Silva Fennica 42(1) research articles
www.metla.fi/silvafennica ł ISSN 0037-5330
The Finnish Society of Forest Science ׂ The Finnish Forest Research Institute
Vendor Managed Inventory in Wood
Processing Industries ע a Case Study
Manfred Gronalt and Peter Rauch
Gronalt, M. & Rauch, P. 2008. Vendor managed inventory in wood processing industries –
a case study. Silva Fennica 42(1): 101–114.
Solid structure timber (SST) is an important building material in the wood construction busi-
ness, in which its production volume is largely related to that respective business. Due to the
large variability in the demand and seasonal factors, SST producers’ inventories are likely to
be simultaneously overstocked for one type of timber and out of stock of another. An inventory
policy that ensures a high service level and relatively low stocks is required. In the present
paper, we propose the vendor managed inventory (VMI) approach for controlling the stock
of deals that are produced at a sawmill and delivered as raw material for SST-production. We
evaluate two VMI implementations against the actual inventory management for three differ-
ent market scenarios. Furthermore, we layout the necessities for reconfiguring the business
processes, and subsequently set up an organisational framework within VMI, which is indeed
applicable in this segment of the woodworking industry. In our application background, VMI
as an inventory control system is able to reduce the overall raw material stock by more than
37% by simultaneously increasing the SST service level.
Keywords building materials, service level, solid structure timber, SST, wood construction
Addresses BOKU – University of Natural Resources and Applied Life Sciences, Feistmantelstr.
4, 1180 Vienna, Austria
E-mail peter.rauch@boku.ac.at
Received 12 March 2007 Revised 30 October 2007 Accepted 12 November 2007
Available at http://www.metla.fi/silvafennica/full/sf42/sf421101.pdf
1 Introduction
chain. Solid structure timber (SST) producers are
faced with a situation where customer’s orders
The European forest products industry is currently
need to be supplied within a few days’ time, and
facing strong competition. There is an ongoing
each order that consists of several SST dimensions
concentration process in the wood-processing
must be fulfilled in whole or is thereby lost. Even
industry. New markets and arising competitors
slow seller products have to be stocked continu-
in Eastern Europe are supporting the need for sub-
ously. In the present paper, we describe a stepwise
stantial cost reductions in the forest-wood supply
vendor managed inventory (VMI) implementation
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research articles
by two wood processing companies. The vendor
Sales data /
Order proposal
VMI -
sales forecasts
produces lumber at a specific sawmill site and
system
the customer (buyer) manufactures solid wood
and glued beams for the construction industry. In
Stock
levels
order to sustain the market position, managing the
Purchase
order-delivery process between the companies in
turn becomes an important issue.
Supplier
Customer
For many companies, collaboration along the
Delivery
Delivery
Final customer
supply chain is seen as a key task. However, as
VMI supply chain
there are a number of well-known opportunities,
new challenges result from reorganising the order-
Fig. 1. Information and material flow in a two stage
delivery process and the perception of planning
VMI supply chain.
responsibilities. Disney and Towill (2003) define
a supply chain as a system consisting of material
suppliers, production facilities, distribution serv-
vendor, people that were formerly involved in the
ices, and customers who are all linked together via
ordering process can then adapt their activities to
the downstream feed-forward of materials (deliv-
customer services and special order treatments.
eries) and the upstream feedback of information
Småros et al. (2003) also use a simulation
(orders). In a traditional supply chain, each actor
approach in order to discover the impact of
is responsible for their own inventory control and
increased demand visibility on the production
production, or distribution ordering activities.
and inventory control by defining different por-
Especially when reducing chain inventories,
tions of VMI based vendor-buyer relations. They
new co-operation issues such as vendor managed
show that a vendor can even benefit from a partial
inventory (VMI) are applied. VMI is a supply
increase in visibility. Furthermore, they show that
chain strategy wherein the vendor or supplier is
the planning cycle length is an important element
given the responsibility of managing the custom-
for smoothing a vendor’s production in a VMI
er’s stock. The fundamental change is that the
approach.
