Final Exam Flashcards
A few hallmarks of an APS system usually include:
- fewer internal users than ERP systems.
- the use of memory resident models in addition to traditional data base management systems.
- advanced planning & scheduling functionality.
- advanced optimization algorithms such as linear programming and other heuristics.
- planning at a finer time increment.
- ability to do rapid what-if simulation.
- advanced problem notification.
Major APS software providers are:
- SAP
- i2 Technologies
- Manugistics (now JDA)
- Oracle (up and coming)
- plus others.
The SAP APO application is SAP’s version of
Advanced Planning & Scheduling
APO is bundled with several other advanced planning applications into mySAP SCM 5.0.
- Advanced Planning & Optimization (APO)
- Forecasting and Replenishment–retail.
- Inventory Collaboration Hub
- Event Manager
- Extended Warehouse Management
(^^all of those 5 things have one thing in common—> all used for supply chain.
APO is all about
planning.
APO Demand Planning (DP) is used
to create a forecast of market demand for your company’s products.
APO DP allows you to take into consideration the many different causal factors that affect demand.
DP Contains a large library of statistical forecasting models.
-customers may also develop unique forecasting models using a powerful macro tool.
Forecasts created by APO DP may be released to
APO Supply Network Planning or passed to R/3 for MRP planning.
APO Supply Network Planning (SNP) integrates
purchasing, manufacturing, distribution, and transportation so that a comprehensive tactical planning and sourcing decisions can be simulated and implemented on the basis of a single, global consistent model.
Starting from a demand plan, Supply Network Planning creates a
medium-term, rough-cut plan for fulfilling the estimated sales volumes.
Supply Network Planning uses advanced optimization techniques, based on
constraints and penalties, to plan product flow along the supply chain.
APO Production Planning/Detail Scheduling (PP/DS) is intended to be a
short-term (1-6 weeks), detailed planning and scheduling tool.
The PP portion of PP/DS is capable of creating
finite supply chain plans taking capacities into consideration.
The DS portion of PP/DS is capable of creating
optimized scheduling sequences.
PP/DS accomplishes its primary mission by
using various advanced heuristic and linear programming algorithms.
APO Global Available to Promise (GATP) is
an advanced order promising tool.
GATP extends the Available-To-Promise capability currently in SAP R/3 to include:
- Multiple Plant Planning
- Simulation of orders (Capable-To-Promise)
- Rule-based order promising.
APO Transportation Planning/Vehicle Scheduling (TP/VS) is intended to
optimize the planning and scheduling inbound and outbound freight.
The Transportation Planning portion of TP/VS enables you
to make optimal use of the available capacity of trucks, trains, ships, and airplanes.
The Vehicle Scheduling component of TP/VS will
optimize the delivery routes.
TP/VS utilized
advanced linear programming algorithms to accomplish its mission.
The APO Alert Monitor is an
advanced monitoring system to detect supply chain problems at the earliest possible time.
The APO Alert Monitor is capable of
operating within all the APO sub-modules (DP, SNP, PPS/DS, TP/VS).
APO Alert conditions may be
customized by company or individual user.
The portion of the APO Architecture where most data and calculations are performed is called
Live Cache.
The purpose of the BW (Business Warehouse) is
to store historical sales data to forecast.
The APO Modules where forecasting is done is
Demand Planning.
The APO Module used for Advanced Order Promising is called
Global ATP
The APO module used for advanced problem notification is called
Alert Monitor.
Characteristics usually in an APO System include:
- Fewer internal users than ERP Systems (fewer users).
- The use of memory resident models in addition to traditional data base management systems.
- Advanced planing & scheduling functionality.
- Advanced optimization algorithms such as linear programming and other heuristics (advanced mathematical techniques).
- Planning at a finer time increment.
- Ability to do rapid what-if simulations (rapid what-if simulations).
- Advanced problem notification.
