Resources Archive

Network optimization

When your inventory network consists of multiple inventory points, the entire network can be optimized using multi-echelon optimization (MEO). As the inventory level at an inventory point influences the expected availability of other inventory points, an integral optimization is required.

Echelons

In inventory networks, echelons are different distribution levels, representing a link in the supply chain network. Inventory points in a certain echelon typically receive supply from an upstream echelon and fulfill demand for a downstream echelon.

In Lanza, this is modelled by differentiating between local and central warehouses. Local warehouses are network end-points that directly serve customer orders, while central warehouses are all intra-network warehouses that serve network replenishment orders.

Multi-echelon optimization (MEO)

The algorithm used for MEO is based on consists of four steps:

Calculate forecasts for local warehouses,
Calculate lead time for central warehouses,
Create scenarios for possible central inventory levels and corresponding required local inventory levels to satisfy availability targets,
Choose scenario that minimizes total network inventory.

The calculations are based on a ‘waiting time’ principle, where the lead time for local warehouses is based on the (expected) waiting time for the central warehouse.

Combining direct and downstream demand

In some, more complex networks, an inventory point can serve as a supplier for downstream echelons but also serve direct customer demand. In this case, Lanza combines direct and downstream demand for this inventory point, making sure that customer availability targets are achieved and total inventory value is optimized.

Supply management

Managing supply is essential in spare parts management. Lanza supports this process in several ways. Amongst others by using realistic lead times, giving insight into historical supply, and by optimizing your purchasing efficiency.

Lead times

Realistic lead times are essential to accurately determine inventory levels. In Lanza, there are three ways to determine what lead time to use in calculations:

Actual lead time
Historical average lead time and lead time deviation, when reliable*.
Default lead time
Lead time from ERP-system.
Manual lead time
Manually enter a lead time and lead time deviation.

* when reliable: with the setting ‘Actual’-lead times, the historical lead times are only used when they are considered reliable. What is considered reliable is dependent on . The exact numbers are configurable in the global settings, the default values are a maximum coefficient of variation of 1 and a minimum number of deliveries of 3. If the lead times for a certain part do not comply with these restrictions, the default lead time is used.

Additional lead times

On top of the lead time from the supplier, it is important to consider any internal processing time that is necessary to acquire new parts. In Lanza, these are split up into internal processing time (e.g., the time to receive goods in the warehouse) and review period (e.g., the time to convert a order trigger into a purchase order).

These additional lead times can be configured per segment and on a part-level.

Repairables and repair lead times

For repairable parts, Lanza also accounts for the difference between new-buy purchase and repair lead times. For more information, see Repairables.

Order quantities

Correct order quantities are important to optimize your purchasing efficiency. For this purpose, Lanza calculates optimal order quantities. This is done with three methods:

Economic Order Quantity
Order quantity that minimizes the long term holding and order costs. To determine the holding and order costs, the cost per order and holding cost % are configurable per segment and on a part-level. Note that it is possible to limit the order quantity to at maximum be the expected demand over a certain period, e.g., 2 years as in the example below.
Interval
Order quantity that orders the required amount to satisfy demand in a certain period of time, or ‘interval’. The length, in number of days, of the interval is configurable per segment and on a part-level. Often the interval is differentiated based on the segment (larger intervals for cheap parts and smaller intervals for expensive parts).
Manual
Manually enter an order quantity.

Minimum and rounding order quantities

Lanza is able to account for supply restrictions imposed by suppliers or other factors. This is done by entering a minimum order quantity (MOQ) or rounding quantity (MOD) on a part-level. On a segment and part-level, you can choose to account for or ignore the MOQ/MOD restrictions.

A minimum order quantities (MOQ) stipulates that the order quantity should at least be the MOQ. If activated, Lanza compares the calculated order quantity with the MOQ, if the calculated order quantity is lower, the MOQ is used as order quantity. The MOQ is often used to account for supplier restrictions.

A rounding order quantity (MOD) stipulates that the order quantity should be a multiple of the MOD. If activated, Lanza rounds the calculated order quantity to the closest, or most optimal, multiple of the MOD. The MOD is often used to account for packaging sizes, e.g., there 100 screws in a container and purchasing is done per container.

Demand forecasting

Lanza offers three planning methods: reactive, proactive, and mixed. For each planning method, different forecasting algorithms are available. These settings can be adjusted on a segment and part level basis.

Configurable settings include:

Planning method
Forecast method
Smoothing factors (if applicable)
Demand stream
Initalisation period

Reactive planning

Suitable for forecasting based on historical demand. Lanza offers specialized forecasting algorithms aimed at fast moving and slow moving parts.

Fast movers

Lanza offers multiple forecasting algorithms for fast moving-parts. Where applicable, smoothing factors can be adjusted.

