1. Solving Issues Arising from AVESTA Computing FESA Consolidation Website: www.fesaconsol.com Email: avesta@flexsystem.com Telephone: (852) 3524 0500 Last Update: 19-Dec-2013

2. About FlexSystem FlexSystemFlexSystem is a recognized leader in enterprise management software industry in the Greater China region. Over the past 26 years, FlexSystem has been delivering high quality application software and services to maximize the client's operational efficiency in the accounting, order processing, payroll and human resources, manufacturing, workflow and business management. FlexSystem In recent years, FlexSystem has been investing a dedicated R&D, consulting and support team to implement the advanced automation of Group Consolidation and Budgeting for sizable organizations. They have achieved significant success in software industrialization – no longer to rely on “Programming”, but unleash the power of software configuration to deliver customization of systems address to specific requirements of different user groups very efficiently. Besides our staff are enriching their practical experiences, they are also participating to conduct various researches from time to time. This documentation summarize our insights of computing issues deriving from the works of Group Consolidation and Budgeting. This can be your next agenda solving computing issues relevant for your organization.

3. Group Consolidation & Budgeting The works of Group Consolidation & Budgeting are usually involving manipulation of massive volume of heterogeneous data derived from any combination of 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 and further complicated by the following scenarios:  Objectives of reporting Commercial organization and/or non-profit organization Commercial organization and/or non-profit organization Listed group and/or private group Listed group and/or private group Operational management and/or strategic management Operational management and/or strategic management Internal reporting and/or external reporting Internal reporting and/or external reporting  Natures of data source Past, present and/or plan/predict futures Past, present and/or plan/predict futures Transaction, voucher, trial balance and/or pivot table like report Transaction, voucher, trial balance and/or pivot table like report On-balance-sheet, off-balance-sheet and/or post-balance-sheet On-balance-sheet, off-balance-sheet and/or post-balance-sheet Financial and/or non-financial Financial and/or non-financial Numerical and/or non-numerical Numerical and/or non-numerical SQL and/or NoSQL (e.g. spreadsheet is an example of NoSQL) SQL and/or NoSQL (e.g. spreadsheet is an example of NoSQL)  Assumptions of accounting practices Tax accounting, financial accounting and/or management accounting Tax accounting, financial accounting and/or management accounting Accrued accounting, cash accounting and/or fund accounting Accrued accounting, cash accounting and/or fund accounting IFRS, PRC GAAP, HK GAAP, Japan GAAP, US GAAP etc IFRS, PRC GAAP, HK GAAP, Japan GAAP, US GAAP etc

4. A Review of Your Systems n BI.BPM ERP.POS.CRM Are you feeling that n software is most relevant for your works of consolidation and budgeting despite it have been triggering AVESTA computing issues?

5. Group Consolidation & Budgeting Computing issues you are usually encountered despite your organization had heavily invested on computerization. This may due to the following reasons:  Diffusion of unexpected users’ expectation across your organization Demanding from computerization to advanced automation Demanding from computerization to advanced automation Relying on exporting raw data from computerized systems to spreadsheets for further data manipulation is no longer be acceptable for several reasons Relying on exporting raw data from computerized systems to spreadsheets for further data manipulation is no longer be acceptable for several reasons  Active group restructuring as resulting from acquisition and disposal Diminishing returns on investment in standardization of business practices and systems across the dynamic group structure Diminishing returns on investment in standardization of business practices and systems across the dynamic group structure  Implemented systems are mainly function as input and storage devices It is far from minimizing human involvement of data manipulation across all phases of computing It is far from minimizing human involvement of data manipulation across all phases of computing Senior staff spends most of their time on tedious data processing works Senior staff spends most of their time on tedious data processing works  Implemented systems cannot adapt change of external environments Reluctant to incur high cost to maintain continuing modification of existing systems when it is triggered diminishing returns on investment Reluctant to incur high cost to maintain continuing modification of existing systems when it is triggered diminishing returns on investment

