Case Study Blackline to ARCS Transaction Matching migration at tronc

Transcription

1 Case Study Blackline to ARCS Transaction Matching migration at tronc This session walks through our client's successful journey of migrating a highly complex Transaction Matching solution from Blackline to Oracle ARCS Rahul Bansal - Technology Lead, Infosys Ashwin Tandon - Principal Consultant, Infosys Joe Guillotte

2 Customer Profile - tronc tronc is National Newspaper Publisher and Online Content Provider 92 Pulitzer Prizes 10 Major Newspapers Including the Chicago Tribune, LA Times, New York Daily News, Baltimore Sun, San Diego Union Tribune, Sun Sentinel, Orlando Sentinel, Hartford Courant, Allentown, Newport News FY 2015 Gross Revenue $1.7 billion Our Current Financial systems Employees 7,000+ PeopleSoft ERP, Microsoft AX, Blackline Cloud Journey - Major Shift to CLOUD PeopleSoft/ AX Blackline Oracle Fusions CLOUD ARCS Consistent ERP platform for GL, AP, AR and Fixed Assets. Streamline and standardize processes Eliminate customization challenges.

3 tronc s Objectives tronc s As-is Processes tronc objectives Blackline used for reconciliation and TM Complex transaction matching setup with 15+ bank Sources and over 14,000 transactions per reconciliation 2,400 reconciliations per period Limited flexibility in assigning due dates Need for effective status tracking and enhanced employee performance monitoring Complex data integration setup Have best in class close and reconciliation solution with reduced TCO Enable business for a faster and improved close cycle Ability to perform complex transaction matching across 20+ data sources UI affinity and single platform with enhanced monitoring and analytics

4 Decision Why did we choose to move from Blackline to Oracle ARCS 1 Ease of use and intuitive user interface 2 Reporting & rules engine 3 TCO (License + Implementation fees) 4 Transaction matching 5 Integration (Seamless integration with Oracle fusion cloud) More Comprehensive Less Comprehensive

5 ARCS Implementation Project Snapshot Reconciliation system migration from Blackline to ARCS Project duration - 6 Months with Feb 2018 Go-Live tronc Team (Champions who made it possible) - Kevin Kleiner, Joe Guillotte, Kama Kallembach, Diem Tran INFOSYS End to End Program Management, Design & Build Migration, Testing, User Training and Go-LIVE Partnerships ORACLE Involvement of ARCS product development leadership for product issues and enhancements Infosys (Implementation partner) Peak team size - 4 Onsiteoffshore ratio - 35 : 65

6 Key to success 6

7 Our Key Wins Enhanced data analytics and improved monitoring (Biggest benefits over Blackline) Rich and intuitive reporting capabilities Out of the box dashboards with filters Flexibility to assign due dates based on risk ratings (Our Favorite!!!) Ability to manage employee s time better Enhanced control to manage close cycle Use of Custom attributes to capture information specific to our business Operational efficiencies by reducing the number of manual matching of transactions through efficient match processes More scalable solution to handle additional interfaces and reconciliations/transactions without additional cost Dynamic Risk Rating Flux Analysis FCCS Integration of Close Manager and ARCS FCCS For consolidation and management reporting

8 Key Implementation Considerations Standardization of reconciliation templates and account profiles for consistent presentation Plan to archive historical reconciliations 3 Identify process improvements in addition to Lift-n-Shift Enhancements to transaction matching setup based on new COA and changes in data sources Identify matching rules for increased focus on cash reconciliation and 3 way matching Identify dependencies from other Cloud implementations and plan contingencies

9 How Infosys helped us in smooth transition from Blackline to ARCS 01 Infosys experience in ARCS and ARM implementations were used as Template Leveraged their Diamond partnership with Oracle to engage them at right times Continued parallel development for Transaction matching on ARCS Beta version (for required feature planned in future release) Provided A team with hands on experience of ARCS and expertise in reconciliation space Acted as independent advisory consultants to review impacts coming from other ongoing Cloud conversions Increased Coordination with tronc technology for seamless integration planning and interface development

10 Major Challenges Faced While Migrating to ARCS Multiple Data Sources Multiple data sources for Blackline involved 3-way matching; however, for setting up match processes, ARCS allowed configuration of two data sources only Solution: Worked with Oracle Product Team and introduced multiple data sources functionality in ARCS accomplishing multiple match sets and rules. While Oracle was working on delivering this functionality to all customers, we worked on their beta environment for delivering the solution as per stated timelines even though this challenge would have sent us months back. Filter and Grouping Mechanism Blackline can group or filter transactions based on certain criteria and then define match set over it, whereas, ARCS did not have such functionality Solution: Architected and leveraged the custom-calculated functionality of ARCS and delivered better transaction matching capabilities compared to Blackline

