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Business process mapping and discrete-eventsimulation of two forest biomass supply chains

Johannes Windisch a,*, Dominik Roser b, Blas Mola-Yudego c,Lauri Sikanen c, Antti Asikainen a

aFinnish Forest Research Institute, Jonesuu Research Unit, P.O. Box 68, FIN-80101 Joensuu, Finlandb FPinnovations, 2665 East Mall, Vancouver, BC V6T 1W5, CanadacUniversity of Eastern Finland, School of Forest Sciences, P.O. Box 111, FIN-80101 Joensuu, Finland

a r t i c l e i n f o

Article history:

Received 1 September 2011

Received in revised form

16 May 2013

Accepted 24 May 2013

Available online 22 June 2013

Keywords:

Supply chain management

Discrete-event simulation

Forest bioenergy

Organisation of work

Forest fuel procurement

* Corresponding author. Tel.: þ358 40 801 51E-mail address: johannes.windisch@metl

0961-9534/$ e see front matter ª 2013 Elsevhttp://dx.doi.org/10.1016/j.biombioe.2013.05.0

a b s t r a c t

Previous research in forest biomass procurement has been focussing on reducing

harvesting costs. However, organisation and management of supply chains as well are

considerable cost factors. The present study applies a methodological framework to

investigate two forest biomass supply chains in different operational environments of two

European countries (Finland and Germany) in order to identify the business processes and

stakeholders making up the supply chains using a business process mapping methodology.

Additionally, the work time expenditure for organisational and managerial tasks for each

of the supply chains is estimated using discrete-event simulations.

The business process mapping revealed that the number of processes in the supply

chains varies considerably involving 213 project objects (activities, information items,

others) in the Finnish supply chain and 268 in Germany. The work time expenditure

on managerial and organisational tasks assessed by discrete-event simulation was

1483 min/100 m3 in the Finnish and 1381 min/100 m3 in the German supply chain. Even

though the results of the study are company specific and cannot be directly generalized, as

each supply chain reflects the characteristics of its operational environment, the proposed

methodology has shown its potential for the in-depth analysis of supply chains in forest

business and it is a step towards holistic cost calculation and business process improve-

ment approaches on supply chain level.

ª 2013 Elsevier Ltd. All rights reserved.

1. Introduction

The essential role of wood-based bioenergy to meet the

ambitious targets of the European Union has been recognized

by European policy makers [1,2]. The existing forest resources

in the EU would allow a considerable increase of wood-based

bioenergy utilization when managed on a sustainable

basis [3e5]. Even though there is a large potential

of technically harvestable wood biomass, the economic

97.a.fi (J. Windisch).ier Ltd. All rights reserve22

availability is still a bottleneck at current market prices as has

been cited by numerous studies [6,7].

Closing the gap between technically harvestable and

economically available potential is the major task of research

on procurement of forest biomass for energy. In recent years

numerous studies have tried to offer solutions for this chal-

lenge using different approaches. For instance, different

alternatives to procure energywood in an economically viable

way to maximise forest owners’ profit and thus increase the

d.

b i om a s s a n d b i o e n e r g y 5 6 ( 2 0 1 3 ) 3 7 0e3 8 1 371

exploitation of energywood [8e10] through improvement

and adaptation of existing procurement systems, e.g. the

harvester-forwarder chain [11,12], and new, innovative tech-

nologies such as accumulating felling heads and the logging

residue bundling system [13,14], in order to lower procure-

ment costs by increasing the productivity of the machines.

Furthermore, transportation is a significant cost factor, com-

pounded by the fact that the transportation of forest biomass

is a major challenge due to the low density of raw material

[15]. Consequently, numerous studies have been published

investigating different transport and logistics chains to reduce

transport costs [16e18]. A further important field of research

in the context of forest technology is the mathematical

modelling and optimisation of supply chains. For instance,

Gunnarsson et al. [19] modelled a supply network to provide a

decision support tool for strategic and tactical planning for the

supply of forest fuel. Philpott and Graeme [20] developed an

optimisation model for solving tactical and strategic decision

problems in a paper supply chain.

