SlideShare a Scribd company logo
1 of 34
Proprietary and confidential. | 2016 AXIA Consulting™ | All rights reserved.
Phantasmal Item Descriptions in Your Organization?
Oracle Product Information Management to the Rescue
Agenda
• Introduction & Overview
• Session Objectives
• The Problem and the Aftermath
• Key Terms
• Item Description Generation Solution Approach
• Taxonomy Design
• Item Classification
• Schema Design
• Meta-Data Configurations
• SKU Build
• Normalization / Governance
• Description Generation
• Business Considerations
• Best Practices
• Q&A
AXIA Consulting
About AXIA Consulting
At AXIA Consulting, we understand the importance of
choosing a trustworthy partner who takes the time to
understand your business and we have the proven
ability to deliver meaningful results.
With a team of industry experts who average 20 years of
experience in the field, AXIA’s accessible business and
technology leaders hardness their expertise to solve our
clients’ most complex problems.
Founded in 2005, AXIA is 100% employee-owned and
employs approximately 100 Senior Consultants. We are
a global company, delivering results for clients in more
than 54 countries over six continents.
www.axiaconsulting.net
Committed To Excellence
AXIA is driven by values and our commitment
to excellence, resulting in trusted partnerships
and lasting client relationships
Session Objectives
• To help the audience gain basic understanding of
taxonomy, schema and item description process
• To model the solution approach in Oracle PIM along
with setups and configurations
• Simple item description generated from PIM in Oracle E-
Business Suite (EBS)
• To provide a list of business considerations and best
practices in generating item descriptions through
Oracle PIM
“Phantasmal” Problem
• “Phantasmal” Item Data Standards:
• No guidelines to follow when creating or uploading new items
• No guidelines to follow when importing items with new or different structure
(e.g., acquisitions, new roll-outs)
• “Phantasmal” Item Descriptions:
• Difficult to find items (internally and for our e-commerce customers) based
on descriptions
• Difficult to prevent duplicate item descriptions
• Inconsistent, vague, incomplete and of-course incomprehensible item
descriptions
• “Phantasmal” Data Governance
• Lack of control perpetuates the problem
• External and Internal customer “phantomisms” with item
descriptions
Results of Problem
Decimals/Fractions
Abbreviations/full words
Invalid DescriptionsDuplicate Descriptions
Information that does not
belong
BOTTOMLINE – CUSTOMER FRUSTRATION
Key Terms
• Taxonomy: The practice of classification; the order and hierarchy of your
products. Grouping like items into a specific category
• Node: Item catalog category to which an item will be assigned
• Schema: The collection of attributes and their characteristics, such as field type,
size and whether a List of Values is provided
• Attributes:
• Required Attributes: Attributes that are included in system-generated
descriptions
• Optional Attributes: Additional attributes that are not included in system-
generated descriptions
• Normalization: Task to review List of Values and cleanse them down to a
unique list
• Meta-Data: Item Catalogs, Attribute Groups, Pages, Functions, Associations,
etc.
Item Description Generation Approach
Taxonomy
• Taxonomy: the practice of building a classification structure;
the order and hierarchy of your products. Grouping like
items into a specific category
• As Taxonomy is built, it is important to think about your
audience, using relevant language for the audience
• Item Catalog Categories (ICC) form a tree structure in PIM to
create the taxonomy to which items can be assigned
• Taxonomy in PIM
• Top level parent ICC node
• Intermediate ICC nodes
• Leaf ICC nodes
Taxonomy Examples
Item Classification to Taxonomy
• This is the process of assigning items to the taxonomy
structure
• It is important to do this as you are building the Taxonomy,
this will ensure that the Taxonomy will work for your
organization
• Business may decide to normalize the taxonomy after sign
off and item assignment for:
• Removal of redundant nodes
• Consolidation of nodes
• Addition of new nodes
• Taxonomy normalization may lead to:
• Re-assignment of items assigned to the affected nodes
• Loss of attribute information and attribute values for the affected
items if not handled through a defined ICC re-assignment process
Schema Design
Schema: the collection of attributes and their characteristics, such as
field type, size and whether a List of Values is provided
• These are grouped by end node
• Depending on the leaf node and attribute group, the number of
attributes can be different
• Some attributes may not be required and not used to build a
description
• Decision to create separate UOM attributes to reference numeric
values stored in text attributes or use the standard UOM feature with
numeric attributes
• Time intensive phase as different business stakeholders influence
the process of building the schema structure pertinent to their
department and needs
Schema Examples
Attributes ranked with a 0 are not
required, and will not be used to
generate descriptions
Attribute Name Data Type Ranking
Product Type LOV 1
Motor Horsepower Number 2
Motor Horsepower UOM LOV 3
Frame Size Text 4
Motor Type LOV 5
Motor RPM Number 6
Motor RPMUOM LOV 7
Motor Phase LOV 8
Motor Voltage Text 9
Frequency Number 10
Frequency UOM LOV 11
Mounting Type LOV 12
Enclosure Type LOV 13
Brake Type LOV 14
Brake Full Load Torque Number 0
Brake Full Load Torque UOM LOV 0
Brake Horsepower Number 0
Brake Horsepower UOM LOV 0
Brake Voltage Number 0
Brake Voltage UOM LOV 0
Efficiency Rating Text 0
Feedback Device Type LOV 0
Full Load Amp Rating Number 0
Full Load Amp Rating UOM LOV 0
Motor Full Load Torque Number 0
Motor Full Load Torque UOM LOV 0
Number of Poles Number 0
Product Line Text 0
Service Factor Number 0
AC Motors
Attribute Name Data Type Ranking
Product Type LOV 1
Overall Length Number 2
Overall Length UOM LOV 3
Overall Width Number 4
Overall Width UOM LOV 5
Abrasive Material LOV 6
Backing Material LOV 7
Color Text 8
Product Line Text 0
Abrasives
Configurations and Setups in PIM
• Meta-data creation is an essential component of PIM setup
and thereby generating item descriptions
• Meta-data Load Approaches:
• PIM User Interface – very tedious and time consuming
• PIM Interface tables – only inbound approach
• FNDLOAD – very technical approach
• iSetup – very limited to couple of entities
• Mandatory Meta-Data Configurations:
• Item Catalog Categories (ICC)
• Attribute Groups and User Defined Attributes (UDA)
• PIM Functions
