FESA Consolidation Series

Website: http://www.fesa-s.com Email: [email protected] Last update: 28-Jan-2014

Solving AVESTA Computing Issues

FESA Consolidation Series

Collection

Storage

Reporting Standardization

Tagging

Financial Management


Analytical Performance Management

Group Consolidation

Budgeting & Rolling Forecast

Your Reporting Issues

Your Recording Issues Financial Management

Transformation

Our Reporting Framework

Our Recording Framework

Our Reporting Solutions

FESA Query FESA Analyst

FESA Planning FESA Consol

Our Recording Solutions

AVESTA Finance

Computing Solutions FESA

AVESTA Aim At Achieving Advanced Accounting Automation At Anywhere

Efficient multi-dimensional aggregation and elimination processes integrated with versioning for audit trial and reporting purposes

Moving ahead with advanced automation through standardization and tagging for massive volume of heterogeneous data

Achieving ultimate automation with alerts that empower your “analytical performance management at anywhere”

Phase 2

Phase 1

Phase 3

3 Progressive Phases of Implementation

Consolidation Aggregation

Basic Consolidation Definition

Elimination

Many Records (Rows) • Many Business Activities • Many Spreadsheets & Formats • Many Versions & Amendments • Many Dimensions

Many Dimensions (Columns) • Many Scenarios / Assumptions • Many Companies • Many Business Units • Many Locations / Branches • Many Periods

Basic Consolidation Computing Issues

Aggregation

On-line Aggregation Results

Aggregation


Aggregation


Aggregation

How to configure query report?


Aggregation


Aggregation


Aggregation


Aggregation

Liability Life Cycle Management

Budgeted

Liabilities • Approved Budget

Utilizing

Budgeted

Liabilities

• Approved Purchase Requisitions

Committed

Liabilities • Signed Purchase Orders

Incurred

Liabilities • Received Goods or Rendered Services

Invoiced

Liabilities • Received Invoices

Confirmed

Liabilities • Confirmed Contracting Parties

Settled

Liabilities • Registered Evidences

1

2

3

4

5

6 7

Aggregation

Budgeted Liabilities

Utilizing Budgeted Liabilities

Committed Liabilities

Incurred Liabilities

Invoiced Liabilities

Confirmed Liabilities

Settled Liabilities

Analyzed by consolidation group, legal entity & business unit

Analyzed by date, expense and liability nature, department & project

Analyzed by contracting party & relationship

Analyzed by contracting currency

Analyzed by aging (incur & due date)

Analyzed by settlement type

Contr

acti

ng P

art

ies

7 Stages with Different Dimensions


Aggregation


• Matching of Debits & Credits of A/C Hist. • Netting of Related Accounts for Settlement • Hedging to Offset Potential Losses/Gains

Group Consolidation & Budgeting (Consolidated Financial Statements) • Reversal of Inter-Co Sales & Purchases • Reversal of Inter-Co Due To/Due From • Reversal of Investment in Subsidiaries • Reversal of Unrealized Profits / Losses

Financial Management (Procure to Pay, Order to Cash, Treasury)

Elimination Elimination Aggregation


• Consolidated inventory is one of the key problem

areas

Elimination for different measures • Quantity (for different unit code)

• Amount (for different reporting currencies)

Elimination for unrealized profits / (losses)



Key problems encountered by headquarters

• Duplication of works of elim for every report • Is not easy to eliminate for all relevant dimensions • Inconsistence amongst different reports trigger

extra effort for reconciliation


Dynamic Elimination Management

Elimination

Supports Query Formula


Elimination Aggregation

Additional Consolidation Computing Issues

• Version control for audit trial purpose

• Version control for reporting purpose

Two types of computing issues


Versioning

Two types of version control • Version control for audit trial purpose

• Version control for reporting purpose

Key problems encountered by headquarters • Manually assign version number of file and folder name

Problem to support multi-user enquiry Issue of security control Not easy to maintain completeness

• Implement standalone document management system

Can keep every version of data file upload itself rather than post and store relevant raw data within database