However, an important issue concerns the overall organi-

sation of work flows in the supply chains. A quite common

example for this issue is the scheduling of machinery [21],

particularly trucks, which in many cases leaves space for

improvements. For example, a significant part of the delays in

chipper operations are caused by poor operational planning

[22,23] what underlines the crucial role of operational man-

agement and emphasises the role of research that addresses

the study of the whole organisation of the supply chain

instead of focussing on the individual machine. Addressing

the operation as a whole not only involves the improvement

of machine productivity and scheduling of machine opera-

tions, but also the structure of work input in terms of

personnel efforts and supporting technology. Recently

Windisch et al. [24] indicated that a considerable potential lays

in the reduction of work time expenditure in themanagement

and organisation of forest fuel procurement operations.

This necessarily implies to have a detailed knowledge

about the different business processes and stakeholders that

conform the forest fuel supply chain. In fact, the study of

bioenergy supply chains is extremely relevant as there is an

increasing demand for the transfer of technology and know-

how from well-established to emerging bioenergy markets.

In addition, knowledge about time consumption for organ-

isational and managerial tasks that are not part of the actual

production is essential in order to improve the overall effi-

ciency by minimising non-productive workload. However,

the large variability of the supply chains and working

environments in different regions across Europe pose a great

challenge that require the development of appropriate

methodological tools.

In this sense, a method to analyse and compare different

supply chains that can help to gain a more detailed insight is

the method of business process mapping [25]. This method

presents the ability to depict processes and procedures within

and across functional units which makes it a commonly used

tool for identifying starting points for subsequent improve-

ment approaches in many different sectors, for example:

construction [26,27], agriculture [28] and public organisations

[29]. The application of mapping methodologies for system

analyses has been used in different studies. Flow-charting, for

example, was used to describe the behaviour of decision

making processes [30], describe machine interaction [31] and

has been taken as a basis for simulation models. In supply

chain management, schematic supply chain or value stream

mapping methods are used, in most cases, to investigate the

flow of goods or services from raw material suppliers to end

customers without focussing on the particular processes

involved, particularly in large enterprises in the forest product

industry [32,33].

Nonetheless, the number of publications using detailed

business processmapping has been increasing during the past

decade. It is used for optimisation approaches in roundwood

supply chains [34,35], but also to analyse business processes of

the wood processing industry [36]. Although, on a lower level

of detail, Eberhardinger used this methodology to analyse

processes in biomass procurement chains [37]. Therefore, the

application of this method together with discrete-event

simulation is regarded as a progressive approach to investi-

gate forest biomass supply chains and to gain a deeper un-

derstanding of the various processes within.

The aim of this study is to provide a methodological

framework for the in-depth analysis of the structure and

functioning of forest fuel supply chains in different opera-

tional environments. The framework is to be applied to assess

the fuel supply chains in two case studies located in Finland

and Germany and should involve gathering the relevant in-

formation for the construction and analysis of business pro-

cess maps to identify all the processes and stakeholders

involved, the estimation of the times used in each activity

involved and the overall simulation for the assessment of the

supply chain.

2. Materials and methods

2.1. Overview of the supply chains

The investigated supply chain in Finland supplies a 1.2 MW

district heating plant in the city of Eno (ENO) in the region of

North Karelia. The supply chain is managed by a local forest

service company having the procurement of industrial

roundwood and energywood as their core business. The

company organises the whole procurement operation from

purchasing stands to delivering the chips to the plant using

local entrepreneurs. The local forestry centre Metsakeskus, a

public institution supporting private forest owners, assists in

finding suitable stands for energywood exploitation. The

chipping and transportation to the plant is done indepen-

dently by the contractor who is also responsible for plant

maintenance. Forest biomass from pre-commercial thinnings

makes up a major share of the supply. The average removal

per operation is 90 m3.

The supply chain in Germany is located in the southern

part, in the municipality of Feldkirchen-Westerham (FELD). It

supplies a local 1.5 MW district heating plant in the nearby

municipality of Glonn. Similar to the Finnish case, this plant is

run by a local cooperative which is an affiliated company of

the local forest owners association (FOA). The FOA is one of

the main suppliers of raw material to the plant.

Table 2 e Nomenclature of process objects used in thebusiness process maps.

Type Object Description

Activities Payment Transfer of money between

functional units

Communication Exchange of data and paper

documents by means of emails,

phone calls, oral conversations,

postings

Action Action are performed to fulfil sub

tasks in the process such as

creating maps, evaluating stands,

moving between work sites etc.