The APO Core Interface Framework (CIF) is used for
the data exchange between SAP APO and SAP R/3 Systems.
The CIF will transfer both
master data and transaction data from SAP R/3 to SAP APO and also from SAP APO to SAP R/3.
Data passing between SAP R/3 and SAP APO may be
either real-timed or batched.
The IT Technology used for the interface is the
Remote Function Call (RFC).
The passing of data is enabled by
the creation and maintenance of Integration Models.
All Integration Models are defined in
SAP R/3 (host system)
Multiple Integration models will be used in connecting SAP R/3 to APO. Each model will transfer different data.
Example– an integration model will be defined for transferring the organizational data elements (plant, storage locations, etc) to APO.
Integration models are always defined in the
SAP R/3 system.
Various definitions muse be made in configuration in
both R/3 and APO.
R/3 and APO contain various tools for
monitoring and handling integration errors.
Master data that was originated in SAP R/3 is
maintained in R/3.
Master data that is unique to APO is
maintained in APO.
All Master Data transferred using the CIF is
automatically assigned to model 000 (Active model) in live cache.
-Therefore models in APO contain master data.
Since APO may be used for simulation or what-if planning,
other models may be created that contain master data different from the model 000 (Active model).
All transaction data that is transferred to APO through the CIF is
stored in Version 000 (Active Version).
-Examples of transaction data would be forecasts, sales orders, etc.
Since APO may be used for simulation or what-if purposes,
other versions may be created that contain transaction data different from Version 000 (active version).
All transaction data transferring from APO to R/3 must be
stored in Version 000.
The key ingredient to passing data through the Core Interface is
Integration Models.
The Core Interface can connect
multiple R/3 systems to a single APO server.
Master data that originated in R/3 and passed to APO through the Core Interface should be maintained in
R/3.
When Transaction data passed through the Core Interface it is stored in which area of Live Cache?
Version 000.
Master data is stored in
Models.
Transaction data is stored in
Versions.
Integration models are always made in the
ERP (R/3).
The Master Data Objects in SAP APO have different names from their SAP R/3 counterparts. For example, the material master in R/3 is named
Product Master in APO.
Many of the APO master data fields originate in R/3 and are
transferred through the Core Interface (CIF).
APO has many master data fields that do not have counterparts in R/3. These master data fields are
needed to perform the APS functionality that does not exist in R/3.
APO also has one master data objects that
does not have a R/3 counterpart.
Master data is maintained in its
system of origin.
R/3 fields in R/3 and APO fields in APO.
The Location Master is a common master data object used to house the following R/3 objects:
- Plant
- Customer
- Supplier
- Plus others.
The location master is crucial to supply chain management because
it is the building block for so many other relationships.
The Location Type will
distinguish between the different location masters.
The APO Transportation Lane (TL) does
NOT have a R/3 counterpart.
The TL defines all
valid transportation methods between two locations.
TLs may be defined for
all products moved between two locations or may be specific by product.
If no TL exists between two locations then
one location cannot be a source of supply to the other.
The TL may define
multiple valid transportation means (truck, rail, air) along with the transportation time and cost for each.
APO sourcing algorithms will examine the
TL for cost and time data to determine the optimum method.
The Quota Arrangement determines the
source and quantity demanded when several possible suppliers (i.e. locations) are available.
Quota arrangements exist in R/3 but
are NOT used in APO.
Quota arrangements may be defined for all products sourced from a location or
it may be product specific.
Product splits may be defined as:
- Fixed split.
- Determined by a heuristic algorithm.
- Determined optimally and then remain fixed.
If there is only 1 source of supply than
no quota arrangement is needed.
The APO Product Master is the
direct equivalent of the R/3 Material Master.
Most of the data from the MRP data views will
pass through the Core Interface to create the Product Master.
The Product Master will also contain data elements that do not exist in R/3. A few examples are:
-Penalty Costs–these reflect the relative cost of missing an order due date.
