5. Finance Performance Days - EY · PDF file5. Finance Performance Days ... Investment...

5. Finance Performance DaysDas Forum für aktuelle Finance-, Controlling- und BI-Themen

17. November 2016 - Düsseldorf

Seite 2

Agenda

Einführung 09:30

Digitalisierung (Robotics) im Finanzbereich (Teil 2) 11:00


10:45

11:45

Schlusswort 12:45

Analytics und die zukünftige Rolle der Finanz- und IT-Funktion

Pause

Business Lunch 13:00

November 2016

Pause

12:00

5. Finance Performance Day

Seite 3

Agenda

Einführung 09:30



10:45

11:45

Schlusswort 12:45


Pause


Pause

12:00

5. Finance Performance DayNovember 2016

Seite 4

This session aims at providing an understanding of RPA project leading practice


Session objective is to share insights of: ► Background on RPA► Vendor considerations► Project phases and purpose ► Key activities for each phase ► Deliverables for each project phase ► Milestones and time frame► Examples from projects► Lessons learned

November 2016

Seite 5

If you do RPA wrong, it will fail like a white elephantproject – everybody talks about but no use case


Seite 6

Robotics originated with industrial appliances


Unmanned ground vehicles

Laboratory Automation

Anthropomorphic robots and toys

Precision-controlled robotic surgery

Picking, packing, and sorting robots

Injection molding, machining, and robotic controls

Sensors and components

Heavy robotics (aerospace, construction, and agriculture)

Warehouse automation

Industrial robotics

Autonomous marine systems

Unmanned aerial vehicles

Commercial inspection robotics (e.g., assembly lines)

Robotic surgery platforms

Bionics and exoskeletons

Humanoid and highly mobile robots

Solar and semiprocess Robotics

1950–1990Early focus on heavy

robotics for industrial, warehouse, and military

applications

1991–2000Increased focus on unmanned aerial

and marine vehicles

2001–2005Growth in medical and

Anthropomorphicapplications

2006-2010Rapid growth in

anthropomorphic robots and toys, robotic

surgery and lab automation, and unmanned ground vehicles

2011–2014Growth in unmanned

aerial vehicles for agriculture,therapeutic bionics, and consumer

applications

November 2016

Seite 7

Nearly half of US jobs may be susceptible toautomation over the next two decades


Probation Officers and Correctional Treatment Specialists

Ambulance Drivers and Attendants, Except Emergency Medical Technicians

Sales Representatives, Wholesale and Manufacturing, Technical andScientific Products

Agricultural Engineers

Telecommunication Line Installers and Repairers

Police, Fire, and Ambulance Dispatchers

Court Reporters

Demonstrators and Product PromotersDental Assistants

Postmasters and Mail Superintendents

Tile and Marble Setters

Painters, Construction and Maintenance

Transportation Attendants, Except Flight Attendants

Nuclear Power Reactor Operators

Real Estate Brokers

Models

Credit Analysts

Bookkeeping, Accounting, and Auditing Clerks

.25 .50 .75 .95+

Occupations according to their probability of automation

November 2016

Seite 8

RPA needs to be put in context with other technology solutions that enable automation

Key: Relative ROI %, Relative difficulty/time to implement

Robotics

Task Specificity

Freq

uenc

y of

Tas

ks

e.g. ERP, CRM

e.g. BPMS

1X50X

2X10X

10X

1

lowlow

high

high

Hardest, Consuming

Big, Risky

Scalable, Fast

Illustrative Automation Horizon

All back office functions are facing a disruptive revolution. Automation is changing the way corporations work dramatically.

The technology is developing fast and can be described by three categories depending on the level of “intelligence”:1. Rule-based automation – Robots that

follow a set of pre-defined rules that describe tasks

2. Enhanced/intelligent process automation – Robots that can understand unstructured data, human communication (e.g. voice or email) and draw conclusions from data cross-checking

3. Cognitive platforms – Robots that learn from experience in the same way as humans do in order to perform complex tasks without human interference


Seite 9

Enabling business functions to achieve excellence by orchestrated Resource Orchestration with RPA

What are the benefits of RPA?


Seite 10

Seite 11

Identifying the most suitable scope of implementation is key to unlocking the full value of RPA

üüüü

ü

üüüü

ü

There are a set of “key tells” that provide guidance on where RPA will be a solution with strong capability to unlock value. (All points do not have to be fulfilled)

• Data intensive• Repetitive in nature • Rule-driven• Electronic trigger to the

process• Have electronic start-

points and endpoints

• Involve manual calculation• High error rates • Sensitive content • Can be performed out of

office hours • Complex IT landscape

Examples of support functions that involve processes with proven potential for RPA

IT services

► Installation ► FTP download,

upload and backup► Server application

and monitoring► Synchronizing,

deleting and emptying folders

► File management► Email processing ► Batch processing► …

HR services

► Payroll► Benefits admin► Payslip management► Time and attendance

management► Recruiting process► Onboarding► Education and

training► Compliance

reporting► …

Supply chain

► Work order management

► Demand and supply planning

► Quote, invoice and contract management

► Returns processing► Freight management► …

F&A

► Sales order► Order to cash► Collection► Procure to pay► Incentive claim► Record to report► Supply chain vendor

setup► Trend tracking ► ..


Seite 12

Scope considerations in Finance

A B C D E F G H I J K L

OperationalAccounting

Procure to Pay

General Accounting

Financial & External

Reporting

Performance &

ManagementReporting

Budgeting, Planning and Forecasting

Policy,Controls,

Governance & Compliance

Internal Audit Treasury

Capital Management

& Investments

Tax Planning& Accounting

Investor Relations

1Loan Accounting Strategic

Sourcing

Chart of Accounts Maintenance

Financial Reporting Responsibility

ReportingStrategic Planning

AccountingPolicy & Gov.

Risk & Control Framework

Debt/Equity Management Capital Planning Tax Planning Stakeholder ID

and Analysis

2

InvestmentAccounting

VendorAdministration

Allocations & Adjustments

Regulatory Reporting Org profit

reporting

Annual BudgetRegulatory Policy & Gov.