Information

items

Data Any kind of information produced

by an activity

Paper document Paper document produced by an

activity such as forms, contracts

etc. Can involve data produced

earlier in the process

Digital data

storage

E.g. a database or Excel file

Paper document

storage

Data stored in form of paper

documents

Others Decisions Decide the path the transaction

takes through the process when

different alternatives are given

Start of process Beginning of the process

End of process Endpoints of the process which

can be successful or unsuccessful

e.g. when the forest owner did not

accept the conditions set by the

forest service provider

Actor A company, institution or other

stakeholders in the process. Can

be made up of several functional

units or act as standalone

functional unit.

Functional

unit

E.g. an operations supervisor or

logging contractor. Carries out

activities in the process to fulfil

a specific task in the supply chain.

b i om a s s an d b i o e n e r g y 5 6 ( 2 0 1 3 ) 3 7 0e3 8 1372

In general, forest operations solely for energywood pro-

curement from pre-commercial thinnings are not common in

Germany (unlike in Finland). Therefore, raw materials for

forest fuel mainly are logging residues from integrated har-

vesting operations. The logging residues are procured by the

FOA and sold to the cooperative which takes care of the

chipping and transportation using local entrepreneurs. The

average removal per logging site is 150 m3. The biomass is

regarded as a by-product, and depending on the logging site it

makes up roughly 10% of the overall removal and the average

removal per operation is 150 m3. Concerning the calculations,

there is no distinction between assortments of merchantable

roundwood and logging residues.

2.2. Research material and processing

2.2.1. Process mappingThe data for the business process mapping was gathered

using expert interviews. The interviews followed a detailed

sequence of open questions and involved key actors in the

supply chains (Table 1). The sequence of data gatheringwas as

follows: First the exact tasks of the stakeholder were outlined.

Then the specific activities involved in them were discussed

step by step. Finally, the interactions with other stakeholders

in the supply chain were covered including dependencies and

contact points between stakeholders, points and methods of

communication and data exchange and sources for conflicts

and errors. Time was reserved for open discussion so that the

sequence of activities could be developed and discussed

jointly. After the first round of interviews the maps were

created using Sigmaflow� software.

The resulting business process maps were re-evaluated in

subsequent meetings with the interviewees. After this second

round of interviews, the maps were further developed and

corrections or details were added, when necessary, until there

was agreement that no more improvements could be made.

Finally, the information provided by the different stake-

holders was cross-checked to verify whether the resulting

interactions matched to each other.

As a starting point for the data processing, basic tech-

niques for business processmapping, as described by Damelio

[25], were used. The aim of the study includes the process

sequence itself as well as the communication and data

transfers between the functional units as well as payment

processes. Therefore, process maps presenting the flow of

data and information along the supply chain besides the

sequence of activities (Table 2) were developed. They were

produced with the software Sigmaflow� Mapper, as it

Table 1 e Functional units of which the personal wasinterviewed during the data collection.

FELD ENO

Logging Contractor Forest Authority

FOA Operations Supervisor Forest Service Company

FOA Accounting Office Logging Contractor

Chipping Contractor Chipping Contractor

MWB Sales Manager

MWB Logistics Manager

facilitates drawing and handling even comprehensive process

maps. It is part of the Sigmaflow� Modeller and Workbench

software package (www.sigmaflow.com). Silverstein et al. [38]

described this tool as business process improvement software

which enables the user to draw and analyse business process

maps and build discrete-event simulation models based on

the process maps.

2.2.2. Model buildingNaturally, the sequence of processes is relatively complex and

is influenced by various decisions and events occurring over

time. It constitutes a dynamic discrete system [39]. Therefore,

discrete-event simulation models were chosen in order to

determine the work time expenditure for managerial and

organisational tasks. After the development of the business

process maps, the mean time consumption for every single

activity was estimated by a panel of three experts from the

Finnish Forest Research Institute that have been working in

the field of forest fuel procurement in both countries. In the

Exploratoryinterviews to

determine actorsand functional

units

Collection of keyfigures of thesupply chains

Identification ofkey personnel

Expert interviewsand discussion onbusiness process

Drafting ofprocess maps

Evaluation,validation,

improvement withexperts

Maps valid?

