inspire 2013 - paychex +alteryx = efficiency redefined
DESCRIPTION
Over the past several years, with the growth of big data, the need for high-level analytics at Paychex has grown exponentially. For quite some time, hard work, long hours and expertise in basic database management software was enough to get by and meet deadlines. However, in the current environment with growing information demands, the pre-existing technology environment wasn't cutting it. Enter Alteryx. Alteryx has redefined Risk Analytic's capabilities and bandwidth within the organization. After just a few months of usage, we are recognizing a 32x improvement (at the minimum) in processing speeds alone. This has, and will continue, to open doors for new projects, larger data sets and cutting edge predictive modelingTRANSCRIPT
Paychex + Alteryx = Efficiency Redefined
Paychex, Inc.
Wednesday, March 6th
Michael Barone
Paychex, Inc. Profile
Provider of comprehensive payroll, human resource, and benefits outsourcing solutions for small to medium sized businesses
Approximately 564,000 clients & more than 100 offices across the U.S. & Germany
9 million client employees provided with Payroll and HR services
Fiscal 2012 – revenue of over $2 billion and net income of $0.5 billion
Accolades
Risk Analytics – Who are we?
Risk Management
Frank Fiorille, Director
Risk Analytics
Erika McBride, Manager
Paychex Peer Process Program
(P4)
1 Analyst
Predictive Analytics
3 Modelers/SAS Programmers
MIS & Portfolio
4 Analysts
Risk Analytics – What we do…
Model Profiles
PST1000
(Paychex Smart Time)
Identifies clients most likely to purchase our Time Clock solution
Workers Compensation
Identifies clients most likely to purchase our Workers Compensation product
PATRICK
(Predictive Algorithm Targeting Retirement Investment Client Knowledge)
Identifies clients most likely to purchase our 401(k) product
STEPH
(Sales Tool Evaluating Potential Health and Benefit Clients)
Identifies clients most likely to purchase one of our Health and Benefit products
PAUL
(PEO Algorithm Utilizing Leads)
Identifies clients most likely to cross over to our Professional Employer Organization product
Up-Sell Cross-Sell Models
Operations and Risk Models
PAM
(Paychex Attrition Model)
Client retention model geared towards controllable losses
OLIVER
(Objective Lifetime Indicator of the Value of Expected Revenue)
Predicts lifetime value for revenue and retention propensity
PEG
(Price Elasticity Gauge)
Clustering model that gauges the price sensitivity of each client
TIM
(Territory Identification & Mapping) Ranks the inherent sales opportunities within a zip code
SARAH
(Sales Rep Attrition Heuristic) Identifies our outside sales reps with a propensity to turn over for controllable reasons
SAM
(Sales Anticipation Model)
Predicts the number of sales units per zip code for the coming fiscal year
Sales Strategy Models
MARCO
(Model for Accounts Receivable Collections Optimization )
Identifies which delinquent accounts are most likely to repay their balance within 90 days
Credit Risk
Identifies clients most likely to have a payment returned within the next 90 days
In Development
Client Referral Model
Prospect Model
Product Sequencing
Discount Recommendations
Monthly Data Prep and Processing Overview
55 data files
Text
Excel
HTML
10 GB new data storage
each raw file overwritten
18
databases
Access
Oracle
Netezza
475 variables
33 hours processing
time
55 data files
Text
Excel
HTML
3 GB new data storage
each raw file can be saved
9 Alteryx databases
475 variables
51 minutes
14 Alteryx
modules
Alteryx BEFORE
AFTER
Saves 7 GB per month new data storage
and
32 hours per month processing time
Specific Example (PAUL Model) – Before Alteryx
Database 1
1 GB
5 linked files
12 queries
3 temp tables
3 final tables
1 hour processing time
Database 2
1 GB
3 linked files
4 queries
1 temp tables
1 final table
1 hour processing time
Database 3
1 GB
4 linked tables
1 ODBC connection
48 queries
16 temp tables
1 final table
2 hours processing time
ODBC
Database
Specific Example (PAUL Model) – After Alteryx
Another Example Wanted to track and trend detailed client historical firmographic information over several years, outside of the Enterprise Data Warehouse (no IT involvement)
Each month required its own database due to size limitations (currently we are at 60+ databases, each holding about 500,000 records)
When querying the data, we’d have to link these databases together, and running queries took hours, if not days
Making a change to the process could take up to a week
With an Alteryx database (.yxdb) we can store all data in one place
Querying the data takes minutes
Other benefits! Top of the line Support Team ([email protected]) – quick response time, knowledgeable and makes you feel like you’re their only client
Very user-friendly interface
Superb ‘Alteryx Help’ files - actually explains and walks you through things instead of just repeating definitions like most help files!
What’s next…
Enhance/expand data mining
Convert internal data warehouse process to Alteryx
Explore ‘Big Data’ opportunities
Continue driving Analytics further into Paychex
Explore analytical services for our clients
Thank You!