Functional Auditing

FX ManagementCapital Structure and Asset level

Tax Accounting / Tax data management

Stakeholder engagement

3Insurance Accounting

Contract Negotiations

Journal Entry Processing

Reporting Product Profitability

Quarterly/ Rolling forecast

Statutory Policy & Gov. Consultation

Liquidity Management

Business Case Support

Tax accounting / Analysis

Stakeholder relations

4 Reinsurance Accounting

Accounts Payable

Reconciliations Statutory Reporting

Customer Profitability Earnings

Forecast

Mgmt. Accounting Policy & Gov.

Cash Management Acquisitions &

Divestitures

Tax accounting /Preparation and review

Corporate Communications

5 Fund AccountingRequisitions & PO Processing

Inter-company Transactions Audit Support

Fund Profitability Internal Process & Controls

Capital Strategy Project Accounting

Tax compliance Rating Agency Relations

6Accounts Receivable Payroll Consolidation Cost

Development

SOX Compliance Bank RelationsTax controversy/tax audits

7Billing & Collections

Exp Accounting & Reimbursement

Close Cost Allocations Tax & Treasury Policy

Treasury Strategy

8 Dispute Resolution

Fixed Asset Accounting

Funds Transfer Pricing

Finance Master Data Governance

Global Economics

9 Policy Accounting

Securities Pricing & Product Control

Ad hoc Reporting

10Legal EntityMgmt/ maintenance

Analytics & Decision Support

6

Robotics

OCR / Structured Forms

Rules EnginesDigital / Workflow

6 Desktop Acceleration

Situationally valuable

6

6

6

6

6

6

6

6


Seite 13

Example how to get started in Finance


Map Ref. Finance Process

Automation

Opportunity

Illustrative Use Case

C.3Journal Entry Processing

Automated Journal Entries:• Prepare and enter corporate and consolidated GAAP journal entries to close the company books

during quarterly closing process• Prepare and enter journal entries for other regulatory process needs - e.g. for Tax ledger

C.4 C.5 I.6 Reconciliation

Intercompany Difference Reconciliation :• Triage and action exception items from intercompany differences regionally and aggregating into

parent• Support intracompany match and elimination for multi-national reinsurance business• Match and reconcile operating expenses eliminating duplicated controls and charges

Bank Reconciliation :• Reconciliation of balances and transactions on the bank statements to GL/cash flow systems. This

could also include creating balancing journal entry to handle discrepancies.

C.10G.8

Entity & Account Maintenance

Entity, Account, mappings & adjustments maintenance for downstream systems (e.g. Tax systems):• Identify and synchronize master data (Legal Entities-Jurisdictions, Non-legal Entities, Partnerships,

BU-cost centers, Accounts & adjustments) from finance / legal systems to downstream systems (e.g. Tax systems)

C.7Close

Controller focused management review deck preparation:• Prepare management review deck by collecting data from GL & multiple systems for non-operating

expenses and cash balances. Builds confidence in data lineage.

Mock close & mock conversions:• Support mock close, mock conversions and testing during system implementation of a new GL

System Implementation project (e.g. automate process flow from mock conversion to mock close to balance reconciliation – to be repeated of all involved entities)

Capacity and critical path

Eliminate Material Human Effort

Refocus knowledge workers for greater value

Reduce costly errors; improve quality

November 2016

Seite 14

Myth about RPA


“All the office work can be automated by RPA”

“RPA is primarily useful to cut operational costs”

“Robots will eventually replace the majority of my employees”

“RPA can be implemented without the support and involvement of the CIO org.”

“RPA is the silver bullet for optimizing my admin. and operational organization"

1

2

3

4

5

The easiest way to describe RPA is as software that mimics human behavior.This human behavior should typically be "rule-based" and requires digital inputs for the RPA software to be effective.Terms such as “robots”, “augmented technology” and “artificial intelligence” have however rendered in some persistent myths

November 2016

Seite 15

RPA impact goes beyond POCs and deployment and needs to be embedded in a holistic approach


Org

aniz

atio

nla

yer

Exec

utio

nla

yer

Res

ourc

ela

yer

• Develop and deliver RPA optimized end to end processes to maximize benefits• Establish global RPA policies and

governance framework to support risk management

• Review control frameworks to ensure documentation and testing appropriate for RPA

• Structure the organization to consider new RPA roles to support the business

• Define appropriate local, regional, global structures including shared services and outsourcing

• Define a set of consistent global data standards and common chart of accounts then deploy utilizing RPA with existing systems until future system deployment projects

• Implement RPA single source of data projects

• Define RPA systems and tools strategy to support cross-functional use in front, middle and back office

• Successful programs typically benefit from a constellation of tools

• Consider impacts on existing software contracts and future system implementations

• Develop new RPA frameworks for performance measurement

• Develop RPA COE and continuous improvement program

• Build new competency models considering Robot/Human interactions

• Develop career ladders and job roles for RPA enabled teams for new skill needs

• Adjust talent strategy to new competency models

Process

People

Organization

November 2016

Seite 16

.. and needs to be adjusted accordingly for GBS


Service Delivery ManagerGlobal Process Owner Solution Designer

[E2E Process] Operations

SSC / Delivery unit IT

Uni

ts

Rol

es a

nd T

asks

► Manage process execution team including robotic environment

► Updates rules in accordance with process

► Reports on performance KPIs to SSC / Delivery unit head and Function head

► Define the functional IT solutions and enablers

► Supports in more advanced and IT architecture related topics of RPA

► Reports to Function head and IT on process and IT KPIs

Design / Build Execute Build / EnableFocus:

► Defines the processes

► Defines the RPA process requirements for Solution Designer

► Reports on process-KPIs to Function head

Updated GBS governance model ► The governance

model is adjusted to fit the shift in delivery model

► IT is a highly important stakeholder but the responsibility for delivery remains with the Service Delivery Manager, in accordance with the process developed by Global Process Owner and with the support of Solution Designer regarding IT enablement

November 2016

Seite 17

A Centre-of-Excellence (CoE) structure can provide support for RPA


Training

• Develop training material as well as plan and perform trainings

• Certify robotics practitioners

Solution insights

• Gather, consolidate and share knowledge of vendors and tools

Methodology and approach

• Develop and share leading practice methodology and approach

Project delivery • Provides resources that can lead

and support in project • Focus on building capabilities

within: process analysis, robot development and robot IT infrastructure

• Perform quality assurance on robotics projects (independent of size)

Support provided by the CoE ► CoE team provides competencies needed to provide E2E support in the four areas to the right. This entalies

► Ensuring delivery capabilities (significant team size to ensure ability to meet project demands)

