DNA of the CFO: Disruptive technologies that will reshape finance as we know it. February 22, 2017

Transcription

1 DNA of the CFO: Disruptive technologies that will reshape finance as we know it. February 22, 2017

2 Agenda 7:30-8:00 a.m. Registration and breakfast 8:00-8:15 a.m. Welcome and introductory remarks Glen Wedel, Associate Partner, Performance Improvement Finance, EY 8:15-8:45 a.m. Presentation: DNA of the CFO - Robotic process automation and impact on the finance operating model Kim Connors, Partner, National IT Advisory Leader, EY 8:45-9:30 a.m. Panel discussion: Robotics and impact on operating model 9:30-10:00 a.m. Presentation: DNA of the CFO - Leveraging machine learning for better forecasts as an example of how analytics will change the way finance operates David Klur, Partner, Advisory Services Analytics, EY 10:00-10:45 a.m. Panel discussion: Analytics and predictive forecasting 10:45-11:00 a.m. Closing remarks Page 1

3 Welcome: DNA of the CFO In EY s first The DNA of the CFO study, conducted in 2010, we painted a picture of a role that had broadened to encompass not only traditional financial skills, but also more strategic and market-facing responsibilities. Our latest research shows that in the 7 years since, several forces have continued to transform the face of finance leadership: Technological innovation is providing an opportunity for CFOs to transform their finance function into a fact-based decision centre for the whole organization. Page 2

4 Welcome: DNA of the CFO series Part 1: Do you define your CFO role? Or does it define you? The disruption of the CFO's DNA. Part 2: Is the future of finance new technology or new people? Preparing for the future finance function. Part 3: As the CFO role blurs, how can future finance leaders find focus? Redefining the path to a CFO appointment Page 3

5 Welcome: DNA of the CFO CFOs are focused on technological transformation and new skill development Page 4

6 DNA of the CFO Part 2: Is the future of finance new technology or new people? Preparing for the future finance function. Finance Function Page 5

7 Robotic process automation and impact on the finance operating model Kim Connors, Partner, National IT Advisory Leader, EY

8 What is Robotic Process Automation, and why is it such a hot topic now? Page 7

9 As a useful tool, where does it fit in the technology armoury? Process Value / volume ERP, CRM Process Spectrum ERP Customisation / Integration / BPMS Robotic Process Automation People / Desktop / Lean Key Features of RPA software User Interface Focussed: Accesses existing applications via user interfaces with no/minimal impact to core systems Scheduling & Monitoring: Can run 24x7 in a data-centre with performance and incident monitoring, flexible scheduling options Business User Friendly: 100% visual, with little or no coding or macro language skills required Full Audit History: including process definitions, and each task processed Full Security: including fully secured credential management Fully Scalable: run thousands of processes Frequency of change Page 8

10 Video: Robot in action Page 9

11 Common client outcomes Page 10

12 Robotics has the ability to dramatically change the amount of manual effort in Finance Today Effort to process transactions Tomorrow Manual effort based on transactions Effort automated through robotic process automation Process exceptions driven by human error Process exceptions driven by other factors Reduction in human error Manual effort based on transactions Exceptions - human error Process exceptions driven by other factors Page 11

13 How automation technologies creates value in Finance Accounts Receivable Customer Master Data Management Accounts Payable Travel & Expense General Ledger Closing & Reporting Asset Management Tax Operations InterCompany Internal Accounting Vendor Master Data Management (for financial view) Administer T&E Policy Manage General Ledger Account Master Data Closing Management Investment Process (Accounting View) Tax set-up IC Invoice Processing Automatically (IXB) Define & Manage SAP CO Master Data, Structures & Value Flow Catalogue Changes Process Receipts Process Invoices Manage T&E Related Master Data Perform Manual General Ledger Posting (standard cases) GL Closing activities Asset Accounting Master Data Creation/ Maintenance Country specific manual IC Invoice Processing tax processes Manually Perform & Check Cost Allocations Credit Control Activities Process Payments Process T&E Claim Perform Manual General Ledger Posting (special cases) Perform actual reporting in CoReP Assets Transfer, Tax data review and Disposal, Change & Sale preparation IC Reconciliation Activities Define & manage Profit Center Accounting (PCA) (prepare OAS/ cash flow) Dispute Management Query Handling, Vendor T&E Additional Account Maintenance & Support/ Activities Period End Activities Perform Account Monitoring & Clearing Perform actual reporting HB 1 Reporting & Closing Tax declaration Intercompany Clearing (BIC) Perform product costing standard costs GO Activities Reporting Manage Physical Inventory Tax payment and adjustment Month-end Preparation, Reporting and Projects Perform product costing actual costs and Inventory valuation Eliminate material human effort Capacity and critical path Reduce costly errors; improve quality Situationally valuable Potentials Manage tax audit queries T.O activities for other local Taxes Define & manage Service Accounting Support Planning Refocus knowledge workers for greater value Withholding Tax activities (Originally in GL) Page 12