• Value Sets and Values for UDA list of values
• Pages and Page Entries
• ICC – Attribute Group Association
• ICC – Function Association
Meta-Data Load Approach Comparison
Configuration Entity Relationships
ITEM CATALOG CATEGORY
ATTRIBUTE
GROUPS
PAGES
USERDEFINED
ATTRIBUTES (UDA)
PAGEENTRIES
FUNCTIONS
PARAMETERS
VALUE
SETS
Item Catalog Categories
Navigation: Inventory > Setup > Items > Catalog Groups
Attribute Groups
Navigation: Development Manager > Setup > Setup Workbench > Items (T) > Attribute Groups (T)
User Defined Attributes (UDA)
Navigation: Development Manager > Setup > Setup Workbench > Items (T) > Attribute Groups (T)
Description Generation Function
Navigation: Development Manager > Setup > Setup Workbench > Function (T)
ICC – Function Association
Navigation: Development Manager > Setup > Setup Workbench > Click on Item Catalog
Category > Description Generation
ICC – Attribute Group Association
Navigation: Development Manager > Setup > Setup Workbench > Click on Item Catalog
Category > Attribute Groups
ICC Pages
Navigation: Development Manager > Setup > Setup Workbench > Click on Item Catalog
Category > Item Pages
Meta-Data Interface Insert Scripts
Meta-Data Import Program
Navigation: Development Manager > View > Requests > Submit a New Request > Single Request
SKU Build
• SKU Build comprises of:
• Filling out the attribute values for the attributes defined in the
schema structure (can be done offline in excel workbook)
• Uploading the attribute values into the system for building
descriptions (custom PL/SQL process)
• Major work lies in gathering the attribute value information:
• Internal product information and knowledge
• Supplier/Manufacturer provided manuals, emails, calls, etc.
• “What is Good Enough”
• Attribute data available may not be specific enough to fill in values
for all the attributes created for the end node
• May need to do research in order to fill in the data
• A decision point needs to happen to determine “What is Good
Enough” in order start generating descriptions
• It may take several iterations to determine that and it will be a
different answer based on the node
Normalization/Governance
• Normalization
• Taxonomy and Schema
o Consolidation
o Remove Redundancy
• Meta Data
o Attributes
o Value Sets
o Functions
o Pages, etc.
• Review List of Values and cleanse them
• Typos
• Differing abbreviations
• Different data being added for a different parts within the same end node
• In the current organization the word Motor may be in descriptions like this:
o Motor
o MTR
o MOTR
• Using LOVs and agreeing on one abbreviation for Motor ensures
consistency across all descriptions
Description Generation
• Within PIM the description function calls a custom PL/SQL
package to create the description
• Each PIM Function can call a different PL/SQL function
• The definition of the function will pass all of the required
parameter values to the PL/SQL package
• The PL/SQL package can then be created to concatenate the
values together to make a description
• Only the Description field is updated, not the Long
Description
Description Generation Enhancements
• Create a Long Description with all attributes spelled out
• Regular Description will use abbreviations from LOVs
• Ability to add abbreviations for the attribute names, and add
them as prefixes or suffixes to the attribute value within the
description
• Ability to regenerate descriptions for all items in an end node
if an abbreviation needs to change in an LOV
• Overload 1 PL/SQL function so that all call PIM Functions call
the same PL/SQL function
Description Generation Examples
ITEM
NUMBER ORIGINAL DESCRIPTION DESCRIPTION LONG DESCRIPTION
185063 BEARING MLLR F-1665-7H W/GRS
BEARING, FLANGE MOUNT, 0 BOLTS, RND HSG
TYPE, BALL, .451IN BORE DIA, GR, STD
Bearing, Flange Mount, 0 Number of Bolts,
Round Housing Type, BALL, .451In Bore
Diameter, Greased, STD
200597 BRG FLG 1-3/16B 2B MLLR BRG
BEARING, FLANGE MOUNT, 2 BOLTS, BRKT
HSG TYPE, 1.1875IN BORE DIA, LUBRICATED,
FOOD GRADE
Bearing, Flange Mount, 2 Number of Bolts,
Bracket Housing Type, 1.1875In Bore
Diameter, Lubricated, Food Grade
3802001 PL 3/8X60X60 HR 1045
PLT, STL, HRS, C1045, .375IN THK, 60IN
OVERALL LEN, 60IN OVERALL WD
Plate, Steel, Hot Rolled, C1045, .375In
Thickness, 60In Overall Length, 60In Overall
Width
7043341 PLATE HRPO 1/4 C1045 48X120
PLT, STL, HRS, C1045, .25IN THK, 120IN
OVERALL LEN, 48IN OVERALL WD
Plate, Steel, Hot Rolled, C1045, .25In
Thickness, 120In Overall Length, 48In Overall
Width
420D410 ROLLER_DRIVE_CPL_Ø98_BW1200
ROLLER, STRAIGHT UNPOWERED, 98MM
ROLLER DIA, 2 GRV, 35MMAXLE SZ, RND, STL
TUBE, ZINC-PLATED, TIMING SPROCKET
Roller, Straight Unpowered, 98mm Roller
Diameter, 2 Number of Grooves, 35mm Axle
Size, Round, Steel Tube Material, Zinc-
Plated, Timing Sprocket
70701010 1 X 1-1/4 X 1-1/4 BOSTON BEARI
BEARING WASHER, PLAIN THRUST, 1.004IN
BORE DIA, 1.253IN OD, 1.25IN THK, BRZ
Bearing Washer, Plain Thrust, 1.004In Bore
Diameter, 1.253In Outside Diameter, 1.25In
Thickness, Bronze
Website Example
Business Considerations
• Is the data customer facing?
• How do different segments of the business use the data?
• Different segments of the business may have differing
opinions about the data
• Build the solution incorporating the requirements of all
stakeholders
• Training – this will change the process that item induction
uses, data previously not gathered will need to be gathered
• Segment data in order to update the data in chunks instead
of a big bang. Big bang is overwhelming
Best Practices
• The user of the data should not have to think when determining
where an item would be found in the taxonomy. This can be
difficult to achieve
• It is important that as the taxonomy and schema are being built to
take examples of the data and apply them to the taxonomy and
schema to them to validate what is being built
• Once the Schema is finalized, get it to Production so that all new
data conforms to the new process. This can be done prior to
generating descriptions
• Continuous review of the attribute fill rate before the go-no-go
decision of Production migration
• Once inducting items with PIM, it’s important to turn off item
induction process in Inventory module
Contacts
For more information, visit
http://www.axiaconsulting.net/
or give us a call at 866.937.5550
AXIA Consulting is a global provider of business and technology solutions
focused on maximizing investments and delivering results. With experience
across multiple industries and more than 54 countries, AXIA’s senior team
helps organizations tackle tough challenges, from large-scale ERP
implementations and post-merger integrations, to organizational change
and more.

