User's Guide Template 3.0 for BAAN IVc Purchase Guide Template 3.0 for BAA… · Business Template A collection or subset of export session, iBaan ETL model, dimension, and cube definitions

iBaan Decision Manager Business Templates

User's Guide Template 3.0 for BAAN IVc Purchase

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Baan Development B.V. P.O.Box 143 3770 AC Barneveld The Netherlands

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© Baan Development B.V. 2002. All rights reserved.

The information in this document is subject to change without notice. No part of this document may be reproduced, stored or transmitted in any form or by any means, electronic or mechanical, for any purpose, without the express written permission of Baan Development B.V.

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Document Information

Code: U7905A US Group: User Documentation Edition: A Date: May, 2002

i

User's Guide Template 3.0 for BAAN IVc Purchase

1 Overview of iBaan Decision Manager 1-1 Definitions, acronyms, and abbreviations 1-4

2 Business Content Purchase 2-1 Introduction 2-1 Data warehouse content for Purchase 2-3 Purchase OLAP cubes 2-4 Vendor_Reliability cube 2-5 Purchase_Order_Process cube 2-6 Cube Vendor_Reliability2 2-7 Cube Contract_Turnover 2-11 Cube Contract_Perf 2-12 Cube Pur_Cost_Tracking 2-13 Cube Pur_Maverick 2-14 Cube Vendor_Allocation 2-16 Cube Pur_Quotation 2-17 Cube Pur_Change_Analys 2-18 Cube Pur_LeadTime_Analy 2-19

3 Examples 3-1 Vendor reliability analysis 3-1 Supplier delivery performance analysis 3-2 Supplier’s quality performance analysis 3-4 Suppliers price performance 3-6 Supplier’s performance – To acknowledge the purchase order lines 3-6 Purchase order process analysis 3-7 Contract turnover/performance analysis 3-8 Maverick analysis 3-8 Vendor allocation analysis 3-9 Cost reduction tracking analysis 3-10 Purchase order line change/cancellation analysis 3-11 Purchase order lead-time analysis 3-11 Request for quotation analysis 3-12

Table of contents

Table of contents

User's Guide Template 3.0 for BAAN IVc Purchase ii

User's Guide Template 3.0 for BAAN IVc Purchaseiii

iBaan Decision Manager is a decision support solution that you can use to:

Extract and analyze key data from your business management system. Obtain the information required to support your decisions. Take measures in time to avoid bottlenecks in your business processes.

For example, you can use Decision Manager for various types of sales performance analysis, production performance analysis, and purchase data analysis.

For each area that you want to analyze, the Business Content defines what data is extracted from the source system, and how Decision Manager presents the data to you for further analysis. When you install Decision Manager, the Business Content is predefined for a number of areas.

This manual describes the BAAN IVc Purchase business template version 3.0. The business template is developed for iBaan Decision Manager 2.2.

The manual also describes what data you can use for performance analysis of the various aspects of Purchase, and provides some examples of business management questions that can be answered by a specific type of analysis.

This document contains the following chapters:

Chapter 1, “Overview of iBaan Decision Manager,” briefly describes the Decision Manager concepts and components. The chapter also explains the function of the Business Contents in the Decision Manager solution.

Chapter 2, “Business Content Purchase,” provides a functional description of the data that is available for the analysis of your Purchase performance.

Chapter 3, “Examples,” describes example analyses that you can carry out, based on the Business Content for Purchase.

For a more technical description of the Business Content for Purchase, refer to the online metadata.

About this document

About this document

User's Guide Template 3.0 for BAAN IVc Purchase iv

User's Guide Template 3.0 for BAAN IVc Purchase1-1

iBaan Decision Manager is a decision support solution that you can use to:

Extract key data from your business management system (currently, BAAN IVc).

Store the data in a data warehouse and OLAP databases. Analyze the data. Present the analysis in the form of reports and graphs.

For each area that you want to analyze, for example, sales or purchase, the Business Content defines what data is extracted from the source system, how the data is stored in the data warehouse, and the information made available for analysis.

The Business Content consists of:

Extraction, Transformation, and Loading (ETL) scripts. OLAP cubes.

This chapter briefly explains the various Decision Manager concepts and the components related to the Business Content.

ETL scripts

The ETL scripts:

1 Extract the data from the source systems. 2 Transform the data into useful information for decision-making. 3 Load the information in a data warehouse.

After the information is loaded, the data warehouse contains the required fact and dimension data for analysis.

Facts

Facts reflect the events in your business that you want to analyze. The facts consist of the dynamic data that Decision Manager extracts from your Baan database, such as order quantities; delivery dates, invoiced amounts, and completed orders.

1 Overview of iBaan Decision Manager

Overview of iBaan Decision Manager

User's Guide Template 3.0 for BAAN IVc Purchase 1-2

Dimensions

Dimensions represent a point of view from which you can analyze the data. The dimensions consist of comparatively static data or master data, such as customers, price lists, warehouses, and time, related to the facts. For example:

Item dimension to analyze your sales order amount with respect to the items sold.

Time dimension to analyze the number of early or late deliveries. Warehouse dimension to analyze which warehouses issue most, or none, of

the goods.

Data warehouse

The fact data and dimension data is stored in fact tables and dimension tables, respectively, in a data warehouse. The ETL scripts update the data in the warehouse with the data from the live database. To perform the analysis on data warehouse, you can use the following two ways:

Build and process OLAP cubes. Design Analytic applications. For example, Crystal Analysis Professional

applications.

Before you analyze the data using your OLAP Client, the data warehouse data must be processed to prepare the data for analysis.

OLAP cubes

The OLAP cubes contain a combination of fact data and dimension data, as well as the results of computations, such as totals, average numbers, and percentages. To access the OLAP cubes, you can use your OLAP Client, as well as any analytic or reporting applications.

OLAP Client

You can use an OLAP Client to view the data in the OLAP cubes from various angles. You can apply formulas, filters, graphs, and so on, to the data in OLAP cubes to obtain information about trends, causes of events, exceptions, and other interesting facts. For instructions on how to use your OLAP Client, refer to the OLAP Client User Guide (U7782A US).

NOTE



Analytic applications reporting

You can use Analytic applications for reporting, for example, Crystal Analysis Professional, to access and print reports on the information contained in the data warehouse and in the OLAP cubes. The available User Manuals describe how you can define the applications to analyze the data, and to build views for reporting.

