Data management & automation in tax October 22, 2018

Transcription

1 Data management & automation in tax October 22, 2018

2 Kelly Necessary Partner, DHG Tax Kelly Necessary serves as Partner and leader of DHG BluePrint, the firms tax transformation services group. She has more than 20 years experience, including 13 years with Big Four accounting firms. Most recently, Kelly spent 10 years in corporate tax leading the tax operations for both income and property taxes. Prior to that, Kelly practiced in the multistate tax practices of both KPMG LLP and Deloitte Tax LLP. During her tenure in public accounting, Kelly focused particularly on tax planning and implementation of state tax strategies for large multistate corporations. She assisted companies with the design and implementation of corporate restructurings, performed multistate return reviews and assisted with above-the-line tax opportunities. Throughout her career, she has served as lead project manager on numerous legal entity rationalization projects and process improvement initiatives with tax functions, including system implementation for income tax provision and depreciation, tax account reconciliations, and tax compliance. She was recognized among the five inaugural Taxologist award winners at the 2014 Annual OneSource Synergy conference and participated in TEI s 2016 roundtable publication on tax technology.

3 Daren Campbell Partner, EY Tax Technology and Transformation Profile Daren has more than 20 years of professional experience and became an EY partner in Daren is a partner in EY s Tax Technology and Transformation (TTT). TTT assists clients in responding to changing international, federal, state and local tax law by solving the complexity around extracting, analyzing and reporting. Experience Daren provides data services, including analytics and intelligent automation, and develops and provides services to handle challenges not resolved by commercially available products. Daren has extensive experience in a variety of tax and accounting areas including provision and compliance process automation, Section 199, research credits, ASC 718, capitalization, and sales and use. Daren focuses on reducing cost, identifying value and controlling risk through technology and analytics. During his career, Daren has provided services to some of the firm s largest clients covering a variety of industries including consumer products, aerospace & defense, public utilities, automotive, financial services, life science, retail and engineering. Daren has experience extracting, analyzing and updating data from variety of software systems including SAP, Oracle, PeopleSoft, PowerPlant/PowerTax, EquityEdge and Sage Asset Accounting. Because of his background in both tax and computers, Daren is able to effectively communicate with a client s tax department and information technology department in obtaining and managing client data. Education and certifications Daren has a Bachelor of Science in accounting and Masters of Accountancy Tax from Brigham Young University. Daren is a certified public accountant licensed in the state of Colorado, New York and Washington DC. He is a member of the American Institute of Certified Public Accountants.

4 Moderator and panelists Kathleen Metzger Executive Tax Director Verizon Office: Kelly Necessary Partner, Tax Transformation Services Dixon Hughes Goodman LLP Office: Daren Campbell Partner, Tax Technology and Transformation Ernst & Young LLP Office:

5 Learning Objectives / Agenda Background Data Management & Automation Trends Approaching Your Data Dilemma with structure Practical Examples De-mystifying the options What, where, how much?? Tip/Recommendations Questions 15 minutes 30 minutes 5 minutes 5 minutes

6 Data Management Trends ERP/Cloud Migrations Business Intelligence The Tax Office Tax Department Data pains are increasing Options for solutions also increasing Re-evaluation of tax technologies/data solutions in holistic manner Data science infiltration into tax function IT learning-curve/integration varies greatly, but more reliance on company technologies

7 Business Intelligence SAS Institute Survey Over half (52%) of enterprise organizations stated BI is used across the entire organization; 34% for middle market** All respondents put high importance on data-related activities, but believe they are currently ineffective at it GAPs exist across board between importance and effectiveness Largest barriers to adoption (over 50% rated at 4/5 on 1-5 scale): Turning analytics insights into action Finding & retaining skilled talent Communicating results into business insights For enterprise organizations, governance and data quality also high Organization strong in adoption of BI more likely to have a central IT-led data and analytics environment 65% of strong adopters said employees outside of IT are able to make use of BI tools * 2016 IIA Business Intelligence and Analytics Capabilities Report commissioned by SAS and executed by International Institute for Analytics ** Enterprise = employees over $1b revenue; Middle market = employees $50-$1mrevenue

8 The Tax Office

9 The Tax Office

10 Approaching Your Data Dilemma Tax Data Lifecycle & Automation Categories Automation Categories: Automation within a system Manual Activity Required System to System