11 Key Benefits Moving to Best in Class Oracle ARCS Cloud solution from high cost blackline rationalizes the reconciliation process Around 75-80% transactions are auto-matched with around 25K+ transactions coming each day from 15+ data sources The auto-match runs in less than 10 mins and the auto daily loads happen in less than 5 minutes without need of any manual intervention Ability to match data from different data sources without needing to clone data Ability to define multiple match processes and in-turn even more match rules in a single reconciliation type Use of Custom attributes to capture information specific to tronc business and use them for filtering transactions Enhanced reporting and analytics through custom attributes, which facilitates automated reconciliation process 'Light out' automation - Complete data load into ARCS TM is automated using epm-automate utility and shell scripts New in-transit report for transaction matching provides flexibility to produce key report for financial close process Plan for maximum effort in data integration setup helped deliver best-in-class reconciliation and transaction matching solution

12 Lessons Learnt Plan for maximum effort for Data Integration as ARCS only takes.csv format as input ARCS Transaction matching rules be mindful of order of operations ARCS Transaction matching regression testing the more you test, the more number of transactions can be auto matched depending on the rules that you find out to introduce Involve Oracle team with suggestions and enhancements They help you to deliver Execute a targeted, staged implementation Develop a core ARCS team and include decision- makers ARCS is as much about process change as it is policy change

13 Types of Matching and Data Sources Advertising Cash Matching Accounts Payable Cash Matching Payroll Cash Matching Lockbox FirstData Credit Card Data AMEX Credit Card Data AX Accounts Receivable Data GL Cash Deposit Data Bank of America Statements GL AP Activity Details Bank of America Statements GL Payroll Data Chase Bank Statements Workday Payroll Data

14 Data Volume, Attributes, and Matching Criteria More than 25,000 daily incoming transactions prompted below attributes to be defined, including defining additional attributes These attributes have been defined for matching rules and match sets. Below table shows data source, its attributes and the custom attributes defined for that data source Data Source Attributes Additional Custom Attributes GL Cash Deposit AMEX Source AMEX Subsys AR Source AR Subsys Lockbox Source Lockbox Subsys Firstdata Source Firstdata Subsys Bofa BAI Subsys Chase BAI Subsys 17 6 GL AP Details Source 20 5 Workday Source Workday Subsys 40 5

15 File Format / Conversion and Mappings ARCS only accepted.csv format files for transaction matching and all the source files from 15+ data sources were coming in different file formats shown below five boxes To change above formats and convert / map them to ARCS specific and readable.csv formats MuleSoft tool was used and.bai to.csv converter was developed in-house by Infosys This helped us in delivering the ARCS TM solution in desired, effective and quick manner

16 Data Flow Diagram

17 Representative List of Infosys Oracle Cloud Clients Among the first SIs to invest, co-develop and build competency around Oracle Cloud / Fusion Products EPM Cloud Wins HCM Cloud, CX Cloud, PaaS and BI Cloud Wins HCM Cloud CPQ Cloud Fusion CRM Marketing Cloud Sales Cloud, Commerce, JCS, ICS, DSS, BIS, OMC,Social Sales, ERP, Marketing, BI Cloud, ICS, JPS, DCS, CPS Marketing Cloud Sales Cloud, JCS, DSS, BIS Sales & BI Cloud Sales Cloud Marketing Cloud Marketing Cloud Marketing Cloud Sales & BI Cloud CPQ Cloud Marketing Cloud

18 Infosys Oracle Cloud Snapshot Clients Engagements Go Lives Deals in the Pipeline % 3 Service revenue growth rate Digital license influence growth Certified consultants in Oracle Cloud Only partner with over 3,000+ person-months of co-development effort on Fusion HCM, CRM, ERP, EPM products Only partner working with Oracle on Cloud PaaS solutions Atradius Collections' Success with Oracle Sales Cloud Resolution Life- Oracle ERP Financials Cloud Experian s Oracle Sales Cloud - MDM Dubai Chamber Finance, HCM & Procurement KOJ : HCM Cloud Oasis Investment Company Fusion Accounting Hub

19 Q&A