More Related Content

Similar to Oracle PIM: Phantasmal Item Descriptions in your Organization

oracle enterprise manager training | oracle enterprise manager course | orac...
oracle enterprise manager training | oracle enterprise manager course |  orac...oracle enterprise manager training | oracle enterprise manager course |  orac...
oracle enterprise manager training | oracle enterprise manager course | orac...Nancy Thomas
 
Oracle Business Intelligence Enterprise Edition
Oracle Business Intelligence Enterprise EditionOracle Business Intelligence Enterprise Edition
Oracle Business Intelligence Enterprise EditionESRI Bulgaria
 
SharePoint Search - SPSNYC 2014
SharePoint Search - SPSNYC 2014SharePoint Search - SPSNYC 2014
SharePoint Search - SPSNYC 2014Avtex
 
Oracle BI Publsiher Using Data Template
Oracle BI Publsiher Using Data TemplateOracle BI Publsiher Using Data Template
Oracle BI Publsiher Using Data TemplateEdi Yanto
 
AnalytixLabs - Data Science 360 (Nasscom)-1648178720283 (1).pdf
AnalytixLabs - Data Science 360 (Nasscom)-1648178720283 (1).pdfAnalytixLabs - Data Science 360 (Nasscom)-1648178720283 (1).pdf
AnalytixLabs - Data Science 360 (Nasscom)-1648178720283 (1).pdfNamanGulati17
 
Maintainable Sitecore Solutions
Maintainable Sitecore SolutionsMaintainable Sitecore Solutions
Maintainable Sitecore SolutionsThomas Eldblom
 
Activating massive omnichannel personalization
Activating massive omnichannel personalizationActivating massive omnichannel personalization
Activating massive omnichannel personalizationVasiliy Fomichev
 
Salesforce Presentation
Salesforce PresentationSalesforce Presentation
Salesforce PresentationChetna Purohit
 
Product Catalog and IT Service Management
Product Catalog and IT Service ManagementProduct Catalog and IT Service Management
Product Catalog and IT Service ManagementDrew Madelung
 
Hundreds of queries in the time of one - Gianmario Spacagna
Hundreds of queries in the time of one - Gianmario SpacagnaHundreds of queries in the time of one - Gianmario Spacagna
Hundreds of queries in the time of one - Gianmario SpacagnaSpark Summit
 
An intro to building an architecture repository meta model and modeling frame...
An intro to building an architecture repository meta model and modeling frame...An intro to building an architecture repository meta model and modeling frame...
An intro to building an architecture repository meta model and modeling frame...wweinmeyer79
 
Lifecycle Management with SharePoint Apps and Solutions
Lifecycle Management with SharePoint Apps and SolutionsLifecycle Management with SharePoint Apps and Solutions
Lifecycle Management with SharePoint Apps and SolutionsSPC Adriatics
 
Products and Categories
Products and CategoriesProducts and Categories
Products and CategoriesMuhammad Sajid
 
Informatica mdm online training in chennai
Informatica mdm online training in chennaiInformatica mdm online training in chennai
Informatica mdm online training in chennaiGoLogica Technologies
 
COLLABORATE 18 Presentation: Success Story- Cloud Product Information Managem...
COLLABORATE 18 Presentation: Success Story- Cloud Product Information Managem...COLLABORATE 18 Presentation: Success Story- Cloud Product Information Managem...
COLLABORATE 18 Presentation: Success Story- Cloud Product Information Managem...Jade Global
 
JD Edwards Manufacturing Deep Dive Workshop
JD Edwards Manufacturing Deep Dive WorkshopJD Edwards Manufacturing Deep Dive Workshop
JD Edwards Manufacturing Deep Dive WorkshopTerillium
 
Structured Authoring for Business-Critical Content
Structured Authoring for Business-Critical ContentStructured Authoring for Business-Critical Content
Structured Authoring for Business-Critical ContentLavaCon
 
Building Data Warehouse in SQL Server
Building Data Warehouse in SQL ServerBuilding Data Warehouse in SQL Server
Building Data Warehouse in SQL ServerAntonios Chatzipavlis
 

Similar to Oracle PIM: Phantasmal Item Descriptions in your Organization (20)

oracle enterprise manager training | oracle enterprise manager course | orac...
oracle enterprise manager training | oracle enterprise manager course |  orac...oracle enterprise manager training | oracle enterprise manager course |  orac...
oracle enterprise manager training | oracle enterprise manager course | orac...
 
