GDP Mapping Exercise – Illustrations from recent studies

By Surabhi Mall, IFMR Rural Finance

In the previous blog post of the KGFS Model Incubation series, we drew out the implications of mapping the GDP of a branch’s service area on strategic decisions related to district selection, branch potential, product suitability and customer centricity. In this context, some of the pertinent follow-up questions that arise are – How much will this activity cost? Should this capability be harnessed indigenously or simply outsourced? What is a statistically approved research design to follow? This post essentially focusses on understanding the ABC of executing this study with relevant elaborations and learning from the past.

The GDP exercise can serve different purposes and based on the objective use and nature of requirement the scope of the study can be defined. The following two studies conducted in two different districts in Tamil Nadu attempt to illustrate this.

The objective of the first study was to compare the gross potential of a branch in the Krishnagiri district, Tamil Nadu, to that of a model KGFS branch[1] wherein ‘comparable’ was defined as a range with an acceptable degree of error from the estimates of the model branch. In this case, focus of the study was to get the aggregate number and not necessarily its constituents. Simply put, this means that while sector-wise distribution of the branch economy could be insightful, it was not the focus of the study per se. Resources used as part of this included a full-time staff that spent one day in assimilating secondary data, three working days on the field to collect primary data as well as to validate the secondary data. The staff was actively supported by a Wealth Manager at the branch location.

The second study at Ellakuruchi village in Ariyalur district, Tamil Nadu, was done with an objective of profiling the district as well as the branch service area. District profiling required a thorough review of the district’s demography, geography, economic status, main crops, enterprises and occupations. Profiling the branch service area required field insights on aspects such as different occupations that thrive in the area so as to map each economic activity with its volume; cash-flows associated with the occupation so as to map business potential; formal and informal financial providers so as to understand current and potential gaps in the financial landscape among others. This objective required one data analyst responsible for secondary data collection, methodology design, primary data collection, data collation and presentation of the findings. Primary data collection was actively supported by 1-2 Wealth Managers in the field for 6-8 working days. The entire exercise was executed in one month. In order to add greater rigour and sanctity to the estimates, a similar study was executed in another branch in the district.

Below are pie-charts depicting the findings from both GDP studies in Krishnagiri and Ariyalur districts respectively.

GDP Mapping Exercise

One of the big challenges in initiating such a study is that the data records of this kind are not methodical, very contextual and mainly absent from conventional databases for any triangulation. The other concern may be related to the design of the research methodology for the intended purpose of the study. Often, simple doubts such as the size of a representative sample directly impact the resource requirements and rigour of the study. To address these issues simple project management tools such as defining the objective, scope and research design a priori through a clear project plan will be quintessential. In the first study, since the objective was clearly identified as “compare the gross potential of the branch to that of a model KGFS branch,” an exhaustive sector-distribution map of the branch’s economy was not required. Conversely, in the second study, to “profile the district and branch service area”, there was need for profound understanding of the demographic and economic constitution of the area. This in turn required information about the share of each activity in the total economic pie.

In cases wherein the objective of the exercise is to design a customer engagement strategy or an optimal capacity plan for the branch by projecting lean and peak cash requirement periods, activity mapping will need to be extremely exhaustive. This would imply that aspects such as the ‘crop net income’ component of the GDP pie be further broken down to list the main crops, their seasonality, and cash flow projections related to each crop.

It is also important to acknowledge the homogeneity in variables during the study. For example, if a service area constitutes of four villages of 300 households each[2], the economic map of one village can be multiplied to give the macroeconomic map of the branch. This adds to operational efficiency in the execution whilst minimizing scope for error.

Since the KGFS model is designed to entrench itself in the community it serves by developing a deep understanding of the geography, the local culture, the economic activities and dominant customer segments, the GDP exercise is perfectly tailored for the KGFS model. Understanding its benefits as a principal and inaugural step in model incubation and thereby budgeting for the costs involved will lead towards deepening the very foundation of the model.

The next blog post in the series will discuss the heuristics of site selection in a rural village context. By illustrating the KGFS’ experience across diverse geographies, it will attempt to showcase the various components that may play a foundational role in the science of site selection.

[1] The model KGFS branch is conceived and defined based on the KGFS mission, the business requirements and past learning experience.
[2] Unit of aggregation may vary from a household, a village, a panchayat or a block.