ordering phase of the process is saved, and the
However, alongside the success stories of VMI
supplier is handed the authority and responsibility
implementations, failures are also reported. A
to take care of the entire replenishment process.
major barrier to the success of VMI is establishing
Reduced delivery and administration costs for
trust among supply chain partners (Kuk 2003).
the buyer as well as lower delivery costs for the
Acceptance problems result from the high trans-
vendor are reported by Holmström (1998). Fig.
parency of the buyer’s business as well as from
1 shows the information and material flow of the
the shifted inventory responsibility. Increasing the
order-delivery process in a two stage supply chain
producer’s responsibility, frequency of the deliv-
with VMI control.
eries of stocks, as well as expensive advanced
Simulation studies of two level supply chains
technology is required. Therefore, increased
conducted by Disney and Towill (2003) show
expenses for the producers are the most common
that using VMI typically halves the bullwhip
disadvantages of VMI (Simchi Levi et al. 1999).
effect. A further result of implementing VMI
In our case, one company is the shareholder of
is an improvement in customer service levels
the other, so the transparency of the business as
coupled with a significant improvement in inven-
well as trust in each other already exists as a good
tory turnover (Achabal et al. 2000). In the short
starting basis for VMI.
term, VMI usually reduces inventory-related costs
In recent research, (Boute et al. 2007) an inte-
mostly through optimising shipment quantities.
grated production and inventory analysis of order
Throughout a longer period, when the buyer and
smoothing in a two echelon supply chain where
seller adjusts their production and distribution
the retailer’s order decision has a direct impact
as well as marketing activities to VMI, the sales
on the manufacturer’s production is considered.
volume is likely to increase (Dong and Xu 2002).
With their order pattern smoothing they can bring
As the ordering responsibility is shifted to the
advantages for both parties in the supply chain.
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Gronalt and Rauch
Vendor Managed Inventory in Wood Processing Industries – a Case Study
VMI was enriched according to the princi-
lead times, expeditiously needed deals are often
ple of postponement in order to flatten demand
unavailable in due time. Large orders from SST
deviations. Van Hoek (2001) defines postpone-
customers are faced with a lead time that is given
ment as “delaying activities in the supply chain
by the total of the sawmill’s and SST producer’s
until the customer’s orders are received with the
order to delivery time. Delivery problems can
intention of customising products, as opposed to
occur if insufficient raw materials are available
performing those activities in the anticipation of
with the required dimensions at the sawmill’s
future orders”. Postponement effects depend on
round wood stock.
the product variety. The more varied the manu-
Production planning at the SST producer is
factured products are, the larger the effect of
performed according to the customer’s orders,
postponement will be (Silver et Minner 2005).
finished products stock, and raw material stock.
The applicability of VMI and redesigning the
If the SST booker thinks it is useful to replenish
entire procurement process as a prerequisite for
the raw material stock, an order is sent to the saw-
VMI in forest based industries are investigated in
mill. No explicit demand forecasting techniques
detail in the present paper. We analyse the VMI
are used. Production lot sizes at the sawmill are
approach for controlling the stock of deals that
constrained by the technical criteria of wood
are being produced at a sawmill and delivered
drying to the size of a wood kilning chamber. The
as raw material for SST-production. Two VMI
SST producer runs a traditional buyer managed
implementations are evaluated against the actual
inventory. Applying VMI necessitates real-time
inventory management under three different
data from the buyer, which is to be provided to
market scenarios. By conducting this case study
the vendor as well as a commitment that the
we will show that VMI is an appropriate manage-
vendor shall trigger orders to establish an agreed
ment approach for the forest based industry in
service level.
order to save inventory costs and to improve the
Due to the need for fulfilling customer orders
service level.
(retailers or mainly construction companies)
The present paper is organised as follows. In
within two days, the SST producer always has on
Section 2, the production process of the SST and
hand a large finished goods stock. The production
VMI approaches are explained. Section 3 shows
time within the SST producers is approximately
the structure of the simulation experiments that
one to two days if the appropriate raw material
we will conduct for testing several inventory
is in stock. The order lead time for a raw mate-
policies and VMI. The results and a comprehen-
rial order from the SST producer to the sawmill
sive discussion are provided in Sections 4 and 5,
ranges from 9 to 14 days depending on the prod-
respectively.
uct’s dimensions, where most of this allotted
time is utilised for drying the sawmill products.