The following figure shows how the various Decision Manager components are related:

AnalyticApplications

OLAP Client

Baan Database

OLAPCube

DataWarehouse

iBaan Decision Manager

TemplateExtract,Transform,Load (ETL)

ReportingApplications

Figure 1-1 High-level Architecture Overview – iBaan Decision Manager



Definitions, acronyms, and abbreviations Term Description Business Template A collection or subset of export session, iBaan ETL model,

dimension, and cube definitions that cover a particular business area, for example, Finance - Operational Review. Business templates are used to extract data from an operational source system, such as iBaan ERP, and store the data in the data warehouse, from which the data can be analyzed using OLAP or any Reporting technology.

Business Intelligence The total concept of data visualization and analysis. iBaan Decision Manager An end-to-end solution delivering ready-to-implement business

templates, and which is designed to analyze business processes in an enterprise. Business templates enable you to make dynamic decisions right out of the box. iBaan Decision Manager contains, the iBaan Decision Manager Console and the Business Templates components.

Data warehouse An integrated collection of data used in the support of management’s decision needs. The data warehouse data consists of the fact data and the dimension data defined by the Business Content of various business areas.

Dimension A point of view from which you can look at and analyze your data, for example, time, product, or customer.

Fact Numeric information about a business area that is extracted from your business management system and that is available in the data warehouse, for example, turnover, total costs, and spent hours.

OLAP Online Analytical Processing: A category of software technology that enables analysts and managers to gain insight into data through fact, consistent, and interactive access. OLAP provides a wide variety of possible views of the information. OLAP functionality is characterized by dynamic multidimensional analysis of consolidated enterprise data that reflects the real dimensionality of the enterprise as understood by the user.

OLAP Navigator A browser-based hyper relational OLAP client that provides the business user with an overview and analytical support in addition to enterprise decision models. With the hyper-drill technology, users can navigate intuitively between tactical and operational information needs.

OLAP cube A set of related facts and dimensions. The cube is the central metadata object recognized by OLE DB for OLAP.

Crystal Analysis Professional

Crystal Analysis Professional is an OLAP tool, which provides an analytic application front-end for the iBaan Business Intelligence Solution. This tool can translate the multidimensional data in the iBaan Business Intelligence Solution into Web-based reports for interactive viewing.


Introduction The data for purchase that is extracted from BAAN IVc is related to the purchase order history, purchase contract history, and purchase quotation history. The data is transformed and loaded into the data warehouse. The data is stored in data warehouse tables and OLAP cubes, which serve as the basis for the following types of analyses:

Purchase order process. Vendor reliability. Contract turnover. Contract performance. Maverick (contract leakage). Cost tracking. Vendor allocation. Purchase quotation.

In Purchase Order Process analysis, you can analyze several aspects related to the Purchase function, including:

Purchase process: Purchase order flow in terms of quantity and value of orders placed, order cancellations, and orders for which receipts are made.

Purchase order portfolio: Quantities and amounts related to purchase orders that are not yet completed.

Purchase variance: Difference between the purchase price and the standard cost.

Purchase price movements: The variation of price for items supplied by various suppliers over a period of time can be analyzed.

In the Vendor Reliability analysis, you can analyze the following aspects, which are required to gauge the performance of the supplier:

Supplier Quality Performance: Suppliers can be analyzed for the quality in terms of volume of rejections.

Supplier Delivery Performance: Timeliness and completeness of receipts related to purchase orders.

2 Business Content Purchase

Business Content Purchase


The cost performance indicator enables you to analyze how a particular supplier’s average price for an item, stands against the average price across all the suppliers for that item in a particular period.

In Purchase Contract Turnover analysis, the user can analyze the consumption of the contract by the various purchase orders over time.

In Purchase Contract Performance analysis, the user can analyze the contract’s performance in the elapsed time.

In Maverick analysis, you can analyze the purchases that have happened outside contracts for items under contract. In addition, you can track the loss and savings incurred as a result of such undisciplined buying.

In Purchase Cost Reduction Tracking analysis, you can track the potential savings for items that have been placed under contract as compared to the last period. The actual savings that have happened for the contracted items as compared to the last period can also be tracked.

In Vendor Allocation analysis, you can analyze how the allocation of contracted quantities across various suppliers have shifted over a period of time.

In Purchase Quotation analysis, you can analyze the quantities, value, and number of quotation lines that have been placed, replied, successful, and unsuccessful.

In Purchase Change Order analysis, you can analyze the changes that were made to a purchase order line for various reasons.

In Purchase Order Lead Time analysis, you can analyze and compare the standard lead-time with the planned lead time (as available in the purchase order line) and standard lead-time with the actual lead-time.

This chapter describes the content of the data warehouse and the OLAP cubes from a functional point of view, and explains how you can use the Purchase Business Content for purchase performance analysis.

For a detailed technical description of the design of the data warehouse and the OLAP cubes, refer to the online metadata.



Data warehouse content for Purchase For the various forms of analysis described in the previous section, several facts and dimensions are available. The facts are the numbers of interest related to the aspects described previously. The dimensions define the aggregation levels on, and angles from which you can analyze the inventory transactions. The data warehouse contains several dimension tables, as well as the following tables and views that contain the facts required to perform the purchase analysis:

DW_PUR_HISTORY. Contains records from the Purchase Orders History (tdpur050) table and the Purchase Order Line History (tdpur051) table. This table is used to carry out Purchase order process analysis. This table contains the measures on order-line-transaction level. On the DW_PUR_HISTORY table, view, PUR_ORDERLINES and PUR_VENDOR_RELIABILITY, are created after a series of intermediate views. These views are converted into a table, DW_ PUR_ ORDERLINES_ FINAL and DW_PUR_VENDOR_RELIABILITY, to improve the performance. One more view DW_PUR_LEAD_TIME_ANALYSIS is created on this table.

DW_PUR_ORDERLINES_FINAL. Contains aggregated information of records from DW_PUR_HISTORY that correspond to one purchase order line and calculates the supplier reliability statistics for the order lines.

DW_PUR_VENDOR_RELIABILITY. Contains information from DW_PUR_HISTORY to calculate the supplier reliability statistics at purchase order line and purchase order receipt level.

DW_PUR_CONTRACTS_HISTORY. Contains records from the Purchase Contract History (tdpur305) table and the Contract Line History (tdpur306) table. On the DW_PUR_CONTRACTS_HISTORY table, one view, DW_ PUR_ CONTRACTS_ FINAL, is created.

DW_PUR_CONTRACTS_FINAL (VIEW). You can use this view to analyze the contract performance, for example, the quantity expected to be consumed in elapsed time and the quantity actually consumed in elapsed time.