6. The Existence of Multiway Data Writing Wikipedia Article: Multiway Data Analysis Writing Wikipedia Article: Multiway Data AnalysisMultiwayExample One-way data Line graph of monthly consolidated net income – IFRS Line graph of monthly consolidated net income – IFRS Two-way data An executive dashboard including different time-series KPIs An executive dashboard including different time-series KPIs Consolidated P&L (Actual cf Budget) by business units Consolidated P&L (Actual cf Budget) by business units Full set of standardized voucher list for a group of companies Full set of standardized voucher list for a group of companies Three-way data Full set of consolidated financial statements Full set of consolidated financial statements Full set of sales transaction list, purchase transaction list, inventory list, payroll transaction, fixed assets list etc Full set of sales transaction list, purchase transaction list, inventory list, payroll transaction, fixed assets list etc Fourth-way data SQL and NoSQL managed by a headquarter SQL and NoSQL managed by a headquarter Fifth-way data Different SQLs and NoSQLs managed by regional offices Different SQLs and NoSQLs managed by regional offices Multiway data analysis is attributed to any multiway model that can facilitate analyzing large heterogeneous data set. The ultimate goal is to reduce the multiway data from widerway down to more focusway that can be digested by different user groups.

7. 3 Progressive Phases of Automation Efficient multi- dimensional aggregation and elimination integrated with versioning for audit trial and reporting purposes Moving ahead to advanced automation of standardization and tagging for massive volume of heterogeneous data Achieving ultimate automation of alert that empower your analytical performance management at anywhere Phase 1 Phase 2 Phase 3

8. A lert T agging S tandardization E limination V ersioning A ggregation Domain Specific Model Model Determination Basis  Based on our experiences and researches, our multiway model establishment is determined on a principal of separate of concerns  The primary objective is to support simplifying the process to reduce the multiway data (i.e. heterogeneous data) from widerway down to more focusway that can be digested by different user groups based on objectives of reporting and assumptions of accounting practices Six Aspects of Our Multiway Model

9. Level 6: A lert Level 5: T agging Level 4: S tandardization Level 3: E limination Level 2: V ersioning Level 1: A ggregation Six Levels of Advanced Automation

10. Level 6: A lert Level 5: T agging Level 4: S tandardization Level 3: E limination Level 2: V ersioning Level 1: A ggregation Solving Your AVESTA Computing Issues

11. Aggregation Computing Issues  Simplex form of aggregation 1 + 1 = 2 1 + 1 = 2  Most common aggregation functions Sum(), Count (), Max(), Min() Sum(), Count (), Max(), Min()  Assumptions (Based on standardized data source) Measurement and recognition rules Measurement and recognition rules Chart of accounts Chart of accounts Reporting currencies Reporting currencies Data file formats Data file formats Presentations of transactions or trial balances Presentations of transactions or trial balances  Example Each company of a consolidation group furnishes standardized transactions, vouchers or trial balances to their headquarters for aggregation in order to prepare different kinds of summary reports (i.e. aggregation scenarios) Each company of a consolidation group furnishes standardized transactions, vouchers or trial balances to their headquarters for aggregation in order to prepare different kinds of summary reports (i.e. aggregation scenarios)

12. Aggregation Computing Issues  Key problems encountered by headquarters Issues of unexpected speed and accuracy when Issues of unexpected speed and accuracy when Many data files Many data files Many rows and many columns for each data file Many rows and many columns for each data file Following are examples of column name: Following are examples of column name: Many amendments of data files Many amendments of data files Identifying missing and duplication of data files Identifying missing and duplication of data files Frequent reporting, from monthly to weekly to daily to… Frequent reporting, from monthly to weekly to daily to… Issues of security control Issues of security control Send data through email system to wrong recipients Send data through email system to wrong recipients Ledger code Voucher date A/C period Account code Business unit DepartmentProjectBranch Currency code Org amount Exchange rate Eqv amount Quantity Unit code Unit price Particulars