Usually a SST customer orders several different
dimensions and accepts only entirely fulfilled
2 Material and Methods
orders. Therefore, even the dimensions that would
normally be treated as make to order articles have
2.1 The Production of Solid Structure
to be held in the finished products stock.
Timber
The considered supply chain map (see Fig. 2)
is displayed with arbitrary figures. Horizontal
Our utilised supply chain consists of a sawmill
cycle time (lead indicator) is the time of activi-
that delivers the main part of its deals directly to
ties, such as production planning, procurement,
a Solid Structure Timber (SST) production line.
production, order processing, transport, etc. The
The simplest product of the SST production line is
vertical cycle time is the time that an item spends
called a single SST, which is both an end product
in stock, keeping working capital and not yet
and a preliminary product for further processing
generating income. In the sawmill, production
in order to produce glued beams, namely Duo and
planning is performed only according to the SST
Trio SST. The stocks of both factories are actu-
orders and round wood stock possibilities. The
ally managed separately, and according to long
sawmill production manager uses optimisation
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Silva Fennica 42(1), 2008
research articles
software for examining the optimal round wood
tion-type finger jointed lengthwise to lamellae and
dimensions to be used for the ordered SST raw
planed. The resulting product is called a single
material dimension. The software optimises the
SST, which is, on the one hand, an end product,
value of the main product (SST raw material) and
but on the other hand, also a preliminary product
of the by-products. Depending on the available
for Duo and Trio SST. A Duo SST consists of two
round wood dimensions and sales potentials of
single SSTs that are glued together with their flat
the by-products, the production manager decides
side and then planed, and a Trio SST consists of
as to which round wood dimension is to be used
three. The last step of SST production is to cut
for a given order.
SSTs into lengths according to the customer’s
Depending on the round wood diameter, dif-
requests. The production process is shown in Fig.
ferent deal dimensions can be produced at the
3. The missing arrows indicate that some portion
sawmill. SST is made out of dried, visually graded
of timber was not used for the production of the
softwood deals. Parts of deals with material
actual cut deal dimension.
defects are lopped. Subsequently, deals are fric-
2.2 The VMI Approach for SST Production
Round
wood
Due to crowding out in the SST market as well
as to the expansion strategy of the SST producer,
management was looking for more efficient ways
of linking their processes and inventories with the
SST
supplying sawmill. The sawmill is completely,
stock
and the SST producer is partly, owned by the same
Deal
company. Therefore, a good basis for a strategic
stock
omer
alliance between both of the production sites is
T
ime
tion
o cust
given. VMI is known as a promising possibility
c
essing
duc
o
t t
for minimising system wide stock costs while
o
or
satisfying the required service levels. Therefore, a
Deal
der pr
production
prototype for a simultaneously planning deal and
SST pr
Or
T
r
ansp
SST stocks has been set up to verify the impact of
VMI for the described supply chain. The proto-
type has been programmed in MS Excel.
Time
Using the sales figures of the SST-producer, a
Fig. 2. Supply chain map of SST.
prototype of the inventory management system
Roundwood
Deal
SST
SST
production
production
production
DUO-SST
Deal
Single SST
TRIO-SST
Fig. 3. Material Flow for SST production.
