Matt Webb Email & Phone Number

Allentown, Pa

- Developed a scoring model to identify the likelihood or residential customer going past due based on customer, account, and demographic data.- Developed a regression model to forecast bad debt expense. - Analyzed customer data to determine if there are customers who may qualify for assistance programs but are not taking advantage of those programs.- Identified an error in a reserve requirement study that will save the company $10MM in reserve expense.- Validated the practice of requiring new customers with poor credit scores to place security deposits on their accounts.- Analyzed the benefits of creating more flexible payment plans for past due customers.- Helped train other associates to program in SAS.

Allentown Pa

- Forecast medium to long sales and revenue using multivariate regression analysis incorporating historical load, economic, efficiency, and weather data. - Forecast Accuracy: Weather adjusted base distribution revenue has been within 1% of plan since the 2011 plan.- Developed a month to date report showing actual sales and revenue compared to plan before the end of the month.- Calculate unbilled sales and revenue. - Increased the accuracy of the unbilled estimate, leveraging big data, by developing a process to determine unbilled sales based on actual meter reads rather than use a model. - Worked with Itron to improve the weather normalization process by incorporating various temperature breakpoints and lagged weather data.- Built a process, in MS Access, to automatically produce the month end unbilled report and dashboard reports.- Added code to the monthly report MS Access database to automatically produce the dashboard report that breaks down revenue variations by customer, kWh, and demand charges.- Created a report using interval data on Netezza to identify cancelled accounts with meters that are still registering usage. This report is used by the Customer Service organization to find CIMS and has resulted in a reduction of $2.2MM in outstanding CIMS balances.- Successfully predicted 50 of the top 100 summer hours to meet Act 129 goals for 2012.- Automated the majority of the process to match PLC numbers for meters that switched accounts, eliminating a very labor intensive task.- Wrote SAS code to determine the time periods in which a time of use customer could realize the greatest savings by switching usage to off peak hours while keeping the program revenue neutral if the customer made no changes in behavior.- Built an MS Access data base to automate the monthly expense allocation process. This has saved members of the Budget Consolidation and Reporting group 8 to 10 hours per month.

Bethlehem, Pa

- Maintain Marketing Customer Information Database file based on company files and files supplied by vendors.- Automated database update validation process by writing VBA script to read and compare print files. This saves two hours for each database update.- Introduced auditing and documentation standards for file building and reporting processes.- Increased the number of month end reports by 40% while reducing production time by 60%.- Build direct mail files in Access, using customer data and demographic data in order to predict customer behavior.- Wrote a program to calculate customer and prospect distances to branches to aid in direct mail targeting.- Assess the effectiveness of direct mail programs, by demographic segment. This allowed the bank to reduce mailing file sizes by up to 80% while continuing to generate up to 85% of the new business.- Created source of funds reports to show if increase in service utilization is the result of new funds or the tracking of existing funds.- Create site analysis reports (to determine the suitability of new potential branch sites) with demographic, current customer, and geographic data. - Created an automated call list database, reducing time to produce lists from several hours to less than 30 minutes. - Developed a customer incentive tracking database to automate a manual tracking system in which over 50 branches would send results to the marketing department for manual tracking.- Wrote address standardization and name splitting code to aid in identifying prospects that became customers.

Bethlehem, Pa

- Wrote SAS and JCL programs to process Customer files to be loaded into the Mainframe collections system or into SQL based collections systems.- Analyzed data with SAS, SQL, and Access to produce reports for operations, sales, and marketing managers. These reports were used to determine workflow strategies, set contract pricing, and find potential customers.- Automated production team tasks by writing SAS code to submit JCL to the internal reader. These jobs validated data, reported on data that did not pass validation, and processed data that did pass validation. This process enabled increased efficiency within the production team and reduces the amount of new staff required. - Programmed complex SAS automated treatment matrixes to send letters on delinquent accounts, prompt past due accounts for collector action, and move current accounts in the statuses that indicated no work was required without the need for manual review.- Developed databases, using Access and SQL, to organize collector and administrative team workflow.- Wrote programs to provide feedback on files to customers in their required format or to provide reporting which identifies opportunity areas for limiting bad debt exposure.- Participated in a data center migration of the company mainframe and network.- Created SAS programs to create JCL to automatically submit jobs listed in a dataset. This allowed operators to easily schedule jobs and change notifies without having to rely on a programmer to set up a new Control M job.- Created an AR roll forward that showed not only inventory aging but also demonstrated how the inventory had changed due to new placements, payments, and aging of existing inventory. This allowed mangers to better deploy resources and to explain collection results to customers.