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.

Challenges in and Levers for success of the 24x7 water supply projects in India

As one wonders what has been holding back the operationalization of the 24x7 water supply projects in India, we thought of penning down our observations around it.

Even before kicking-off the operations, one observes that the long gestation period (5+ years) to engage and realize even first pilot is a show-stopper. This is primarily because of:

• lack of standardization of the model, and various agency issues at Central, State & ULB level
• delays in contract sign-off & getting consensus on SLAs and new Tariff agreement
• Delayed financial closures - constricted investments flow from investors, because of perceived high risk of regulated (& politicised) utility

Levers for Successful Implementation of 24x7 Projects

As the operators take-over and start the operations, the first challenge hitting them in the face is the inaccurate baselines. Revisions in tariff, SLAs, employee deputation follow. The lack of education of customers, employees and local politicians on the PPP models affect all the other stakeholders. 

The nascency of the industry has created an acute shortage of skilled middle management resources that are ready to engage on-ground in Tier-2/3 towns. Further to this, the lack of investment from operators in Strategy, Structure, Systems and Processes, and doing it right from long term perspective creates a totally different shade of problems.

The technological levers of GIS modelling based on low confidence data collection, and fast obsoletion, no useful optimization and design possible. Only static view is captured on GIS and no real  updates happen in the system. Even though water metering (bulk and end-customers) and regular auditing is being stressed upon & invested in, no useful actions are enforced based on analytics. (Power sector has long been metering and doing energy audits, but losses have only increased, because of missing actions. Water is just starting to walk on same trail, and will likely see similar results.)

Finally, there seems to be a total lack of SLAs performance monitoring and enforcement institution. This gives rise to ever-moving targets, and cross blaming.

Overall, currently Management change, and Technology are being stressed upon for the success of 24x7 water supply projects. We believe that there is a need for two additional levers - Performance Monitoring and Customer Engagement, to bring effective Change Management. We strongly believe, that its operationalisation of these models that has to be improved, and rest will follow. 

Limitations of existing baseline data shared for Power Distribution Franchisee bidding

The current approach to furnish baseline information for Distribution Franchisee (DF) RFP undertaken by the utility has following limitations:

1. Very high level indicators (on distribution losses; collection efficiencies; customer mix and connected load distribution, arrear’s for each consumer class, brief count of network assets) are shared with no systematic causal analysis to allow bidders to diagnose network's status-quo for capital investment projection. This hampers calculated and informed bidding to happen.
   
   
2. With highly fragmented databases and lack of integrated measurements & good practices on utility's side, the integrity of the top-level data provided is looked upon with doubt, thus making it highly risky investment for the bidders.
   
   
3. In lack of measurements and system level analysis before bidding, the utilities themselves do not have right judgment about the required expenditure and potential revenue increase the area could give under able DF project time. The arising low confidence let them compromise on various aspects of good contract design and post monitoring and not able to get full benefits of the DF model.

Lack of good baseline data & reporting leads to irrational Power Franchisee bidding

The reported success of Bhiwandi Power Franchisee model has attracted more private players and has increased competition for good of the sector (see our earlier blog on 'Many new corporates entering into emerging Power Distribution Franchisee race'). However the very basis of the Power Distribution Franchisee (DF) contract, the baseline data ('information') provided as part of the RFP (Request for Proposal) is not trusted by the bidders driving  irrationality in the bidding. 

Impact on Bidders:

1. High business risk for the DF due to non-trust worthiness of the baseline data provided by the utility: Crompton Greaves Ltd. (CGL) backed from awarded Nagpur DF tender and in the process wasted 2 years. Company quoted that the base line data provided to them was not correct and its not viable for them to service at their quoted input rates.
   
2. Repeated efforts by all bidders to gain confidence on baseline data: Since utility does not take responsibility of the data it provides in the RFP, it is left to the bidders to figure out this information and speculate their bid with little confidence on their business plan and projected returns.