Oracle Business Intelligence Enterprise Edition
Oracle Business Intelligence Enterprise EditionOracle Business Intelligence Enterprise Edition
Oracle Business Intelligence Enterprise Edition
 
SharePoint Search - SPSNYC 2014
SharePoint Search - SPSNYC 2014SharePoint Search - SPSNYC 2014
SharePoint Search - SPSNYC 2014
 
Oracle BI Publsiher Using Data Template
Oracle BI Publsiher Using Data TemplateOracle BI Publsiher Using Data Template
Oracle BI Publsiher Using Data Template
 
AnalytixLabs - Data Science 360 (Nasscom)-1648178720283 (1).pdf
AnalytixLabs - Data Science 360 (Nasscom)-1648178720283 (1).pdfAnalytixLabs - Data Science 360 (Nasscom)-1648178720283 (1).pdf
AnalytixLabs - Data Science 360 (Nasscom)-1648178720283 (1).pdf
 
Maintainable Sitecore Solutions
Maintainable Sitecore SolutionsMaintainable Sitecore Solutions
Maintainable Sitecore Solutions
 
Activating massive omnichannel personalization
Activating massive omnichannel personalizationActivating massive omnichannel personalization
Activating massive omnichannel personalization
 
Salesforce Presentation
Salesforce PresentationSalesforce Presentation
Salesforce Presentation
 
Product Catalog and IT Service Management
Product Catalog and IT Service ManagementProduct Catalog and IT Service Management
Product Catalog and IT Service Management
 
Hundreds of queries in the time of one - Gianmario Spacagna
Hundreds of queries in the time of one - Gianmario SpacagnaHundreds of queries in the time of one - Gianmario Spacagna
Hundreds of queries in the time of one - Gianmario Spacagna
 
Micro strategy 7i
Micro strategy 7iMicro strategy 7i
Micro strategy 7i
 
An intro to building an architecture repository meta model and modeling frame...
An intro to building an architecture repository meta model and modeling frame...An intro to building an architecture repository meta model and modeling frame...
An intro to building an architecture repository meta model and modeling frame...
 
Oracle apps r12 scm functional training
Oracle apps r12 scm functional trainingOracle apps r12 scm functional training
Oracle apps r12 scm functional training
 
Lifecycle Management with SharePoint Apps and Solutions
Lifecycle Management with SharePoint Apps and SolutionsLifecycle Management with SharePoint Apps and Solutions
Lifecycle Management with SharePoint Apps and Solutions
 
Products and Categories
Products and CategoriesProducts and Categories
Products and Categories
 
Informatica mdm online training in chennai
Informatica mdm online training in chennaiInformatica mdm online training in chennai
Informatica mdm online training in chennai
 
COLLABORATE 18 Presentation: Success Story- Cloud Product Information Managem...
COLLABORATE 18 Presentation: Success Story- Cloud Product Information Managem...COLLABORATE 18 Presentation: Success Story- Cloud Product Information Managem...
COLLABORATE 18 Presentation: Success Story- Cloud Product Information Managem...
 
JD Edwards Manufacturing Deep Dive Workshop
JD Edwards Manufacturing Deep Dive WorkshopJD Edwards Manufacturing Deep Dive Workshop
JD Edwards Manufacturing Deep Dive Workshop
 
Structured Authoring for Business-Critical Content
Structured Authoring for Business-Critical ContentStructured Authoring for Business-Critical Content
Structured Authoring for Business-Critical Content
 
Building Data Warehouse in SQL Server
Building Data Warehouse in SQL ServerBuilding Data Warehouse in SQL Server
Building Data Warehouse in SQL Server
 

More from AXIA Consulting Inc.

Performing an R12 Upgrade in a Highly Customized Environment with a Worldwide...
Performing an R12 Upgrade in a Highly Customized Environment with a Worldwide...Performing an R12 Upgrade in a Highly Customized Environment with a Worldwide...
Performing an R12 Upgrade in a Highly Customized Environment with a Worldwide...AXIA Consulting Inc.
 
Oracle Applications Upgrade Strategies
Oracle Applications Upgrade StrategiesOracle Applications Upgrade Strategies
Oracle Applications Upgrade StrategiesAXIA Consulting Inc.
 
How to get the most from your E-Business Suite Developers
How to get the most from your E-Business Suite DevelopersHow to get the most from your E-Business Suite Developers
How to get the most from your E-Business Suite DevelopersAXIA Consulting Inc.
 

More from AXIA Consulting Inc. (6)

What is Agile Methodology?
What is Agile Methodology?What is Agile Methodology?
What is Agile Methodology?
 
Performing an R12 Upgrade in a Highly Customized Environment with a Worldwide...
Performing an R12 Upgrade in a Highly Customized Environment with a Worldwide...Performing an R12 Upgrade in a Highly Customized Environment with a Worldwide...
Performing an R12 Upgrade in a Highly Customized Environment with a Worldwide...
 
Oracle Time and Labor
Oracle Time and LaborOracle Time and Labor
Oracle Time and Labor
 
Oracle Applications Upgrade Strategies
Oracle Applications Upgrade StrategiesOracle Applications Upgrade Strategies
Oracle Applications Upgrade Strategies
 
How to get the most from your E-Business Suite Developers
How to get the most from your E-Business Suite DevelopersHow to get the most from your E-Business Suite Developers
How to get the most from your E-Business Suite Developers
 
Oracle OBIEE in Utilities
Oracle OBIEE in UtilitiesOracle OBIEE in Utilities
Oracle OBIEE in Utilities
 

Recently uploaded

Keppel Ltd. 1Q 2024 Business Update Presentation Slides
Keppel Ltd. 1Q 2024 Business Update  Presentation SlidesKeppel Ltd. 1Q 2024 Business Update  Presentation Slides
Keppel Ltd. 1Q 2024 Business Update Presentation SlidesKeppelCorporation
 
NewBase 22 April 2024 Energy News issue - 1718 by Khaled Al Awadi (AutoRe...
NewBase  22 April  2024  Energy News issue - 1718 by Khaled Al Awadi  (AutoRe...NewBase  22 April  2024  Energy News issue - 1718 by Khaled Al Awadi  (AutoRe...
NewBase 22 April 2024 Energy News issue - 1718 by Khaled Al Awadi (AutoRe...Khaled Al Awadi
 
Lean: From Theory to Practice — One City’s (and Library’s) Lean Story… Abridged
Lean: From Theory to Practice — One City’s (and Library’s) Lean Story… AbridgedLean: From Theory to Practice — One City’s (and Library’s) Lean Story… Abridged
Lean: From Theory to Practice — One City’s (and Library’s) Lean Story… AbridgedKaiNexus
 
A.I. Bot Summit 3 Opening Keynote - Perry Belcher
A.I. Bot Summit 3 Opening Keynote - Perry BelcherA.I. Bot Summit 3 Opening Keynote - Perry Belcher
A.I. Bot Summit 3 Opening Keynote - Perry BelcherPerry Belcher
 
