Top 15 - Field analysis of Customer Indexing for a Utility Company

GIS based consumer indexing is one of the effective tool to improve the complex network of consumers for the utility company. The complexity of network and minimal baseline data available, the utility needs to take substantial efforts on field to create a strong database of the consumer.

While working with a major water utility in India, some of our observations are listed below. These observations could help in creating a strong database of consumer.

Problems & Resulting Issues:

A) Systemic Problems (arising due to problem in process/system)

• Background and purpose not clearly defined which is essential for correct inputs and improve the quality of data. 
• Lack of strong processes and system base implementation for customer indexing
• Recruitment of low quality people for on-field surveys which leads to lack of presentations skills, confidence, convincing capabilities, etc.
• No processes for submission of on-field data which results in faulty batching of data and missing of survey forms
• No regular updates of data (Monthly or Quarterly)
• Lack of effort estimation and resource allocation which results in exceeding deadlines and duplication of efforts

B) Data Collection Problem (Due to Presentation / Understanding / Customer Support)

• Wrong plot markings of property polygons in GIS base maps
• Incomplete information filled by surveyor to achieve the daily target
• Missed out consumers and properties by surveyors
• No validation of Consumer Indexing process compliance by surveyors who are doing mistakes on field
• No continuous tracking of surveyor records and inputs
• Management of surveyors becomes difficult due to high attrition rate on-field
• Difficulty in categorizing registered, unregistered and no-connection Consumers 
• Lower level supervisors tackling the issues arising out of political influence may create unwanted barriers

Recommendations:

- Create a strong stakeholder (internal & external) agreement on what is required output of the consumer indexing survey
- One of the most effective ways to ensure high quality of data collected is to emphasize more on re-validation of the data by a field team
- Preliminary survey by taking GIS base map also helps to minimize GIS related issues on-field.
- On-field continuous training and quality monitoring of surveyors which will help minimise mistakes at ground level
- Appropriate costing and effort estimation is required for timely delivery of data
- Frequent updates of data is important which will help resolve to bring consistency in data

Prologue:

A systematic execution of customer indexing creates a whole new intelligence about the local variables. At the same time it can suggest strategic interventions which could be used for creating a positive cash flow for the utility.

Before you start consumer indexing...

There has been a huge hue and cry about the unavailability of consumer data with the Indian utilities. However, the question that needs to be asked is that whether we have really made an effort to collect the right data set? And if we have, do we have the processes to continuously update the database and maintain it?

In this post, I've tried to list down baby-steps that would go a long way in creating a reliable and comprehensive customer database through the Consumer Indexing (CI) process.

# 1 Create consensus on how the data is required across the teams within utility 
A lot needs to be done to really come to a common consensus across the utility stakeholders about how the utility plans to use the consumer data, not just to create a database because it's a mandate in the contract. This would also require the utility to project and decide how the data will be maintained finally when the utility operations smoothen up in due course.

Further, one also needs to take a call on what data is the priority and when and how it will be collected.

# 2 Create a methodology to collect the data
Now, most widely used methodology currently adopted is the consumer surveys or consumer indexing, as many call it. However, the whole process is extremely tedious and static. One needs to think destructively to really create a methodology which will be, not just fast, but also reliable enough to feed data continuously to the other internal teams. 

This could encompass use of social media to really entice and engage the customers to voluntarily post their data and update their data.

What precaution needs to be taken is to adopt a infrastructure to really accept data from multiple sources and consolidate the same into one piece of data.

# 3 Support systems needs to be designed and put in place to receive and organize the customer data
As the process of consumer data upgradation picks up pace, the utility should really be ready to receive huge chunks of data from various sources - viz. legacy systems, new connections, on-field checks, consumer indexing process, social media, etc.

I believe that MS Excel is fairly strong a tool to manage such data, provided the data structure is correctly created. At the same time, appropriate end-to-end integration needs to be done for the data collection methodology.

# 4 Selecting the right tool for the right data
GIS systems, though being one of the latest of technologies adopted by the utilities, has a major drawback. The data once imported into a GIS system is static. A GIS system will always take only that data as input that you'll feed to the system without doing any sanity check.

Now this creates a major loop hole in the system that can only be fixed by selecting a robust tool for data collection. This tool should also take into account that at times, the data might need to be collected from the field. Our experience in the field of customer data collection has proved that even a simple smart phone integrated with web-based forms is good enough. However, a well-designed consumer survey form is the easiest of all techniques used to initially populate the customer database.

Once the base-data is ready, the Billing Centers and Customer Care Centers should be developed to act as the nodal touch-points to gather the customer data on a more regular process.

# 5 Create the right training and monitoring modules
Even with the best of the methods and tools, without a systematic training and monitoring methodology, a good consumer indexing process could go for a toss. Right tools for training, and data audits are indispensable parts of the CI process

One of the speakers at the recently concluded India Utility Knowledge and Networking Conference (12-Feb-2013, New Delhi) pointed out that the utilities will go slow when it comes to adoption of technology and partner with smaller, local players to help them roll out the operations. We believe that there is a whole lot of internal thinking that needs to go in to really ensure that the utilities hit the ground running. Lack of clarity from the utility, coupled with the inefficiencies of the local players could kill the effort spent in the consumer indexing process.

Further readings: Putting your best foot forward - Best Practices in Consumer Indexing

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.