advanced analytics and reporting in pim/mdm...3 introducing enterworks empowering business & it...
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Advanced Analytics and Reporting in PIM/MDM
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Our Presenters
Kerry Young VP & General Manager
Ramesh Prabhala Founder and CEO
Satheesh Ramachandran Data Science Advisor
Kartik Nanda AI Advisor
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Introducing EnterWorks
Empowering Business & IT Users for over 21 years
All-in-one platform for MDM, PIM, and DAM
Only Solution that is a Leader on both the Forrester PIM and MDM Waves
Highest customer satisfaction marks on industry analyst reports
Industry expertise: distributors, manufacturers, retail, hospitality, service companies, and member / buying groups
Strong Global SI & Technology partnerships
Business Mission Enable Our Customer’s Growth,
Efficiency and Differentiation through Exceptional Competency in Data
as Enabled by our MDM Technologies
Complexity Mastered
Master Shared and Application Data for
Business Model Agility
Discrete Views of Everything
Provide a Central View of Data Across Enterprise
Networks
Differentiated Experiences
Leverage Multiple Domains for Combinatorial Precision
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A Division of
51% LICENSES
OUTSIDE U.S.
2,200+ GLOBAL
CUSTOMERS
75+ COUNTRIES
200+ NEW ACCOUNTS
ANNUALLY
22 OF SAP’S TOP 25
CUSTOMERS
48 NET PROMOTER
SCORE
Auto Apparel Oil & Gas Food &
Beverage Consumer Products Retail Pharma Chemical Entertainment
ADVANCED
ANALYTICS AND REPORTING
IN
PIM/MDM
There are hidden treasures in every data, we help find them!
Ramesh Prabhala Founder, IntelliTide
Speakers
Satheesh Ramachandran PhD.
Data Science Advisor, IntelliTide
Kartik Nanda AI Advisor, IntelliTide
Experienced data scientist with a broad background in applied statistics, data mining, text mining, forecasting and operational research, with over two decades of experience in multiple domains
Was involved in some of the largest MDM rollouts and many years of experience consulting for global corporations
His expertise is Artificial Intelligence, Signal Processing and Algorithms (with multiple patents in these areas) spanning two decades and multiple domains including consumer electronics, e-retail, renewable energy and food supply chain
OUR COMPANY
We are the Masters of Data Science
Data Management
+
Analytics
We glean Insights from your Master Data
(Yes, that occasionally involves coalescing Master Data with other types of data)
We are a Global Solution Partner
Our Customers
MASTER DATA
AND
ANALYTICS
RELATIONSHIP
The Role of Analytics/AI in MDM
The Role of MDM in Analytics
• Lets flip the script - does MDM play a role in advanced analytics? IT ALREADY DOES!
• LOT MORE TO ACCOMPLISH if data scientists, MDM architects and business SME’s collaborate
– In the CRISP-DM model, MDM has a key role to play
– The challenge is awareness and collaboration
– Improved data quality leads to improved analytical outcomes
ANALYTICS WITH MASTER DATA
AND
USE CASES
Analytics Using Master Data & Beyond
MDM Analytics exists at two levels 1. Leveraging Master data (from MDM systems)
2. Leveraging Master data + Transactional data
Use Case 1: Price Change Analysis - Objective
• There are specific price change patterns depending on
product categories.
• Key idea – can these patterns be learnt, and coded
within a machine learning model for predicting price
change?
Thanks to IDEA for the data!
Use Case 1: Price Change Analysis – Model Formulation
Formulation approach –
• Create enough example scenarios from historical data consisting of products at time snapshots.
• Label each snapshot as Yes/No depending on if price changed within a future time window of 90 days.
• Create a profile for the snapshot – how long back was the last price change, how old is the product, product family, etc.
• Correlate the profile with the Label
Use Case 1: Price Change Analysis – Model Performance
• ~900k sample snapshot profiles were created, each with the future Label (price change = yes/no). Baseline change rate = 33%
• Model calibrated on 50%/50% test train sample. Top predictors that are correlated with recent-future price change include
• Aging factors such as time since last status update, time since last price change, age of product
• Product attributes such as product family, Price, Country of Origin, etc.
• Model performs well, strongly able to discriminate the products that are about to have a price change
Use Case 2: Product Classification
Product taxonomy/hierarchy classification is a challenging manual problem
• Wrong classification impacts sales
• Product classification fraud is a concern
• Syndication to online marketplaces exacerbates the problem
• Amazon has nearly 33,000 categories!
• Home Depot has thousands! See here
AI/ML can solve this problem!
Use Case 3: NPI Velocity Prediction
GOAL The speed of introduction of products to the market is critical need of any MDM
Schematic Predictive Model
Sample Product Risk Score
* NPI = New Product Introduction
ADVANCED REPORTING
IN MDM
Goals of Reporting
Aggregate and Present Information for Business Users
User Friendly Application to Empower Business Users
Support Better Business Decision Making
Advanced Business Intelligence Capabilities
Reporting and Visualization Overview
A variety of off shelf tools for reporting and visualization
• EnterWorks and other MDM solutions offer features to embed reports within the UI
• Data can also be extracted via API or files
Use Case: Vendor Performance Scorecard
Measuring of vendor performance is a popular requirement in the MDM industry
Vendor Performance scorecards utilize data from the Vendor and Product domains
Goals
• Detect vendors with the highest volume of product returns
• Reward vendors with the fastest completion of onboarding process
• Measure fulfillment rate by vendor
• Plot vendor deliveries by month
Features
• The dashboard in the top right corner was created in Microsoft Power BI tool
• The dashboard in the bottom right corner was created in Tableau
• Both reports were embedded within EnterWorks
QA AND THANKS!
Questions?
EnterWorks MDM Virtual Conference Join us for Upcoming Webinars in the Everything MDM Virtual Conference Series
PIM, MDM, DAM – Oh My! – Demystifying Terminology of the Data Management Universe
Building from PIM, Customer/Supplier MDM Best Practices: Delivering the Ultimate Data Hub for Your Business
Customer Portals – Enabling a New Level of Customer Empowerment in Today’s Digital Economy
April
14 April
15 April
16
Week 4: Best Practices
Presented by Jean Bordelon and Dean Rutter of Bounteous
Presented by Scott Rompala of DataCatalyst
Presented by Octavio Perales of Intershop
enterworks.com/virtual-conference-mdm/