Call Girls In Connaught Place Delhi ❤️88604**77959_Russian 100% Genuine Escor...
Call Girls In Connaught Place Delhi ❤️88604**77959_Russian 100% Genuine Escor...Call Girls In Connaught Place Delhi ❤️88604**77959_Russian 100% Genuine Escor...
Call Girls In Connaught Place Delhi ❤️88604**77959_Russian 100% Genuine Escor...lizamodels9
 
VIP Call Girl Jamshedpur Aashi 8250192130 Independent Escort Service Jamshedpur
VIP Call Girl Jamshedpur Aashi 8250192130 Independent Escort Service JamshedpurVIP Call Girl Jamshedpur Aashi 8250192130 Independent Escort Service Jamshedpur
VIP Call Girl Jamshedpur Aashi 8250192130 Independent Escort Service JamshedpurSuhani Kapoor
 
Lowrate Call Girls In Laxmi Nagar Delhi ❤️8860477959 Escorts 100% Genuine Ser...
Lowrate Call Girls In Laxmi Nagar Delhi ❤️8860477959 Escorts 100% Genuine Ser...Lowrate Call Girls In Laxmi Nagar Delhi ❤️8860477959 Escorts 100% Genuine Ser...
Lowrate Call Girls In Laxmi Nagar Delhi ❤️8860477959 Escorts 100% Genuine Ser...lizamodels9
 
(8264348440) 🔝 Call Girls In Mahipalpur 🔝 Delhi NCR
(8264348440) 🔝 Call Girls In Mahipalpur 🔝 Delhi NCR(8264348440) 🔝 Call Girls In Mahipalpur 🔝 Delhi NCR
(8264348440) 🔝 Call Girls In Mahipalpur 🔝 Delhi NCRsoniya singh
 
Call Girls In ⇛⇛Chhatarpur⇚⇚. Brings Offer Delhi Contact Us 8377877756
Call Girls In ⇛⇛Chhatarpur⇚⇚. Brings Offer Delhi Contact Us 8377877756Call Girls In ⇛⇛Chhatarpur⇚⇚. Brings Offer Delhi Contact Us 8377877756
Call Girls In ⇛⇛Chhatarpur⇚⇚. Brings Offer Delhi Contact Us 8377877756dollysharma2066
 
Investment analysis and portfolio management
Investment analysis and portfolio managementInvestment analysis and portfolio management
Investment analysis and portfolio managementJunaidKhan750825
 
BEST Call Girls In BELLMONT HOTEL ✨ 9773824855 ✨ Escorts Service In Delhi Ncr,
BEST Call Girls In BELLMONT HOTEL ✨ 9773824855 ✨ Escorts Service In Delhi Ncr,BEST Call Girls In BELLMONT HOTEL ✨ 9773824855 ✨ Escorts Service In Delhi Ncr,
BEST Call Girls In BELLMONT HOTEL ✨ 9773824855 ✨ Escorts Service In Delhi Ncr,noida100girls
 
Catalogue ONG NƯỚC uPVC - HDPE DE NHAT.pdf
Catalogue ONG NƯỚC uPVC - HDPE DE NHAT.pdfCatalogue ONG NƯỚC uPVC - HDPE DE NHAT.pdf
Catalogue ONG NƯỚC uPVC - HDPE DE NHAT.pdfOrient Homes
 
Marketing Management Business Plan_My Sweet Creations
Marketing Management Business Plan_My Sweet CreationsMarketing Management Business Plan_My Sweet Creations
Marketing Management Business Plan_My Sweet Creationsnakalysalcedo61
 
RE Capital's Visionary Leadership under Newman Leech
RE Capital's Visionary Leadership under Newman LeechRE Capital's Visionary Leadership under Newman Leech
RE Capital's Visionary Leadership under Newman LeechNewman George Leech
 
2024 Numerator Consumer Study of Cannabis Usage
2024 Numerator Consumer Study of Cannabis Usage2024 Numerator Consumer Study of Cannabis Usage
2024 Numerator Consumer Study of Cannabis UsageNeil Kimberley
 
rishikeshgirls.in- Rishikesh call girl.pdf
rishikeshgirls.in- Rishikesh call girl.pdfrishikeshgirls.in- Rishikesh call girl.pdf
rishikeshgirls.in- Rishikesh call girl.pdfmuskan1121w
 
M.C Lodges -- Guest House in Jhang.
M.C Lodges --  Guest House in Jhang.M.C Lodges --  Guest House in Jhang.
M.C Lodges -- Guest House in Jhang.Aaiza Hassan
 
Call Girls In Kishangarh Delhi ❤️8860477959 Good Looking Escorts In 24/7 Delh...
Call Girls In Kishangarh Delhi ❤️8860477959 Good Looking Escorts In 24/7 Delh...Call Girls In Kishangarh Delhi ❤️8860477959 Good Looking Escorts In 24/7 Delh...
Call Girls In Kishangarh Delhi ❤️8860477959 Good Looking Escorts In 24/7 Delh...lizamodels9
 
The CMO Survey - Highlights and Insights Report - Spring 2024
The CMO Survey - Highlights and Insights Report - Spring 2024The CMO Survey - Highlights and Insights Report - Spring 2024
The CMO Survey - Highlights and Insights Report - Spring 2024christinemoorman
 
Case study on tata clothing brand zudio in detail
Case study on tata clothing brand zudio in detailCase study on tata clothing brand zudio in detail
Case study on tata clothing brand zudio in detailAriel592675
 

Recently uploaded (20)

Keppel Ltd. 1Q 2024 Business Update Presentation Slides
Keppel Ltd. 1Q 2024 Business Update  Presentation SlidesKeppel Ltd. 1Q 2024 Business Update  Presentation Slides
Keppel Ltd. 1Q 2024 Business Update Presentation Slides
 
NewBase 22 April 2024 Energy News issue - 1718 by Khaled Al Awadi (AutoRe...
NewBase  22 April  2024  Energy News issue - 1718 by Khaled Al Awadi  (AutoRe...NewBase  22 April  2024  Energy News issue - 1718 by Khaled Al Awadi  (AutoRe...
NewBase 22 April 2024 Energy News issue - 1718 by Khaled Al Awadi (AutoRe...
 