13. Aggregation Computing Issues  Aggregation scenarios Scenario 1: Aggregation for strategic management Scenario 1: Aggregation for strategic management Five-year budget planning with multi-scenario analysis Five-year budget planning with multi-scenario analysis Acquisition and disposal decisions Acquisition and disposal decisions – Capital asset, legal entity, branch, product line Scenario 2: Aggregation for operational management Scenario 2: Aggregation for operational management YTD actual profit and loss by business unit by month YTD actual profit and loss by business unit by month Monthly forecast by business unit by department Monthly forecast by business unit by department Actual cf budget scenarios cf rolling forecast versions Actual cf budget scenarios cf rolling forecast versions Sale-thru analysis by different dimensions Sale-thru analysis by different dimensions Scenario 3: Aggregation for statutory compliance Scenario 3: Aggregation for statutory compliance YTD actual consolidated trial balance by company by the following GAAPs: YTD actual consolidated trial balance by company by the following GAAPs: – PRC GAAP – US GAAP – HK GAAP – Japan GAAP

14. Aggregation Computing Issues  An example of dynamic on-line aggregation summary

15. Aggregation Computing Issues  An example of dynamic on-line aggregation breakdown

18. Aggregation Innovation Introduction www.fesaconsol.com/fionbrick.pdf Demo Video www.fesaconsol.com/fionbrick.mp4FionBrick

19. FionBrick

20. Dashboard Designer

21. Dashboard Viewer

22. Solving Computing Issues Arising from Multi-dimension Aggregation FESA Q uery www.fesaconsol.com/fesaquery.pdf

23. Versioning Computing Issues  Definition Versioning means version control over data processing and/or reporting based on same sets of assumptions Versioning means version control over data processing and/or reporting based on same sets of assumptions It shall be differentiated from aggregation scenarios It shall be differentiated from aggregation scenarios  Two types of version control Version control for audit trial purpose Version control for audit trial purpose Version control for reporting purpose Version control for reporting purpose  Version control for audit trial purpose Who, when, how about the submission of data files Who, when, how about the submission of data files Who, when, why about the subsequent amendments Who, when, why about the subsequent amendments Who, when, what about the authorization of data postings Who, when, what about the authorization of data postings About the status of process: pending, completed, fail About the status of process: pending, completed, fail  Version control for reporting purpose Q1, Q2, Q3, Q4 version of rolling forecast Q1, Q2, Q3, Q4 version of rolling forecast

24. Versioning Computing Issues  Key problems encountered by headquarters Manually assign version number of file and folder name Manually assign version number of file and folder name Problem to support multi-user enquiry Problem to support multi-user enquiry Not easy to maintain completeness Not easy to maintain completeness Issue of security control Issue of security control Implement standalone document management system Implement standalone document management system Can keep every version of data file upload itself rather than post and store relevant raw data within database 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 It cannot support to automate aggregation, so it cannot support the retrieval of particular version of consolidated rolling forecast

25. Versioning Computing Issues  An example of versioning for audit trial purpose

26. Versioning Computing Issues  An example of versioning for reporting purpose

27. Efficient Multi-dimensional Aggregation Collaborate with Version Control for Audit Trial and Reporting Purposes FESA P lanning www.fesaconsol.com/fesaplanning.pdf www.fesaconsol.com/fesaplanning.ppt x

28. Elimination Computing Issues  Duplication of data Assuming no duplication within each company/business unit Assuming no duplication within each company/business unit Duplication exist upon aggregation for a set of data Duplication exist upon aggregation for a set of data Across different legal entities Across different legal entities Across different business segments Across different business segments Across different geographical segments Across different geographical segments  Types of elimination adjustments Operating activities: Sales and purchases Operating activities: Sales and purchases Financing activities: Borrowings, repayments and settlements Financing activities: Borrowings, repayments and settlements Investing activities: Acquisition and disposal Investing activities: Acquisition and disposal  Elimination for unrealized profits / (losses) Consolidated inventory is one of the key problem area Consolidated inventory is one of the key problem area  Elimination for different measures Quantity (for different unit code) Quantity (for different unit code) Amount (for different reporting currencies) Amount (for different reporting currencies)