Moving Average (MA), applicable for parts with steady demand
Single Exponential Smoothing (SES), applicable for parts with fluctuating demand
Double Exponential Smoothing (DES), applicable for parts with trending demand
Triple Exponential Smoothing (TES) or Holt-Winters, applicable for parts with seasonal demand
Optimal, option to let Lanza choose the optimal method based on minimizing the forecasting error

Slow movers

Lanza offers specialized forecasting algorithms to tackle the challenges of forecasting slow moving-parts. Because of the lack of data, regular forecasting methods often do not provide accurate results. For more information on forecasting slow movers, see Slow mover management.

Croston, applicable for (cheap) slow movers with intermittent demand.
Typical Demand Quantity (TDQ), applicable for (expensive) slow movers with lumpy and intermittent demand.

Proactive planning

Suitable for forecasting based on future expected demand. Future expected demand is typically gathered from future maintenance schedules, sales forecasts, production planning, or other sources of future expected demand.

Within future expected demand, Lanza differentiates between different demand streams, such as fixed reservations (amount and timing of demand is known beforehand, e.g., for preventative maintenance) and projected demand (amount and timing of demand is uncertain, e.g., for inspection-based maintenance). It is possible for Lanza to assist in creating future expected demand based on reliability information, for more information see reliability-based planning.

Using proactive planning, the reorder point is calculated based on the expected demand of a future planning period. This planning period can be configured by the user by adjusting the planning window. Using default settings, the planning window is the period between t₀ + lead time ↔ t₀ + lead time + lead time.

Mixed planning

Suitable for forecasting based on a combination of historical and future expected demand.

Within historical demand, Lanza differentiates between different demand streams, such planned and unplanned demand. Where possible, accounting for this difference enhances the forecasting accuracy.

Reliability-based planning

A specialized way, developed for the MRO-world, to provide input the proactive or mixed planning approach is to use reliability information.

In this approach, Lanza forecasts demand based on:

Asset utilization
Accounting for usage hours, travelled kilometers, on-offs, landings, etc.
Failure behavior
Accounting for Mean Time Between Failure (MTBF) or Mean Time Between Unscheduled Removal (MTBUR).
Installed base
Accounting for the installed base for a part on asset and asset type-level.

Test

This is a test block

Inventory models

The basis for each planning concept is an inventory model. Lanza has three inventory models: fast, slow, non.

Fast

For fast movers, Lanza uses a R,s,Q-inventory model, calculating the reorder point and order quantity. Inventory is reviewed every period (R). When the inventory drops below the reorder point (s), a replenishment is triggered for replenish the inventory with the order quantity (Q).

Applicable for fast moving parts
Uses R, s, Q-model
Assumes normal distribution of demand
Default model for: ‘Wholesale’, ‘Lean’, ‘Proactive’

Slow

For slow movers, Lanza uses a S-1, S-model, calculating a basestock level. When inventory drops below the basestock level (S), a replenishment is triggered to replenish the inventory back to the basestock level.

Applicable for slow moving parts
Uses S-1, S-model
Assumes (compound) Poisson distribution of demand
Default model for: ‘Just in case’

Non

For non-movers, Lanza uses no inventory model, as there is no demand.

Applicable for non-moving parts
Default model for: ‘Non stock’

Classification

Lanza lets you classify your parts in the Classification app. Based on the data available Lanza classifies your parts into assortments and segments.

Assortments

Lanza is able to categorize your parts portfolio into so called assortments. Assortments are groups of parts that can be used for reporting and for optimization purposes. Each assortment contains an optimization matrix.

Segments

This matrix is used to classify the parts in each assortment over different segments. These segments are determined by the 2 dimensions of the matrix. These dimensions are technically customizable, but we always advise to use Price and Demand Frequency.

Each dimension (in the image above: Price and Demand frequency) has a few thresholds. These thresholds can be altered by a user. With the right thresholds an accurate division of the parts over the matrix can be achieved.

Note: it is possible to configure extra rows or columns if needed. For example when you want to separate extreme slow movers.

Planning health check

One of the additional services offered by Lanza is the planning health check. For companies that use Lanza without any additional support, it is strongly recommended to perform a yearly planning health check.

Why?

You are, or will be, using Lanza and want to assure that you get the maximum value from the software. Together, we make sure that: Lanza is used in the intended way, Lanza is set-up correctly to achieve my business targets, and Lanza utilizes smart business rules to automate recurring processes and checks.

What?

The result of the planning health check is a scorecard on six focus areas, including proposals and recommendations for improvement. The focus areas are:

Alignment with business targets
Do the settings comply with your business targets, are expected results achieved, and does Lanza have the right scope these targets?
Utilization and processes
How is Lanza used, do you follow the correct processes, are there additional efficiencies to be found?
Classification and planning concepts
Is your classification still up-to-date and are planning concepts configured according to best-practices?
Relevance check
Are custom additions to Lanza still relevant and up-to-date?
Manual changes
What patterns are distinguishable in manual changes, are these changes sustainable, can these changes be automated by using business rules?
Adoption of functionalities and best practices
Are you using the latest new functionalities and following Lanza best practices?

Technical support

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