-Storage Costs–the relative cost of storing a product.
-Good receipt/issue costs.
~These costs are used to influence the Optimizer program in Supply Network Planning.
The APO Resource Master is the direct equivalent of the
R/3 Work Center (discrete) or Resource (process).
The APO Resource Master is considerably more
flexible than its R/3 counterparts.
For example, in R/3 a work center may have multiple capacities (labor and machine).
When used in a APO environment,
APO Resource Master
each capacity will create a separate and distinct resource. This allows for capacity planning for both resources.
Finally, the APO Resource may be used to
model transportation and material handling resources.
Resources in APO may be
Model/Version dependent for what-if simulation purposes.
The APO Production Process Model (PPM) is a
complicated and sophisticated object that combines the major components of the R/3 BOM and Routing.
There the PPM will contain
all the materials required and all the process steps, resources and processing times.
Additionally the PPM may also contain production cost data. This allows for PPMs to be created for various locations (plants) with different production costs.
A linear programming sourcing model may then determine the optimum quantity to source from each location.
Two Types of PPMs
PPM=Production Process Model
- PP/DS Plan
- SNP Plan
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The APO Procurement Relationship object is the direct equivalent of the R/3 Purchasing Information Record, Contract or Scheduling Agreement.
Since all of these R/3 objects define a valid relationship between a supplier and a trading partner the Core Interface will automatically create a Transportation Lane.
The APO master data object that is required before a valid source of supply can exist is the
Transportation Lane.
The APO master data object that does not have a direct equivalent in R/3 is
Transportation Lane.
The APO master data object that combines the R/3 BOM and routing together is the
Production Process Model (PPM).
A purchasing Information Record in R/3 that passes through the Core Interface will automatically create what APO master data object?
Procurement Relationship and Transportation Lane.
A forecast is a
prediction of a variable of interest for a future time period.
The three absolutes of forecasting are:
- Forecasts are always wrong.
- Forecasts are more accurate in groups rather than individuals.
- Forecasts are more accurate in the near term.
Forecasting techniques in SAP are:
- Manual
- Sales & Operations Planning (SOP)
- Flexible Planning (R/3)
- APO Demand Planning
Forecasts are almost always generated at a product family level as a background job that runs automatically.
Various organizations may make independent forecasts. Examples may include: sales, marketing, finance, and operations management.
The frequency of running the forecast will vary from company and industry.
However, a monthly update frequency is the most common.
For each forecast cycle some time periods will be re-forecasted and some time periods will be forecasted for the 1st time. The overall horizon of the forecast is dependent upon several factors including:
- Purpose of Forecast.
- 2. Cumulative Product Lead Time.
The forecast cycle may terminate with a consensus forecast as part of a Sales & Operations Planning (S&OP) meeting.
When the automatic forecast is completed, any alert conditions are noted and sent to customers.
-Adjustments to automatic forecast are usually performed manually.
Typical Industry Forecasting Process:
1-Update history. 2-Automatically generate forecast. 3-Review/correct forecast. 4-Reach consensus forecast. 5-Approve forecast. ---then repeats and goes back to 1-update history, and so on.
Elements of a Good Forecast:
- Timely
- Reliable
- Accurate
- Meaningful
- Written
- Easy to Use
Approaches to Forecasting:
- Qualitative Method
- Quantitative Method
Qualitative Method (approach to forecasting):
-Subjective inputs.
Subjective inputs
- “Soft” information-(human factors, personal opinion, hunch)
- hard to quantify.
Quantitative Method (approach to forecasting):
- objective, or hard, data
- projection of historical data
- associative models utilizing explanatory variables.
Types of Forecasts:
- Judgmental
- Time Series
- Associative Models
Judgmental
type of forecast
- Qualitative Method
- uses subjective inputs.
- -(consumer surveys, sales staff, managers/executives expert panels).
Time series (type of forecast)
- Quantitive method
- uses historical data assuming the future will be like the past.