DW_PUR_MAVERICK (VIEW). This view is a join of DW_PUR_HISTORY and DW_PUR_CONTRACTS_HISTORY to analyze the Maverick purchases. Only the weighted contract average price is calculated from the DW_PUR_CONTRACTS_HISTORY table, while the rest of the fields are calculated from the DW_PUR_HISTORY table.



DW_PUR_QUOTATION. Contains records Purchase Inquiry History (tdpur010) table and Purchase Inquiry line History (tdpur011) table. These tables contain the purchase inquiry related data, and are used to analyze the result and status of the inquiries.

DW_PUR_ORDERS_CONTRACT (VIEW). This view is a join of DW_PUR_HISTORY and DW_PUR_CONTRACTS_HISTORY. This view is used to analyze vendor allocation and cost reduction tracking.

DW_PUR_LEAD_TIME_ANALYSIS (VIEW). This view is created from DW_PUR_HISTORY to analyze and compare the various purchase order lead times.

Purchase OLAP cubes The following cubes are available for Purchase:

Purchase_Order_ Process. Vendor_Reliability. Vendor_ Reliability2. Contract_Turnover. Contract_Perf. Pur_Cost_Tracking. Pur_Maverick. Pur_Quotation. Vendor_Allocation. Pur_LeadTime_Analy. Pur_ ChangeAnalys.

Purchase_Order_Process cube and Vendor_Reliability cube were a part of Template 2.0 for BAAN IVc Purchase. Each cube contains measures and dimensions. The measures and dimensions are described for the cubes in the following section. Single company and multicompany cubes have the same measures. The dimensions are described for single company cubes only. In case of multicompany cube dimensions, the Physical Company (PhysComp) is part of the dimension hierarchy. Even though the cube dimension, Logical Company, is described for single company cubes, this dimension is relevant when used in multicompany cubes.



Vendor_Reliability cube This cube contains measures to analyze the reliability of the supplier. The measures that are available in this cube are:

Measures Description ApprovedQuantity Approved quantity for all the purchase receipts. Rejected Quantity Rejected quantity for all the purchase receipts. Order Line Quantity Order line quantity of all the purchase orders placed.

For return order the order line quantity is considered as 0. Received Quantity Approved + rejected quantity. Early Quantity Approved quantity for those receipt lines for which:

actual receipt date < target receipt date. On Time Quantity Approved quantity for those receipt lines for which:

actual receipt date = target receipt date. Late Quantity Approved quantity for those receipt lines for which:

actual receipt date > target receipt date. Early Quantity Percentage Percentage of the received quantity that is received early.

(Early Quantity / Approved Quantity) On Time Quantity Percentage

Percentage of received quantity that is received on time. (OnTime Quantity / Approved Quantity)

Late Quantity Percentage Percentage of received quantity that is received late. (Late Quantity / Approved Quantity)

Order Line Approved % Percentage of order lines for which not a single receipt is rejected.

Order Receipt Approved % Percentage of receipts that is not rejected. Approved Quantity % Percentage of received quantity that is approved.

Avg. No. of Deliveries Per OrderLine

Average No. of receipts made per order line.

Early Order Percentage Percentage of completed orders for which all the receipts are made before the target receipt date. Or: Percentage of orders for which lateness is negative. Lateness is defined as difference between last receipt date and target receipt date.

On Time Order Percentage Percentage of completed orders for which the last receipt date is equal to the target receipt date.

Late Order Percentage Percentage of completed orders for which the last receipt is made after the target receipt date.

Avg. Lateness by Order Average No. of days by which the late orders are late. Avg. Earliness by Order Average No. of days by which the early orders are early.



The following dimensions are available for this cube:

Dimension Available levels of detail Item All / Item Group / Item Item All / StatGrpPur / Item Order System All / Ordersystem ItemType All / ItemType

All / FinSupplGrp / Supplier Supplier All / Country / Supp Category /Supplier

Warehouse All / Warehouse ReceiptDate All / Year / Quarter / Month / Day Pur Normal Return Order All / Normal Return Order Type

Purchase_Order_Process cube You can use the purchase order process cube to analyze the purchase order process, which consists of order intake procedures, cancellation procedures, and order receipt procedures. The measures available to perform this analysis are described here:

The cube contains the following measures:

Measures Description Quantity_Order_Received Received quantity in inventory unit. Amount _Order_Received Net value of the received quantity. Discount for Quantity Received

Discount amount for the received quantity.

Total_Cost_For_Goods_ Received

Total cost of good received.

Quantity_Order_Placed Quantity in inventory unit for the purchase orders placed.

Amount_Order_Placed Net value of the purchase orders placed. Quantity_Order_Deleted Deleted quantity in inventory unit. Amount_Order_Deleted Net value of deleted qty. Open Order Quantity This is the quantity of open order until date (at the

end of a specific period) in terms of inventory unit. Open Order amount This is the value of open orders until date (at the

end of a specific period) in terms of inventory unit. Variance Difference between Total_Cost_For_Goods_

Received and Amount_Order_Received. Net_Price This is calculated by dividing Amount

_Order_Received by Quantity_Order_Received.



The available dimensions for purchase order process analysis are:

Dimension Available levels of detail Item All / Item Group / Item Item All / StatGrpPur / Item Order System All / Ordersystem Item Type All / ItemType Supplier All / FinSupplGrp / supplier

All / Country/Supp Category/ supplier Supplier All / FinSupplGrp / supplier

Transaction Date All / Year / Quarter / Month / Day Pur Normal Return Order All / Normal Return Order Type

Cube Vendor_Reliability2 The cube contains measures to analyze the reliability of the supplier in terms of adherence to quality and delivery. The measures that are available in this cube are:

Measures Description Approved_Quantity Approved quantity for all purchase receipts. Rejected_ Quantity Rejected quantity for all purchase receipts. Orderline_Quantity Order line quantity of all purchase orders placed. For a

return order, the order line quantity is considered zero. Received_ Quantity Approved + rejected quantity. Received_Amnt The value of Received_Qty. Ontime_Receipts_CurrPlanRecDt Number of receipt lines that are received on time. The

actual receipt date is compared with the current planned receipt date to determine whether the receipt is on time.

Late_Receipts_CurrPlanRecDt Number of receipt lines that are received late. The actual receipt date is compared with the current planned receipt date to determine whether the receipt is late.

Early_Receipts_CurrPlanRecDt Number of receipt lines that are received early. The actual receipt date is compared with the current planned receipt date to determine whether the receipt is early.

Rejected_Receipts_Inspection Number of receipts with rejection. The rejections being registered during the approval process for normal orders.