29. Elimination Computing Issues  Key problems encountered by headquarters Eliminating transactions manually Eliminating transactions manually Duplication of works for every report and reporting Duplication of works for every report and reporting Is not easy to eliminate for all relevant dimensions Is not easy to eliminate for all relevant dimensions Inconsistence amongst different reports trigger extra effort for reconciliation Inconsistence amongst different reports trigger extra effort for reconciliation Implementing traditional consolidation systems Implementing traditional consolidation systems It may demand for creating a huge volume of account codes on both regional and headquarters levels in order to support automation of elimination It may demand for creating a huge volume of account codes on both regional and headquarters levels in order to support automation of elimination

30.  An example of WYSIWYG elimination configuration Elimination Computing Issues

31. Standardization Computing Issues  Key standardization issues Differing transaction and reporting currencies Differing transaction and reporting currencies Differing account codes and other dimensional codes Differing account codes and other dimensional codes Differing units of measurements Differing units of measurements Differing accounting policies and practice Differing accounting policies and practice Differing accounting systems Differing accounting systems Differing year end dates Differing year end dates  Differing accounting policies and practice Differing measurement and recognition rules Differing measurement and recognition rules Allocation, amortization, depreciation Allocation, amortization, depreciation Differing disclosure and presentation rules Differing disclosure and presentation rules IAS 24 Related-parties disclosures IAS 24 Related-parties disclosures IFRS 7 Financial instruments disclosures IFRS 7 Financial instruments disclosures IFRS 8 Operating segments disclosures IFRS 8 Operating segments disclosures  Differing accounting systems Differing design of account code e.g. very long account code Differing design of account code e.g. very long account code Differing database e.g. SQL and NoSQL Differing database e.g. SQL and NoSQL Posted vouchers can or cannot be amended Posted vouchers can or cannot be amended

32. Standardization Computing Issues  Strategy of standardization is all depend your choices Re-do implementation of existing systems Re-do implementation of existing systems Acquire and implement new systems Acquire and implement new systems Instruct regional office to re-classify, re-measure and re-input data on a set of standardize entry forms that follow accounting policies and practice for the purpose of consolidation Instruct regional office to re-classify, re-measure and re-input data on a set of standardize entry forms that follow accounting policies and practice for the purpose of consolidation Implement automation of standardization for every data file submission by regional offices Implement automation of standardization for every data file submission by regional offices Involve initial setting up of mapping tables Involve initial setting up of mapping tables Involve subsequent updating of mapping tables Involve subsequent updating of mapping tables  Uncontrollable areas of standardization Differing convertibility of currencies Differing convertibility of currencies Maturity of financial assets Maturity of financial assets Differing sovereign credit ratings Differing sovereign credit ratings Fair value of financial assets Fair value of financial assets Differing time zones and geographical locations Differing time zones and geographical locations Goods and cash in transits Goods and cash in transits Differing legal and regulatory environments Differing legal and regulatory environments Cannot escape from local requirements Cannot escape from local requirements

33. Tagging Computing Issues  Tagging is everyday life you may use, for example Tagging of mp3 files with multiple classification Tagging of mp3 files with multiple classification Tagging of photos associated with your friends (Social network) Tagging of photos associated with your friends (Social network) Tagging of documents within document management system Tagging of documents within document management system  Tagging of each processing base on system-defined tags these system-defined tags including related information about who upload file with invoking processing on particular date/time and subsequent status of processing these system-defined tags including related information about who upload file with invoking processing on particular date/time and subsequent status of processing  Tagging of master records base on user-defined characteristics of each master record tagging a large number of master records including product codes, account codes, staff code, customer based on pre- defined characteristics of individual item tagging a large number of master records including product codes, account codes, staff code, customer based on pre- defined characteristics of individual item long account code can be embed with multi-dimension so user may want to decompose it to uncover useful information long account code can be embed with multi-dimension so user may want to decompose it to uncover useful information