► Ability to challance and develop methodology as well as available tools

► Parttaking in the fast phased development within the RPA market to feed the rest of the organization with knowledge through ad-hoc requiests as well as structured trainings

► Deep understanding of tools used for RPA

November 2016

Seite 18

Agenda

Einführung 09:30



10:45

11:45

Schlusswort 12:45


Pause


Pause

12:00


Seite 19

Agenda

Einführung 09:30



10:45

11:45

Schlusswort 12:45


Pause


Pause

12:00


Seite 20

RPA market overview

UiPathHead office: Bucharest, Romania

Turnover: 6.9m USD***Founded in: 2012

AAHead office: San Jose, USA

Turnover: 2.5m USD**Founded in: 2003

RedwoodHead office: Morrisville, USA

Turnover: 17.5m USD****Founded in: 1993

WorkfusionHead office: New York, USA

Turnover: 5.7m USD*****Founded in: 2010

OpenspanHead office: Alpharetta, USA

Turnover: 12.6m USD******Founded in: 2005

Blue PrismHead office: London, UK

Turnover: 7.5m USD*Founded in: 2001

5bn RPA Market by 2020

60% market growth

│ Headquarters│ Sales offices

*Source: London stock exchange**Source: Estimated value by Manta***Source: Estimated value by Owler

****:Source: Datafox.com*****:Source: Estimated value by Owler******:Source Estimated value by Owler


Seite 21

Most of the providers in RPA rely on the input of other automation enabling technology


Enterprise Infrastructure / Enterprise Cloud

Systems of Record (ERP, CRM, …)Data Warehouse / Data Lake

Cognitive Automation

Digitization

Workforce Orchestration

Autom

ationA

utomation enablers

Mobile

BPM/DCM

Classical UX

Data Science

Dat

a In

tegr

atio

n (E

TL, D

Q, M

DM

)

Robotic Automation

Aut

omat

ion

BI/A

naly

tics

Embe

dded

Aut

omat

ion

Note: list of companies is non-exhaustive

November 2016

Seite 22

EY has the knowledge of the key RPA suppliers and their capabilities to deliver value to clients


EY is continuously following the fast development on the market in order to know about the:

► Capabilities ► Product portfolio► Strengths and weaknesses ► Latest innovation ► Trends► Large deals ► Partnerships and alliances ► etc.

RPA suppliers

And many others..

November 2016

Seite 23

How do we select the right vendor

Matching & challenging of RPA long-list potentials with vendor capabilities

Cost & criteria ranking of RPA vendors

► Analysis of the most relevant RPA potentials in terms of process volatility and complexity

► Matching of RPA potentials with capabilities of RPA vendors

► Challenging of the results in 1st working session► Agree and sign-off of matching

► Analysis of cost structure of relevant RPA vendors (Licensing, administration cost, etc.)

► Provide results of criteria analysis ► Discuss results and agree on RPA vendor short-list

for further vendor selection approach (Vendor trade show, RfP process)

1 2


Seite 24

RPA tools were evaluated through user testing and conversations across vendors emphasising ease of development, automation functionality, enterprise class management and infrastructure.

Key selection criteria

Ease of development including availability of on-site and virtual training, Self-learning training and extensive documentation

Thin client interaction with the ability to RDP and allowing for Citrix based automation

Business friendly UI based on the use of visual process mapping,process recording and allowing for out of the box development independent of coding

Unattended automation with virtual and physical offerings which is managed externally through server or control room (fully external)

OCR capability allowing for basic scanned image recognition to complex self-learning handwriting recognition

Enterprise class management including existence of ‘control room’, resource pools, audit and session log capabilities

UI Integration facilitating Integration with; win32, HTML, Java and mainframe based applications not limited to the use of API’s


Seite 25

Example of GL automation assessment II/III


Description (BEAM) Automation potential Comments and considerations

Indicative level of

automation

Common time frame

Perform manual General Ledger posting (special cases)

§ The robot can perform postings for special cases and perform the validation of the postings prior to approval

§ Automated approval for postings that receive OK after the validation can be considered

§ Keep 4-eyes –principle and check

Perform account monitoring and clearing

§ The robot can perform the monitoring, automatic clearing and exception handling for the accounts

§ Standard criteria for clearing in SAP § Quantum (hedging) results in minor

rounding differences (cents) § Differences can be verified by Robot

based on transactions (rules) and perform clearing (overnight)

§ Manual clearing and update of criteria cannot be automated

§ For available automatic clearing, additional benefits from Robotics?

§ Could be supported by Robot via usage of existing tools

Near Mid Long

Near Mid Long

► The robot can formally validate the request and perform maintenance of items or entire tables, follow-up on the upload to SAP, ticketing and exception and error handling

► The robot can perform postings for special cases and perform the validation of the postings prior to approval, approvals are manual

► Time frame for rollout sequense is usually relatively short

Examples of robotics opportunities within General Ledger

November 2016

Seite 26

Example of GL automation assessment III/III


Description (BEAM) Automation potential Comments and considerations

Indicative level of

automation

Common time frame

Perform balance carry-forward (GL, subledger, CSL)

§ Robot can monitor closing and perform postings of balance carry-forward Near Mid Long

► The robot can formally validate the request and perform maintenance of items or entire tables, follow-up on the upload to SAP, ticketing and exception and error handling

► The robot can perform postings for special cases and perform the validation of the postings prior to approval, approvals are manual

► Time frame for rollout sequense is usually relatively short

Examples of robotics opportunities within General Ledger

November 2016

Seite 27

AR example workshop output


Robotics opportunities identified during the workshop

% of Automation

Process ID Process name Details of automation potential identified Comments

AR-30-20-40AR-30-20-50AR-30-20-60AR-30-20-70

• Verify and post doubtful debts and provision for bad debts

• Verify and post write offs

• Verify and post reversal of provision for bad debt

• Post and clear open items on customer account

The following process can be done by the bot1. The bot can log into SSF and create a ticket for data to

AccP2. The bot can then log into the SAP download the data

and then covert that into an excel file 3. Bot can perform necessary credit adjustment

calculation in excel based on rules set by customer portfolio group

4. Bot can send it to CM team for review5. The bot can then send it to authorization based on the

names defined in SAP6. Based on the response from the authorized personal,

bot can either post the doubtful debts7. Once done the bot can then post the provisions for bad

debts8. The bot can then log in and clear the open items on the

customer account.

