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Extracting Collection Data From Websites TRMG April 16, 2012.

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Presentation on theme: "Extracting Collection Data From Websites TRMG April 16, 2012."— Presentation transcript:

1 Extracting Collection Data From Websites TRMG April 16, 2012

2 Agenda Part 1: Technology – How do web pages work? – Why would you want data from a web page? – What are your options for web page data? Part 2 How does this relate to Collections? – How do the two go together? – What is the information I’m looking for? – What will I do with the info when I get it? – What is my overall benefit?

3 Technology Part 1

4 How Do Web Pages Work?

5 Your Web Browser Sees This

6 You See This

7 Putting it all Together XML HTML JavaScript ColorColor ColorColor FontFont FontFont SIZESIZE SIZESIZE Location

8 What if You Could Capture This Data? $549.95

9 4. Login to customer’s B2B portal, retype data from customer app, confirm pick-up 3. Login to customer app, retype data from email, schedule pick-up 2. Read, print, file email “Robots”: Automating Data Capture 9 1. Shipping request arrives in email

10 Data Capture Options Print screen/copy by hand between sessions – Low apparent cost but very costly in staff time – High error rate, unsuitable for a growing business Write some programs – These programming skills are very hard to find Browser add-in – Defeated by modern websites (JavaScript, etc.) – Limited targets, can’t integrate applications Data feed/service provider – Easy and convenient if cost and delivery time are OK Integration and automation engine – Needs in-house tech support

11 Making a Decision? How many sites? How much data? Are updates frequent? Are new sites added often? How complex are the sites? – Login – Navigation – Multiple pages – AJAX … Where does the data need to go?

12 Web Extraction For Credit and Collections Operations Part 2

13 Web Extraction and Collections Operations How does this apply to me? What is the information I’m looking for? What is my overall benefit?

14 Web Portals aka Payables Sites Today’s market has driven more and more A/P Departments to pushing their payment data to the web. Examples – Paying Services (ie Cass, Data2, etc) – Large Companies – Logistics Companies – Many Many more….

15 Multiple Sites Daily = Labor Hours! My Employee Employees logging on and off of sites daily. Cut and Paste or manual entry. Automation could reduce your labor associated with this by 85 – 100%

16 What is available on these sites? Payment Date Check Numbers Dispute Information Acknowledgement of Receipt

17 Why does earlier make it better? 1.Payment Info: Pay date, Check Number, Amount Paid. Reduce the number of Invoices your team calls on. Improve Cash Application. Recognize potential short pays. Integrate into cash flow management/forecasting. 2.Acknowledgement of Receipt But I have EDI…. Who sends you the 997? Receipt Acknowledgement? Improve Invoice Accuracy by improving address correction. Imagine if a customer told you that they hadn’t gotten a bill, and it was already past due?

18 Why does earlier make it better? 3.Dispute Information: Know about Short Pays, How much, and why. Allow the work flow to start earlier and resolve issues more timely. Create a better customer perspective overall. Improve Cash Flow and DSO. When is the best time to search for info? What is the Sweet Spot?

19 Manual Sweet Spot Current (1-30 Days)31-6061 – 9090+ 75%18% (11 -7)5%2% Labor Version Sweet Spot In attempting to manage exceptions and minimize manual labor, this point of biggest reduction is a normal spot for labor to look up status. Approximately 42 Days Old

20 Payables Process Efficiency Service Provider Day 7 A/P Department Receives Invoice/ Audits Bill Day 16 Payment or Dispute Information is Keyed into Payables System Day 18 Status of Invoice is populated to Customer Web Portal Day 30 If Payment is mailed based on scheduled Payment Date Prime Point of Data Gathering

21 How do they Match Up? Current (1-30 Days)31-6061 – 9090+ 75%18% (11 -7)5%2% A/P A/R Approximately 27 Day Gain!!

22 Carrier Perspective: Using Technology to Increase Productivity and Avoid Costs

23 The Situation Credit & Collections – Seven collectors handling over 1,500 accounts using 3rd party freight payment agencies – Over 70 different websites with different logins and navigation – Manual process to research disputes and transfer payment information to commercial C&C software