Expert estimationson time

consumption peractivity

Building ofdiscrete-event

simulation models

Validation ofresults with

experts of thesupply chains

yes

no

Fig. 1 e Flowchart of the methodological steps taken during the analysis.

b i om a s s a n d b i o e n e r g y 5 6 ( 2 0 1 3 ) 3 7 0e3 8 1 373

first round, independent estimates were provided by the ex-

perts and the resulting values were analysed. If the deviation

among the estimates provided was higher than 100% (respect

the lowest value), the estimate was then discussed by the

experts and re-evaluated in the second round. Finally, as a

means of validation, all the estimates and the overall time

consumption per stakeholder were verified by the interviewed

experts of the supply chains analysed and corrections were

included if necessary (Fig. 1).

Based on the process object types activities, others and

functional units (Table 2) used in the process maps and the

expert estimates of the time consumption, a number of

object-oriented discrete-event simulation models were built

in order to determine the organisational andmanagerial work

load (OMWL). OMWL includes all activities that are related to

Fig. 2 e Example from the business process map

organisation and management of the supply chain and the

operations. Depending on the activity, random numbers were

generated according to different distributions. Communica-

tion activities, such as phone calls and personal conversa-

tions, were approached by using a left skewed Erlang

distribution with shape parameter k ¼ 3, based on Gans et al.

concerning lengths of phone calls [40]. The other activities

were approached by using normal distribution [39]. Since in

practice the time consumption of the different activities will

vary over a wide range, the standard deviation was set to

�25% of the mean.

For the simulations, 30 different random number streams

were used and for each random number stream 30e35 simu-

lations of an average stand were performed, resulting in over

1000 simulations in total. The software used for the model

of the supply chain studied in Eno (Finland).

b i om a s s an d b i o e n e r g y 5 6 ( 2 0 1 3 ) 3 7 0e3 8 1374

building and running the simulation was SigmaFlow� Mod-

eller. An independent model was constructed for each func-

tional unit of the supply chain, resulting in 21 different

models. Two additional models were constructed in order to

assess the following conditions:

� the overall OMWL of ENO and FELD when the OMWL of the

Forest Owner is left out of the simulation

� the OMWL of the functional units in FELD that are in charge

of managing and organising the supply chain.

The results for the OMWL are presented in min/100 m3.

However, the time consumption of many activities of the

business processes, such as payments and communication,

and also actions like creatingmaps andmoving betweenwork

sites are not affected by the procured volume. Therefore, the

OMWL is also given in min per operation.

3. Results

3.1. Structure of the supply chains

3.1.1. Eno (ENO)The ENO supply chain involves 6 different actors and 7 func-

tional units (Table 3). The local forest authority Metsakeskus

(Forest Authority) supports private forest owners in forest

management activities, supervises operations, and can sug-

gest forest areas to be harvested. The forest owners (Forest

Owner) decide to perform a forest management operation in

their forest, for instance a pre-commercial thinning, and

monitors the operations in this forest. The forest service

company (Forest Service Company) usually buys the assortment

as standing timber and takes care of planning and carrying out

of the procurement operation. Local entrepreneurs are con-

tracted for logging and forwarding (Logging Contractor) as well

as chipping and transportation of chips (Chipping Contractor).

The last actor in this supply chain is the district heating

cooperative which is the customer buying the chips. It is

represented by two functional units: The accounting office

(Accounting office) and the chairman of the cooperative

Table 3 e Grouping of functional units for the two supply chai

Group FELD

Actor Functional unit

FO Forest Owner Forest Owner

FA Forest Authority Forest Authority

FSP Forest Owners Association FOA Operations Superv

FOA Accounting Office

Timber Broker Timber Broker

CON Logging Contractor Logging Contractor

Chipping Contractor Chipping Contractor

Hauling Contractor Hauling Contractor

PLA MW Biomasse MWB Logistics Manage

MWB Sales Manager

MWB Plant Manager

MWB Accounting Offic

(Chairman). These two play an active role in the monitoring of

deliveries and payment of delivered chips. The accounting of

the chips is based on calorific value, like it is common practice

in Finland.

3.1.2. Feldkirchen-Westerham (FELD)The FELD supply chain involves 8 actors and 12 functional

units (Table 3). Like in ENO, the forest owner (Forest Owner) and

the local forest authority (Forest Authority) are involved in the

supply chain. The Forest Authority supports and monitors pri-

vate forest owners and their forest management activities.