Associative models (type of forecast)
- quantitive method
- uses explanatory variables to predict the future.
Time Series Forecasts
- -Time Series-time-ordered sequence of observations taken at regular intervals.
- -Assume future can be estimated by past.
- -Identify underlying behavior without identifying causes.
Trend
(Time Series Forecasts
long-term upward/downward movement in data.
Seasonality
(Time Series Forecasts
short-term regular variations in data
Cycle
Time Series Forecasts
wavelike variations of more than one year’s duration
Irregular Variations
Time Series Forecasts
caused by unusual circumstances
Random Variations (Time Series Forecasts)
caused by chance… what’s left.
Techniques for Averaging
- Historical data has “white noise or variation”
- Averages smooth variations
- 3 techniques:
- -Moving average
- -weighted moving average
- -exponential smoothing
Moving Averages
Technique that averages a number of recent actual values, updated as new values become available.
Weighted Moving Averages
more recent values in a series are given more weight in computing the forecast.
Exponential Smoothing
weighted averaging method based on previous forecast plus a percentage of the forecast error.
-where alpha (Smoothing error) is greater than or equal to zero but less than or equal to 1.
Picking a smoothing constant
- low alpha -stable average
- high alpha- changing average
After the demand plan has been approved for it must be released for operations planning.
Various potential paths exist for releasing the demand plan.
After the release process, the forecast requirements will be classified as
planned independent requirements (PIR).
The forecast release almost always will contain four basic parameters:
1) product
2) location
3) quantity
4) time
MRP in R/3 or SNP in APO may act on
PIRs to create replenishment planned orders.
APO Supply Network Planning (SNP) is
an intermediate time frame planning function.
APO Supply Network Planning (SNP) primary purpose is
to provide supply and demand matching across the entire supply chain.
SNP may be used for
either infinite or finite capacity planning.
Three separate and unique replenishment planning engines are bundled into SNP:
- Heuristic
- Capable-To-Match (CTM)
- Optimizer
In addition to supply and demand matching, SNP is capable of performing two additional supply chain management functions:
- Deployment
- Transportation Load Builder
Medium to Long-term Planning Strategies:
SNP Planning Engines
- Infinite Planning
- Finite Planning
Infinite Planning
SNP Planning Engines
-Heuristic: Resources and material availability are not checked when creating planned orders and stock transfers.
Finite Planning
SNP Planning Engines
-Capable-to-Match (CTM) and optimizer:
Simultaneous quantity and finite capacity scheduling: SNP resources and material availability are checked during creation of orders.
Short-Term Replenishment Planning (Deployment)
SNP Planning Engines
- Heuristic and optimizer
- Transport Load Builder (TLB)
Heuristic and Optimizer:
SNP Planning Engines
Adjust stock transfers according to the current demand and receipt situation.
Transport Load Builder (TLB)
SNP Planning Engines
Groups together stock transfers.
All transaction data is stored as
orders in the order live cache.
Order Based Live Cache
- ATP categories are used to differentiate orders.
- ATP categories can be grouped together into ATP category groups.
The role of Heuristic planning is to
plan the supply to meet demand throughout the entire supply chain.
Heuristic planning is
quantity-based planning.
This means it will create a supply quantity for a specific time period regardless of the actual order quantities.
The SNP Heuristic plans in a level-by-level planning method similar to
MRP in SAP R/3.
Heuristic planning assumes
infinite capacity when planning.
Sourcing decisions (that is, what locations should be used as supplies) is driven primarily by
Quota Arrangements.
Quota Arrangements in Heuristic
IOTDT
- I-Inbound quota arrangements control distribution of demands.
- O-outbound quota arrangements control distribution of receipts.
- T-there are quota arrangements for individual products and selections.
- D-Demands can be split (minimum quantity) and grouped together for time periods.
