Inventory Planning and Replenishment
Inventory Planning and Replenishment (IPR) is a solution for inventory control
based on reorder points. The main features of the solution are:
- Classification of parts based on the history records of inventory turnover
value, frequency and lifecycle stage.
- The classification can be used to assign inventory planning policies
which are inherited to all parts with a particular classification. This
makes it easy for the planner to deploy a differentiated planning for a
large number of parts in an efficient and a fair way.
- IPR is integrated with IFS Demand Planning, but can also be used as
a stand-alone solution. In case demand planning is used, the demand forecast
and the estimated forecast error can be used to calculate planning parameters.
- IPR contains a number of planning models which allows for successful
inventory planning of both high frequent fast movers as well as slow movers
such as spare parts.
Scope of Solution
The solution is aimed for inventory planning of parts with independent internal
or external demands. Independent demands are those that are not just a function
of a demand for another part. Typically this implies the demand for sales parts,
requested by customers or for spare parts needed for repair. Also supply should
be decoupled since a reorder point system will plan each part independently
of other parts. It means that in case a part is supplied through transformation
of other parts, no advanced signal will be given to supply also those parts
one level down in the bill of material.
In practice this means that the
IPR solution should be used mainly in distribution and spare parts management.
The solution can also be used in businesses where a component is used in a large
number of structures as the demand for that component can be seen as decoupled
from the demand for the products the component is used in.
IPR can be used
as a single planning solution within a company or in combination with other
components such as Kanban for rate-based planning and for master-scheduling
and MRP for parts with dependent demands.
It can also be used to plan parts
that are purchased, manufactured or distributed from internal suppliers such
as upstream warehouses. The solution does not include any particular support
for repair, where parts are supplied through repair of defect parts.
Define Basic Data
Like any planning solution the IPR is dependent of accurate and complete
basic data. The solution depends on a couple of basic parameters and attributes
such as lead-times, ordering cost and inventory interest rate. Those parts that
should be planned by IPR should have the Planning Method on the inventory part
set to B for reorder point based planning.
One of the most important elements in the solution is the classification
of parts. The classification is based on historical transactions and will group
parts along four dimensions:
- Asset Class or Site – the classification is done for all parts within
a site or within a particular asset class and site. The classification can
be done for the entire site if all parts are similar from a planning point
of view. The parts can also be divided into different asset classes if they
belong to different categories within the site. This is useful when it is
necessary to distinguish the classification between, for example spare parts,
raw materials and finished goods.
- Volume value – which is the product of the inventory value of the part
and the issued quantity. A part belongs to either of the classes A, B or
C which by default corresponds to 80%, 15% and 5% of the total inventory
turnover value within the asset class that the part belongs to.
- Frequency – where the number of issue transactions per month is compared
with the defined frequency limits. A part belongs to Fast Movers, Medium
Movers, Slow Movers or Very Slow Movers.
- Lifecycle stage - When the system makes the classification it considers
the lifecycle stage of the pats and classifies them in to individual groups.
As parts mature, decline and eventually become obsolete they will automatically
move between lifecycle stages and the inventory planning policies that applies
for a particular lifecycle stage will be automatically utilized.
The result can be seen as a matrix where for example, fast moving A parts
and slow moving C parts are easily recognizable. The system will create one
of those matrixes for each lifecycle stage and combination of site and asset
class.
In order for the classification to work some basic data has to be defined:
- ABC classes. By default parts that belong to class A will in total correspond
to 80% of the volume value within that asset class or site, B parts 15 %
and finally C parts, 5%. It is possible to change those percentages. The
ranges for the ABC classification are global and the same values will be
used across all parts planned by the IPR.
- Frequency limits which are used to determine if a part is considered
a fast mover, a medium mover, a slow mover or a very slow mover within its
site, asset class and lifecycle stage. The frequency limits are defined
by site or if applicable on the asset class.
- Seasonality, it is possible to indicate that the demand pattern for
an asset class should be considered seasonal. If a part is indicated as
seasonal the system will fetch its history a year back, going forward instead
of fetching the most recent history going backwards. Seasonality can be
indicated on the asset class, which means that separate asset classes should
be created for parts with a seasonal demand pattern.