If the Forest Owner decides to contract work to the local FOA,

the FOA operations supervisor (FOA Operations Supervisor)

takes over. In collaboration with the Forest Authority, the

FOA Operations Supervisor plans the treatment of the stand.

The operations are carried out by a local logging contractor

(Logging Contractor) which is contracted by the FOA Operations

Supervisor. Once the logging operation is completed, the tim-

ber broker (Timber Broker) measures both the roundwood and

energywood assortments in the forest. This procedure is used

to guarantee unbiased measurement by a neutral individual.

After the measurement the energy cooperative, in the form of

the logistics manager (MWB Logistics Manager), takes over. The

MWB Logistics Manager visits all energywood assortments on

offer, checks quality and volume and negotiates the purchase

price with the FOA Operations Supervisor. After the purchase,

the pile is added to the stock. TheMWB Logistics Supervisor is in

touch with the second functional unit of the cooperative: the

plant manager (MWB Plant Manager). When the bunker of the

plant needs to be refilled, theMWB Logistics Manager schedules

a suitable time with the chipping contractor (Chipping

Contractor) and the haulage company (Hauling Contractor).

Contrary to the supply chains in ENO, the responsibility for

the processing and transportation of chips lies with the chip

customer. When the chipping operation is finished, the

monitoring and accounting is done by the accounting office

(MWB Accounting Office) and sales manager of the energy

cooperative (MWB Sales Manager). The accounting office of the

FOA (FOA Accounting Office) monitors the incoming payment

and matches them with their database and finally pays the

Forest Owner and the Logging Contractor. The accounting of

ns analysed in FELD (Germany) and ENO (Finland).

ENO

Actor Functional unit

Forest Owner Forest Owner

Forest Authority Forest Authority

isor Forest Service Company Forest Service Company

Logging Contractor Logging Contractor

Chipping Contractor Chipping Contractor

Energy Cooperative Chairman

Accounting Office

r

e

PLAFO FSP CONFA

Finding stand

Negotiations and completion of contract

Preparation of logging

Logging

Logging follow-up

Payment to forest owner and logging

contractor

Preparation of chipping

Chipping and transport to plant

Chipping follow-up

Accounting for biomass

Supervision

Payment to chipping

contractor

Evaluation of calorific value

Fig. 3 e Map of sub-processes involved in the procurement process in the supply chain of Eno in Finland (FO: Forest Owner;

FA: Forest Authority; FSP: Forest Service Company; CON: Logging Contractor, Chipping Contractor; PLA: Chairman,

Accounting Office).

b i om a s s a n d b i o e n e r g y 5 6 ( 2 0 1 3 ) 3 7 0e3 8 1 375

forest biomass is based on volume what is still common

practice in Germany, among others.

3.2. Business process maps

The business processing mapping revealed a large number of

activities in the two supply chains which are undertaken

during the procurement process. As presenting the entire

processmaps is not possible due to their size, a segment of the

process map for the ENO case is provided (Fig. 2). Figs. 3 and 4

present the sub-processes involved in the procurement pro-

cess. The functional units are grouped as presented in Table 3

to lower their complexity: The functional units providing

services to the Forest Owner are grouped in forest service

providers (FSP). One group represents the contractors (CON)

and another one the functional units of the actor running the

heating plant (PLA).

The results of the analysis identified 183 activities and a

total of 268 process objects for the supply chain of FELD in

Germany, and 128 activities and a total of 214 process objects

for the chain in ENO, Finland reflecting a higher organisational

and managerial effort put into the operations from forest to

the plant for the FELD plant.

The differences regarding the responsibilities are reflected

by the distribution of activities (Fig. 5) aswell as by the number

of information items produced (Fig. 6). In the supply chain of

ENO a single functional unit, the Forest Service Company, is in

charge of organising the entire fuel procurement operation

(purchasing, organisation, logging, processing, transportation,

payments). In the supply chain of FELD multiple functional

units take care of the organisation. The FOA Operations Super-

visor, the Timber Broker, and the FOA Accounting Office manage

the operation from finding the stands to the logging operation

to measuring and selling the raw material. As MW Biomasse

PLAFO FSP CONFA

Finding stand

Negotiations and completion of contract

Negotiations and completion of contract

Preparation of loggingPreparation of logging

Logging

Manual measurement of

removal

Logging follow-up

Evaluation of quality and purchase

Preparation of chipping

Supervision

Chipping follow-up

Accounting for raw material and

chipping

Payment forest owner and logging

contractor

Supervision

Chipping and transport to plant

Fig. 4 e Map of sub-processes involved in the procurement process in the supply chain of Feldkirchen-Westerham in

