DocXtractor II INVOICE

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Kathleen Richard
6 years ago
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1 DocXtractor II INVOICE Automated invoice processing and business process optimisation ELO Digital Office ELO Digital Office GmbH 1

2 structured and unstructured information of any source making documents work... to capture information to provide information to organise information ELO Digital Office GmbH 8

3 Objectives of Document Related Technologies Meaning of Document Related Technologies: Capturing as needed, systematical organisation as well as appropriate access to all information Connection between document and business process to capture information Resulting business objectives: Efficient information processing Safety of quality and efficiency of processes, decisions, products etc. Prevention of misallocation of resources Creation and assurance of competitive advantages to organise information to provide information ELO Digital Office GmbH 9

4 forms semi structured documents free-form documents input media: paper, , fax etc. ELO Digital Office GmbH 10

5 Connection between data, information and knowledge image objects layout structure image characters data d S 2 words INFORMATION interpretation processes information presentation logical objects sender recipient date subject signature... knowledge message type offer order invoice... business data ELO Digital Office GmbH 11

Challenge of free form incoming mail processing forms & free structured documents data Capture view paper email fax

Documents are central input factor of business processes business process s view business processes Company

6 Challenge of free form incoming mail processing forms & free structured documents data Capture view paper fax etc. field 1 field 2 field 3 Heterogeneous documents High daily volume Growing amount of free form documents Documents are central input factor of business processes business process s view business processes Company Customer Today business process? design is often isolated from document processing steps data capture ELO Digital Office GmbH 12

7 A person as an interface between paper and ERP system Manual acquisition n-- The difficulties High costs of manual capturing and processing ( 3-12) High error rate in manual capturing media changes Suboptimal process continuity High duration of invoice processing (missed deadlines) Business knowledge e Customer DB Business processes Redundant data capturing ERP system ELO Digital Office GmbH 13

8 Technical success factors for invoice processing + + Process quality Process speed Process flexibility High data quality with minimum verification efforts Homogenous data (consistency with ERP/ host systems) Invoice processing as an end-to-end solution Process acceleration and automation Adherence to time and dates (terms of payment, cash discounts,...) Cash flow optimisation Processing of invoice documents from any supplier No customisation needed for new suppliers Flexibility in regard to data extraction Processing invoices efficiently + ELO Digital Office GmbH 14

9 Economic sucess factors for invoice processing + + Acquisition costs Investment costs Process costs Initial installation costs Verification costs Data quality... Software costs Hardware costs Project planning costs (internal und external)... Vendor specific adaption effort Servicing costs Flexibility regarding fields extracted... Short payback period of investment + ELO Digital Office GmbH 15

10 1 ELO Digital Office About us 2 Invoice processing The challenge 3 DocXtractor II II INVOICE The product DocXtractor II INVOICE The system architecture Questions ELO Digital Office GmbH 16

11 Highlights of invoice processing with DocXtractor II INVOICE Capturing of creditor and invoice recipient including booking code/accounting are; processing of CPD creditors Substantial extraction of header and footer data including unplanned extra costs and up to three VAT rates Fully automated differentiation of FI and MM invoices via pre-configured and configurable rules Extraction of terms of payment and VAT conformity check (possibility of individual configuration) Processing of national and international invoices with different languages Substantial extraction of position data including order item matching by order data and incoming goods data Self-learning and self optimizing system with auto-adaptive, intuitiv and visual administration and configuration support Substantial statistical analysis and reporting in test environment as well as in production for performance measurement and ressource planning ELO Digital Office GmbH 17

12 Document process with DocXtractor II INVOICE and DocXtractor II SCAN (internal workflow) import automated document processing with DocXtractor II INVOICE export SCAN import master data ERP paper export database fax fax server import automated analysis workflow archive verification workplace server electronic documents training workplace administration workplace automated processing or accountants DocXtractor II INVOICE uses master data to optimise the automated invoice process and to provide the required information electronically. ELO Digital Office GmbH 19

