Consumer Analysis Tool Utility Customer Information Management

1. Consumer Analysis ToolUtility Customer Information Management At Southern Power Distribution Company of A.P. Limited

2. Background • 101 Private Accounting Agencies perform the billing activity for Discom. • Almost every agency works on a different platform and process for doing the billing. • The exceptional reports are generated and distributed only at local level leaving no tool with management to monitor the exceptions at the field. • The Discom needs to shelter PAAs for any reports or for doing any analysis on sales trends & consumption patterns.

3. Development • In order overcome the above challenges Consumer Analysis Tool (CAT) is designed to: • Gather and Consolidate the information available with the PAA into a central database. • Validations are performed to the data and then the database is brought to an common format (Mining). • Information thus consolidated is used to create necessary reports • Generate Reports and provide to the management and field personnel for taking necessary action • Now CAT has been decentralized at Circle level for easy data handling and for early processing of data thereby reducing the time lags for taking the necessary actions • CAT database is extended and is used as Sales Database

4. Consumer Analysis Tool • Consumer Analysis Tool (‘CAT’) focuses on generating prioritised and focused consumer information relating to all business aspects at Summary and Detailed levels • CAT implementation involves process improvementand effective use of technology for: • Identifying the critical problems; • Prioritising problems based on impact for action initiation; • Action initiation and monitoring Process Improvements Sourcing of problem Prioritisation of problems based on impact Action initiation & monitoring Targeted Algorithms Prioritised Reports Technology - Tools and Enablers

5. Class Structure Collection % Default % CAT Process Involved Private Accounting Agencies Circles CAT Team at DISCOM HQ Action / Users Sections / Circles SEs / Circles • Consumption pattern • Demand/ Billings • Receivables • Collections • Demographic trends • Connected load profile • Other Exceptions Vigilance Finance Customer Database Performance Management Top Mgmt decision support Regulatory Cell Customer Support Circles upload data through VSAT to CAT Team • Central team generates analyses and sets priorities • Provides targeted inputs to relevant user • Monitoring and follow-up on actions • Phased refinement of consumer data - moving towards customer care Build process controls and checks for action initiation and follow-up PAAs provide soft files to Circle, every month

6. Analysis framework developed For the purposes of analysis, a consumer classification methodology has been developed that considers the following parameters for consumer related data over a 12 month period : • Timeliness / promptness of payment by consumers ie, default history • Collections vis-à-vis demand raised during the review period These parameters are captured through the Consumer Analysis Tool (‘CAT’)

7. For the twelve month period, at individual consumer level the collections made against the demand raised are analysed and assigned a numeric code of 1, 2, 3, 4 or 5 based on the collection percentage Each consumer analysed for 12 months period Class Structure Collection % Default % Based on the default percentage of the consumer, the alphabetic code of A, B, C, D E and F are assigned The combined alpha-numeric code is assigned to each consumer based on the default and collections history (for a period of twelve months), thus profiling the entire population on collections parameter The CAT framework As entire billing information is available, reports related to key business processes of Metering, Billing, Collection and Data maintenance generated

8. Generic risk profile of consumers based on collection F High risk classes Require urgent attention D4 E C3 Non-collections D3 Medium risk classes Require urgent monitoring to try and shift to lower risk class categories C2 D2 B2 C1 Low risk classes Attempt to further push all towards A1 class D1 B1 A1 Default

9. Sales Database Class Structure Collection % Consumer Database Default % What are the benefits of CAT? Feeds consolidated information across business unit levels, ie, discom, circle etc Aids in analysing metering, billing and collections data Generates prioritised and focused reports for action initiation Database Dumps Used for managerial and Regulatory Requirements Aids in reducing the response time for report generation and action initiation Acts as an effective monitoring tool, helping management in exercising control Addresses needs of finance, operations, vigilance, regulatory affairs personnel

10. “Prevention of power theft is vital for the proposed financial turnaround of various state electricity boards.” --RV Shahi, Secretary Ministry of Power “In the changing scenario, consumer management would be the focus of the organisational business strategy involving, attracting and retaining the right consumers, growing mutually beneficial loyal relationships and optimising long term value for the customer and supplier.” --The Economic Times Necessity for CAT

11. CAT Helps Cat Helps in: • Accurate and timely availability of information for the key business processes of Metering, Billing and Collections for decision making • Effective monitoring of processes and action initiation • Effective control of energy flow • Focused action plans and targets with defined responsibilities • Target loss reduction with fall in irregularities

12. 1 1 2 2 6 3 5 4 7 3 4 11 8 12 14 5 10 16 9 13 6 15 7 8 10 11 12 13 14 15 16 CAT Helps In Identifying Risk Areas: • Low collections rate • High percentage of energy pilferage • Low percentage of functional meters • Under declaration of connected loads • Absence of focused reports • Consumer details maintained on discrete databases and varying platforms • Poor quality of data and records • Critical data fields not captured for analysis • High delinquency rate • Weak monitoring controls • Inspection processes require strengthening • Significant arrears outstanding for over 1 year • Inaccurate billing • Absence of energy audit • Absence of meter deployment and replacement plans Significance Likelihood We have prioritised the identified risks/issues based on their significance and likelihood

13. Reports

14. Classification of Reports • Reports on Metering Irregularities • Class F Consumers • Live Class F Consumers • Bill Stopped Case • Reports on Collection Irregularities • Metering Irregularities • Under Disconnection Consumers • Meter Stuck-Up Cases • Nil Consumption Cases • Meter Not Existing • Readings not Furnished.

15. Reports targeting irregularities Business processes Suspected problems Non-functional/abnormal meters Metering Abnormal consumption Inaccurate billing Non-collection of dues • Revenue leakage on account of: • - Continuing supply to defaulting consumers • - Unbilled consumption Consumption/ Billing Inaccurate declaration of tariff categories Multiple connections Under-declared connected load details Collection/ Receivables Fictitious/ghost consumers Inaccurate and incomplete customer information Teeming and lading Data maintenance Probable collusion Types of reports Trend analysis Key ratios Comparative analysis Benchmarking reports Exception/Status reports

16. Sample view of data analysed Note:This Report shows Category wise Summary of Receivables Vs Revenue by the end of February 04

17. Sample Profile of CAT Class at SPDCL This sample profile is summary of approximately 5 lac consumers being analyzed to drill down F-Class consumers

18. Profile of CAT Class F consumers (Jan’04 Report) The Consumers receivables are divided into various slabs and a focussed way of collection drive is organised.

19. Collections and receivables irregularities as on Feb 2004 - to be part of management review process *

20. Metering irregularitiesDiscom snapshot as on Feb 2004 *

21. Metering irregularitiesDiscom snapshot as on Feb 2004 *

22. Journey in CAT • Cat Started with the aim of: • Creating a central Database at the Discom Level • Creating Exceptional Reports • Monitoring the action taken on the reports • Cat Database Extended: • After successful implementation at the Discom Level CAT has been Decentralised to the respective circles for better monitoring and faster generation of reports thereby reducing the time lags for taking the necessary actions. • Cat Today: • Used as E-Seva Server for online collections at E-Seva Centers • Used as Sales Database for Managerial and Regulatory Requirements

23. Class Structure Collection % Default % Sales Data Base and drilling down of performance trends etc. for Managerial and Regulatory Requirements • Consumption pattern • Demand/ Billings • Receivables • Collections • Demographic trends • Connected load profile • Other Exceptions Customer Database Extension of CAT Run algorithms to reveal exceptions from the integrated data Integrate billing and collection data from PAAs and IHCs Provide exception cases to field officers for follow-up Information updated at eSeva servers at each of the circles of Discom