34. Tagging Computing Issues  Tagging of every changes in master records Change in legal & management group structure Change in legal & management group structure Change in % of shareholdings Change in % of shareholdings Change in allocation ratios and amortization periods Change in allocation ratios and amortization periods Change in product list prices and discount rates Change in product list prices and discount rates  Tagging of transactions base on user-defined characteristics any key word such as "loss", "worst“, “fail” and etc. as included in transactions can be tagged as pre-defined analysis code attributed to specific dimensions. any key word such as "loss", "worst“, “fail” and etc. as included in transactions can be tagged as pre-defined analysis code attributed to specific dimensions. CRM is heavily implemented on tagging of sales data such as income group, age group, nationality, gender etc. CRM is heavily implemented on tagging of sales data such as income group, age group, nationality, gender etc.  Computing issues No tagging may trigger computing issues of reporting despite you have obtained all relevant data for reporting No tagging may trigger computing issues of reporting despite you have obtained all relevant data for reporting Do tagging manually also trigger computing issues Do tagging manually also trigger computing issues

35. Moving Ahead to Advanced Automation of Elimination, Standardization and Tagging for Massive Volume of Heterogeneous Data FESA C onsol www.fesaconsol.com/consol.pdf www.fesaconsol.com/consol.ppt x

36. Alert Computing Issues 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 Manager Supervisor Alert Manually

37. Alert Computing Issues  There are two different kinds of alerts Process management alert Process management alert Analytical alert Analytical alert  Process management alert Uploaded, Validated, Void, Fail, Completed, Restored Uploaded, Validated, Void, Fail, Completed, Restored  Analytical alert similar to continuing monitoring Inventory turnover ratio for any product class above the predefined value 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 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 Total for consolidated fixed assets do not reconcile with its movements  Is it possible or are you demand for achieving advanced automation of analytical alert?

38. FESA A nalyst Achieving Ultimate Automation of Alert that Empower your Analytical Performance Management at Anywhere

39. www.fesaconsol.com

40. Finance Computing Framework Company Level Processing GroupLevelProcessing GroupLevelProcessing

41. A lert T agging S tandardization E limination V ersioning A ggregation The Multiway Model Crossovers with the Finance Computing Framework Domain Specific Model Information System Model x

42. S tandardization C ontrol T ransformation C ollection E limination V ersioning R eporting T agging A lert S torage A ggregation Leveraging the Principle of Separation of Concerns to Solve AVESTA Computing Issues

43. S tandardization C ontrol T ransformation C ollection E limination V ersioning R eporting T agging A lert S torage A ggregation C onfiguration “No Programming” can Deliver Customization of Systems to Most of User Groups Very Efficiently

44. FESA Consolidation Series FESA Q uery P lanning F inancial C onsol P rofessional A ccounting A nalyst

45. Scope of Solutions & Services Mix Level of Automation & Investment Level of Automation & Investment FESA Q uery FESA P lanning FESA F inancial FESA C onsol FESA P rofessional A ccounting FESA A nalyst Budget Planning & Rolling Forecast Management Reporting Regional Financial Management Group Consolidation & Budgeting Multinational Financial Management Analytical Performance Management FESA Consolidation Series

46. Unifying Finance Operations for Each Regional Management FESA F inancial www.fesaconsol.com/fesafinancial.pdf

47. P rofessional A ccounting Managing Global Consolidation with Localization of Financial Management FESA

48. Transaction Voucher LedgerReport Rule Processor Central Database Query Processor FESA Professional Accounting

49. Financial & Professional Accounting Following sub-systems provide solutions specialized in different areas of financial & professional accounting:  FESA Account Payable  FESA Account Receivable  FESA Account Revaluation  FESA Account Reconciliation  FESA Account Allocation  FESA Account Amortization  FESA Cash Management  FESA Inter-company, RPT & Elimination  FESA Fixed Asset  FESA Job Management  FESA Rental Billing  FESA Procurement Management  FESA Inventory Management

50. Sale StockMembership Purchase Inventory Performance Management

51. Sale Amount and Quantity Cost Amount and Quantity Purchase Amount and Quantity Stock Amount and Quantity Sell Thru % = Qty Sold / (Qty On-Hand + Qty Sold) Gross Profit % = ( Sale Amount – Cost Amount ) / Sale Amount Inventory Performance Management