District selection and estimating the potential of the KGFS entity through GDP Mapping

By Surabhi Mall, IFMR Rural Finance

This is the first blog post in the KGFS (Kshetriya Gramin Financial Services) Model Incubation series. The objective of the series is to methodically conceptualize an approach to build the branch network while incubating a new KGFS entity or expanding to contiguous districts. The posts focus on themes that range from district selection to identification of branch locations and optimization of the distribution network.

In this post we start with a brief discussion on the choice of a district and later discuss geography-specific questions that influence the economics of the model. Finally, the post stresses on GDP mapping as a heuristic solution to those questions.

Among the early steps of setting up a KGFS model is identifying a district. District selection is mostly a matter of organisational strategy and choice. The choice may be based on parameters such as district’s rural population, its population density, credit to GDP ratio, forest cover, road density, among others. Reviewing these attributes prior to finalising the district provides an elementary sense of the KGFS’s business potential, composition of the product basket in the branches as well as the degree of customisation that may be required to set up the model. Following this, reconnaissance (Recce) of the district provides insights to questions such as – Does the model need any fundamental changes or customisation in the given geography? What is the degree of competition it is likely to face? What is the current status of customers – i.e. their access to credit, income earning potential, and savings or repayment behaviour. This step serves as a final validation to the district selection strategy.

Recce gives field-level insights on the geography and competition in the district while secondary data helps understand the demography and infrastructure availability. Since geography, demography and the availability of credit in a place have significant influence on how the local economy develops, this should provide reasonable understanding of village-level economics and perhaps its influence on the branch’s business. It may even be leveraged to formulate the entity’s business plan, its competitive strategy and the network of branches. However, is this sufficient to understand the requirements and provide suitable comprehensive financial services? Is this information adequate for each branch to realise and achieve its potential volume of business at every life-stage? In fact, how does one quantify potential of a typical service branch in the chosen district? Finally, can the impact that the branch or the entity would have in the economic well-being of people in the long-run be measured? Estimating the branch service area’s Gross Domestic Product (GDP) provides powerful insights in unpacking such questions.

Figure 1: Three steps prior to setting up a new KGFS branch

Why the GDP?

To start with, what do we mean by estimating the GDP of a branch service area? GDP of an area is essentially the summation of different economic activities that thrive and contribute to the economy of that area.

Now, a KGFS stands to ensure the financial well-being of ‘every’ customer and enterprise in the area. This dictates that each customer’s needs be identified, acknowledged and serviced. In this context, the GDP exercise provides valuable insights on the composition of different sectors that thrive in the area. This can then be used to segment customers, identify their respective needs, customise the product basket at the branch and design an apt pricing as well as marketing strategy for them. A deep dive into the village economics through this exercise enables the branch to identify and prioritize customers from occupations with high degree of cash-flow mismatches, i.e. customers who are most likely to benefit from financial services. In effect, all this reinforces the KGFS’ geographic commitment by accounting for all possible households and economic drivers in the area.

The exercise gives insights on the share of existing financial players (from the interest income generated in the area), the median profile of a customer’s household and her debt servicing capacity. At the very outset, these can serve as a filter (post the Recce) to re-assert the choice of the district and the working estimates of the business plan. These estimates can then be built into the annual and monthly business targets for the branch. The activity can also be designed to give a rich sense of actual business that the branch is expected to do, i.e. its market share1. By capturing the share of other formal and informal financial institutions in the area, one can assess the volume of competition. This can then be netted off from the estimated demand for credit, thereby giving the potential market share of the branch.

From an operational point of view, data from GDP can be used to add greater granularities to the branch’s customer management database. It also enables scope for new business development2. For the product development team, it helps estimate occupation-based credit requirement and decisions regarding risk-exposure limits.

More generally, the GDP map helps visualise what kind of financial services are required to increase the size of the pie in the first place. It is a quantifiable measure that may be used as baseline for a ‘village profile’ in order to assess the financial viability and/or impact of a branch.

When – Ex-ante or ex-post?

While the above arguments advocate executing this prior to branch opening, this may not be a binding proposition. One can customize the scope of the exercise based on the objective sought at different life stages of a branch. For example, for an existing, low-performing branch where the enrolled database isn’t representative of the area’s population, the study’s objective can be to capture the economic drivers, re-estimate the branch’s potential and identify untapped business avenues. It may also aid to gauge the share of competition of other players’ vis-à-vis that of the KGFS branch.

