Putting your best foot forward - Best Practices in Consumer Indexing

As the operator tries rolling out the services, the foremost task at-hand is creating the base-line for the utility. This, typically, is collated using a consumer survey called consumer indexing (CI). The operator main aim is to collect the information required for consumer demography and demand estimation.

The figure below shows the variety of data the consumer indexing, if designed properly, can yield:

Consumer Indexing - Why is it important?

Here's the catch though.

Since the consumer indexing process is an extensive full-city activity, our observation has been that it becomes extremely important for the operator to monitor the survey process continuously and ensure data accuracy.

Some of the Critical Factors for Success (CFS) for successful consumer indexing survey are listed below:

1. S.M.A.R.T. Goals: It is very important for the operator to upfront decide the data he wants to collect as a part of the consumer indexing process. The goals need to be identified across the teams which are going to be the users of the data collected. At the same time, the goals need to be clearly defined to the survey vendor so as to apprise him of the data usage. During our engagement with our clients, we have noticed that not much is done in documenting all the teams' requirements right in the beginning. We strongly recommend writing up a  well defined Data Requirement Document (DRD). It not only becomes one of the most important pillars of the CI Process but also avoids endless discussions between teams on what is required, by whom and by when.
2. Data collection methodology and medium: The operator should identify all the options available to select the best suited methodology to collect the data identified in the goals of the CI process. In the same step, the operator should also develop and design the medium, usually a survey form, for the CI process. The "wow" effect of the survey form design changes and improved efficiency of the consumer interview was observed when we re-designed the survey form from a functional flow question to a consumer interaction flow.
3. Well Defined Technical Specifications: The geo-spatial information being collected in the consumer indexing requires high end technical inputs to be ready for the survey before the start of the survey. These specifications include the likes of a high resolution satellite image of the area under survey, clear definitions of boundaries of zones and sub-zones (if any), etc.
4. Appropriate Data Validation Rules (DVR): Once the DRD and Technical spcs are frozen, the operator should identify for itself the validation rules he needs to apply to check the data being collected by the CI vendor. Inappropriate or too rigid validation rules lead either to mass rejection or too poor quality of data being collected.
5. Vendor Selection and Engagement: Identifying a vendor capable of delivering the DRD as per the pre-set data standards becomes the core of the CI project execution. As much important it is to identify the correct vendor, it is also the operator's responsibility to engage the vendor in a manner where the CI process can be handled in a smooth and timely manner.
6. Design and Deployment of Project Management Techniques: The CI activity usually spans a substantial period of time. This necessiates deployment of a Project Management team which is well versed with the DRD and Data Collection methodology. A well formed PM team with participation across stakeholder teams forms one of the important CFS for CI Process. The KRAs of the PM team should include Unitization of Work, Timeline planning, Progress monitoring, etc.
7. Business Process Management: The operator should be engaging in monitoring of not just the data being collected, but also the vendor processes. This, in the long term, helps the operator to achieve more accurate and timely data. Independent audits of internal as well as vendor processes always helps.

The data collected through CI process forms the base-line for the operator to put its plans (CapEx, OpEx, Revenue Planning) in place. Therefore, we believe, the onus of successful execution of the CI process is as much on the operator as it is for the survey vendor.

Price bid curves and analytics from Bihar Distribution Franchisee projects

Our earlier blog 'Key amendments in Bihar Distribution Franchisee after pre-bid meeting' covered key points raised in pre-bid meeting and its responses in revised amendments.

Bihar State Power (Holding) Company Limited (BSPHCL) has given minimum benchmark input price curve for all the regions, mandating bidders to bid higher than given price curve for all 15 years. The bidders in pre-bid meeting requested to lower or removed the rates, as current rates to allow them  innovating on financial structuring.

See below table with useful bid analytics (click on the image to see enlarged view):

Some top level observations are:

• Average growth rate of around 20% in initial first 2 years, with max. in first year; followed by receding growth rate to average 10% by 5 years; almost stable and slow receding of around 0.5% until 15 years
• Gaya has lowest start point at Rs. 1.684/kWh, with PESU highest at Rs. 3.330/kWh
• Bhagalpur has lowest end point at Rs. 4.124/kWh, with Muzaffarpur highest at Rs. 4.742/kWh  
• The ratio of max. to min. rates for each curve is close to 0.4 and above  
• The highest ratio is for PESU, resulting into lowest delta of Rs. 1.085 between the max and min rates of price curve
•  The lowest ratio is for Gaya, resulting into highest delta of Rs. 2.563 between the max and min rates of price
• The Levelised Input Price (LIP) calculated at discount rate of 11.08% is highest for PESU at Rs. 4.154/kWh, followed by Muzaffarpur, with lowest for Bhagalpur at Rs. 3.280/kWh
• Average Billing Rate (ABR) of Gaya is lowest at Rs. 5.310/kWh, revealing greater improvement opportunity for that DF. On the other hand, PESU has highest ABR of Rs. 5.770/kWh
• Ratio of ABR to LIP is highest 1.726 for Bhagalpur, 1.591 for Gaya and lowest 1.380 for Muzaffarpur. (This ratio is static indication of profit margin for bidders, with close to 1.00 value is indication of lower margins and higher risks for DF operator)

Posted by: Kunjan Bagdia @ pManifold

Key amendments in Bihar Distribution Franchisee after pre-bid meeting

BSEB's (hereafter referred as Bihar State Power (Holding) Company Limited (BSPHCL)) organized pre-bid meeting on revised Bihar Distribution Franchisee on 16th Nov. 2012 saw good participation from around 10+ companies. The companies that participated are Reliance Infrastructure, Tata Power, Direct Media Distribution Pvt Ltd, Supreme Infrastructures, Spanco Ltd, Delhi, SPML, CESC, Pan India Network Ltd., Shyam Indus Pvt Ltd, etc. 

This is the third attempt by BSEB to privatize the power distribution in its areas of Patna, Muzaffarpur, Bhagalpur & Gaya. Earlier in 2009, Glodyne Power Limited and CESC were the highest bidder and second highest bidders respectively. Later, CESC became highest bidder as Glodyne was held ineligible for participating in the bid after its partner stepped out of the consortium. In June 2011, BSEB cancelled CESC's bid, saying that it would lose heavily if it awards bid to CESC as the tender was floated in 2009 on the basis of tariff rate of 2007-08. In second attempt, only Essar Power submitted and others refrained from submitting bids due to certain issues on Minimum Benchmarking Price, but as Essar has not submitted formal acceptance within timescale, LOA was cancelled.