Saturday, October 22, 2011

Local business intelligence on utilities performance - take informed bidding on MP Distribution Franchised towns

The revised MP Distribution Franchisee RFPs has brought down on average coverage area by 100%, number of consumers and electricity sales by 60% and number of DTCs by 77%. Also with mandated capex of Rs. 170 cr for Gwalior, Rs. 70 cr. for Ujjain and Rs. 30 cr. for Sagar and target ATC reductions to 15% in 2 years, the bids will become more competitive and likely also volatile. It has become more important now to integrate various perspectives and data sets of information to validate assumptions and prepare informed bidding numbers. 

pManifold is an Information and Advisory company and is working broadly with relevant stakeholders to help scale-up of the emerging Distribution Franchisee model in India. In this role, we conducted a first type of study to measure Customer Opinions, Preferences and Satisfaction for Electric Utilities of Ujjain, Sagar and Gwalior, which brings a fair customer perspective that could be integrated with technical perspective to arrive at tighter estimates of Capex and Opex. We have compiled a Consolidated report on the 3 towns (priced at Rs. 25K), which could provide winning edge in the MP bids. 

Also available are comprehensive regional packages (priced at Rs. 25K) each consisting of 4 separate reports with GIS visualization and together they could help find answers to the following viability questions:
  1. Customer Satisfaction – Top Results (30+ slides) includes top level findings with attribute and factor level comparisons and recommendations
    • What are the key customer segmentation trends in terms of geographical localization, avg. monthly consumption, economic loss due to power outages, types of meters, backup equipments, education/profession, access to internet, electricity bill payment preferences, opinion on DF privatization etc? (across 4 consumer categories of Residential, Industrial, Commercial & Agri)
    • What are the key issues on Power reliability, Metering/Billing, Customer services, utility communications, utility IT and records handling, Tariff and utility Management as perceived by customers across 28+ attributes? (across for 4 consumer categories and also overall)
    • What areas required capital expenditures to improve overall utility's performance? How to prioritize capital expenditure for highest return on customer satisfaction, which is found to be correlated with ROI?

  2. Customer Satisfaction – Detailed Results (60+ slides) includes findings with GIS visualizations and individual factor level aggregated  responses at overall level and for each customer segments – residential, commercial, industrial and agriculture.
    • Which locality/pockets has more issues with voltage stability, electricity infra, power disruption (unplanned and load shedding), customer facilitation centres, metering/billing/payments etc. which will govern CAPEX
    • Which locality/pockets has more issues with unplanned outages, safety & maintenance, breakdown restoration, meter complaints, new connections, access to customer services, delayed payments, records handling etc which will govern OPEX
    • Which revenue class of customers whether residential, commercial, industrial and/or agriculture struggles with what pertinent issues related to power services and delivery to accordingly prioritize investments? How much of an issue is important for different customer class to comply well with proper consumption and payments?

  3. Distribution Franchisee RFP Data Analysis - (10+ supplementary slides)
    • How has been the load growth trends across different categories of consumers measured in no. of consumers, connected loads, electricity sales, revenue billed etc. across 5 years
    • What are the key revenue customer segments (measured by billed and realized avg. tariff) and their contradicting growth patterns potentially obstructed by poor electricity service delivery?
    • How has tariff policy effected load growth across different consumer categories?

  4. Socio Economic Parameters impacting load growth - (15+ slides)
    • How are key Economic factors like population, per capita income, workforce participation, District Domestic Product (DDP) broken down into its sub-components correlated with load growth in different consumer categories? 
    • How are key Social factors like Human Dev. Index (HDI), slum population, SC/ST population, rural electrification, literarcy, financial access etc. correlated with load growth in different consumer categories? 
    • How could these various Socio-Economic parameter trends could be projected forward in time to estimate future load growth?

With purchase of all 3 regional packages (priced at Rs. 60K), we will provide additionally support in drawing inferences and validating key assumptions in preparation of the bid. The reports will be best used to further augment on-site technical due-diligence, validating forward assumptions and estimating capex and opex. Our reports are equally valuable to the non-bidders to increase their understanding on relevant utility & DF business drivers and could become competitive edge for your next DF preparations.

We would be glad to support any further custom needs in Distribution Franchisee area including Bid Advisory and facilitating Entry strategy. 

Post by: Rahul Bagdia @ pManifold

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