Total_Rejected_Receipts Total number of receipts with rejection. The rejections being registered during the approval process of normal orders or on account of return orders.

Lines_Received_Complete Number of order lines completely received and processed.

Ontime_Receipts_FirstPlanRecDt Number of receipt lines that are received on time. The actual receipt date is compared with the first planned receipt date to determine whether the receipt is on time.

Late_Receipts_FirstPlanRecDt Number of receipt lines that are received late. The actual receipt date is compared with the first planned receipt date to determine whether the receipt is late.

Early_Receipts_FirstPlanRecDt Number of receipt lines that are received early. The actual receipt date is compared with the first planned receipt date to determine whether the receipt is early.

Rejected Order Line Number of order lines that have rejections. Early_Qty_CurrPlanRecDt_% Percentage of received quantity that is received early.

The actual receipt date is compared with the current planned receipt date to determine whether the receipt is early.

Late_Qty_CurrPlanRecDt_% Percentage of received quantity that is received late. The actual receipt date is compared with the current planned receipt date to determine whether the receipt is late.

Ontime_Qty_CurrPlanRecDt_% Percentage of received quantity that is received on time. The actual receipt date is compared with the current planned receipt date to determine whether the receipt is on time.

Early_Receipts_CurrPlanRecDt_% Percentage of receipt lines that are received early. The actual receipt date is compared with the current planned receipt date to determine whether the receipt is early.

Late_Receipts_CurrPlanRecDt_% Percentage of receipt lines that are received late. The actual receipt date is compared with the current planned receipt date to determine whether the receipt is late.

Ontime_Receipts_CurrPlanRecDt_%

Percentage of receipt lines that are received on time. The actual receipt date is compared with the current planned receipt date to determine whether the receipt is on time.

AvgDaysEarly_CurrPlanRecDt Average number of days by which the receipt lines are early. The actual receipt date is compared with the current planned receipt date to determine whether the receipt is early.



AvgDaysLate_CurrPlanRecDt Average number of days by which the receipt lines are late. The actual receipt date is compared with the current planned receipt date to determine whether the receipt is late.

AvgDaysEarly_CurrPlanRecDt_Wt Weighted average number of days the receipt lines are early. The actual receipt date is compared with the current planned receipt to determine whether the receipt is early. The quantity received against the receipt line is used as weight to calculate the weighted average.

AvgDaysLate_CurrPlanRecDt_Wt Weighted average number of days by which the receipt lines are late. The actual receipt date is compared with the current planned receipt date to determine whether the receipt is late. The quantity received against the receipt line is used as weight to calculate the weighted average.

Early_Qty_FirstPlanRecDt_% Percentage of received quantity that is received early. The actual receipt date is compared with the first planned receipt date to determine whether the receipt is early.

Late_Qty_FirstPlanRecDt_% Percentage of received quantity that is received late. The actual receipt date is compared with the first planned receipt date to determine whether the receipt is late.

Ontime_Qty_FirstPlanRecDt_% Percentage of received quantity that is received on time. The actual receipt date is compared with the first planned receipt date to determine whether the receipt is on time.

Early_Receipt_FirstPlanRecDt_% Percentage of receipt lines that are received early. The actual receipt date is compared with the first planned receipt date to determine whether the receipt is early.

Late_Receipt_FirstPlanRecDt_% Percentage of receipt lines that are received late. The actual receipt date is compared with the first planned receipt date to determine whether the receipt is late.

OnTimeReceipt_FirstPlanRecDt_%

Percentage of receipt lines that are received on time. The actual receipt date is compared with the first planned receipt date to determine whether the receipt is on time.

AvgDaysEarly_FirstPlanRecDt Average number of days by which the receipt lines are early. The actual receipt date is compared with the first planned receipt date to determine whether the receipt is early.



AvgDaysLate_FirstPlanRecDt Average number of days by which the receipt lines are late. The actual receipt date is compared with the first planned receipt date to determine whether the receipt is late.

AvgDaysEarly_FirstPlanRecDt_Wt Weighted average number of days by which the receipt lines are early. The actual receipt date is compared with the first planned receipt to determine whether the receipt is early. The quantity received against the receipt line is used as weight to calculate the weighted average.

AvgDaysLate_FirstPlanRecDt_Wt Weighted average number of days by which the receipt lines are late. The actual receipt date is compared with the first planned receipt to determine whether the receipt is late. The quantity received against the receipt line is used as weight to calculate the weighted average.

Approved_Quantity_% Percentage of received quantity that is approved. Order_Receipt_Approval_% Percentage of receipts for which no rejections exist in

the receipt line. Orderline_Approved_% Percentage of order lines for which not a single receipt

was rejected. Avg_Deliveries_Per_Line Average number of receipts made for each order line. Avg_LeadTime_OrderConfirmation Average number of days between the order date and

the date when the order line is acknowledged. Cost_Performance_Ratio The average of the cost performance ratio, which is

calculated for the individual receipt lines. At the receipt line level (order number + position + sequence), the cost performance ratio is defined as the ratio of net price for the receipt line by the average purchase price applicable at that instance.

First planned receipt date: For a Purchase order line, this is the First of the planned delivery dates as agreed between the Buyer and Supplier. This is the confirmed delivery date of the First receipt of the purchase order line. If the confirmed delivery date is not available, the planned delivery date is considered.

Current planned receipt date: The confirmed delivery date or plan delivery date for the back order as agreed by the supplier. This is the confirmed delivery of the receipt line. If the confirmed delivery date is not available, the planned delivery date is considered.

NOTE




Dimension Available Levels of detail Item All / Item Group / Item All / Stat Grp Pur / Item Order Type All / Normal Return Order Type Order System All / Order system Item Type All / Item Type FinSupplGrp All / FinSupplGrp Supplier All / Country / Supp Category / Supplier Receipt Date All / Year / Quarter / Month / Day Logical Company All / Logical Company Warehouse All / / Warehouse Finance Company All / Finance Company Employee All / Employee

Cube Contract_Turnover You can use this cube to analyze the invoiced value against contracts.

Measures Description Apportioned Qty Apportioned quantity in inventory unit. The lowest

level of time at which you can analyze is Month. Net Apportioned Value Net value of the apportioned quantity. The lowest

level of time at which you can analyze is Month. Invoiced Quantity Invoiced quantity in inventory unit. Net Invoiced Value Net value of invoiced quantity.