• The customers need to be grouped in portfolios according to specific criteria for credit adjustment

TimelineNear Mid Long

No of FTES No of Systems

• SAP, SSF,email

HighVolumes Average handling time

Benefits overview

• Time saving; reduction of manual effort; reduction of manual errors;

November 2016

Seite 28

Example from AR functional design


Seite 29

Example of agile approach for delivery


Seite 30

Process breakdown and bundling of user stories to accelerate the implementation of the RPA software

Bundle user story & implementation Rebuild of agile rebuild of business process

1

M1

1 4

MM

2

1 2

3

21

14

3 22

2

3

3

ActivitiesProcesses are split into work packages based on tasks defined in the user stories during the Business Process Analysis-phase

Breakdown into robotic- and manual-processes

ActivitiesBundle user stories based on identical applications to speed-up the implementation

Modular approach could leverage the reuse of bot sequences

ActivitiesRebuild entire business processes in a test environment

Validate automated process and test results with the process design teams

Analysis of high-, medium-, and low complex processes:

► Define user stories, sub-task and estimate time required for development and implementation

► Define task on a detailed and granular level to understand complexity of the process

► Mapping of data transfer between each application and define data interface

Bundle user stories and prioritize:

► User stories are grouped based on the underlying identical application

► The developer will focus on user stories from identical application

► Experts will identify the steps that can be bundled and how the information from the same application can be processed

Rebuild business processes:

► Design process in sprints to rebuild the business process

► Integrate interface to manage user interactions with the robots (notifications, control room, changing business rules, etc.)

► Test processes on developer laptops and on runtime environment

Excel HOST WebGUIManual

1 M1 1 4

2 2 3 3

M M 2

Detailed process mapping


Seite 31

Our agile method supports the tight deadline, allows fast reaction to unpredictable issues and raises user acceptance

Illustrative agile scrum methodology (typically used for software development)

PlanBuild

TestMove

Review

Initi

al d

eadl

ine N

ew d

eadl

ine Sequentially designed (one phase to be

completed to launch the next phase)

Build

Move

Plan Test

Build

Move

Plan Test

Build

Move

Plan Test

Review Review

RPA for all

processes

RPA for all processes

RPA for some

processes

RPA for some

processes

Sprint 1 Sprint 2 Sprint 3

Incrementally designed (several sprints create product ready to use)

Delivering benefit

Delivering benefit

Delivering benefit

Delivering benefit

Any challenges that might occur

Illustrative waterfall methodology (typically used for traditional project management)

Any challenges that might occur


Seite 32

Knowledge inception in the design phase

Knowledge transfer in SSC Knowledge independence from EY for all other waves

EY KnowledgeTransfer

EY

Initialize Industrialize Institutionalize

Early days – Robotics team Robotics Center of Expertise Advanced automation and virtual workforce

Typical approach to transfer knowledge to your organization


Seite 33

EY has identified a set of key success factors from RPA implementations


1. Define strategy and set desired outcome / targets early in the process

2. Build business case

3. Perform proper analysis to target the right operations

4. Involve IT early

5. Deploy a strong Change Management workstream

6. Start small and agile, but be clear about ambition

7. Secure access to testing environment (internally or through supplier)

8. Evaluate maturity level internally and by supplier – focus on transformational capacity

9. Ensure that there is a match with supplier long term strategy (RPA is at an early stage and will develop fast)

10. Design new governance models

EY has gathered experience from several implementations with clients from different industries, different functions and with different maturity related to RPA. Some success factors do however stand out as key when implementing RPA.

November 2016

Seite 34

EY is investing heavily in a global integrated delivery approach for Robotics


What differentiates EY is: ► Innovation Lab- client, vendor,

industry innovation partnerships ► Robotics Academy- RPA training

on tools and methodologies► Solution Stacks- EY IP on

existing technologies for functions and sectors jump start RPA programs

► Technology and Delivery agnostic- independent advice to select the right tools and delivery

► Vendor Alliances- strategic, collaboration and joint solution development

► Comprehensive support- 70+ value enhancers in Tax, Controls, People, Change, Functions, etc.

► Eat our Own Dog Food- RPA deployed internally in EY GBS

► Large Global Footprint- One of the largest and more experienced global network of RPA >350 practitioners

► Digital RPA experience lab-showcasing RPA in action(Frankfurt and Silicon Valley)

RPA Strategy

RPA Heat Mapping

RPA Proof of Value

RPA Implementation

RPA Innovation lab

RPA Managed Service

EY RPA Advisory offering

RPA Solution Coordination Americas – Weston Jones

RPA Technical Team Americas – Oscar Marinez

RPA Solution CoordinationEMEIA – Martin Weis

RPA Center of ExcellenceEMEIA – Aurelia Costache

RPA Solution Coordination APAC – Pascal Bornet

RPA Technical TeamAPAC – Varghese

Abraham

120 FTE

160 FTE

140 FTE

Six Global Delivery COEs- Bucharest, Romania; Buenos Aires, Argentina; Dalian, China; Manila, Philippines; San Jose, Costa Rica and Trivandrum, India

November 2016

Seite 35

EY has the capabilities in RPA and deploys it internally as well


EY has the capabilities and resources to deliver sustainable efficiency on a global scale with a strong footmark in developing your automation strategy.

EY has a preferred alliance partnership with Blue Prism globally. being engaged with Blue Prism for robotics deployment across multiple businesses.

EY’s robotics Center-of-Excellence facilitates global alignment in tools, accelerators, frameworks and approach. For example, In 2015, we were 140+ strong RPA practice globally who delivered 15+ PoC and 5+ engagements in RPA.