It cannot support to automate aggregation, so it cannot support the retrieval of particular version of consolidated rolling forecast


Version Control for Audit Trial


Versioning

Version Control for Reporting


Versioning


&

Demonstration

Improving Planning Process Management

Advanced

Reporting

Aggregation

Recording Issues

Versioning

Elimination

Phase 1 AVESTA

AVESTA Aim at Achieving Advanced Accounting Automation at Anywhere on Phase by Phase Basis


Planning Process Management

Planning Process Management

Additional Consolidation Computing Issues Additional Consolidation Computing Issues

&

Recording Issues

Versioning

Elimination

Phase 1 AVESTA



Reporting Issues

Aggregation

Advanced Consolidation Computing Issues

Versioning

Progressive Automation of Advanced Recording to Reporting

Rolling Forecast


&

Group Consolidation

Phase 2 AVESTA

Recording Issues

Versioning Standardization Tagging

Elimination

Phase 1 AVESTA

Financial Management & Group Consolidation



Reporting Issues

Aggregation

HK US Taiwan Europe Macau PRC Russia Brazil India

Conglomerate Group

Logistics Insurance Property

Development Investment Management

Hotel Retail

HR Finance Admin Marketing Procure IT

Multi-location, Multi-dept & Multi-business

Manipulation of massive volumes of heterogeneous data which originates from the combination of different dimensions eg multi-company, multi-company-group, multi-headquarter, multi-department, multi-business-unit, multi-budget-owner, multi-location, multi-currency, multi-project, multi-period, multi-system. Objectives of reporting

• Internal reporting and/or external reporting • Operational management and/or strategic management

Natures of data source • Past, present and/or futures • Transaction, voucher, trial balance and/or pivot table like reports • SQL and/or NoSQL (e.g. spreadsheet is an example of NoSQL)

Assumptions of accounting practices

• Tax, financial and/or management accounting • IFRS, PRC GAAP, HK GAAP, Japan GAAP, US GAAP etc


x

BI.BPM

ERP.POS.CRM

Are you feeling that x software is most relevant for your computing works despite it have been triggering AVESTA

computing issues?


Are you working on a mainly paperless environment relying heavily on manual

intervention or any other scenario?


Paper Based Paperless

Manual

Automation x

BI.BPM

ERP.POS.CRM

Dr Cr Dr Dr Cr Cr

500-Year Evolution of the Accounting Model

+ - Standardization

- Dr Cr Dr Dr Cr Cr

500-Year Evolution of the Accounting Model

+ Account Doc Num Currency Amount

Cash I012345 HKD 200

Sales I012345 HKD -200

Invoice Number

Currency Sales Value

Discount Currency Cash Receipt

I012345 HKD 200 0 HKD 200

This system fail to follow the accounting model

Standardization

Measurement scenarios transactional, functional, presentation currencies/amounts & varying

types of units and associated quantities Explosive number of taggable dimensions e.g. document date, document number, due date, company, project,

department, branch, contracting party, movement type Elimination of matched debit and credit entries for different kinds of asset, liability and equity accounts Generating micro accounting entries based on assumptions

based on a set of assumptions and/or transactions for group consolidation and budgeting purposes.

Account Analysis 1 … Analysis n Doc Num Currency Amount

Cash I012345 HKD 200

Sales I012345 HKD -200

Key standardization issues • Differing transaction and reporting currencies • Differing account codes and other dimensional codes • Differing units of measurements • Differing accounting policies and practices • Differing accounting systems • Differing year end dates

Differing accounting policies and practice

• Differing measurement and recognition rules Allocation, amortization, depreciation

• Differing disclosure and presentation rules IAS 24 Related-parties disclosures IFRS 7 Financial instruments disclosures IFRS 8 Operating segments disclosures

Differing accounting systems

• Differing design of account code e.g. very long account code • Differing database e.g. SQL and NoSQL • Posted vouchers can or cannot be amended


Standardization

Tagging of transactions base on user-defined characteristics • CRM is heavily implemented on tagging of sales data such as income group,

age group, nationality, gender etc. • any specific key words included in transactions can be tagged as pre-

defined analysis code attributed to specific dimensions.