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Gronalt and Rauch
Vendor Managed Inventory in Wood Processing Industries – a Case Study
consisting of a forecasting procedure and order
(booker’s policy). In our application we do not
replenishment policy was established by the
consider each specific SST-type but rather we
vendor. Stock parameters such as safety stock and
control the aggregated SST-stocks. The impact
reorder points were set dynamically in order to
of the respective SST-types (single, DUO, TRIO)
support a quick adaptation to market disturbances,
is estimated by their relative sales portion. Each
and static to verify the effects of the dynamic
specific SST can be manufactured within the
setting. Additionally, a policy to order and fore-
guaranteed order-delivery time.
cast raw material on an aggregated basis for end
The simulation prototype was used to test the
products with the same basic deal dimension
system and to find strategies for some pitfalls
was applied by combining the demand patterns
(holidays, 5 day work week, 7 day work week,
for solid construction timber with duo and trio
major order, and promotions). Various scenarios
laminated beams to a single basic SST demand.
and different inventory policies were tested to
By combining products for joint disposition,
ensure that the set up inventory management
volatility decreases because of a lower standard
system works smoothly under real world condi-
deviation of the aggregated products compared to
tions. The results of a numeric study illustrate the
specific end products. As a consequence, lower
effects of the suggested method due to various
volatility also enables the lumber producer to
market and product sales scenarios.
smoothen its production. The VMI system was
set up as a simulation prototype that is carried
out in Excel.
2.3 The Order Replenishment Process
Implementing VMI takes several project steps
that can be concisely explained as follows: 1) top
One element in VMI is to reorganise the order
management commitment, 2) process redesign,
replenishment process. In Fig. 4 we show the
3) developing inventory management systems,
developed order fulfilment process model includ-
4) develop a prototype, 5) test the prototype, and
ing the activities at the vendor’s and producer’s
6) implementation.
units. The model also explains how the replenish-
Top management of both companies recognised
ment activities are organised. The process starts
the implementation of VMI as a rather impor-
with the acceptance of a customer’s order. Next,
tant project and communicated that message to
the SST stock is checked as to whether or not the
the lower management levels. Furthermore, they
ordered unit(s) is (are) in stock. If the ordered deal
stayed in touch with the ongoing project and
is not in stock, at first, the basic deal stock that
signalled their will to realise the system. Techni-
needed to produced is checked. If it is not there,
cally important questions such as the passage of
the drying chamber, and lastly, the sawmill’s
title, use of storage, exception rules, and relevant
planned deal delivery date are checked. Knowing
decision variables were all fixed in the proc-
at which stage the needed SSTs or basic deals
ess redesign. Developing inventory management
are, the delivery date can then be calculated. If
systems such as VMI meant a radical change in
the customer accepts the scheduled delivery date,
the ordering processes of the buyer and vendor.
the order is confirmed and the ordered units are
Traditional replenishment processes, where actors
booked. Once daily forecasts are calculated at
of different companies operate independently had
the sawmill, the inventory position is compared
to be changed into an inter-organisational replen-
with the reorder point. If the inventory position
ishment process using real-time stock and sales
is below the reorder point, deals are ordered and
data.
produced. With the transport of the ordered SSTs
Stock parameters, such as safety stock and
to the customer, the process model ends. For
reorder points, are set dynamically (dynamic
dynamic VMI, safety stock and reorder points
VMI) to support a quick adaptation of inventory
are also calculated anew once daily.
control parameters to market disturbances, and
static (static VMI) to analyse the effects of these
different settings. As a third stock keeping policy,
the one actually implemented is also calculated
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Silva Fennica 42(1), 2008
research articles
Yes
accept order
check SST
unit on stock?
schedule
confirm order
book ordered
transport
stock
delivery date
No
units
to customer
once daily
check basic
deal stock
run forecast
calculation
Yes
basic deal
check SST
check inventory
on stock?
production plan
position and
No
reorder point
Yes
check drying
chamber stock
inventory
position higher
than reorder
point?
No
Yes
deal in drying
check drying
chamber?
time
No
order deal
dimension
check deal
produce deal
delivery date
dimension
from sawmill
Fig. 4. Order replenishment process.