Global resources and Vendor Network

EY offers a global robotics capability with a consistent delivery across geographies

We have a broad RPA vendor network with a clear view of their individual strengths and weaknesses

Technology Leader and Knowledge Champion

We are in constant contact with RPA market leaders & Start-up’s to know about latest artificial intelligence applications & technologies

Leveraging our knowledge of software capabilities, EY provides guidance on what can be achieved; how best to deploy & most effectively use the software

Program-, Quality-, Change-Assurance

EY ensures that RPA implementations are audit reliable and follow a smooth program and quality assurance approach

We accompany you during times of transitions & changes to establish new governance structures

November 2016

Seite 36

Some illustrative deliverables to provide a more hand-on feel for the scope of work in an RPA project


► Strategic direction – cost efficiency considerations ► Business case framework and indicative potential► Scope and high level process description► Detailed as-is process map (workflow)► Detailed process info► Functional design (to-be process) ► Detailed implementation plan► Technical design► Automated process (video from POC)► Re-defined delivery- and governance model

November 2016

Seite 37

Representative tools and accelerators


Work product Illustrative Description

Defined configuration Accelerator's for Data Robotics

EY has defined 3 core configuration formats for data robotics , each with defined selection criteria and detailed setup procedures.► During the mobilization phase , the accelerator enables for a faster decision

and configuration of the robotics platform.► This enables practitioner’s to select the right configuration as per business

needs .

Development and deployment guides and playbooks for Data Robotics

EY has multiple development and deployment playbooks with defined best practices and standards .► These playbooks help practitioner’s use the best and the most efficient

methods of development.► Helps build Standardized code base (Bots) across multiple business

processes.► Guides through object, action, element, process creation and deployment.

Comprehen-sive detailed design for Robotics CoE

EY provides comprehensive roadmap to build-out the data robotics COE with the organization .► As the virtual workforce expands , it becomes necessary for the organization

to build a COE.► This accelerator , provides detailed design which help client build out the

COE.► The accelerator provides detailed inputs regarding client federated COE ,

client managed COE and Managed service COE helping the client make the right choice .

November 2016

Seite 38




Design authority governance framework

This framework details the roles and responsibilities for the principal body (cross-functional) to challenge, agree and maintain design principles and decisions throughout the project lifecycle. It provides a standard process for decision escalation, resolution and communication, and informed decision making. Key objectives include agreeing to key design principles, ensuring consistency and traceability of design decisions, overseeing design decisions that are cross functional, centralize and standardize both functional and technical policy, ratify design recommendations, and approve escalation exceptions.

Data sourcing strategy These templates assist in creating an initial inventory and profile of potential

in-scope source systems. Additionally, it helps in collecting system profile information like type of system (e.g., transactional, reference, data warehouse), products, lines of business, and geography along with existing data quality issues, enhancement or decommissioning plans, etc.

Data profiling framework

This toolkit is a web-based application that perform data profiling, data comparison, data standardization, and data validation. The tool generates visual reports that provide qualitative and quantitative information about the data. The toolkit can be deployed on a local system, deployed on an EY server, or deployed on an end-client server.

Executive Steering Committee

Design Authority Committee (DACM)

Design Authority Working Group (WG)

External stakeholder 1 DACM

External stakeholders

Other DACMs

PMO

TO

CCB

Workstream 1

Architecture Review

Workstream 3

Architecture Review

Workstream 5

Architecture Review

Workstream 2

Architecture Review

Workstream 4

Architecture Review

* The Design Authority’s mandate addresses policy and decis ion making for architecture across the program workstreams. Business governance decisions and oversight of Project Governance/workstream Governance Boards are not in the DA’s Scope of Authority.

Architecture Decision Escalation/Policy Syndication*

Program Governance

The DACM will be the highest level architecture governance body on the program responsible for ratifying key design decisions and issuing formal design policies. Its key responsibilities will consist of the following:

• Set architecture design policy for the program• Ratify architecture design recommendations

approved by the DA Working Group• Ratify official architecture blueprint baselines

and changes to the baselines• Approve escalated exceptions to architecture

design policies• Issue formal guidance to be used as part of

the to II-gate review process to monitor design policy compliance

The WG will be the governance body responsible for managing all aspects of the decision acceptance, evaluation, recommendation, socialization, and sign-off process before decisions are escalated to the DACM for ratification. Its key responsibilities will consist of the following:

• Assign and/or validate decision resolution ownership

• Oversee development of the resolution recommendation and socialization of the recommendation with key stakeholders

• Approve design resolution recommendations for submission to the DACM

• Maintain central decision and policy logs• Communicate ratified architecture design

policies

External stakeholder 2

DACM

External stakeholder 3 DACM

November 2016

Seite 39




Data mapping templates

The data mapping template provides detail of the data attributes, general ledger accounts, and other information that will be mapped to report line items.

DQ rules catalog

EY has developed this catalog, with rules applicable to various data qualitydimensions like completeness, accuracy, uniqueness, conformity ,integrity, timeliness and comprehensiveness.

Data quality framework/scorecard

This scorecard measures the health of a critical data element versusagreed-upon criteria. These can include: ► Availability - data element does not exist within the model, is null, not

captured, or defaulted► Granularity - data is captured at insufficient level of detail► Conformity - data is outside expected range, or a limited set of values (e.g.,

reference data)► Precision► Accuracy - data does not reflect underlying reality or business specific rules

November 2016

Seite 40




Risk and controls matrix templates

This matrix assists in identifying the risk for each sub-process as well as documenting control objectives and control attributes. Current state controls are assessed against expected controls.

Gap analysis and prioritization templates

These templates will be leveraged for the tracking of gaps with specific focus on prioritization, ownership, and dependencies.

Remediation plan template

This template lays out the group of projects that need to be executed as a program, shows execution timeline that aligns to business priorities and external priorities such as regulatory mandates, and highlights major business, IT and infrastructure capabilities that will be enabled at each phase along with order-of-magnitude time, resource and cost estimates.

November 2016

Seite 41




Project planning tools

EY has a suite of project management tools:► Project plan templates, which are used to outline key activities milestones,

and dependencies that are typically needed for a current state assessment.► Project charter templates, which are used to describe the purpose of the

project, its major elements and decisions. ► Status report templates, which provide information on work plan activities,

issues, risks, change requests, milestones, and work products. ► The RAID log tracks all risks, assumptions, issues, and dependencies for an

engagement.

Robotics Agile methodology

EY implement data conversion using robotics using a time-boxed and resource-boxed agile sprints for rapid value.

November 2016

Seite 42

Methods and accelerators


Comprehensive detailed design for Robotics CoE

Development and deployment guides

Solution Framework for assessment and prioritisation of processes, benefit assessment, etc.

Defined road map

November 2016

Seite 43 5. Finance Performance Day

A) Das Thema Robotics ist noch neu für mich

B) Ich bin mit dem Thema Robotics vertraut

C) Ich habe ein gutes Verständnis zum Thema Robotics und denke über den Einsatz in meinem Unternehmen nach

D) Ich habe praktische Erfahrungen / Robotics ist bereits im Einsatz

Frage: Haben Sie sich bereits mit dem Thema Robotics im Accounting auseinandergesetzt?