Germany Germany (FO: Forest Owner; FA: Forest Authority; FSP: FOA Operations Supervisor, FOA Accounting Office, Timber

Broker; CON: Logging Contractor, Chipping Contractor, Hauling Contractor; PLA: MW Biomasse Logistics Manager, MW

Biomasse Sales Manager, MW Biomasse Plant manager, MW Biomasse Accounting Office).

b i om a s s an d b i o e n e r g y 5 6 ( 2 0 1 3 ) 3 7 0e3 8 1376

itself takes care of the biomass supply, the MWB Logistics

Manager, MWB Sales Manager and the MWB Accounting Office,

are involved in the organisation of the chipping operation and

the accounting of it. Taking this into consideration the num-

ber of activities occurring for the organisation and manage-

ment of the SC is 72 in ENO and 103 in FELD.

A noteworthy difference between the supply chains is that

forest owners in the Finnish supply chain are much more

involved in the forest operations compared to the German

one. Furthermore, the forest work carried out by the con-

tractors is usually done more independently and contractors

are given more responsibility than in Germany. For example,

the Logging Contractor in Finland has the final decision on

which trees are going to be cut whereas in Germany that de-

cision lies with the Forest Authority. Furthermore, in Germany

the logging sites are monitored on a daily basis by the FOA

Operations Supervisor and chipping operations by the MWB

Logistics Manager. This is one reason for a lower amount of

activities in the procurement process in ENO.

Fig. 7 gives an overview of the data exchanges between

the different functional units and the links between them. The

numbers shown are maxima, meaning that not all of these

exchanges are executed in every procurement operation.

For instance, if an operation runs without any errors and

failures the number can be significantly lower. The total

number of data exchanges per operation is 39 and 66 in ENO

and FELD, respectively.

3.3. Time consumption

The results showed that the overall average time consumption

of the organisational andmanagerial work load (OMWL) in ENO

Fig. 5 e Distribution of the number of activities, including

actions, communications and payments, by group of

functional units of Feldkirchen-Westerham (FELD) in

Germany (FO: Forest Owner; FA: Forest Authority; FSP: FOA

Operations Supervisor, FOA Accounting Office, Timber

Broker; CON: Logging Contractor, Chipping Contractor,

Hauling Contractor; PLA: MW Biomasse Logistics Manager,

MW Biomasse Sales Manager, MW Biomasse Plant

manager, MW Biomasse Accounting Office) and Eno (ENO)

in Finland (FO: Forest Owner; FA: Forest Authority; FSP:

Forest Service Company; CON: Logging Contractor,

Chipping Contractor; PLA: Chairman, Accounting Office).

Fig. 6 e Number of information items, including e.g. data,

paper documents, by group of functional units of

Feldkirchen-Westerham (FELD) in Germany (FO: Forest

Owner; FA: Forest Authority; FSP: FOA Operations

Supervisor, FOA Accounting Office, Timber Broker; CON:

Logging Contractor, Chipping Contractor, Hauling

Contractor; PLA: MW Biomasse Logistics Manager, MW

Biomasse Sales Manager, MW Biomasse Plant manager,

MW Biomasse Accounting Office) and Eno (ENO) in Finland

(FO: Forest Owner; FA: Forest Authority; FSP: Forest Service

Company; CON: Logging Contractor, Chipping Contractor;

PLA: Chairman, Accounting Office).

b i om a s s a n d b i o e n e r g y 5 6 ( 2 0 1 3 ) 3 7 0e3 8 1 377

and FELD is 1335 and 2071 min/operation, respectively (Fig. 8).

The simulations also demonstrated that the supply chain with

the highest number of functional units and activities involved

(FELD) also involves the highest OMWL. As the assortments

produced differ between the supply chains, the results of

calculating the OMWL per 100 m3 gives a slightly different

picture. While in ENO a work time input of 1483 min/100 m3 is

required, in FELD it amounts to 1381 min/100 m3 given the

higher output of the roundwood procurement operations.