Dimension Hierarchy Item All / Item Group / Item

All / Country / Supp Category / Supplier Supplier All / FinSupplGrp / Supplier

ConTransaction Date All / Year / Quarter / Month / Day Employee All / Employee Contract Type All / Contract Type Logical Company All / Logical Company



Cube Contract_Perf This cube analyzes the expected percentage contract consumption, which assumes the uniform consumption of a contract over time against the actual percentage of contract consumption through the current date.

Measures Description Agreed Quantity Agreed quantity in inventory unit. Net Agreed Value Net value of agreed quantity. Invoiced Quantity Invoiced quantity in inventory unit. Net Invoiced Value Net value of invoiced quantity. Time Elapsed If the date stored is earlier than the contract

expiry date, time elapsed is the time difference between the contract effective date and date stored. Otherwise, time elapsed is the difference between the contract expiry date and the effective date. The date stored is the date on which the data warehouse is uploaded.

Expected Quantity Quantity expected to be received in time elapsed, which assumes the uniform consumption of contract over a period.

Actual Invoiced Quantity % Percentage of the agreed quantity that has been Invoiced. Calculated as: Invoiced quantity/Agreed quantity.

Expected Quantity % Percentage of the agreed quantity that is expected in the elapsed time. Calculated as: Expected quantity/Agreed quantity.


Dimension Hierarchy Item All / Item Group / Item

All / Country / Supp Category / Supplier Supplier All / FinSupplGrp / Supplier

Turnover Date All / Year / Quarter / Month / Day Employee All / Employee Logical Company All / Logical Company

The turnover date is the transaction date of the last turnover record for a contract number and position number.

NOTE



Cube Pur_Cost_Tracking This cube is used to analyze the planned and the actual savings. The actual savings are calculated based on the contract and actual purchase made. The potential savings are calculated with reference to the last period.

Measures Description Planned Contract Qty The agreed quantity by a contract for a period.

The lowest level of time at which you can analyze is Month.

Planned Contract Value Net Value of Planned Contract Qty. The lowest level of time at which you can analyze is Month.

Received Qty Inv Total of actual received quantity in inventory unit. The lowest level of time at which you can analyze is Month.

Net Received Amnt Net Value of Received Qty Inv. The lowest level of time at which you can analyze is Month.

Avg Price LastPeriod_Int Internal measure that is exposed to the end user. This is a calculated measure and cannot be hidden. This measure is used for calculating Avg Price LastPeriod.

Avg Price LastPeriod The average purchase price for the previous period. Calculated as follows: sum (Net Received Amnt)/sum (Received Qty Inv) for previous period.

Target Avg Price CurPeriod The average contracted price for the current period. Calculated as follows: Sum (Planned Contract Value)/sum (Planned Contract Qty).

Avg Price CurrentPeriod The average purchase price for the current period. Calculated as follows: Sum (Net Received Amnt)/Sum (Received Qty Inv) for current period.

Potential Savings Potential saving for the current period. Calculated as follows: Planned Contract Qty*(Avg Price LastPeriod - Target Avg Price CurPeriod).

Savings Achieved Actual saving for the current period. Calculated as follows: Received Qty Inv *(Avg Price LastPeriod - Avg Price CurrentPeriod).




Dimension Hierarchy All / Item Group / Item Item All / Stat Grp Pur / Item

Item Type All / Item Type All / Country / Supp Category / Supplier Supplier All / FinSupplGrp / Supplier

Analysis_Period All / Year / Half Year / Quarter / Month Logical Company All / Logical Company

Cube Pur_Maverick This cube enables you to analyze leakage in the purchase process due to undisciplined buying outside purchase contracts. This type of undisciplined buying is referred to as Maverick buying. This cube also analyzes the savings or loss that is incurred due to Maverick buying.

Measure Description Received Quantity The quantity received against all purchases

made. Net Received Amnt The value of the quantity that was received. Received Qty WithCont Purchases made against a contract. Net Received Amnt WithCont Value of the purchases made against a contract. Maverick Quantity The quantity purchased without using a contract,

in spite of having a valid contract. Maverick Amnt The value of the quantity purchased without

using a contract, in spite of having a valid contract.

Received Qty W/O Con The quantity received for items that had no contract.

Net Received Amnt W/O Cont The value of quantity received for items that had no contract.

Maverick Variance Difference between the Maverick value and the product of Maverick quantity and weighted average price from contracts.

Positive Maverick The value of Maverick purchases that has lead to savings.

Negative Maverick The value of Maverick purchases that has lead towards the incurrence of a loss.

Savings Maverick The savings made due to Maverick purchases. Loss Maverick The loss incurred due to Maverick purchases.





Item Type All / Item Type Order System All / Order system Supplier All / Country / Supp Category / Supplier FinSuppGrp All / Finance Supp Grp Analysis Date All / Year / Half Year / Quarter / Month / Day Employee All / Employee Logical Company All / Logical Company Warehouse All / Warehouse



Cube Vendor_Allocation This cube analyzes the planned contract consumption against the actual consumption of contracts over time and supplier.

Measure Description Planned Contract Qty The agreed quantity, by a contract for a period.

The lowest level of time at which you can analyze is Month.

Planned Contract Value Net Value of Planned Contract Qty. The lowest level of time at which you can analyze is Month.

Received Qty Inv Total of actual received quantity in inventory unit. The lowest level of time at which you can analyze is Month.

Net Received Amnt Net Value of Received Qty Inv. The lowest level of time at which you can analyze is Month.

Received Qty Con The received quantity against a contract. The lowest level of time at which you can analyze is Month.

Net Received Amnt Con The value of received quantity against a contract. The lowest level of time at which you can analyze is Month.



Item Type All / Item Type Supplier All / Country / Supp Category / Supplier All/ Fin Supp Grp / Supplier Analysis_Period All / Year / Half Year / Quarter / Month Logical Company All / Logical Company



Cube Pur_Quotation You can use this cube to analyze the results and status of requests for quotations sent to various suppliers.

Measure Description Placed Quantity The quantity for which the request for quotation

was placed on suppliers. Returned Quantity The quantity for which the supplier returned the

request for quotation. Successful Quantity The quantity for which the request for quotation

was successful. The quotation is successful when it is converted into a purchase order.

Unsuccessful Quantity The quantity for which the request for quotation was unsuccessful.

Net Returned Amount The value of the quantity with discount for which the request for quotation was returned.

Net Success Amount The value of the quantity with discount for which the request for quotation was successful.

Net Unsuccessful Amount The value of the quantity with discount for which the request for quotation was unsuccessful.

Gross Returned Amount The value of the quantity without discount for which the request for quotation was returned.

Gross Success Amount The value of the quantity without discount for which the request for quotation was successful.