November 2016


A) General Accounting

B) Performance and Management Reporting

C) Budgeting, Planning and Forecasting

D) Treasury

E) Keine von den genannten

Frage: In welchen Bereichen nutzten Sie bereits Robotics?

November 2016


A) Harmonisierung der Anforderungen im Unternehmen (z.B. einheitliche IT-Strukturen, standardisierte Prozesse etc.)

B) Durchführbarkeit für den Ausbau von Robotics

C) Kosten für die Umsetzung / den Ausbau von Robotics

D) Know How für Umsetzung / den Ausbau von Robotics

E) Eine andere Herausforderung

Frage: Wo sehen Sie die größten Herausforderungen für den weiteren Ausbau von Robotics?

November 2016


A) Shared Services sind die geeignete Organisationsform für Managementprozesse auch bei weitreichender Automatisierung

B) Bei weitreichender Automatisierung fallen viele transaktionale Tätigkeiten weg, so dass eine dezentrale Organisation geeigneter ist

C) Auch bei weitreichender Automatisierung muss Prozesswissen global gebündelt werden. Shared Services sind dazu am besten geeignet

Frage: Glauben Sie man benötigt noch ein SSC bei einem weitreichenden Ansatz von Robotics?

November 2016


A) Bei uns gibt es bereits Ansätze SSC zurückzuholen und durch Robotics zu ersetzen

B) Wir sind in der Überlegung SCC zurückzuholen und durch Robotics zu ersetzen

C) Nein, wir haben darüber noch nicht nachgedacht

Frage: Gibt es Ansätze Shared Services zurückzufahren und durch Robotics zu ersetzen?

November 2016

Seite 48

Agenda

Einführung 09:30



10:45

11:45

Schlusswort 12:45


Pause


Pause

12:00


Seite 49

Agenda

Einführung 09:30



10:45

11:45

Schlusswort 12:45


Pause


Pause

12:00


Seite 50

Disclaimer & My Background

McDonald’s global revenue VS.

Value of U.S. exports of non-edible fishery product


Seite 51

Digital is the mega-trend of our time, but the explosive growth and impact has barely begun

Digital trends impacting Finance

Finance

Big data

Value-driven analytics

3D-printing

Internet of things

► Much less BI required; significantly simplified IT architecture

► Self-service fruition► Line-item detail available

in real time

► Finance systems need to be able to capture and process data from a variety of IoT sources

► Analytics will enable new insights into performance, with predictive capabilities

► Analytics will require other skills and finance roles than today

► 3D printing will enable local “production” of goods that still need to be controlled end-to-end

► Tax and duty questions also arise

Cloud computing / mobile apps

Cyber security

► Mobile payment will be the norm; Finance systems need to be able to capture payments from all sources

► Blockchain will enable peer to peer financial transactions

► Cloud and mobile will be the norm

► Stronger process and system standardization required

► Cyber security will become a board agenda topic

► RPA and AI will significantly reduce the number of finance resources requiredRobotics / AI

Mobile payments / Blockchain

1

2

3

4

5

8

6

7


Seite 52

It’s no longer a debate… analytics excellence drives significant economic returns and competitive advantage

*Source: Economic Intelligence Unit. Survey conducted with 530 senior executive across industries (Feb 2013)

77% companies ‘good’ with analytics are also ahead in YOY growth compared to peers

None None

Substantially ahead

Somewhat ahead

On par

Somewhat behind

Substantially behind

23%

49%

28%

2010

2011

2012

37%58%

67%67% companies gained a significant competitive advantagefrom using analytics (15% increase from last year and 80% increase from two years ago)

*Source: MIT Sloan Management Review Survey conducted with more than 2500 executives across industries (Mar 2013)

Financial performance of companies ‘good’ with analytics

% of companies indicating a competitive advantage with Analytics


Seite 53

CFOs are facing new and diverse challenges … and analytics can help drive tangible business value

Three-year change in EBITDA

A recent survey1 of 652 CFOs finds that the use of data and analytics is associated with improved financial performance -- companies who give analytics a very high priority have had higher EBITDA growth over the past three years

1 “Partnering for Performance, Part 3: the CFO and the CIO”, EY 2015


Seite 54

Essentially, Data Analytics helps on five different kind of questions

Is this A or B?

Is this weird?Hoch much – or –How many?

How is this organized?What should I do next?

Each one of these questions is answered by a separate family of machine learning methods, called algorithms.

Monday Tuesday Wednesday Thursday

18° C

?24° C22° C


Seite 55

Claude Monet Vincent Van Gogh


Experience how machine learning works

November 2016

Seite 56

Claude MonetVincent Van Gogh


Who is the painter?

November 2016

Seite 57

Claude Monet Vincent Van Gogh


Who is the painter?

November 2016

Seite 58

Vincent Van Gogh


Who is the painter?

November 2016

Seite 59

1 + 4 = 5

2 + 5 = 12

3 + 6 = 21

8 + 11 = ?


Choices:

A) 40

B) 19

C) 96

D) Another number

Pattern Detection – Which alternative is correct?

November 2016

Seite 60

1 + 1 * 4 = 5

2 + 2 * 5 = 12

3 + 3 * 6 = 21

8 + 8 * 11 = 96

1 + 4 = 5

2 + 5 + 5 = 12

3 + 6 + 12 = 21

8 + 11 + 21 = 40


Pattern Detection

November 2016

Seite 61

Applying Data Analytics…starts with Business QuestionAvoid the “Wikipedia Approach"

• Identify the appropriate mathematical algorithms to help uncover patterns within the data

• Compare the results and insights from these alternative techniques

• Choose the most effective visualization technique to convey the key communication topics

• Translate the results back to the business problem

• Infer actionable insights• Take action, inform decisions• Measure results and initiate iterative

improvement, extensions and continuous monitoring of efficiency

• Prioritize the data needed• Identify the relevant and available data

sources• Analyze possible gaps (i.e. missing

important data) and identify possible alternative sources

• Assess the data quality• Prepare, consolidate and set-up the data

• Understand the problem • Address it in a way that it becomes clear

which insights needs to be discovered• Formulate the corresponding business

questions

finance problem domain knowledgeBusiness Analysts with industry knowledge and

finance problem domain knowledge ProfessionalsData Manipulation, Management and Governance