53. F lexSystem E nterprise S oftware A rchitecture

54. Web & Windows Login Client

55.  Connectivity Internet and cloud ready Internet and cloud ready Thin-client technology (support low bandwidth) Thin-client technology (support low bandwidth) Web and Windows/Excel login client Web and Windows/Excel login client  Scalability Multi-user Multi-user Message center Message center Scheduling and queuing Scheduling and queuing  Usability Multi-language Multi-language Rich user interface Rich user interface  Security Data encryption Data encryption Server activity log Server activity log  Extensibility Application expression (AX) Application expression (AX) System integration (Internal and external) System integration (Internal and external) FESA (A 5-tiers software architecture)

56. S tandardization C ontrol C ollection E limination V ersioning T agging A lert A ggregation FESAFESA C onfiguration AVESTA @ 6 Major Software Modules R eporting S torage T ransformation

57. S tandardization FESA P lanning FESA C onsol FESA F inancial E limination V ersioning FESA A nalyst T agging A lert FESA P ro A/C A ggregation FESA Q uery A udit Trial & R eporting E fficient O ptimize D ual M odels C ommon D ata S et D ynamic L ookup M ulti- dimension L ookup D ynamic L ookup P rocess & A nalytical P rocess M anagement P rocess Management & A na. Group P rocess M anagement C ommon D ata S et Q uery F ormula R eporting A udit Trial & R eporting A udit Trial & R eporting A udit Trial & R eporting A udit Trial & R eporting M ulti- dimension L ookup A nalysis G roup P rocess Management & A na. Group N/A AVESTA @ 6 Major Solutions Q uery F ormula D ual M odels

58. FESA P lanning FESA C onsol FESA F inancial FESA A nalyst FESA P ro A/C FESA Q uery A llocation, C urrency & M apping R ule-based E ntry S creen & U pload T riple M odels C ustomize S tandard U pload E xcel N/A D ual D ata S tore B asic S tandard B asic + O ptional T riple M odels A mortization R ule-based D ual D ata S tore D ual D ata S tore D ual D ata S tore O ptimize D ata S tore O ptimize D ata S tore C ustomize S tandard + O ptional S tandard + O ptional S tandard + O ptional A dvanced + O ptional A dvanced + O ptional S tandard + O ptional S tandard + O ptional S tandard + O ptional S tandard + O ptional S tandard + O ptional A dvanced + O ptional U pload E xcel U pload E xcel C ontrol C ollection FESAFESA R eporting S torage T ransformation 6 Major Modules @ 6 Major Solutions

59. Summary and Conclusion  The Existence of Multiway Data  3 Progressive Phases of Automation 6 Aspects of Our Multiway Model 6 Aspects of Our Multiway Model 6 Levels of Advanced Automation 6 Levels of Advanced Automation Solving Your AVESTA Computing Issues Solving Your AVESTA Computing Issues  AVESTA Crossovers with Finance Computing Framework  6 Different Solutions Classified by Red, Greenand Blue  6 Different Solutions Classified by Red, Green and Blue FESA Query & Analyst FESA Query & Analyst FESA Financial & Professional Accounting FESA Financial & Professional Accounting FESA Planning & Consolidation FESA Planning & Consolidation  FlexSystem Enterprise Software Architecture (FESA)  FESA Financial & Professional Accounting 9 Optional Sub-systems for Financial and Management Accounting 9 Optional Sub-systems for Financial and Management Accounting 4 Optional Sub-systems for Planning and Consolidation 4 Optional Sub-systems for Planning and Consolidation  Analysis of AVESTA @ Modules @ Solutions AVESTA @ 6 Major Software Modules AVESTA @ 6 Major Software Modules AVESTA @ 6 Major Consolidation Solutions AVESTA @ 6 Major Consolidation Solutions 6 Major Modules @ 6 Major Solutions 6 Major Modules @ 6 Major Solutions