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.