Professionals

Support organisation (CIO)Business Stakeholders and Analysts, Analytics

Support organisation (CIO) Scientists) Data Modelers, Mathematicians, Statisticians (Data

Scientists)

Framing the Business Problem

Taking Action & Measurement Analytics & Visualisation

Information Collection


Seite 62

Finance Performance & Management Reporting

Procure to Pay

General Accounting

Financial & External Reporting

Budgeting, Planning & Forecasting

Operational Accounting

Policy, Controls, Governance & Compliance

Internal Audit

Treasury

Capital Management & Investment

Tax Planning & Accounting

Investor Relations

Get a deep understanding of the business and its dynamics to serve the business better

OperationsCustomerFinancials

► `

People Social EnvironmentBrand

Data Analytics

BIG DATA & ANALYTICSIT - TECHNOLOGIES


Seite 63

► Determining the most critical KPIs that drive performance, to allow leadership to focus on the measures that matter

► Integrating operational, market and financial data to create forward-looking business insights

► Changing the way financial information is consumed, using visualization and interactive dashboards with the ability to “drill down” into root causes

► Identifying levers to improve operational efficiency of core finance shared services activities (reducing T&E spend, improving efficiency of A/R and A/P, etc.)

► Improving the speed and agility of the financial close, resulting in more time to analyze results and provide insights

► Uncovering control, non-compliance and fraud issues

► Using analytics to identify the key drivers for driver-based planning

► Predictive modelling to better forecast EPS and support scenario planning

► Enhancing the planning/forecast process by automating certain parts of the plan

► Enhancing analytical capabilities to draw insights critical to the CFO agenda: (liquidity planning, developing pricing strategies, improving working capital, managing indirect expenses, reducing accounts receivable, etc.)

► Enabling data-driven decisions, instead of relying on instinct and gut-feel

Finance organizations are using analytics in four main ways to become better business partners

Decision support

Financial planning and forecasting

Finance operational

improvements

Management reporting and visualization

Business value


Seite 64

Some illustrative examples of Finance Analytics


Seite 65

Example of decision support:Analytics to generate insights on pricing

Year Sales type Price Sales Volume B/E vol. growth

2012 Baseline $5 $100 20 N/A

2013 Constant sales =

$4 $100 25 25% increase

2013 Trend in sales

$4 $120 30 50% increase

Break-even targets:

Resulting in assessment of a good or bad pricing decision

Performance summary by country and productCompare metrics prior to and after a pricing change Compare to actual volume growth

Interactive, low-maintenance solutionBusiness issues

► Desire to increase earnings through improved pricing

► Addressing significant revenue erosion due to sub-optimal pricing decisions

Analytics approach

► Supplementing internal data with external data such as market share, industry growth and competitor response to build a more holistic model of pricing impacts

► Developing a retrospective spotfire dashboard to assess past pricing decisions

► Developing a prospective analysis spotfire dashboard to analyze break-even targets depending on sales forecasts and price erosion

Value unlocked

► Greater insights into the impacts of historical pricing actions

► Data-driven and systematic pricing decisions► Reduced unnecessary price erosion► Increased productivity and efficiency of pricing

approval process


Seite 66

Example of decision support:Analytics to improve collections and generate better cash flow

Identified top 10 customers who were consistently making payments 30 days after due date

Identified customers that are consistently 90 days delinquent

Analyzed customer payment behavior by segment

Business issues

► Ability to identify valuable customers with significant outstanding amount and past due balances

► Ability to identify recurring customers with late payments

Analytics approach

► Developing a series of customer delinquency dashboards to analyze trends in payment timeliness and delinquency by segment

► Recommending a targeted outbound collections approach, tailored to customers based on size and payment behavior to improve payment performance

► Identifying opportunities to renegotiate to net-45 day payment terms for top 10 customers

Value unlocked

► Identified $3.4m cash flow improvement opportunity when net terms where negotiated to 45 days

► $362k investment income gain opportunity from freed up cash flow


Seite 67

Upon review with the business, it was found the forecast had been adjusted to align to goals, but it was unrealistic the business would obtain them

Internal and external data were incorporated into a statistical model to identify key drivers

Business issues

► Improving the forecasting process► Understanding the underlying trajectory of

financial performance, independent of management interventions

Analytics approach

► Identifying data sources containing drivers with an external view of the organization vs. purely internal drivers and data points

► Analysing the historical relationships of these drivers on financial performance

► Developing pure mathematical/statistical models to predict performance in tableau

► Building an interactive dashboard for rapid scenario planning in tableau

Value unlocked

► Provided executive leadership greater visibility into the true financial performance of the company, isolating the inherent biases in management-driven forecasts

► Enabled leadership to rapidly perform scenario planning, focusing on the most critical drivers of performance

Revenue

Marketanalysis

Naturalevents

DisruptionsProductportfolio

Pipeline

Healthcarespending

Macroeconomics

► Pharma growth► Generic penetration► Competitor

performance ► Inflation► Tax rates► FX rates► Economic decline► Demographics► Urbanization

► Govt. spending► Affordable care act► Acute care

hospitalization► Discharge rates

► Clinical trials► FDA approvals/delays► Published clinical

findings

► Product lifecycle► Blockbuster trend► Pending loss of

exclusivity

► Adverse reimbursement decisions► Black box warnings

► Weather► Natural disaster

Interactive dashboards enable rapid adjustments to the model assumptions, useful for scenario planning

Example of improved planning/forecasting:Predictive analytics to enhance financial planning and forecasting


Seite 68

Example of management reporting/visualization:Finance dashboards to help understand drivers of business performance

Business issues

► Enhancing FP&A as part of a broader finance transformation

► Desire for greater insights into performance by multiple metrics with the ability to drill down to answer critical business questions

Analytics approach

► Stakeholder involvement from central and regional finance, and business – common metrics/KPIs and performance language

► Interactive dashboards, designed for different users, with KPIs linked to drivers:► Executive view : Consumed by C- suite, with

the ability to drill down and switch between variance to budget/forecast

► Drill-down view for regional leadership to analyze country and brand level drivers

► Scalable, secure and reliable platform

Value unlocked

► Consistent and highly insightful views used by executive leadership to run monthly operational reviews

► Common metrics/KPI’s gauged to review performance both at consolidated ,regional and country level metrics

► increased decision support from local teams and reduced transactional activities

Role-based dashboards with analytics paths, metrics and levels of detail appropriate for each user type.