Gross Unsuccessful Amount The value of the quantity without discount for which the request for quotation was unsuccessful.

Number of Lines Placed The number of request for quotation lines that were placed.

Number of Lines Returned The number of request for quotation lines that were returned.

Number of Lines Successful The number of request for quotation lines that were successful.

Number of Lines Unsuccessful

The number of request for quotation lines that were unsuccessful.

Number of Lines Returned Late

The number of request for quotation lines that were returned after the return date.

Percentage_ Cumm_Lines_ Not_ Replied

The percentage of request for quotation lines that have not been replied by the suppliers until date.

Percentage_Cumm_Lines Successful

The percentage of request for quotation lines that have been converted to either purchase order until date.

Percentage_Cumm_Lines Unsuccessful

The percentage of request for quotation lines that have not been converted to purchase order until date.




Dimension Hierarchy All / Item Group / Item Item All / Purchase Statistics Grp / Item

Item Type All / Item Type Supplier All / Country / Supp Category/ Supplier Analysis Date All / Year / Half Year / Quarter / Month / Day Logical Company All / Logical Company

Cube Pur_Change_Analys You can use this cube to analyze the changes that are made to purchase order lines for various reasons.

Measure Description Number of Lines Changed Number of order lines that have been changed.

Number of Lines Canceled Number of order lines that have been canceled. The following dimensions are available for this cube:

Dimension Hierarchy Finance Company All / Finance Company FinSuppGrp All / Fin Supp Grp

All / Item Group / Item Item All / Stat Grp Pur / Item

Item Type All / Item Type Supplier All / Country / Supp Category / Supplier Analysis Date All / Year / Half Year / Quarter / Month / Day Logical Company All / Logical Company Change Reason All / Change Reason Change Type All / Type of Change / Change Type Order System All / Order System Warehouse All / Warehouse Pur Normal Return Order All / Normal Return Order Type



Cube Pur_LeadTime_Analy You can use this cube to analyze and compare the standard, planned, and actual lead-time for a purchasing process.

Measure Description Avg Standard Lead Time

The average standard lead-time, as defined for the Item-Supplier combination, expressed in days.

Avg Plan Lead Time

The average plan lead-time, expressed in days. Plan lead-time is the difference of planned delivery date for a purchase order line and the order line date.

Avg Actual Lead Time

The average actual lead-time, expressed in days. Actual lead-time is the difference of actual delivery date for a purchase order line and the order date. For multiple receipts for a purchase order line, the maximum actual receipt date for that purchase order line is considered.

Plan Lead Time Difference

The difference between standard lead-time and plan lead-time.

Actual Lead Time Difference

The difference between standard lead-time and actual lead-time.

Days Early For PlanLeadTime

Number of days by which first planned delivery date of a purchase order line is before the order line date + standard lead time.

Days Late For PlanLeadTime

Number of days by which first planned delivery date of a purchase order line is after the order line date + standard lead-time.

Count Early For PlanLeadTime

Number of purchase order lines for which plan lead-time difference is positive.

Count Late For PlanLeadTime

Number of purchase order lines for which plan lead-time difference is negative.

Count OnTime For PlanLeadTime

Number of purchase order lines for which plan lead-time difference is zero.

Avg Day Late For PlanLeadTime

Average number of days by which first planned delivery date of a purchase order line is after the order line date + standard lead time. Calculated as follows: Days Late For PlanLeadTime/Count Late For PlanLeadTime.

Avg Day Early For PlanLeadTime

Average number of days by which first planned delivery date of a purchase order line is before the order line date + standard lead time. Calculated as follows: Days Early For PlanLeadTime/Count Early For PlanLeadTime.

Timely Plan Procurement %

Percentage of purchase order lines for which the plan lead-time difference is positive or zero.

On Time Plan Procurement %

Percentage of purchase order lines for which the plan lead-time difference is zero.

Late Plan Procurement %

Percentage of purchase order lines for which the plan lead-time difference is negative.

Early Plan Procurement %

Percentage of purchase order lines for which the plan lead-time difference is positive.




Dimension Hierarchy Finance Company All / Finance Company Logical Company All / Logical Company

All / Item Group / Item Item All / Stat Grp Pur / Item

Item Type All / Item Type Supplier All / Country / Supp Category / Supplier FinSuppGrp All / Fin Supp Grp Analysis Date All / Year / Half Year / Quarter / Month / Day Order System All / Order System Warehouse All / Warehouse Employee All / Employee


This chapter describes several forms of analysis that you can carry out based on the Business Content described in the previous chapter.

The following examples show the capabilities of the Business Content for purchase. Thanks to the flexibility of the OLAP environment and the reporting environment, several issues can be clarified with the help of the Business Content. Because these environments work with the notion of dimensions extensively, you can easily produce the information on the level you want.

Vendor reliability analysis You can judge the reliability of a supplier by the performance of the supplier in the following areas:

Conformance to the delivery schedule. Conformance to quality of the delivered goods. Performance compared to average price. Performance in purchase order line acknowledgment.

In addition to the Vendor Reliability cube provided in the version 2 of the Purchase template, Template 3.0 for BAAN IVc Purchase provides an additional cube Vendor_Reliability2. This cube is built on the fact table DW_PUR_VENDOR_RELIABILITY; the granularity of this fact table is purchase ordine receipts. This provides the user an option to track the vendor delivery performance at purchase receipt level.

With the Vendor_Reliability2 cube, the user can carry out the following types of analysis:

3 Examples

Examples


Supplier delivery performance analysis You can use this analysis to judge the level of the supplier’s adherence to the delivery schedule.

The user wants to find the number of purchase order line receipts that were received on time, late, or early, and investigate the cause of why some purchased order line receipts were received late.

The information can be presented for a specific supplier or for all suppliers, and for purchase order lines with an actual receipt date that falls within a specific date range.

The ‘lateness’ is calculated for the individual receipt lines. Two definitions are used to determine whether a receipt line is late. For the first definition, the actual receipt date of an individual receipt line is compared with the current planned receipt date, to determine whether the receipt line is late. For the second definition, the actual receipt date of an individual receipt line is compared with the first planned receipt date to determine whether the receipt line is late.

Using these two definitions, you have two sets of measures that you can use to check how well the suppliers are adhering to the planned receipt dates.

These measures provide you with answers to the following questions:

How many receipt lines are late, early, and on time? What percentages of receipt lines are late, early, and on time? How many days on average are the receipts lines late, early, and on time? What percentage of the received quantity is received late, early, and on time?

In addition to these measures, received quantity is used as a weight factor to calculate measures, which also provide answers to the third and fourth questions discussed in the previous list.