Tagging of every changes in master records

• Change in legal & management group structure • Change in % of shareholdings • Change in allocation ratios and amortization periods • Change in product list prices and discount rates


Tagging

Match Data Source Return User-defined Value

Dynamic Lookup Management

Tagging

Return User-defined Value Match Data Source


Supports Query Formula & Supports Partial Word Matching

Standardization

Tagging

Return User-defined Value Match Data Source


Supports Multi-User with Access Control & Version Control


Versioning Tagging

Elimination

Progressive Automation of Advanced Recording to Reporting

Budget Planning

Rolling Forecast

&


&

Group Consolidation

Phase 2 AVESTA

Recording Issues


Elimination

Phase 1 AVESTA




Reporting Issues

Aggregation

Ultimate Consolidation Computing Issues

Analytical & Actionable Performance Management

& &

Phase 2 AVESTA

Recording Issues


Elimination

Reporting Issues

Phase 1 AVESTA




Phase 3 AVESTA

Alert


Aggregation

CEO

CFO

Finance

Head

Manager

Supervisor

Manager

Supervisor

HR

Head

Manager

Supervisor

Company

Secretary

Manager

Supervisor

CIO

IT

Head

Manager

Supervisor

COO

BU

Head

Manager

Supervisor

BU

Head

Manager

Supervisor

Measure and Monitor Trigger Points of Alert Manually


There are two different kinds of alerts • Process management alert • Analytical alert

Process management alert

• Uploaded, Validated, Void, Fail, Completed, Restored


There are two different kinds of alerts • Process management alert • Analytical alert

Process management alert

• Uploaded, Validated, Void, Fail, Completed, Restored

Analytical alert similar to continuing monitoring • Inventory turnover ratio for any product class above the predefined

value • Sales performance any salesman is below pre-defined level for over 3

measurement periods • Total for consolidated fixed assets do not reconcile with its

movements


Selection Criteria 1,2,3,…n

Membership (X-Templates)

By Gender Group

By Age Group

By Member Grade

By Nationality


FESA Application Server

Data Sources

Collection Transformation Storage Reporting

Outputs

Processing Rules

Reporting Recording to Reporting

Query Formulas

System Control

Collection

Transformation

Storage

Reporting

Recording

Rule Processor Query Processor

User Interface

System Control

Master Settings

Finance Computing Framework

Collection Transformation Storage Reporting

FESA Application Server

Collection

System Control

Versioning

Aggregation

Versioning

Elimination

Elimination

Elimination

Versioning

Standardization

System

Configurations

Aggregation Versioning

Elimination

Standardization

Tagging

Alert

Transformation Storage Reporting AVESTA

Requirements

Rule Processor Query Processor

The six modules work together can reduce the multiway data from widerway down to more focusway that can be digested by different user groups.

Multiway Example

One-way data • Line graph of monthly consolidated net income – IFRS

Two-way data • An executive dashboard including different time-series KPIs • Consolidated P&L (Actual cf Budget) by business units • Full set of standardized voucher list for a group of companies

Three-way data • Full set of consolidated financial statements • Full set of sales transaction list, purchase transaction list,

inventory list, payroll transaction, fixed assets list etc

Fourth-way data • SQL and NoSQL (e.g. Spreadsheets) managed by a headquarter

Fifth-way data • Different SQLs and NoSQLs (e.g. Spreadsheets) managed by regional offices

Transforming Multiway Data for Reporting

Processing Rules

Processing

Rules

Windows Single Sheet SQL

Supports Different Types of Data Sources

Internal

Data

Storage

External

Data

Storage

NoSQL Multi-sheet Excel

Supports Different Types of Data Collection Methods

Existing Data Store

User-defined Data Entry Forms

Existing Data File

Collecting Transaction Detail and/or Aggregated Information

Collecting Structured Data and/or Unstructured Data

Web

Mobile

Query Formulas

Alert

Tagging

Standardization

Elimination

Versioning

Aggregation

Recording Reporting

An Evaluation Form

Software

FESA Consolidation Series