2.4 Inventory Management System
duction lead time at the sawmill is assumed to be
12 days. The service rate was set at 98%. When
Out of one deal dimension, at least three differ-
the echelon stock inventory position drops below
ent SST dimensions can be produced. Applying
the reorder point, a new production quantity is
a postponement strategy here means summing
initialised. During the same period, the inventory
up the demand forecasts of the individual SST
position is increased by this order and after the
dimensions and putting forth the decision as to
lead time, the physical inventory also increases.
what SST dimension will be made out of the
The inventory management is based on the fol-
deal during the very last processing step. The
lowing principles:
following data were used in the inventory man-
–
Exponential smoothing is used to forecast the
agement system: sales per period and inventory
aggregate demand for each period, e.g. one day,
position, which is the sum of the stock keeping
and for each deal dimension. The method is
unit (SKU) of a basic deal in the production and
adapted according to the proposals of Gudehus
kilning chambers at the sawmill, deal stock, and
(2002) in order to cope with demand variations.
SST stock at the SST producer.
–
The forecasting method adapts the smoothing
The calculated figures are the forecast, safety
parameter for different products according to the
stock, reorder point, reorder quantity, and physi-
expected values as shown in Fig. 5. A nervous
cal stock of deals. The reorder quantity is related
volatile system works with a longer smoothing
to the capacity of the used drying kiln. The pro-
period, and vice versa.
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Gronalt and Rauch
Vendor Managed Inventory in Wood Processing Industries – a Case Study
Fig. 5. Smoothing parameter and shape of the sales development.
The calculation of safety stock, reorder point,
the kiln drying chamber. In Period 3, an order is
and reorder quantity is performed for a given
posted and will lead to an inventory increase in
production lead time and service rate. We denote
period 15, which is merely one period after a new
LT as the production lead time, σ as the standard order was generated. In periods 13 and 14 we are
deviation of the forecasted sales, and k as the
faced with stock-outs.
safety factor of the standard normal distribution.
The safety stock ss is calculated with the standard
formula: kσ LT . The reorder point s is the sum
of the safety stock plus the expected demand
3 Simulation Experiments
during the lead time. Whenever the inventory
position drops below the value of the reorder
Three different inventory policies are tested under
point, a new order is placed that will be delivered
various scenarios. The actual inventory policy
after the lead time.
of the booker as the status quo is described as a
simple algorithm that takes the week’s sales as a
forecast and checks if the future sales during the
2.5 Inventory Development Example
lead time can be fulfilled by the actual stock. In
the case of the calculated stock out, the booker
For all the stock policies we apply the same base
will place an order. The second policy is static
stock control as shown for one particular deal
VMI, wherein the safety stock and reorder point
dimension in Table 1. We consider 20 Periods,
are calculated at the beginning of the year with
in which a period in this case is equivalent to one
the previous year’s data. A dynamic VMI policy
workday. The sales column provides the sum of
is introduced where the safety stock and reorder
the sold SSTs made of the same basic deal. By
point are calculated anew for each period, i.e.
applying a postponement strategy, different SSTs
daily. Although this work was motivated by a
are put together here. The inventory position
real life case, in evaluating our approach, we used
reflects the echelon stock of a basic deal, which is
a simulation test bed to generate various sales
the sum of the stock in the production and kilning
curves. 20 sales series, each covering 250 periods,
chambers at the sawmill as well as the deal stock
were generated where the number and amount of
and SST stock at the SST producer. The order
orders are randomised, in which both seasonal-
quantity is fixed at 40500 m3 i.e. the capacity of
ity and disturbances can be modelled (Gudehus
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Silva Fennica 42(1), 2008
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Table 1. Order quantity calculation and inventory development for dynamic VMI.