The following example helps explain the performance indicators that are required for lateness:

Purchase order number

Position Receipt number

Received quantity

Current planned receipt date

Actual receipt date

Lateness (First planned receipt date)

Lateness (Current planned receipt date)

100 10 1 60 Day 10 Day12 2 2 100 10 2 30 Day10 Day13 3 3 100 10 3 10 Day 10 Day15 5 5 200 10 1 30 Day 20 Day20 0 0 200 10 2 70 Day 28 Day 29 9 1

EXAMPLE

Examples


First planned receipt date: For a Purchase order line this is the ‘First’ of the planned delivery dates as agreed between the Buyer and Supplier. This is the confirmed delivery date of the ‘First ‘ receipt of the purchase order line. If the confirmed delivery date is not available, the planned delivery date is considered.

Current planned receipt date: The confirmed delivery date or plan delivery date for the back order as agreed by the supplier. This is the confirmed delivery of the receipt line. If the confirmed delivery date is not available, the planned delivery date is considered.

In this example, for order number 100 the first plan delivery date is not changed for the subsequent back orders. Therefore, the lateness calculation that considers both the definitions provides the same result.

However, for order number 200, the back order planned delivery date as agreed by the supplier is day 28. The back order date is registered in BAAN IVc to know when the remaining quantity is expected. From a vendor rating perspective, the first planned delivery date is the date when the supplier promised to deliver the goods. Using the first planned receipt date, the lateness for the second receipt line of order number 200 is nine days, compared to one day if you compare the actual receipt date with the current planned receipt.

For the previous example, the following equations result:

Average days late (considering-First planned receipt date) = (2+3+5+9)/4

=19/4 = 4.75 days

Wt Average days late (considering-First planned receipt date) =(2*60+3*30+5*10+9*70)/170= 890/170

= 5.23 days

Late quantity % (considering-First planned receipt date)=(60+30+10+70)/200

= 170 /200 = 85% Average days late (considering-current planned receipt date)=(2+3+5+1)/4

=11/4

= 2.75 days

Wt Average days late (considering-current planned receipt date) =(2*60+3*30+5*10+1*70)/170 = 330/170

= 1.94 days

Late quantity % (considering-current planned receipt date)=(60+30+10+70)/200

= 170 /200 = 85%

NOTE

Examples


Weighted average related measures have made use of quantity as a weight. The value of the individual receipt line has also been provided. To use the value of receipt line as a weight factor, the user must create a new set of measures using this value rather than quantity as a weight factor.

Similarly, you can also compute the performance indicators related to average earliness.

Another performance indicator that can be of interest to the end user is the following:

Avg. No. Of Deliveries Per Order Line = Number Of Receipts / Received Order Line Count.

This indicator shows that, on average, the supplier has completed these orders in “N” number of deliveries. You can carry out this analysis at item level or at aggregate level.

Supplier’s quality performance analysis The user can analyze the quality performance related to deliveries of a particular item from various suppliers over a particular time period.

This information is available using the OLAP cube.

The following are the performance indicators that are available in the vendor reliability cube that assist the user to analyze vendors in terms of the quality of their deliveries:

Order Line Approval % = ((Received Order line - Rejected Order Line) / Received Order line) * 100.

Order Receipt Approval % = ((Number Of Receipts - Rejected Receipts Inspection) / Number Of Receipts) * 100.

Approved Qty % = (Approved Qty / Received Qty) * 100.

The following example illustrates the difference between the first two measures:

A supplier (S1) has delivered 100 order lines for a particular item. These orders were delivered in 400 receipts. 80 of the 100 order lines only have a single receipt with rejection. In this case, the order line approval percentage is 20%.

The remaining 20 order lines each have two receipts with rejection. Therefore, the total number of receipts with rejection is 80 +20 * 2 = 120.

In other words, (400-120)/400 70% of the receipts are approved against 20% of the order lines that are approved.

EXAMPLE

Examples


To better understand the importance of these measures, consider the pros and cons of the measures, as explained in the following table. These three measures provide a good view of the quality of supplies from the vendor.

Measure Pros Cons Order Line Approval %

Helps determine the number of purchase order lines rejected.

Even if a small part of one partial delivery is rejected, the complete order line is counted as Rejected. A supplier with several small errors will receive a very low score based on this measure.

Order Receipt Approval %

Helps determine the number of receipts for Normal orders that have rejections.

Both If quantities are rejected after being taken into inventory, the quantities are shipped back by a return order. One return order can ship back quantities from multiple receipts. In this case, the measures rejected order line and rejected receipt_inspection are misleading. As these counts are made use of for calculating the previous measures in this table.

Approved Qty %

Because this measure is based purely on quantities and not on counting order lines or partial deliveries, the measure does not suffer from any of the count-related problems mentioned previously.

Because quantity values depend on the inventory unit of the item, items with a small unit, such as grams, have large quantity values, and items with a large unit, such as tons, have a small quantity value. When you aggregate this measure over multiple items, the items with a small unit overemphasize the result. This analysis is most effective if the user analyzes this measure at item level.

Examples


Suppliers price performance It would be interesting for the user to know how a particular supplier’s price compares to the average price of an item, in a particular period. The vendor reliability cube makes available the performance indicator cost performance ratio to track this aspect.

To arrive at this performance indicator, for each receipt line in the DW, the price (InvoicedAmount/InvoicedQuantity) for that receipt line is divided by the average purchase price applicable at that instance.

For example, if the actual unit price for a particular receipt line is 9, and the average purchase price for that item from all suppliers is 10 at that instance of time, the cost performance ratio for that receipt line is 9/10= 0.9. A value of less than 1 indicates a favorable price.

The cost performance ratio at the cube level for a particular period is calculated by considering the average of the ratio’s calculated for all the receipt lines for that period.

Supplier’s performance – To acknowledge the purchase order lines The vendor reliability cube makes available the measure, which enables the user to track the lead time required by the suppliers to acknowledge the purchase order line.

Avg_LeadTime_ OrderConfirmation

Average number of days between the order date and the date when the order line is acknowledged.

The previous analyzes are examples of analysis that you can perform using the vendor reliability cube provided in the OLAP client. Simply select the performance indicators explained previously, and slice on dimensions such as supplier, item, and actual receipt date.

Examples


Purchase order process analysis With the Purchase Order Process cube, the user can carry out the following types of analysis:

Comparison of the quantities and values for orders placed and received in a period of time This type of analysis enables the user to compare the value of business that is offered to various suppliers at an aggregate level, or for various item group, or at an item level over a period of time.