- Lifecycle stage, a part will move between a couple of different, predefined
lifecycle stages. The stages are Introduction, Mature,
Decline and Expired. When the system makes the classification
it will consider the lifecycle stage of the parts and classify them in individual
groups. As parts mature, decline and eventually become obsolete they will
automatically move between lifecycle stages and the inventory planning policies
that applies for a particular lifecycle stage will be automatically utilized.
In order to determine the lifecycle stages the system uses a couple of offsets
that are defined either by site or by asset class.
It is possible to distinguish how many months of history that should be used
for the classification using the field Classification Periods on the
asset class. It is also possible to indicate the number of periods to use when
the classification job is launched.
Perform ABC, Frequency and Lifecycle Classification
The classification of parts is done on basis of the history of issue transactions.
In order to simplify the switchover, for example when IFS Cloud is replacing
another, system data can be imported into a special transaction table which
will be used together with the transactions created in IFS during the switchover
period.
The classification is useful on its own in order to understand what
the most important parts are, to identify candidates for termination as well
as parts that require extra attention. The classification is also used to define
inventory planning policies as described in the next section.
The classification
type that a part has received is shown on the
Inventory Part
page.
The classification values set by the classification job
in the
Inventory Part
page can be manually overriden and the time-period for this
manual setting of a classification parameter should then be defined. Meaning
that via a locked until date the manual values set for classification of the
part will still be the values used even after running classification job.
When running the classification job on a date later than the defined
time-frame, the classification will revert to be based on historical data.
This can be used to adjust planning parameters for new parts where the sales
history is not available but where the forecast of future demand is
considered as input for planning.
Define Planning Policies
The IPR calculates four planning parameters which are used to create replenishment
proposals. They are:
- Lot size, which is the quantity that is proposed when a part needs replenishment.
- Safety stock, which is the quantity in stock that should be held in
order to cover for the variation in demand. The larger the demand variation
is expected to be, the larger the safety stock must be in order to meet
a particular service level.
- Order point, which is the quantity in stock that triggers a replenishment
proposal.
- Next order date, which is the next date a replenishment order should
be raised for the part assuming that the part is consumed in line with its
forecast.
Planning Hierarchy
In order to calculate lot size, safety stock and order point a number of
parameters must be defined. These parameters can be defined on the individual
part, but the better way to do it is to use a hierarchy where the lowest level
is the actual parts. Any value defined in the hierarchy will be inherited downwards.
The levels in the hierarchy, starting from the top are:
1. Company
2.
Site
3. ABC – Frequency – Lifecycle
4. Asset Class
5. Commodity Group
6. Supplier
A value defined on a lower level in the hierarchy always override a value
defined on a higher level. The attributes that can be defined on each of the
levels are:
• Inventory Interest Rate
• Ordering Cost
• Service Rate
(%)
• Demand Model
• Safety Stock Model
• Lot Size Model
• Order
Point Model
• Lot Size Cover Time
• Safety Stock Cover Time
• Max Order
Cover Time
• Lead Time Factor
Together with available quantities, lead-times and demand this constitutes
all the information the system needs to calculate lot size, safety stock, order
point and next order date.
Demand Model
The value for demand model controls how the system will predict future demands
for a part. In order to calculate the planning parameters it is necessary to
have an estimate of demand and demand variation during the lead-time.
This estimate can be calculated in different ways depending on circumstances.
The possible values for demand model are:
- Forecast- this value means that the forecast and the expected demand
variation are fetched from IFS Demand Planning. When a forecast is fetched
from Demand Planning, any future changes are considered. It means if the
forecast increases or decreases for future periods, this will automatically
be taken into account and the inventory planning parameters will dynamically
change in line with the forecast. This is very useful for parts with clear
seasonal patterns, trends or campaigns.
- Yearly Prediction - the value for future demand is manually entered
on the inventory part in the field Pred Year Cons Qty.
- History - the transaction history is used to estimate future demand
and demand variation. The result is a fixed value which is considered to
be valid for all future periods.
Note that different demand models can
be used for different parts or group of parts.
Safety Stock Model
The selection safety stock model decides which method that is being used
to calculate safety stock. The following options are available:
- Manual – the value for safety stock is entered manually on the inventory
part.