Lean: From Theory to Practice — One City’s (and Library’s) Lean Story… Abridged
Lean: From Theory to Practice — One City’s (and Library’s) Lean Story… AbridgedLean: From Theory to Practice — One City’s (and Library’s) Lean Story… Abridged
Lean: From Theory to Practice — One City’s (and Library’s) Lean Story… Abridged
 
A.I. Bot Summit 3 Opening Keynote - Perry Belcher
A.I. Bot Summit 3 Opening Keynote - Perry BelcherA.I. Bot Summit 3 Opening Keynote - Perry Belcher
A.I. Bot Summit 3 Opening Keynote - Perry Belcher
 
Call Girls In Connaught Place Delhi ❤️88604**77959_Russian 100% Genuine Escor...
Call Girls In Connaught Place Delhi ❤️88604**77959_Russian 100% Genuine Escor...Call Girls In Connaught Place Delhi ❤️88604**77959_Russian 100% Genuine Escor...
Call Girls In Connaught Place Delhi ❤️88604**77959_Russian 100% Genuine Escor...
 
VIP Call Girl Jamshedpur Aashi 8250192130 Independent Escort Service Jamshedpur
VIP Call Girl Jamshedpur Aashi 8250192130 Independent Escort Service JamshedpurVIP Call Girl Jamshedpur Aashi 8250192130 Independent Escort Service Jamshedpur
VIP Call Girl Jamshedpur Aashi 8250192130 Independent Escort Service Jamshedpur
 
Lowrate Call Girls In Laxmi Nagar Delhi ❤️8860477959 Escorts 100% Genuine Ser...
Lowrate Call Girls In Laxmi Nagar Delhi ❤️8860477959 Escorts 100% Genuine Ser...Lowrate Call Girls In Laxmi Nagar Delhi ❤️8860477959 Escorts 100% Genuine Ser...
Lowrate Call Girls In Laxmi Nagar Delhi ❤️8860477959 Escorts 100% Genuine Ser...
 
(8264348440) 🔝 Call Girls In Mahipalpur 🔝 Delhi NCR
(8264348440) 🔝 Call Girls In Mahipalpur 🔝 Delhi NCR(8264348440) 🔝 Call Girls In Mahipalpur 🔝 Delhi NCR
(8264348440) 🔝 Call Girls In Mahipalpur 🔝 Delhi NCR
 
Call Girls In ⇛⇛Chhatarpur⇚⇚. Brings Offer Delhi Contact Us 8377877756
Call Girls In ⇛⇛Chhatarpur⇚⇚. Brings Offer Delhi Contact Us 8377877756Call Girls In ⇛⇛Chhatarpur⇚⇚. Brings Offer Delhi Contact Us 8377877756
Call Girls In ⇛⇛Chhatarpur⇚⇚. Brings Offer Delhi Contact Us 8377877756
 
Investment analysis and portfolio management
Investment analysis and portfolio managementInvestment analysis and portfolio management
Investment analysis and portfolio management
 
BEST Call Girls In BELLMONT HOTEL ✨ 9773824855 ✨ Escorts Service In Delhi Ncr,
BEST Call Girls In BELLMONT HOTEL ✨ 9773824855 ✨ Escorts Service In Delhi Ncr,BEST Call Girls In BELLMONT HOTEL ✨ 9773824855 ✨ Escorts Service In Delhi Ncr,
BEST Call Girls In BELLMONT HOTEL ✨ 9773824855 ✨ Escorts Service In Delhi Ncr,
 
Catalogue ONG NƯỚC uPVC - HDPE DE NHAT.pdf
Catalogue ONG NƯỚC uPVC - HDPE DE NHAT.pdfCatalogue ONG NƯỚC uPVC - HDPE DE NHAT.pdf
Catalogue ONG NƯỚC uPVC - HDPE DE NHAT.pdf
 
Marketing Management Business Plan_My Sweet Creations
Marketing Management Business Plan_My Sweet CreationsMarketing Management Business Plan_My Sweet Creations
Marketing Management Business Plan_My Sweet Creations
 
RE Capital's Visionary Leadership under Newman Leech
RE Capital's Visionary Leadership under Newman LeechRE Capital's Visionary Leadership under Newman Leech
RE Capital's Visionary Leadership under Newman Leech
 
2024 Numerator Consumer Study of Cannabis Usage
2024 Numerator Consumer Study of Cannabis Usage2024 Numerator Consumer Study of Cannabis Usage
2024 Numerator Consumer Study of Cannabis Usage
 
rishikeshgirls.in- Rishikesh call girl.pdf
rishikeshgirls.in- Rishikesh call girl.pdfrishikeshgirls.in- Rishikesh call girl.pdf
rishikeshgirls.in- Rishikesh call girl.pdf
 
M.C Lodges -- Guest House in Jhang.
M.C Lodges --  Guest House in Jhang.M.C Lodges --  Guest House in Jhang.
M.C Lodges -- Guest House in Jhang.
 
Call Girls In Kishangarh Delhi ❤️8860477959 Good Looking Escorts In 24/7 Delh...
Call Girls In Kishangarh Delhi ❤️8860477959 Good Looking Escorts In 24/7 Delh...Call Girls In Kishangarh Delhi ❤️8860477959 Good Looking Escorts In 24/7 Delh...
Call Girls In Kishangarh Delhi ❤️8860477959 Good Looking Escorts In 24/7 Delh...
 