However, the maximum utility of the exercise would lie in leveraging it as a diagnostic tool to acclimatize with the new geography of business. Such information, when captured at the very inception stage of branch set-up can greatly aid in understanding the branch’s gross potential and scale of operations, relevant needs of potential customer and perhaps even insights into strategies to thwart current or budding competition. If the GDP study in a branch is conducted at the proposed stage of branch, re-estimation and scoping for new business development through primary studies may then become redundant. Another added advantage of doing this prior is that this can be a part of the branch staff’s training track aimed at familiarizing them to the landscape of the area.

In the long run, a time-series GDP exercise process– prior to branch opening and ‘x years’ post branch opening is perhaps going to be the only real indicator of branch performance. Branch performance in this case will not mean the business at the branch but perhaps the change in (composition of) GDP of the service area and the impact of the KGFS branch on the lives of the people3.

KGFS Impact Long Run = f (actual business and type of customers served by the branch, increase in GDP share contributed by those served in the area that can be exclusively attributed to KGFS’ operations between KGFS0 & KGFS1).
[KGFS0 – is the GDP estimate from the study in time period 0 (prior to branch opening) & KGFS1 – Is the GDP estimate from the study in time period 1 (post x years of operation)]

The next blog in the series is on the Activity-based Costing of the GDP exercise. Through the lens of GDP studies done in the past, it will attempt to provide indicative answers to questions such as time and resource costs of the exercise.


  1. Market share of a branch estimates the actual served market/sales of a branch. This addresses concerns such as market cannibalization.
  2. Based on forward and backward linkage of value chains in the area, loan purpose and occupation type, unexplored segments, etc,.
  3. This estimation needs to account for fixed effects.

We recently hosted a series of knowledge management sessions (Spark Spring Edition 2015), as part of which Surabhi presented on this topic. In her session titled “Gross Domestic Product Mapping”, she spoke on how GDP Mapping can provide an intensive diagnosis of a defined location and how it can be used in a research process aimed at providing richer, robust and relevant information about markets, variables and potential.

View the presentation from her session below:


Field Report on the Impacts of Cyclone Phailin

By S.G. Anil Kumar, CEO, IFMR Rural Channels

The twin calamities

A few weeks ago, Bindu and I visited Dhanei KGFS that serves the districts of Ganjam and Khurda through a network of thirty branches. While we have visited our operations in these districts on several occasions in the past, this time it was to understand the impact of two significant natural calamities – a massive cyclone called Phailin which made its landfall close to Berhampur, the KGFS headquarters, followed by flash floods just a couple of days after the cyclone that inundated vast areas and destroyed plantations and standing crops.

We set out to visit our branches with Manas Ranjan Pani, the Head of Dhanei KGFS. During the drive, he informed us that power had not yet been restored in almost 50% of the branches. Thanks to the elaborate precautionary measures taken by the local administration, the damage to the life and livestock was minimal. However, on the way to our branches, we saw the damage to property and crops was substantial. Standing crop has been damaged, some of the houses and compound walls of several buildings having collapsed, several electricity polls lying on the ground completely uprooted. We also saw brisk activity at several places in trying to erect electricity poles or laying of temporary roads so as to restore some of the infrastructure.


KGFS branch experiences

The first branch we went to was in “Ranajhalli” Panchayat comprising 1986 households and approximately 9000 people. In the branch, we met two bright and young wealth managers – Uma Charan Sahu and Sujata Kumari Dash. While there was no damage to the physical structure of the branch, only the facia and the connectivity tower had to be replaced. Electricity was still not available in the branch and hence there was an off-line process that was put in place.

We were informed by our wealth managers that the people are predominantly engaged in agriculture and allied activities with paddy being the main crop. Several of the households also had lemon orchards and mushroom cultivation. There was also a significant portion of migrant population from this village, living outside. Given the calamities, there was extensive damage to the standing crop, which in turn affected the immediate cash flows of the household, especially in the case of lemon and mushroom farmers. What baffled us was that a vast majority of our customers have still managed to continue servicing their loans even post the two events. Some of those who have not been able to pay their instalments came to the branch to inform of their inability to pay and have sought some time to pay back. When we enquired about the source of income for people in these villages, we were informed that people either are going for daily wage labour mainly in clearing the trees either on roads or in the farms or are getting remittances from their family members residing outside. We were once again reminded about the amazing financial discipline of our clients.