Interactive Country P&Ls and other views with filters, drill-down capabilities and link to drivers


Seite 69

Example of management reporting/visualization:Finance dashboards to help manage indirect costs

Business issues

► A [???] seeking to get better visibility into indirect spend, and identify opportunities to reduce spend

Analytics approach

► Separate excel files automatically consolidated into a database using macro enabled excel tool feeding new Tableau solution

► Charge in/ Charge out processes automated through rule based logic

► Tableau reporting solution functionality designed to deliver dynamic variance analytics with dimensional drill down capabilities

► Consolidated inputs from 22+ different data sources and centralized 12+ mapping files to enable drill down analysis

Value unlocked

► Enabled finance team to focus on value added analytics and develop skillsets while reducing time on data reconciliation efforts

► Summary dashboard providing aggregated view of trends in indirect spend (~$500M)

► Automated business logic for adjustments and exception handling process

Fully integrated “one stop shop” dashboard enabling visibility and reporting across functions, depicting trends and enabling further root cause analysis

Summary dashboard for Indirect Expenses

P&L drill-down

YoY spend variance by type and function, and dynamic P&L view


Seite 70

Example of finance operational improvements:Analytics to drive improvements in the Record to Report (R2R) process

Business issues

► Inefficiencies in the close process, resulting in delayed results and inaccurate information

► Desire to shorten the close cycles, to allow for more time spent analyzing results

► Desired outcome of being materially correct vs. precisely accurate

Analytics approach

► Focus on analyzing key drivers of manual effort during R2R process, to quickly identify areas of improvements and drive actionable outcomes

► Build analytics to analyze high volumes of manual journal entries (a key symptom of a sub optimal close process)

► Interactive dashboards to drill down and explore data, outliers and trends

Value unlocked

► Shorter close cycles and more efficient R2R means more time to spend analyzing results, providing insights and serving as a trusted business partner

► Drill down capability (data joined and mapped to enable interactive dashboard experience across materiality, volume, location, etc.)

► Embedded rules and logic can flag exceptions in the data, highlighting inconsistencies enhancing controls and reducing risk of manual errors

Journal Entry Summary(dynamic materiality analysis, monthly trends by workday, JE category types and preparers

Journal Entry Geographic View (performance management across regions, measure effectiveness of various locations)

Budget Center/GL Summary(low dollar budget centers, dimensional drill down capability, JE-budget center root cause analysis)


Seite 71

Example of finance operational improvements:Finance shared services tracking payment discrepancies resulting from invoicing and payment inaccuracies

Waterfall connecting multiple data sources

Trending by payment discrepancy type

Comparison data to better understand regional and business unit differences

Business issues

► Inability to track a single document from order to invoice to payment to adjustment

► Lack of management visibility into tracking and root cause analysis of payment discrepancies

► ~50% of global payments result in discrepancies

Analytics approach

► Designed and developed a Tableau visualization dashboard, with different views designed to drill down on region, business, discrepancy type, discrepancy sub-type, etc.

► Combined three disparate groups of data to help drive root cause analysis on reason for payment discrepancy

► Train the client for direct use of the tool and resulting analysis of the data

Value unlocked

► First time the business and process owners were able to see how the data cascaded from payment discrepancy to dispute case to sales adjustment

► Supported the business case to reduce payment discrepancies globally by 27% (or a 67% reduction for the target focus)


Seite 72

Enabling and foundational capabilitiesPeople

Acquire the right people with analytics focus, multi-disciplinary skillset. Invest in building capabilities in data science, math,and financial modelling.

Tools

Adopt the right analytical toolset for data mining,integration, modelling and visualization. Standardize at the enterprise level

Data Governance

Make data a fourth pillar of the business, and leverage it as an asset. Improve data quality programs and governance policies and standards to build confidence and reliability

Culture

Analytics requires a cultural shift in mindset and ways of working across the organization to embed data driven decision making in a repeatable, systematic way


To make analytics sustainable, finance needs to consider people, technology, data governance and culture

November 2016

Seite 73

The current level of analytics maturity for the enterprise overall will help guide how finance begins its journey

Emerging Developed Advanced

Data/TechnologyBU-level data, data management not a key priority, poor data governance

Enterprise deployment of analytical tools; master data management initiatives underway

Relentless pursuit of new data and metrics. Data viewed as strategic asset

People Pockets of analytics talent but not pervasive

Senior leaders recognize the importance of analytics and developing analytic capabilities

Strong leaders behaving analytically and showing passion for analytical competition

InitiativesDisparate initiatives, not all of strategic importance or prioritized

Value-generating initiatives prioritized and executed across the organization

Analytics integral to company strategy

Enterprise approach (governance)

Localized analytics, local value

Hybrid operating model to empower BUs with corporate coordinating and enabling key capabilities across

Analytics tools and infrastructure extended broadly and deeply across enterprise

How finance can start on analytics

Identify quick wins to demonstrate the value of analytics and build credibility; find partners in the business to collaborate on analytics initiatives

Identify high-value areas to generate analytics insights;leverage existing analytics resources and tools from across the organization

Use the organization’s focus on data and analytics as a mandate to invest in finance’s capabilities; consider how analytics can transform the finance organization and function

Analytics maturity of the broader organization


Seite 74

Agenda

Einführung 09:30



10:45

11:45

Schlusswort 12:45


Pause


Pause

12:00


Seite 75

Vorausschau: Termine für den 6. FPD (Frühjahr 2017)


Mittwoch, 26. April 2017EY Düsseldorf

Graf-Adolf-Platz 1540213 Düsseldorf

Dienstag, 9. Mai 2017EY Stuttgart

Flughafenstraße 6170629 Stuttgart

Mittwoch, 17. Mai 2017EY Frankfurt

Mergenthalerallee 3–565760 Frankfurt am Main

November 2016

Seite 76

Agenda

Einführung 09:30



10:45

11:45

Schlusswort 12:45


Pause


Pause

12:00


Date post:	13-Mar-2018
Category:	Documents
Upload:	lephuc
View:	220 times
Download:	4 times

5. Finance Performance Days - EY · PDF file5. Finance Performance Days ... Investment...

Documents