The CMO Survey - Highlights and Insights Report - Spring 2024
The CMO Survey - Highlights and Insights Report - Spring 2024The CMO Survey - Highlights and Insights Report - Spring 2024
The CMO Survey - Highlights and Insights Report - Spring 2024
 
Case study on tata clothing brand zudio in detail
Case study on tata clothing brand zudio in detailCase study on tata clothing brand zudio in detail
Case study on tata clothing brand zudio in detail
 

Oracle PIM: Phantasmal Item Descriptions in your Organization

  • 1. Proprietary and confidential. | 2016 AXIA Consulting™ | All rights reserved. Phantasmal Item Descriptions in Your Organization? Oracle Product Information Management to the Rescue
  • 2. Agenda • Introduction & Overview • Session Objectives • The Problem and the Aftermath • Key Terms • Item Description Generation Solution Approach • Taxonomy Design • Item Classification • Schema Design • Meta-Data Configurations • SKU Build • Normalization / Governance • Description Generation • Business Considerations • Best Practices • Q&A
  • 3. AXIA Consulting About AXIA Consulting At AXIA Consulting, we understand the importance of choosing a trustworthy partner who takes the time to understand your business and we have the proven ability to deliver meaningful results. With a team of industry experts who average 20 years of experience in the field, AXIA’s accessible business and technology leaders hardness their expertise to solve our clients’ most complex problems. Founded in 2005, AXIA is 100% employee-owned and employs approximately 100 Senior Consultants. We are a global company, delivering results for clients in more than 54 countries over six continents. www.axiaconsulting.net Committed To Excellence AXIA is driven by values and our commitment to excellence, resulting in trusted partnerships and lasting client relationships
  • 4. Session Objectives • To help the audience gain basic understanding of taxonomy, schema and item description process • To model the solution approach in Oracle PIM along with setups and configurations • Simple item description generated from PIM in Oracle E- Business Suite (EBS) • To provide a list of business considerations and best practices in generating item descriptions through Oracle PIM
  • 5. “Phantasmal” Problem • “Phantasmal” Item Data Standards: • No guidelines to follow when creating or uploading new items • No guidelines to follow when importing items with new or different structure (e.g., acquisitions, new roll-outs) • “Phantasmal” Item Descriptions: • Difficult to find items (internally and for our e-commerce customers) based on descriptions • Difficult to prevent duplicate item descriptions • Inconsistent, vague, incomplete and of-course incomprehensible item descriptions • “Phantasmal” Data Governance • Lack of control perpetuates the problem • External and Internal customer “phantomisms” with item descriptions
  • 6. Results of Problem Decimals/Fractions Abbreviations/full words Invalid DescriptionsDuplicate Descriptions Information that does not belong BOTTOMLINE – CUSTOMER FRUSTRATION
  • 7. Key Terms • Taxonomy: The practice of classification; the order and hierarchy of your products. Grouping like items into a specific category • Node: Item catalog category to which an item will be assigned • Schema: The collection of attributes and their characteristics, such as field type, size and whether a List of Values is provided • Attributes: • Required Attributes: Attributes that are included in system-generated descriptions • Optional Attributes: Additional attributes that are not included in system- generated descriptions • Normalization: Task to review List of Values and cleanse them down to a unique list • Meta-Data: Item Catalogs, Attribute Groups, Pages, Functions, Associations, etc.
  • 9. Taxonomy • Taxonomy: the practice of building a classification structure; the order and hierarchy of your products. Grouping like items into a specific category • As Taxonomy is built, it is important to think about your audience, using relevant language for the audience • Item Catalog Categories (ICC) form a tree structure in PIM to create the taxonomy to which items can be assigned • Taxonomy in PIM • Top level parent ICC node • Intermediate ICC nodes • Leaf ICC nodes
  • 11. Item Classification to Taxonomy • This is the process of assigning items to the taxonomy structure • It is important to do this as you are building the Taxonomy, this will ensure that the Taxonomy will work for your organization • Business may decide to normalize the taxonomy after sign off and item assignment for: • Removal of redundant nodes • Consolidation of nodes • Addition of new nodes • Taxonomy normalization may lead to: • Re-assignment of items assigned to the affected nodes • Loss of attribute information and attribute values for the affected items if not handled through a defined ICC re-assignment process
  • 12. Schema Design Schema: the collection of attributes and their characteristics, such as field type, size and whether a List of Values is provided • These are grouped by end node • Depending on the leaf node and attribute group, the number of attributes can be different • Some attributes may not be required and not used to build a description • Decision to create separate UOM attributes to reference numeric values stored in text attributes or use the standard UOM feature with numeric attributes • Time intensive phase as different business stakeholders influence the process of building the schema structure pertinent to their department and needs
  • 13. Schema Examples Attributes ranked with a 0 are not required, and will not be used to generate descriptions Attribute Name Data Type Ranking Product Type LOV 1 Motor Horsepower Number 2 Motor Horsepower UOM LOV 3 Frame Size Text 4 Motor Type LOV 5 Motor RPM Number 6 Motor RPMUOM LOV 7 Motor Phase LOV 8 Motor Voltage Text 9 Frequency Number 10 Frequency UOM LOV 11 Mounting Type LOV 12 Enclosure Type LOV 13 Brake Type LOV 14 Brake Full Load Torque Number 0 Brake Full Load Torque UOM LOV 0 Brake Horsepower Number 0 Brake Horsepower UOM LOV 0 Brake Voltage Number 0 Brake Voltage UOM LOV 0 Efficiency Rating Text 0 Feedback Device Type LOV 0 Full Load Amp Rating Number 0 Full Load Amp Rating UOM LOV 0 Motor Full Load Torque Number 0 Motor Full Load Torque UOM LOV 0 Number of Poles Number 0 Product Line Text 0 Service Factor Number 0 AC Motors Attribute Name Data Type Ranking Product Type LOV 1 Overall Length Number 2 Overall Length UOM LOV 3 Overall Width Number 4 Overall Width UOM LOV 5 Abrasive Material LOV 6 Backing Material LOV 7 Color Text 8 Product Line Text 0 Abrasives