24 Initial C&C Solution Started with service provider capturing the data Captured data was integrated with our collections software – Easy to test and implement - Minimal IT resources – Most of the major freight payment companies available to “turn on” – Cost effective – No integration fees – Early notification of payment disputes and PTP’s – Automated internal workflow to resolve dispute

25 Customer Service Situation Needed to update/monitor “managed account” websites Faced similar issues to C&C – Websites with different logins – Different sets of navigation – Varying data and timing requirements Constant awareness of shipment status so that information could be updated timely Process manual, convoluted, and untimely

26 CS Needed a Different Solution No service provider solutions captured data from the CS websites we needed to access Purchased software solution to build robots – Automates navigation and updating of customer sites Robots created by non-developers who understand database structure – Average of four hours effort per customer site Can schedule robots to run as needed to meet timing requirements

27 Current Status & Cost Savings Started in Credit & Collections area due to available resource to build robots. – 39 processes built out of 70 available – 80% of freight payment invoices – Approximately $75,000 labor savings per year (both solutions) Customer Service – 3 processes built with several in queue – Approximately $190,000 labor savings per year for these 3 accounts alone.

28 Overall Benefits Credit & Collections (both solutions) – Improved productivity by reducing website inquiries – Shortened time for resolving rejects or disputes due to earlier notification – Streamlined processes by routing rejects to the appropriate resolvers – Allows for better analysis of payment patterns and disputes – Ability to establish robots to capture data for large customers not using freight payment agencies

29 Overall Benefits Customer Service – Reduced labor by automating managed accounts processes – Reduced complexity by streamlining processes – Reduced errors and improved timeliness of updates through customization – Potential to increase revenue by taking on more managed accounts without adding staff

30 Other Uses Completed – Credit & Collections Software Upgrade – State Tax Forms – Rate Web Probe Future – Canadian Customs Form – ECM (TruckLoad) Customer Service

31 Carrier Perspective: Web Scraping

32 Credit & Collections Company has 178 customers utilizing 23 different 3rd party payers with websites – Approximately 25,000 invoices statused per week

33 Process Before Web Scraping Each A/R Analyst visits 3rd party payer's website and obtains invoice status information – Each A/R Analyst usually has various customers utilizing 3rd party payers: CASS, Data2; Sterling; etc. – A/R Analyst downloads/manually captures invoice status and updates Customer Aging (Excel spreadsheet) from each individual website – If a customer begins using or changes 3rd party payers, A/R Analyst has to train on website to know how to capture invoice status

34 Inefficiencies/Break Downs before Web Scraping Time consumed visiting separate websites by each A/R Analyst “Administration” of website spread across A/R Analyst population: access/passwords; training Lack of Standardization on what and how information is obtained & retained/tracked In one word


36 A/R Analyst Customer Website Payer Website

37 Process With Web Scraping (1) A single, assigned individual generates web scraping results We web scrape once a week; on occasion will web scrape an individual “batch” if more immediate update needed The larger 3rd Party Payers are accessible, and more are added on an ongoing basis

38 Process With Web Scraping (2) Steps involved: – Generate our open invoice report for all customers per payer – Add Paying Agent Import ID – Upload report to the Web-Scraping website – Click the "start" link once the file is imported.

39 Process With Web Scraping (3) Steps involved (continued): – Wait for processing to complete: Can take 4 hours for the largest accounts or slowest websites During processing visibility to “UTP” items meaning there is a connection error with that 3PL. It could be expired username/password or the site could just be down. – After processing, there is a download link for an Excel file we use to provide A/R Analysts their invoice status (via V-Lookup by invoice #)

40 Data Capture Data Capture A/R ANALYST A/R Analyst Note: Today Analysts “V- lookup” from excel to update invoice status on master agings. In development – feed of web scrape results directly to Collection Software Open Invoice Data Payer Website

41 Benefits of Web Scraping Significantly reduces the amount of time an A/R Analyst spends statusing invoices/updating agings More efficient detection of issues or disputes (i.e. rejects, missing invoices etc.) before invoices due A/R Analysts more effectively utilize PTP Provides more ability to analyze/report on common rejects by customer Results retained for a historical record/analysis of billing/collection issues and/or trends with specific customers and/or 3rd Party Payers.

42 Questions

43 Thanks for Your Time Bruce Olsen Kapow Software Jeff Jones Gallium Technologies Diana Early PITT OHIO Cindy Douglass Swift Transportation

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