The share of OMWL per grouping of functional units for

both supply chains (Fig. 8) showed a broader range in the case

of ENO. In this case, the Forest Service Company has the largest

share with a total of 710 min/operation (789 min/100 m3). The

organisational tasks carried out by the Forest Service Company

are taken care of by multiple functional units in FELD

grouped in FSP. If their shares of the OMWL are simulated

in a separate model, the result is 913 min/operation

(609 min/100 m3). The results also show that the Forest Owner

in ENO is more involved in the overall processes compared to

FELD. In addition the involvement of the Forest Authority in

FELD is higher due to the fact that the district forester is

marking stands before harvesting and acts as a mediator

between Forest Owner and Forest Owners Association. Also the

Logging Contractor’s involvement in FELD is higher than in

ENO due to higher organisational effort in the preparation of

the logging both in terms of communicating with all involved

stakeholders and practical arrangements of the harvesting

operation.

4. Discussion

This study focused on business process mapping and simu-

lation of forest operations which has not been carried out

earlier in this form. Nonetheless, the general study set up is

similar to earlier studies using discrete-event simulation as

demonstrated, for example, by Tolvanen-Sikanen et al. [30]

and Vaatainen et al. [31]. In these studies as well discrete-

event simulation models were developed on the basis of

process flowcharts. However, the focus of research in the

previous studies was centred on decision making in timber

buying processes and machine interaction, respectively. The

present study again focused on the investigation of business

processes.

There is a wide variability in the results of previous studies

related to the estimation of work load of state foresters.

While Baumann’s study resulted in a work load of only

270 min/100 m3 [35], Hug determined a much higher figure of

960 min/100 m3 [34]. When comparing similar functional

units, the results of this study for FELD and ENO are

a)

Forest service provider Contractors PlantForest owner/Forest

Authority

8

10

2

14

51

3

31

11

Forest service company

Forest owner Logging contractor

Forest authority

Energy cooperative chairman

Energy cooperative

accouting office

Chipping and transportation

contractor

b)

PlantContractorsForest service provider

Forest owner/Forest authority

57

5

5

1 4

1

1

1

1

42

24

1 1

99

21

1

Forest authority

Forest Owner

Timber broker

Forest owner association

accounting office

Forest owners association operation supervisor

Transportation contractor

Logging contractor

Chipping contractor

MW Biomasse plant manager

MW Biomasse sales manager

MW Biomasse logistics manager

MW Biomasse accounting office

Fig. 7 e Number of total data exchanges between the functional units of the supply chain in Eno (a) and Feldkirchen-

Westerham (b). The numbers shown are totals, meaning that not all of them are necessarily exchanged every time.

b i om a s s an d b i o e n e r g y 5 6 ( 2 0 1 3 ) 3 7 0e3 8 1378

606 min/100 m3 and 792 min/100 m3, respectively. It must be

taken into account that there are several differences in the

setup of the various supply chains that precludes a direct

comparison. For instance, in the FELD case energywood is only

a by-product of roundwood procurement from commercial

thinnings and final fellings, which covers the overall

procurement costs and makes the operation profitable. The

ENO case represents an energywood operation from young

stands with a significantly lower recovery per ha.

The analysis of forest energy supply chains is a challenge

due to the fact that forest energy operations are often inte-

grated into traditional roundwood harvesting operations as

0

500

1000

1500

2000

2500

3000

ENO FELD

OM

WL

(m

in/1

00m

3)

Case

Fig. 8 e Comparison of the organisational and managerial

work load (OMWL) in the supply chains of Feldkirchen-

Westerham in Germany (FELD) and Eno in Finland (ENO).

The high-low lines show the absolute minima and

maxima of the OMWL.

0

100

200

300

400

500

600

700

800

900

FO FA FSP CON PLA

OM

WL

(m

in/1

00

m3)

ENO

FELD

Fig. 9 e Organisational and managerial work load by group

of functional units in Feldkirchen-Westerham (FELD) in

Germany (FO: Forest Owner; FA: Forest Authority; FSP: FOA

Operations Supervisor, FOA Accounting Office, Timber

Broker; CON: Logging Contractor, Chipping Contractor,

Hauling Contractor; PLA: MW Biomasse Logistics Manager,

MW Biomasse Sales Manager, MW Biomasse Plant

manager, MW Biomasse Accounting Office) and Eno (ENO)

in Finland (FO: Forest Owner; FA: Forest Authority; FSP:

Forest Service Company; CON: Logging Contractor,

Chipping Contractor; PLA: Chairman, Accounting Office).

b i om a s s a n d b i o e n e r g y 5 6 ( 2 0 1 3 ) 3 7 0e3 8 1 379

was the case in FELD. This makes the analysis more complex

and furthermore a clear separation is not possible in many

cases. In the future, as the demand for forest biomass for

energy is increasing, it can be expected that biomass

increasingly will be procured from young stands. As such

operations are economically critical, supply chains with lean

and efficient business processes will be required.