- Time Coverage – the safety stock quantity is calculated as the current
demand forecast from today and the number of days into the future specified
by the value for Safety Stock Cover Time.
- Historical Uncertainty – this safety stock model calculates the optimal
safety stock quantity given a specific service rate. By service rate we
mean the likelihood that a part is available in inventory when it is demanded.
For example the service rate might be set to 97%. This means that if 100
customer orders with a quantity of 1 are received, then 97 of those orders
can be shipped directly from stock, whilst 3 of them are backordered. The
safety stock quantity is in this case dependent of:
- Historical standard deviation – the higher the variation is the
higher the safety stock must be for a given service rate. Historical
inventory transactions are used to calculate the standard deviation.
- Lead-time – the longer the lead-time is the more safety stock is
required.
- Lot Size – the higher the lot size is, the longer the replenishment
cycle becomes. It means that the inventory reach critical levels more
seldom, which in turn decrease the necessary safety stock quantity for
a given service level.
- Mean Absolute Error – this model uses the same calculation as Historical
Uncertainty, but the estimate of future demand variation is fetched from
IFS Demand Planning.
Lot Size Model
The selection of lot size model decides which method that is used to calculate
the lot size. The following options are available:
- Manual - the value for lot size is entered manually on the inventory
part.
- Time Coverage - the lot size quantity is calculated as the current demand
forecast per day multiplied by the value for Lot Size Cover Time
- Economic Order Quantity (EOQ) which is also referred to as the Wilson
formula. This is a trade-off between inventory holding cost and ordering
cost. The result is dependent on:
- The demand forecast according to the Demand Model used. The
lot size will increase as the forecast increase.
- The part cost, the lot size will decrease as the part cost increase
since the inventory holding cost is higher for more expensive parts.
- The inventory interest rate, higher the inventory interest rate
is, more expensive it is to hold inventory; thus the lot size will decrease
when the inventory interest rate increase.
- The ordering cost which represents all expenses incurred in placing
an order. An increase in ordering cost will increase the lot size.
Three additional parameters also control the lot size
- Max Order Cover Time can be defined to limit the lot size when EOQ is
used. Very cheap parts will get large lot sizes with EOQ which may cover
an unrealistic time into the future considering the risk of obsolescence
etc.
- Durability, if entered, the durability of the part will be considered.
- Min, Max and Multiple Lot Size are considered.
Order Point Model
The selection of order point model decides which method that is used to calculate
the order point. The following options are available:
- Manual - the value for order point is entered manually on the inventory
part.
- Lead Time Driven - the order point is calculated as the demand during
the lead-time plus the safety stock quantity. The demand during the lead-time
is calculated according to the valid demand model.
In addition to this four different models are available for slow moving parts,
for example spare parts. These models are based on the assumption that the demand
for the part is Poisson-distributed rather than Normal-distributed. Typically
the models for slow moving parts give more accurate results when the demand
variation is high in comparison to the average demand for the part. Accuracy
in this case is how well the actual service rate aligns with the specified target
service rate. A rule of thumb is that these models are applicable when the historical
standard deviation is larger than half of the historical demand.
The models
for slow movers are based on the likelihood that a demand for a certain quantity
occurs during the replenishment lead-time. This is after having compared against
the defined target service rate, an order point that gives a theoretical service
rate that is equal to or exceeds the target service rate is assigned. This means
that no explicit safety stock is calculated for these parts.
The available
options for slow movers are:
- Slow Movers – Lifecycle: This model uses the historical transactions
to determine historical demand frequency and quantity. On the basis of this
and the lot size the order point is calculated to meet the specified Service
Rate during the entire lifespan of the part.
- Slow Movers - Lead Time: This model works as Slow Movers – Lifecycle
with the exception that the lot size is not considered. The order point
is on this case calculated to meet the specified Service Rate during one
order cycle.
- Croston – Lifecycle: The model is similar to Slow Movers – Lifecycle
but instead of using historical transaction the values for Expected Demand
Size and Inter Arrival Time from Demand Planning are used.
- Croston – Lead Time: The model works as Slow Movers – Lead Time, but
instead of using historical transaction the values for Expected Demand Size
and Inter Arrival Time from Demand Planning are used.