11 Approaching your Data Dilemma Sample tax process Tax function/process Indirect tax sales and use SUT invoice extraction for audits SUT completing exemption certificates and updating vendor tables SUT tax coding verification and updating Vertex Tax accounting US and Non-US uploading from SAP/HFM, formatting, reconciling and Fx conversion to OTP OTP reporting package extracting completed provision data, reconciling to final accounts International compliance Book to tax consolidated WPs; GL download and reconciliation for 5471s Quarterly foreign tax credit data gathering Preparation for audit readiness US income tax compliance Upload documents/work papers to Tax Master/standardize naming conventions GL download and TB reconciliations Gathering state and local apportionment data, reconciliations and performing analytics

12 Approaching Your Data Dilemma Automation Categories For Different Purposes Automation within a system Manual activity required System to system Scripting SAP, Excel, OneSource, Corptax Robotic process automation Blue Prism, Automation Anywhere, UiPath, WinAutomation Data integration Informatica, SQL Server Integration Services, MS Power Query, Alteryx Cognitive

13 When to use data integration Moving/consolidating data from multiple sources Non-tabular data source formats Approaching Your Data Dilemma Automation Categories For Different Purposes When to use Automation within a system System already licensed for tax processing purposes Minimize cost to maximize system capabilities When to use RPA Replicate tasks typically requiring human action High instance of repetition Manual, repetitive steps to transform data

14 Example 1: Automation within a System ONESOURCE DataFlow ONESOURCE DataFlow extends the capabilities of Excel, making it possible for you to develop customized web-based templates. You can use your existing Excel-based workpapers or tax packages and enhance them by utilizing DataFlow s unique functionality. Creating or converting Collecting Loading and reviewing

15 Example 2: Manual Activity Required Robotic process automation What is RPA? Robots RPA simulates an employee. The software robot has access to diverse applications with an ID or a password. The robot can gather information or change data. Consequently, business and administrative processes can be fully automated. RPA integrates into an existing IT infrastructure. As a renewal of the existing IT landscape is not required, a high level of automation can be reached without major effort. RPA uses established control mechanisms and can communicate with all systems. Therefore, no interface has to be created. deliver repetitive, deterministic, high-volume tasks efficiently, quickly, and consistently. People build relationships, provide subjective judgement, deliver low-frequency tasks, and manage change and improvement. RPA is software. RPA is a computer software that runs repetitive, rulebased processes. The software is trained based on functional specifications and can be adjusted at any time.

16 Example 3: Data Integration Enterprise extract transform load ( ETL ) SQL Server Integration Services ( SSIS )/ Azure data factory

17 Example 4: Data Integration Self-Service extract transform load ( ETL ) Alteryx is a self-service tool with advanced data analytics tool with a visual workflow. Microsoft Power Query is a self-service tool that is part of MS Excel and MS Power BI.

18 Example 4: Data Integration Sample feature comparisons Alteryx Cost $5,200/user/year Free MS Power Query Advanced statistical and predictive tools Has a large library of statistical and predictive tools (i.e., boosted model, neural networks) Basic statistical tools (advanced statistic and predictive tools are available in SQL Server and Azure) Data joins Direct joins and fuzzy matching Direct joins (Fuzzy joins are available in SQL Server and Azure) Financial backing Alteryx 2016 revenue was $86M Microsoft 2016 revenue was $85B Speed and through processing Machine: Core i5, 8 GB Ram with 64 bit OS Recommended use scenarios 250,000 records with 157 columns from a 200 MB Excel file processed in 90 seconds Doesn t tie up machine while running Company has an existing license Processes involve advanced matching, advanced statistics and/or analytics, or spatial analysis Desire for visual process documentation Company uses Macintosh operating system or Google Sheets 250,000 records with 157 columns from a 200 MB Excel file processed in 120 seconds Can slow machine while running Company uses Microsoft Excel 2010/2013/2016 Processes involve basic to intermediate data matching and transformation Company IT strategy is focused on Microsoft and minimizing license management

19 A word on Visualization The last layer in data management strategies Self-service capabilities abound Flexible Great tool(s) for tax department expertise Only as good as the data quality and availability Endless possibilities Review Data/Tax Result Trends Forecasting Predictive?? Sample tools: Tableau, PowerBI, D3.js, Qlikview, Datawrapper, Spotfire, Ploty

20 Visualization across the Tax Life Cycle Cash tax opportunities and risks Return to Provision Country Tax Alerts Tax Performance Management Book Tax Differences Country Executive Summary Entity View Pack Tax Controversy Filing Performance Filing Status Tax Payments

21 Tips and recommendations Data quality, access and management is a key driver when addressing tax automation What is your tax data strategy? Don t analyze automation in a vacuum understand how each fits into your overall data strategy Consider holistic viewpoint It s difficult to turn a tax person into a Data Scientist Be intentional in defining future tax competencies Partnering with IT is important The future may require it

22 Consider holistic approach

23 Q & A Thank you!