- T-The following can be included in a quota arrangement:
- -External Procurement
- -Stock Transfer
- -In-house production.
Other APO Master Data Used in Heuristic
TQLCSSP
- T-Transportation Lanes (valid movements in the supply chain).
- Q-Quota Arrangements (percentage assignment of demands to sourcing locations).
- L-Lot sizing (lot-for-lot, fixed, target days’ supply, rounding profiles, rounding values).
- C-Calendar
- S-Safety Stock
- S-Scrap
- P-PPM
SNP Heuristic planning is based on
the assumption that resources have an infinite capacity.
After the SNP Heuristic run is complete,
the planner can make a capacity check, which allows the planner to see the impact that planned orders will have on resources and to quickly determine whether or not the plan is feasible.
If there is a capacity overload, an alert is displayed.
The planner can decide how to modify the production plan to meet demand before actually going into production.
Capacity Balancing Alternatives
- Increase capacity through overtime or additional resources.
- Move work backward in time where capacity is available (subject to material availability).
- Move work forward in time where capacity is available (subject to material availability).
- Move work to an alternate resource.
- Split the order (i.e. sub-divide) into quantities that will meet available capacity.
APO SNP is an
intermediate range planning tool.
APO SNP will plan supplies to match demands using several potential software algorithms:
- Heuristic-infinite capacity planning only.
- Optimizer-finite capacity planning.
- Capable-To-Match (CTM)-infinite or finite capacity planning.
Linear Programming (LP)
traces its history to the 1940’s as a method of solving complex planning problems with war time implications.
George Dantzig is considered
the primary inventory of LP but John von Neumann is also considered by many as a co-inventor.
LP is a
special class of mathematical problems in which a linear function (called he objective function) is either minimized (like costs) or maximized (like profits).
The other two components of a linear programming problem besides the objective function are:
- Decision variables.
- Constraints.
Decision variables are used to
model the various “decisions” that may be required in supply chain planning.
Examples of Decision variables are:
- What products should be produced?
- How much of each product should be produced?
- Where should the products be produced?
- How should the products be transported?
Constraints represent
realities that essentially “bound” the solution options to that the result is feasible.
Examples of constraints include:
- Demand must be met.
- Cannot exceed capacity.
- Storage capacity is limited.
In many cases, the objective function may be non-linear. In this case other solution techniques must be employed.
A few optimization techniques are:
- Non-linear Programming (NLP)
- Mixed-Integer linear programming (MILP)
- Mixed integer non-linear programming (MINLP)
SAP APO supports
LP and MILP problems
The Optimizer or “solver” in APO SNP uses
linear programming to consider all relevant factors simultaneously.
SAP has embedded a 3rd party “solver”–
ILOG CPLEX into the APO system.
The optimizer compares alternative solutions using costs that would be incurred.
It determines the most cost-effective solution based on the constraints and objective function defined in the system.
You use penalty costs to prioritize demands. If a product brings in high sales revenues, you
set high penalty costs.
The result of the optimization run might be that
due dates are violated or that safety stocks are not replenished.
Capable To Match (CTM) is an
order-based planning method, which means that every single sales order or Planned Independent Requirement PIR is planned separately.
CTM uses
demand priorities as the primary basis performing supply network planning.
Demand priories may be defined using
multiple methods consistent with corporate policy or culture.
- For example, demand priorities may be defined as:
- -preferred customer
- -due date
- -revenue
CTM is capable of planning with
either finite or infinite capacity assumption.
CTM does not perform
optimization.
It terminates when it finds the 1st feasible solution to the problem.
The following uncertainties occur during planning:
- Demand uncertainty (forecast)
- Replenishment lead time.
To safeguard against these uncertainties, you can plan safety stock (SStk) as follows:
- maintaining the safety stock manually in the product master.
- Calculate the time-dependent safety stock in an SNP key figure in the Interactive Planning Table.
- Create a model dependent safety stock to achieve a certain customer service level.