13 Requirements of information extraction field data field extraction vendor recipient invoice number Vollständige invoice date Tabelleninhalte... etc. field tab ble extraction net amount gross amount different VAT rates Vollständige total amount Tabelleninhalte... etc. ELO Digital Office GmbH 20

14 Requirements of table extraction field table data quantity unit price field tab ble extraction Vollständige position price Tabelleninhalte discount... etc. ELO Digital Office GmbH 21

15 Position dependent data extraction invoice number name P e tz, Erwin position 1 94,80 position 2 amount of disposal VAT total amount 190,80 8,16 44, ,82 Position of each field has to be known before extraction A separate document definition (template) is needed for each supplier Keyword search (e.g.invoice number, number, etc...) is additional source of error ELO Digital Office GmbH 22

16 DB matching of reading results OCR result result? Adalf Würth Künzolsau search for most similar match in database mapping of OCR results to database fields mas ster data matching data Position of each field has to be known before extraction Adjustment of incorrect positioned fields is nearly impossible High administration effort while in production ELO Digital Office GmbH 23

10681000 Voith AG Pöltenerstr 74650 Künzelsau62091800 21389700 BMW AG Pacalstr. 70569 Stuttgart 70540660 518378908.

17 ELO Digital Office Top Down Search master data company name street p.code city sort code account Thomas Cook AG Zimmerstr Oberursel Adolf Würth GmbH Postfach Künzelsau Voith AG Pöltenerstr Künzelsau BMW AG Pacalstr Stuttgart Knowledge about location of fields is not necessary Perfect fit for free form documents and invoices Fuzzy search (tolerant against OCR errors and different spellings) Optimal results without training ELO Digital Office GmbH 24

18 Example: Mathematical search of whole document Extraction Net VAT Gross Testing of mathematical inter-dependencies Gross is one of the biggest amounts Net less than gross Gross = Net + VAT VAT = 0.19 or 0.07 * net Clear result Net ,-- VAT 47.00,-- Gross ,-- ELO Digital Office GmbH 25

19 Automatic system optimisation while using the system Generated knowledge is available for usage in the analysis process automated analysis documents to be verified Verifier Generated knowledge of data extraction is available immediately System optimisation without effort in the background Usage of knowledge generated during verification for processing of unknown documents Automatic plausibility checks for information without matching data Creditor-specific training is not necessary at all ELO Digital Office GmbH 26

20 Manual verification process matching with master data invoice number name position 1 position 2 amount of disposal Peetz, Erwin 94,80 190,80 8,16 mathematical checks logical checks quality assured data export VAT 44,06 total amount 337,82 Manual data verification will also use automatic validation routines to improve data quality ELO Digital Office GmbH 27

21 Comparison between classic and content based data extraction + + acquisition costs investment costs production costs verification effort data quality initial installation costs... software costs hardware costs development costs... adaptation effort service costs Flexibility regarding readout fields fixed target value fixed target value pro content based offer content offer content offer content pro content based offer content pro content based With the content based data extraction current costs are minimal in comparison to classic data extraction. ELO Digital Office GmbH 28

22 USPs of DocXtractor II INVOICE Generic invoice reader: Generic approach for document processing rules No need to define and modify processing rules for each supplier Out-of-the-box -solution: usage without adaptation to different document-types is possible Position independent search method (Top Down search) Customization possible (e.g. automatic matching with orders, special fields, etc.) Continuously self learning and self optimising system Automatic table extraction Extraction of terms of payment and invoice line items without training Separation of invoices, credit notes and demand notes Automatic transaction and document separation possible (no presorting / no patch codes) Product extension through components of the DocXtractor II SUITE always possible ELO Digital Office GmbH 29

23 1 ELO Digital Office About us 2 Invoice processing The challenge 3 DocXtractor II INVOICE The product 4 DocXtractor II INVOICE The system architecture 5 4 Questions ELO Digital Office GmbH 36

24 Thank you for your attention ELO Digital Office ELO Digital Office GmbH 37

Corporate transparency and top customer service

>> Seamless external ordering process Corporate transparency and top customer service with seamless ordering processes in ELO The automated end-to-end process from the initial order through to the invoice