepancy of the different measures they use or even if they attempt to do so. We also do not know to what extent they use information generated in different parts of the value chain (prices, information on log quality) as part of their economic evaluation to the extent they do any kind of economic evaluation. It is clear that there is considerable room to expand the opportunities for decision-making on the basis of economic criteria, and we do not know whether those sawmills that did utilize economic measures showed better performance over time. These are all fruitful areas for research; especially as we start considering what kind of polices might be necessary to ensure that firms are seeking to maximize value rather than volume.

References Bouwens, J. and L. van Lent. 2006. Performance Measure Properties and the Effect of Incentive Contracts. Journal of Management Accounting Research 18: 55–75. Dillman, D. 1978. Mail and Telephone Surveys – The Total Design Method. Chapter 2. Which is best: The Advantages and Disadvantages of Mail, Telephone and Face to Face Interviews. pp.39–72. John Wiley and Sons. Garrison, R.H. 1985. Managerial Accounting: Concepts for Planning, Control, Decision Making. 4th ed. Business Publications, Plano, TX. Gibbons, R. 1998. Incentives in Organizations. Journal of Economic Perspectives 12(4): 115–132. Hill, C.W. and G.R. Jones. 1992. Strategic Management Theory. 2nd ed. Houghton Mifflin Company, Toronto, ON. Kaplan, S. and R. Henderson. 2005. Inertia and Incentives: Bridging Organizational Economics and Organizational Theory. Organization Science 16(5): 509–521.

12As

an illustrative anecdote, shortly following completion of the surveys, one of the authors met with senior-level executives of one of the major lumber producers that had a number of mills among those interviewed. In that case, the company had recently announced a strategic shift and a new emphasis on generating value that was explicitly directed at the mill and operational level; yet in comparing that strategic orientation with the responses for those mills, there was only 1 mill (among the more than 5 represented in the sample) that had even indicated any kind of economic measure rather than a production-based indicator as important on a daily or monthly basis. MAI/JUIN 2009, VOL. 85, No 3 — THE FORESTRY CHRONICLE


Kerr, S. 1975. On the Folly of Rewarding A, While Hoping for B. Academy of Management Journal 18: 769–83. Klemperer, W.D. 2003. Forest Resource Economics and Finance. McGraw Hill, New York. Kozak. R. and D. Cohen. 2001. Solution Driven Research for Wood and Wood Products: A North American perspective. Danish Forest and Landscape Research Institute, ØFORSK – Seminar om Forskning og Udvikling Vedrørende Produktion og Videreforædling af Træ [Seminar on Research and Development in Production and Further Improvements of Wood], May 2, 2001. Skjoldenæsholm, Denmark. Available at http://www.forestry.ubc.ca/cbom/presentations/solutiondrivenresearch.pdf. Milgrom, P. and J. Roberts. 1988. An Economic Approach to Influence Activities in Organizations. American Journal of Sociology 94: S154–79.


Martin, R. and D. Porter. 2001. Canadian competitiveness: a decade after the crossroads. C.D. Howe Institute, Ottawa, ON. Niquidet, K., H. Nelson and I. Vertinsky. 2007. Pricing the social contract in the British Columbian forest sector. Canadian Journal of Forest Research 37: 2250–2259. Porter, M. 1991. Canada at the Crossroads – The Reality of a New Competitive Environment. The Business Council on National Issues. Government of Canada. Ottawa, ON. Stirling, J. 2006. Addressing BC’s horrific safety record. Logging and Sawmilling Journal. May. Available at http://www.forestnet.com/ archives/May_06/industry_safety.htm. Williamson, O. 1985. The Economic Institutions of Capitalism. Free Press, London.

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Appendix 1 Survey Instrument for Sawmills: Performance Measure in Solid Wood Processing 1) How do you measure performance in your sawmill?


For each shift

For each day

Volume produced LRF (lumber recovery factor) Value produced ($ / unit vol.) Grade recovery Falldown Injury free days Machine downtime Other Other 2) How do you measure monthly performance? ❏ comparison to budget ❏ value produced ❏ volume produced ❏ net profit ❏ other (specify ❏ other (specify

) )

3) What single measure is most important to evaluate the mills performance? on a daily basis on a monthly basis on a quarterly basis 4) Do you have optimized production? ❏ Yes If no go to 5. If yes answer the following: How often do you update the software? We optimize to

❏ No every

weeks prices

5) When you purchase fibre (logs) from contractors do you: ❏ pay a set price per m3 regardless of species or quality ❏ pay a set price per m3 for each species group ❏ pay a set price per m3 for specific quality classes ❏ pay a set price per m3 based on both species and quality 6) How do you determine transfer pricing from Woodlands to Mill?

7) Does this result in a uniform price for fibre (an average $/m3) or is it differentiated? ❏ Yes it is differentiated ❏ No we use an average $/m3) If differentiated, how is it differentiated (e.g., by species, size, etc.)

8) What method do you use to evaluate investment decisions? ❏ payback period ( months), ❏ net present value %) ❏ internal rate of return (over ❏ other (specify

)

9) What attracts investment from owners or head office? (e.g., cost reduction, recovery gains, replacing labour with technology, increasing revenue, etc.)?

370


Survey Instrument for Woodlands Operations: Performance Measure in Woodlands Operations 1) Are your woodlands a: ❏ cost centre ❏ profit centre 2) How do you measure your performance?


Monthly

Quarterly

Daily targets

volume delivered to mill volume produced value delivered to mill value produced cost per cubic meter quality of logs to mill Other Other 3) What single measure is most important to evaluate woodlands performance? Daily Monthly Quarterly 4) What method do you use to evaluate investment decisions? ❏ payback period ( months), ❏ net present value ❏ internal rate of return (over %) ❏ other (specify

)

5) How do you determine transfer pricing from Woodlands to Mill?

6) When you purchase fibre (logs) from contractors do you: pay a set price per m3 regardless of species or quality pay a set price per m3 for each species group pay a set price per m3 for specific quality classes pay a set price per m3 based on both species and quality


❏ ❏ ❏ ❏

Yes Yes Yes Yes

❏ ❏ ❏ ❏

No No No No

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