14 Identifying and selecting the right use cases is the key first step in your transformation Although detailed process steps vary across firms, candidate processes share common characteristics, they: Areas to prioritize Are manually intensive Processes employing large internal teams Involve multiple, unconnected systems Incur high costs (FTE utilization, frequency, etc.) Involve deterministic, repetitive workflow Transformation roadmap items that are lagging and holding up delivery Service level transformation (converting weekly or daily processes to hourly or less) Page 13

15 Key success factors from RPA implementations we would like to share with you Page 14

16 Panel Discussion: Robotic process automation and impact on the finance operating model

17 Leveraging machine learning for better forecasts as an example of how analytics will change the way finance operates David Klur, Partner, Advisory Services Analytics, EY

18 Traditional financial forecasting methods do not meet the needs of today s CFOs Inefficient Labor-intensive: Hundreds of analysts inputting assumptions at a detailed/granular level; often via spreadsheets Cumbersome: Time-consuming processes to change forecast assumptions for what-if modeling Not accurate Biased: Forecasts are influenced by personal and organizational biases Error-prone: Incorrect assumptions or bad data Limited: Reliance on a limited number of internal data sources as inputs to the forecast Page 17

19 Advanced analytics can improve forecast accuracy A data-driven, statistical/mathematical model of business performance, using internal and external data sources as inputs, and machine learning algorithms to improve accuracy over time Page 18

20 Advanced analytics can also improve forecast agility Fewer people required to input forecast assumptions Pre-population with machine learning allows people to focus on exceptions Quickly identify critical drivers impacting forecasts Changing forecast assumptions can be done instantaneously Page 19

21 Forecasting with analytics is a data-driven, statistical approach that gets smarter over time Hypotheses Data Factors we believe may drive financial outcomes (a starting point for data collection) Internal (e.g., financials, pipeline, customer, product) External (e.g., market, social media, macroeconomic) Train the model; analyze patterns; develop insights and predictions Agile, iterative process of testing and refining models Incorporating finance and business domain knowledge Analytics algorithms Time series Machine learning Regression and multivariate analysis Translate insights and predictions into action Continuous improvement Machine learning improves accuracy over time Data sources and hypotheses evolve with the business Facilitating conversations with the business Incorporating insights into financial and business decision-making Page 20

22 Robotics can automate parts of the forecasting process Extracting data from internal and external sources as inputs to the forecast Using the output from the machine learning forecast to pre-populate the existing forecast tool Updating and training the model over time with new data Accuracy The right result, decision or calculation the first time Scalability Instant ramp up and down to match business needs Reliability No sick days, services are provided 365 days a year Page 21

23 The same analytics-driven approach can be applied to other forecasting activities Treasury Application Forecasting accounts receivable and accounts payable Value Optimize working capital Improve currency hedging Inventory Forecasting inventory requirements Improve working capital Reduce transportation spend Tax Forecasting Effective Tax Rate (ETR) More effective tax planning Page 22

24 The future of forecasting: the human element will continue to be important, but complemented by more technology Whole sections of the P&L will be forecasted automatically Analytics will generate a baseline forecast FP&A personnel can then layer in their knowledge of unique events Routine forecasting tasks will be handled by robotics, giving finance more time to analyze the business Forecasts will be more frequent and more accurate, leading to better decisionmaking Page 23

25 Panel Discussion: Leveraging machine learning for better forecasts as an example of how analytics will change the way finance operates

26 Closing Remarks

27 Closing Remarks 1. Define a vision 2. Rethink technology 3. Invest in people A clear vision for the future finance function, which is aligned with the organization s overall purpose and business strategy, gives finance team members around the world a common ambition, and provides focus for efforts and investment decisions. A bold technology strategy for the finance function will be critical. The function will need to build systems and tools that enable disparate teams to share information and make connected, data-driven decisions. CFOs need to find the new skills and capabilities required to exploit new technologies and increasing volumes of data. They also need to build their people s softer skills, such as their communication and influencing skills. A coordinated approach will be one of the cornerstones. Page 26

28 Closing Remarks: DNA of the CFO series ey.com/ca/dnaofthecfo Part 1: Do you define your CFO role? Or does it define you? The disruption of the CFO's DNA. Part 2: Is the future of finance new technology or new people? Preparing for the future finance function. Part 3: As the CFO role blurs, how can future finance leaders find focus? Redefining the path to a CFO appointment Page 27