Period
Sales
Forecast
Variance of
Safety
Reorder
Order
Inventory
Inventory
Physical



sales forecast
stock
point
quantity
position
increase
inventory
1
900
2012
873
6208
30735
0
38306
0
38306
2
6310
1981
880
6261
30403
0
31996
0
31996
3
768
2095
1116
7941
31713
40500
31228
0
31228
4
3034
2061
1122
7982
33116
0
68694
0
28194
5
1038
2078
1119
7964
32701
0
67656
0
27156
6
1787
2061
1118
7955
32895
0
65869
0
25369
7
3196
2056
1109
7891
32622
0
62673
0
22173
8
5102
2075
1110
7895
32570
0
57571
0
17071
9
2898
2127
1169
8316
33222
0
54673
0
14173
10
5321
2140
1163
8276
33800
0
49352
0
8852
11
500
2193
1224
8705
34389
0
48852
0
8352
12
5246
2164
1233
8771
35082
0
43606
0
3106
13
6084
2213
1283
9130
35101
0
37522
0
–2978
14
3018
2272
1360
9679
36238
40500
34504
0
–5996
15
1347
2283
1353
9629
36898
0
73657
40500
33157
16
2105
2270
1349
9594
36996
0
71552
0
31052
17
2676
2268
1339
9527
36773
0
68876
0
28376
18
576
2274
1331
9466
36684
0
68300
0
27800
19
1625
2250
1336
9508
36795
0
66675
0
26175
20
606
2241
1329
9454
36451
0
66069
0
25569
2002). Seasonality and disturbance parameters
as lost sales volume and valued with an average
were held constant within the 20 sales series to
SST price of 300 Euro/m3. Inventory holding
design three different sales figures.
costs are assumed as 10% of the sales price for
We denote the different sales figures as scenar-
the average inventory level of a year. During the
ios. The scenarios were modelled according to the
experiments, the service level is set at 98% and
real sales data from the past. Scenario 1 describes
the smoothing parameter a is adapted in the range
a standard year, which has in the SST business,
of 2.0 and 0.01.
a seasonal trend with a peak in the summertime
when the building industry is running most of its
yearly projects. However, according to the eco-
nomic situation within the normal cycle, distur-
4 Results
bances may occur at times with volatile increases
of sales. One disturbance is modelled that starts
In order to figure out the most advantageous
in period 80 and ends in period 100 (see Fig. 6A).
policy, the above-mentioned scenarios are used
Scenario 2 stands for a more turbulent year with a
to check the rationality of the described inventory
higher deviation in the number of orders as well
policies to different trends of sales. Depending
as the order quantity. Included in Scenario 2 is a
on the underlying sales scenarios, the inventory
simulated disturbance between period 80 and 100
development is shown in Figs. 7A–C, respect-
(see Fig. 6B). Scenario 3 contains one major sale
ively, for the sales data series 1 in a total of 20
that is approximately 16 times the average period
different series.
sales quantity. This large sale is handled like all
If only a single SST dimension out of a cus-
other sales (see Fig. 6C).
tomer’s complete order, which usually consists of
For all inventory policies, under all three sce-
several dimensions, is not available within a few
narios, the stock out costs and inventory hold-
days, the order is lost and can be assessed as stock
ing costs are calculated. The stock out costs for
out cost. Otherwise, having SST on stock is con-
unsatisfied demand per unit (m3) are estimated
nected with inventory holding costs. As another
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Vendor Managed Inventory in Wood Processing Industries – a Case Study
9000
A) Sales figures scenario 1
8000
7000
6000
)3 5000
4000
Sales (m
3000
2000
1000
0
0
50
100
150
200
250
Periods
16000
B) Sales figures scenario 2
14000
12000
10000
)3
8000
Sales (m
6000
4000
2000
0 0
50
100
150
200
250
Periods
35000
C) Sales figures scenario 3
30000
25000
)3 20000
Sales (m 15000
10000
5000
0 0
50
100
150
200
250
Periods
Fig. 6. Sales figures scenarios 1–3, sales data series 1.
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Silva Fennica 42(1), 2008
research articles
A) Scenario 1
B) Scenario 2
C) Scenario 3
Fig. 7. Scenarios 1–3, results of sales data series 1: physical stock for static
VMI, booker and dynamic VMI.
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Document Outline

• Vendor Managed Inventory in Wood Processing Industries a Case Study
• 1 Introduction
• 2 Material and Methods
  • 2.1 The Production of Solid Structure Timber
  • 2.2 The VMI Approach for SST Production
  • 2.3 The Order Replenishment Process
  • 2.4 Inventory Management System
  • 2.5 Inventory Development Example
• 3 Simulation Experiments
• 4 Results
• 5 Discussion
• References

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