APO SNP provides
more sophisticated safety stock planning than R/3.
At the time of actually executing the distribution plan,
the stock levels, stock receipts and sales orders are not at the same levels as when the planning run was run last.
For example, SNP created a planned order for 500 during a planning run 3 months ago. The order due date is next week. However, there were production problems and the order qty is now 450.
This means that we can only distribute (that is, deploy) 450 instead of the 500 originally expected.
-The SNP Deployment process will determine how the remaining 450 will be deployed to their respective destinations.
It uses various “fair-share” rules.
Actual deployment orders are created in
R/3.
Once the question of deployment has been determined, then we can begin to do some
transportation planning.
Transportation Load Builder (TLB) is a
lite-transportation load builder that will optimize the use of the transportation fleet of vehicles.
TLB only creates
full loads.
TLB does not perform
any route planning.
Actual transportation orders are created in
R/3.
The APO Supply Chain Engineer (SCE) is a
convenient graphical tool that allows customers to graphically view and edit their APO master data objects.
With literally thousands of master data elements in a supply chain,
the management of master data can become overwhelming.
The SCE allows a customer to
create a filter containing those master data objects that are under his responsibility.
-The resulting filtered master data objects is called a “work area”
The resulting filtered master data objects is called a
“work area”
Work areas provide a
convenient way to filter the master data.
Software implementations can be a high risk, high cost and potentially disastrous process for a company.
Rarely are software implementations a slam dunk success.
Many factors influence the overall success of a software implementation including:
- project manager.
- top management support.
- technical issue.
- end user issues.
- end user training.
Software implementation methodologies reduce
the risk and cost of a software implementation.
A methodology is a
structured, proven process of accomplishing a task.
Software implementation methodologies have existed for many years.
They are usually defined by major phases.
The SAP software implementation methodology consists of the following phases:
- Project preparation.
- Business blueprint.
- Realization.
- Final Preparation.
- Go live & support.
The project preparation phase will define the general conditions for implementation the project successfully. It will include:
-defining the goals and objectives of the project.
-establishing the project organization.
-creating the project plan.
-determining the project standard procedures.
-training the project team.
-setting up the SAP 3-system landscape.
creating a communication plan for the project.
-take certain benchmark measurements.
The business blueprint phase is a critical phase in the methodology.
Failure to take adequate time to lack of forward thinking in this phase will significantly increase the risk of the overall project.
In the business blueprint phase, each major department being affected by the scope of the software will undertake an analysis of their current processes.
The resulting analysis will document the functional requirements that the new software implementation.
-Example-the SAP system should capable of automatically determine a source of supply for a requirement.
The Realization phase will begin the implementation of the functional requirements defined in the Business Blueprint phase.
This phase will include the following activities:
- Configuring the SAP system.
- Setting up the test environment.
- Setting up the security/administration settings.
- Setting up any workflow processes.
- Writing test scripts.
The Final Preparation Phase will include the following activities:
- Loading master data.
- Unit, function and integration testing.
- End user training.
- Customer sign-off.
The Go Live & Support phase will launch the new application and provide the necessary support for a period of time required to achieve institutionalization.
Activities include:
- End user re-training.
- Software trouble call support.
- Software de-bug support.
- Configuration re-setting.
Demand Plans (forecasts) created in APO DP may be:
- Released to APO Supply Network Planning.
- Transferred to SAP R/3.
Released Demand Plans must have what information?
- Product
- Quantity
- Location
- Time
After demand plans have been released to APO, they are stored in what part of APO live Cache?
Order-based Live Cache
After demand plans have been released they become what transaction data?
Planned Independent Requirements (PIR)
The APO Supply Network Planning (SNP) module is used primarily for
Intermediate Supply planning.
The objective function may be to
APO SNP Optimizer
minimize costs
or
maximize profits
Transportation Lanes are
unidirectional.