  • 14. Configurations and Setups in PIM • Meta-data creation is an essential component of PIM setup and thereby generating item descriptions • Meta-data Load Approaches: • PIM User Interface – very tedious and time consuming • PIM Interface tables – only inbound approach • FNDLOAD – very technical approach • iSetup – very limited to couple of entities • Mandatory Meta-Data Configurations: • Item Catalog Categories (ICC) • Attribute Groups and User Defined Attributes (UDA) • PIM Functions • Value Sets and Values for UDA list of values • Pages and Page Entries • ICC – Attribute Group Association • ICC – Function Association
  • 16. Configuration Entity Relationships ITEM CATALOG CATEGORY ATTRIBUTE GROUPS PAGES USERDEFINED ATTRIBUTES (UDA) PAGEENTRIES FUNCTIONS PARAMETERS VALUE SETS
  • 17. Item Catalog Categories Navigation: Inventory > Setup > Items > Catalog Groups
  • 18. Attribute Groups Navigation: Development Manager > Setup > Setup Workbench > Items (T) > Attribute Groups (T)
  • 19. User Defined Attributes (UDA) Navigation: Development Manager > Setup > Setup Workbench > Items (T) > Attribute Groups (T)
  • 20. Description Generation Function Navigation: Development Manager > Setup > Setup Workbench > Function (T)
  • 21. ICC – Function Association Navigation: Development Manager > Setup > Setup Workbench > Click on Item Catalog Category > Description Generation
  • 22. ICC – Attribute Group Association Navigation: Development Manager > Setup > Setup Workbench > Click on Item Catalog Category > Attribute Groups
  • 23. ICC Pages Navigation: Development Manager > Setup > Setup Workbench > Click on Item Catalog Category > Item Pages
  • 25. Meta-Data Import Program Navigation: Development Manager > View > Requests > Submit a New Request > Single Request
  • 26. SKU Build • SKU Build comprises of: • Filling out the attribute values for the attributes defined in the schema structure (can be done offline in excel workbook) • Uploading the attribute values into the system for building descriptions (custom PL/SQL process) • Major work lies in gathering the attribute value information: • Internal product information and knowledge • Supplier/Manufacturer provided manuals, emails, calls, etc. • “What is Good Enough” • Attribute data available may not be specific enough to fill in values for all the attributes created for the end node • May need to do research in order to fill in the data • A decision point needs to happen to determine “What is Good Enough” in order start generating descriptions • It may take several iterations to determine that and it will be a different answer based on the node
  • 27. Normalization/Governance • Normalization • Taxonomy and Schema o Consolidation o Remove Redundancy • Meta Data o Attributes o Value Sets o Functions o Pages, etc. • Review List of Values and cleanse them • Typos • Differing abbreviations • Different data being added for a different parts within the same end node • In the current organization the word Motor may be in descriptions like this: o Motor o MTR o MOTR • Using LOVs and agreeing on one abbreviation for Motor ensures consistency across all descriptions
  • 28. Description Generation • Within PIM the description function calls a custom PL/SQL package to create the description • Each PIM Function can call a different PL/SQL function • The definition of the function will pass all of the required parameter values to the PL/SQL package • The PL/SQL package can then be created to concatenate the values together to make a description • Only the Description field is updated, not the Long Description
  • 29. Description Generation Enhancements • Create a Long Description with all attributes spelled out • Regular Description will use abbreviations from LOVs • Ability to add abbreviations for the attribute names, and add them as prefixes or suffixes to the attribute value within the description • Ability to regenerate descriptions for all items in an end node if an abbreviation needs to change in an LOV • Overload 1 PL/SQL function so that all call PIM Functions call the same PL/SQL function
  • 30. Description Generation Examples ITEM NUMBER ORIGINAL DESCRIPTION DESCRIPTION LONG DESCRIPTION 185063 BEARING MLLR F-1665-7H W/GRS BEARING, FLANGE MOUNT, 0 BOLTS, RND HSG TYPE, BALL, .451IN BORE DIA, GR, STD Bearing, Flange Mount, 0 Number of Bolts, Round Housing Type, BALL, .451In Bore Diameter, Greased, STD 200597 BRG FLG 1-3/16B 2B MLLR BRG BEARING, FLANGE MOUNT, 2 BOLTS, BRKT HSG TYPE, 1.1875IN BORE DIA, LUBRICATED, FOOD GRADE Bearing, Flange Mount, 2 Number of Bolts, Bracket Housing Type, 1.1875In Bore Diameter, Lubricated, Food Grade 3802001 PL 3/8X60X60 HR 1045 PLT, STL, HRS, C1045, .375IN THK, 60IN OVERALL LEN, 60IN OVERALL WD Plate, Steel, Hot Rolled, C1045, .375In Thickness, 60In Overall Length, 60In Overall Width 7043341 PLATE HRPO 1/4 C1045 48X120 PLT, STL, HRS, C1045, .25IN THK, 120IN OVERALL LEN, 48IN OVERALL WD Plate, Steel, Hot Rolled, C1045, .25In Thickness, 120In Overall Length, 48In Overall Width 420D410 ROLLER_DRIVE_CPL_Ø98_BW1200 ROLLER, STRAIGHT UNPOWERED, 98MM ROLLER DIA, 2 GRV, 35MMAXLE SZ, RND, STL TUBE, ZINC-PLATED, TIMING SPROCKET Roller, Straight Unpowered, 98mm Roller Diameter, 2 Number of Grooves, 35mm Axle Size, Round, Steel Tube Material, Zinc- Plated, Timing Sprocket 70701010 1 X 1-1/4 X 1-1/4 BOSTON BEARI BEARING WASHER, PLAIN THRUST, 1.004IN BORE DIA, 1.253IN OD, 1.25IN THK, BRZ Bearing Washer, Plain Thrust, 1.004In Bore Diameter, 1.253In Outside Diameter, 1.25In Thickness, Bronze
  • 32. Business Considerations • Is the data customer facing? • How do different segments of the business use the data? • Different segments of the business may have differing opinions about the data • Build the solution incorporating the requirements of all stakeholders • Training – this will change the process that item induction uses, data previously not gathered will need to be gathered • Segment data in order to update the data in chunks instead of a big bang. Big bang is overwhelming
  • 33. Best Practices • The user of the data should not have to think when determining where an item would be found in the taxonomy. This can be difficult to achieve • It is important that as the taxonomy and schema are being built to take examples of the data and apply them to the taxonomy and schema to them to validate what is being built • Once the Schema is finalized, get it to Production so that all new data conforms to the new process. This can be done prior to generating descriptions • Continuous review of the attribute fill rate before the go-no-go decision of Production migration • Once inducting items with PIM, it’s important to turn off item induction process in Inventory module
  • 34. Contacts For more information, visit http://www.axiaconsulting.net/ or give us a call at 866.937.5550 AXIA Consulting is a global provider of business and technology solutions focused on maximizing investments and delivering results. With experience across multiple industries and more than 54 countries, AXIA’s senior team helps organizations tackle tough challenges, from large-scale ERP implementations and post-merger integrations, to organizational change and more.