Purchase order variance analysis This type of analysis enables the management of an organization to compare the difference between the values of goods received and the cost of goods for a period of time. This difference, which is known as variance, can be a positive or negative variance, which in turn determines whether the management can take corrective actions.

Open order analysis This cube provides the user with the quantity of open items and their value at the end of a particular period of time. The values can be seen at an aggregated level for all the suppliers for item/item group/all items, or for an individual supplier.

Movement of price You can use this cube to indicate the movement of the net price for a particular item, supplied by various suppliers over a period of time.

1 To calculate the net price, you must divide the net value of received items during a period by the quantity received during that period. For a particular date, if no receipts of a particular item are available, the net price is then reflected as zero in the OLAP client.

2 The Purchase Order Process cube makes use of Purchase Order Line History(tdpur051) as a source table from BAAN IVc. The information related to purchase receipts is updated in tdpur051 (as Record Type = 3) only when the purchase order lines are processed. Hence, it is essential to process the purchase order lines before the data warehouse is uploaded.

NOTE

Examples


Contract turnover/performance analysis With purchase contract turnover analysis, the user can analyze the consumption of the contract by the various purchase orders over time. With purchase contract performance analysis, the user can analyze the contract’s performance in the elapsed time.

The OLAP cube provides measures in terms of quantity and values for the expected and actual consumption of purchase contract by the various purchase orders in the elapsed time.

Maverick analysis Most of the direct materials and indirect materials are purchased against company-wide agreed-upon standards by establishing the contracts to which all purchase orders must refer. In certain cases, a purchase can be made outside contracts for various reasons, such as nonperformance of the existing sources. All such purchases, which existing contracts are not made use of, are referred to as Maverick buying, or contract leakage. Maverick purchases are cost-saving opportunities and must be controlled. This provides the buyer the opportunity to identify where resources are required to eliminate the leakage.

You can perform analysis across dimensions such as Logistic Companies, Item, and Buyer.

To explore the supplier of the Maverick amount, select the measures positive maverick amount and the savings on one axis, and select the supplier on the other axis and then drill down the supplier dimension hierarchy.

Examples


Vendor allocation analysis With the use of the Pur_Vendor_Alloc cube, you can analyze and compare the planned contract consumption against the actual consumption of contracts over time and supplier.

The following table represents the planned allocation for item I1 across various suppliers for a particular period in terms of quantity, value, and percentage (%). Entering into agreements with suppliers by establishing contracts creates the planned allocations.

Supplier Planned contracted quantity

Planned contracted value

% Total by quantity

% Total by value

S1 25 25% S2 35 35% S3 40 40% Total 100

The following table represents the actual allocations that have transpired for item I1 across various suppliers for a particular period in terms of quantity, value, and percentage (%).

Supplier Actual quantity received

Received value

% Total by quantity

% Total by value

S1 15 15/110 S2 30 30/110 S3 45 45/110 S4 (Maverick buying)

20 20/110

Total 110 In addition to suppliers S1, S2, S3, another supplier (S4) is allocated some part of the planned allocation. Making use of the Pur_Vendor_Alloc cube, you can analyze and compare the planned contract consumption against the actual consumption of contracts over time and supplier. The minimum level of time dimension at which you can analyze is Month level. The values related to Percentage by Total must be calculated at OLAP client level.

Examples


Cost reduction tracking analysis Every year, or for a given period, a purchase organization sets targets to contain costs. A target consists of the following three components:

Target set at the beginning of the year. Potential savings. Savings achieved.

In BAAN IVc, you cannot set target information related to potential savings and savings achieved.

With the use of the cube Pur_Cost_Tracking, you can analyze the savings that were planned and what was achieved. The savings are calculated based on the contract relating to actual purchases made.

The following is a calculation for potential savings and savings achieved, for example, at the end of a specific year:

Last year Average Price = Σ (Net Received amount for last year) / Σ (Total quantity Purchased for last year).

Current year Target Average Price (Target Avg. Price CurrentPeriod) = Represents the weighted average price for a period calculated using the information from contracts.

Current year Actual Average Price = Σ (Net Received amount) / Σ (Total quantity Purchased for current year).

Potential Savings = (Σ Apportioned quantity) * (Current year Target average Price – Last year average Price).

Savings Achieved = (Σ Total quantity Purchased for current year) * (Current year Actual average Price – Last year average Price).

Examples


Purchase order line change/cancellation analysis Occasionally, you may have to track changes on purchase orders and the reasons for the changes on these purchase orders, because this can affect the entire supply and delivery process.

The cube Pur_Change_Analy makes available the measure to enable the user to track the number of purchase orders lines changed after release, sorting, and counting, using the change_reason and change_type as dimensions.

Cancellation of purchase orders is undesirable for a number of reasons related to planning and supplier relationships. Close monitoring enables the business to keep the number of cancellations to a minimum. Cancellation reason codes must be captured as part of the purchase order process for analysis.

The cube Pur_Change_Analy makes available the measure to enable the user to track the number of purchase orders lines canceled after release, sorting, and counting, using the change_reason and change_type as dimensions.

Purchase order lead-time analysis You must track orders raised with insufficient lead-time to procure, based on the item supplier lead-time information. The Pur_LeadTime_Analysis cube provides the following lead times to the user:

Avg Standard Lead Time The average standard lead-time, as defined for the Item/Supplier combination, expressed in days.

Avg Plan Lead Time The average plan lead-time, expressed in days. Plan lead-time is the difference of planned delivery date for a purchase order line and the order line date.

Avg Actual Lead Time The average actual lead-time, expressed in days. Actual lead-time is the difference of actual delivery date for a purchase order line and the order date. In case of multiple receipts for a purchase order line, the maximum of the actual receipt date for that purchase order line is considered.

Other measures are available, which help to track the deviations between the various lead times calculated and made available in the cube.

Examples


Request for quotation analysis The Pur_Quotation cube provides a set of measures, which assists the user to track the request for quotations (purchase inquiry) related business process, and assists the user in taking sourcing related decisions more objectively and effectively.

The following list provides several business questions that can be answered using the measures and dimensions provided in the cube:

What is the total value of inquiries placed on a particular supplier? What part of the inquiries has been replied and successful? Which are the items for which the inquiries are mostly unsuccessful for a

supplier?

You can use this cube to analyze the result and status of the request for quotations (purchase inquiry).

Documents

User's Guide Template 3.0 for BAAN IVc Purchase Guide Template 3.0 for BAA… · Business Template A collection or subset of export session, iBaan ETL model, dimension, and cube definitions