Generally, the quality of the process maps strongly de-

pends on the knowledge and experience of the interviewees

and their awareness of the supply chain. Therefore, an itera-

tive interview process with experienced practitioners

involved in the actual operations was chosen as a means

of cross-validating the results and the time estimates.

Their strong involvement as data suppliers, observers, and

evaluators ensures a realistic picture of the real-life working

processes. Nonetheless, business process maps cannot show

the complete reality since the processes within supply chains

are highly flexible, among other reasons. This seems to be the

case particularly in small-scale district heating plants where a

lot of the work is shared between the different functional

units.

The study revealed interesting new results related to the

design and set up of supply chains in two different operational

environments. The investigation of the supply chains revealed,

for example that the number of activities carried out by the

Forest Owner in ENO exceeds FELD by one third. The OMWL is

even four times higher. This indicates that the Forest Owner’s

involvement with their forest is much larger in ENO and that

theyspendmoretimemonitoring theoperations intheir forests.

However, many of the activities carried out by the Forest

Owners, for example monitoring the logging and checking the

worksitesafter theoperations,arenotof immediate importance

for the operation itself. Nonetheless, they influence the overall

OMWL inENOconsiderably as canbe seen from thedistribution

in Fig. 9.When the Forest Owner’sOMWL isnot considered in the

simulation, the difference between the total OMWLs of ENO

(981 min/operation) and FELD (1986 min/operation) indicates a

higher work load in FELD, even when the higher volume recov-

ered is considered (ENO: 1090 min/100 m3, FELD: 1324 min/

100 m3). When these models are used for cost calculations it

must be considered whether taking the Forest Owner’s opportu-

nity costs into account ismeaningful and a careful analysis has

to be done which activities performed by the Forest Owner are

necessary from an operational point of view.

Finally, the use of process maps for the critical evaluation

of each process object is essential to answer the increasing

number of questions surrounding the more intensive use of

forest biomass for energy, as among others, the reasons of

certain operational environments to have less contributors

and stakeholders in the chain, the mechanisms involved in

the information flows among stakeholders, whether the

OMWL can be decreased by eliminating stakeholders and/or

by centralising responsibilities, and what are the potentials of

modern information and communication technologies to

improve the overall chain efficiency.

5. Conclusions

The present study investigated supply chains in two different

locations in European countries and provided a detailed

insight into their internal structure. The business process

mapping revealed considerable differences in the numbers of

activities and functional units involved in different opera-

tional environments. Additionally, the work expenditure

b i om a s s an d b i o e n e r g y 5 6 ( 2 0 1 3 ) 3 7 0e3 8 1380

related to managerial and organisational tasks defined as

organisational and managerial work load (OMWL) was inves-

tigated for the supply chains as a whole and for each of the

functional units. Although the maps are company specific,

both supply chains reflect the characteristics of their opera-

tional environments and can be used to analyse similarities

and differences between these.

The methods and results provided are essential for un-

derstanding the supply chain structure and can be used as a

basis for a modelling approach to develop lean business pro-

cesses for forest biomass procurement. Future research must

be addressed to improve the overall efficiency of supply

chains for forest biomass for energy, for example by imple-

menting a process re-engineering method.

Acknowledgements

The authors are in debt to all enterprises and entrepreneurs

who have provided their valuable time and data, especially

Metsapalvelu Turunen in Eno, Waldbesitzervereinigung

Holzkirchen, and MW Biomasse in Feldkirchen-Westerham.

Also, we would like to thank the help of METLA experts, in

particular Robert Prinz for his help with supplying estimates

for feeding the models. Furthermore, we would like to thank

Urpo Hassinen of Metsakeskus, Gerhard Bauer as well as

Klaus Kagerer of theWaldbesitzervereinigung Holzkirchen for

evaluating and validating the process maps and the expert

estimations on the OMWL.

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