-That is, a valid lane from location 1000 to 2400 is not assumed to be the same as a lane from 2400 to 1000.
Transportation lanes do not
exist in ERP!!
This master data is not created through the CIF even though there is a Quota Arrangement in ERP.
Quota Arrangement-Master data
Quota Arrangement
- Locations
- Distribution Centers
- Right mouse click on DC & choose ‘Quota Arrangements –> Incoming Quota Arrangement.’
The inbound Quota Arrangement is a
sourcing decision data where allocations across multiple sources (suppliers) can be defined.
The Supply Chain Engineer is used primarily to view and manage
master data
The supply chain engineer is a
graphical tool.
Which items can be viewed and managed through the Supply Chain Engineer?
- Transportation Lane
- Transportation Service Provider
- MRP Area
- Transportation Zone.
–NOT: Bill of Material Master (b/c not involved in this area)
Work areas in the Supply Chain Engineer are used to
filter master data in models.
Characteristics
For APO DP, a characteristic is a organizational or master data field.
For example, material (product) or plant, customer, or sales organization.
Characteristics are used to
determine the level at which you are forecasting.
For example, a sales rep may need to create a forecast at the sales-org-product-customer level. Product, sales org., and customer are all characteristics.
Historical data is stored in
the APO BW info cube and is organized by dimensions (characteristics).
once historical data is stored, it may be analyzed to create historical facts of characteristic combinations.
Example:
- info cube contains the following dimensions (characteristics): product, location, customer, sales organization, date.
- Performing an analysis of the historical data yields the combination: Product P-101 was sold to customer 12345 by sales org ABCD and shipper at location 1000.
Characteristic Value Combinations (CVC)
represent the master data for APO DP.
Characteristic value combinations (CVCs) are stored
in a Planning Object Structure (POS).
APO Demand planning supports the following types of forecasting methods
- univariate (statistical)(time series)
- multiple linear regression (MLR) (causal analysis)
- composite)
Key figures are
numeric or quantitive data that are useful for forecasting purposes.
Key figures usually appear as
rows in spreadsheet looking screens.
Planning areas
are that part of LiveCache where we store our characteristics, key figures, as well as planning books, data views, and planning object structures.
Aggregation
is the automatic function by which key figure values on the lowest level of detail are summed at run time and displayed or planned on a high level.
Disaggregation
is the automatic function by which a key figure value on a high level is broken down to the detailed level.
proportional factors are used
to disaggregate the forcast
proportional factors are derived from
historical data and represent ratios or percentages.
Forecasting prerequisites
1) master data in the form of characteristic value combinations (CVC)
2) selection ID-what to forecast
3) forecast profile-how to forecast.
4) historical data.
univariate forecasting is used in APO when
you have one independent variable.
Master forecast profile
- planning area assignment
- definition of key figure to be forecast.
- definition of the past and forecast horizons.
- procedural specification for the following forecasting types:
- -univariate forecasting
- -multiple linear regression
- composite forecasting
Multiple linear regression (MLR)
-use MLR to determine how a dependent variable, such as sales, is connected with independent variables called casual variables, such as prices, advertising, and seasonal factors.
MLR uses historical data as a basis to calculate the
regression coefficients, b, for causal analysis.
The composite forecast
forecasting the demand for new products can be difficult since they have no previous historical data. additional forecasting the “end-of-life” for products being phased out is important from an inventory management point of view.
plm
To make a forecast for a new product that has no previous sales history, what feature of APO DP could be used?
product life cycle (PLM).
Product life cycle (PLM)
you define phase-in and phase-out profiles to model the lifecycle of old and new products.
promotion planning
- Promotions can be created to apply patterns to the demand forecast.
- The patterns can be stored in the promotion pattern library and used, as required (multiple times).
- The function is also available to detect promotion patterns in historical data and to create promotion patterns based on them
- promotions can have major impact on consumer behavior
- you can plan promotions or other special events separately from rest of forecast.