After a brief conversation with the team, we set out for a walk into the village. It was tragic to see paddy fields on either side of the road completely damaged with stagnant water still in the fields. Not too far from the branch, we saw a farm of arecanut trees, with most of the trees having been damaged. We were told that the wind speed reached a peak of 280 KMPH – just short of a super cyclone and the frail trees could not take the intensity of these speeds. We were told that an arecanut tree takes about seven years to grow before it starts yielding returns to the farmer and the income from each tree is about Rs. 1200/- per annum. While we were still recovering from the shock of seeing a completely damaged farm, the owner of the farm – a brave man in mid 40s named Sadanand Samal came in his bicycle. We didn’t know whether to sympathise with him or appreciate his resilience. He seemed to have reconciled to the damage and the loss he has suffered in matter of couple of days. He mentioned that the arecanut trees that have all got destroyed are around 12 years old and he has to plant all of them again, for which he might have to invest around Rs. 400,000/-. His only diversification was his intercropping, where he also grows seasonal vegetables and gets some cash flow.

We then went to another branch located in the village Pandia. The branch is set up to serve around 2180 households in a set of villages, with a population of around 13000. There we met another young team of Ajit Kumar Dalai and Santosh Kumar Swain. This branch was also operating without electricity. The wealth managers shared their experiences in the aftermath of the cyclone and floods, which was very similar to what we heard in the first branch. We were told of a particular customer whose entire stock of fertilizers got damaged as flood waters entered his shop. Fortunately for him, he also trades in steel, which is the only source of his income at this point in time.

Insights for the future

The journey back to the HQ was on how to respond to the financial requirements of our customer households and how do we work with them in re-building their livelihoods and assets. While we are able to insure customers discretely for life, disability, livestock and shop, an event like Phailin requires more comprehensive catastrophic insurance covers for institutions like Dhanei KGFS. We also discussed the need for proactive action to support the small businesses in the region by providing additional credit facilities. There were also important lessons on managing political risk. In certain branches, there were requests for “loan waivers” made by politically connected individuals. The Dhanei team dealt with this by maintaining constant communication with their customers and not getting drawn into negotiations with third-parties.

Back at the HQ later that day, there was a felicitation event organised to recognize the exemplary courage and conviction shown by the team members, some of whom are just a few months old in the organisation. Several of them went above and beyond the call of duty to be available for customers in the branches, in their village enquiring about their safety and security and offering support. We heard stories of how some of our Wealth Managers walked several kilometers to keep the branch open, one of the Wealth Managers reporting for duty despite being injured in the cyclone, people cutting short their personal leave and the leadership team visiting several branches and customers to remind them of our commitment to the region.


Lok Capital and Proparco invest $5 million in IFMR Rural Channels

Lok Capital, a venture capital firm, and one of its limited partners, Proparco, the private sector investment arm of the French development agency AFD, have together invested $5 million in IFMR Rural Channels.

Lok Capital’s series A investment in IFMR Rural Channels, which will be paid out in a single tranche, will be used for building Kshetriya Gramin Financial Services (KGFS) which offers financial services in remote rural locations.

KGFS as an entity aims at delivering a complete suite of products and services to ensure financial wellbeing of households and enterprises in remote rural locations under its unique wealth management approach. At present the KGFS network has 110 branches that serve about 200,000 households in Tamil Nadu, Orissa and Uttarakhand.

Commenting on the investment, S.G. Anilkumar, CEO of IFMR Rural Channels and Services said, “Lok and Proparco’s investment in IFMR Rural Channels and Services (IRCS) indicates their alignment with our mission of delivering high quality financial services in a way that has a profound impact on rural households. This investment also validates the sustainability of the KGFS Model that believes in the core philosophy of adding value to the customer and thereby becoming valuable as a business. With this infusion, we envisage further expansion of the KGFS Model to other remote rural locations across the country in a phased manner.

Click here for: Press Release || News Article


IFMR Rural Channels launches Thenaaru KGFS

Close on the heels of launching its fourth KGFS, IFMR Rural Channels launched its fifth KGFS yesterday – Thenaaru Kshetriya Gramin Financial Services (KGFS) which would be serving the districts of Pudukkotai, Karur and Namakkal in Tamil Nadu. The first branch has been opened at Nagarapatti in Pudukkottai District.

As an entity KGFS aims at delivering a complete suite of products and services to ensure financial wellbeing of households and enterprises in remote rural locations under its unique wealth management approach.

Apart from the recently launched Thennaru KGFS & Vellaru KGFS, the other operational KGFSs include Pudhuaaru KGFS (Thanjavur, Tamil Nadu), Dhanei KGFS (Ganjam, Orissa) and Sahastradhaara KGFS (Uttarakhand).

Images from the Nagarapatti branch launch: