By Aman Kabra, Analyst, MIHM
Availability of essential health products at retails outlets (pharmacies and chemists) in rural areas across India is poor (Maiti, Bhatia, Padhy, & Hota, 2015) and is a major barrier for improving healthcare access (Batliboi & Tambe, 2014). The two major drivers of low availability are – (a) smaller assortments at retail outlets, i.e., some products are never available for purchase by the end consumer, and (b) poor service levels, i.e., even products in the assortment are stocked out more often than urban areas.
Our extensive primary data collection and field observations reveal the following underlying characteristics responsible for the low availability of health products in rural areas.
- Competitive dynamics: In the traditional distribution model, a pharmaceutical company typically procures its products from contract manufacturers, stores them in a central warehouse, and ships them to stockists/wholesalers/distributors (typically 2-3 distributors per district). The distributors then deliver the product to the retail outlets at the district and tehsil level through their own employees (distributor linesmen). A large number of supply chain entities, each entity adding its own margin puts pressure on the margin for the retailer. Lower profit margins disincentivize retailers to purchase and stock health products at their premises. Also, very few distributors serve the rural markets which reduce the options for retailers and their bargaining power.
- Logistics dynamics: Rural markets are small in size and are geographically dispersed; only 13% of the 6.41 lakh villages in India have a population of more than 2000 (Indian Census Data, 2011). In addition, they are also typically remotely located from urban centers where most distributors are present leading to high cost of last-mile delivery and overall distribution cost (Madhavan, Saharia, & Malhotra, 2019). Distributors are, therefore, reluctant to physically deliver goods to these rural markets, forcing rural retailers to pick up the products themselves from distributor warehouses often leading to high opportunity costs.
Several organizations have piloted alternate distribution models to improve the availability of healthcare products within rural areas by overcoming these barriers, primarily by reducing the number of entities in the supply chain. These models typically engage village residents as last-mile carriers to serve their geographical market, which has two main advantages: (a) they built a rapport with the retails outlets by talking in conversing in local language and understanding the retailers’ requirements, and (b) they increased awareness among the end-consumers via marketing campaigns and public interactions by leveraging their understanding of their own communities. In addition, it also encourages entrepreneurial activity in rural communities. We describe three such prominent interventions below.
In the ITC eChoupal Rural Health Initiative (Verma, 2011), the appointed “Village Health Champions” (VHCs) across 66 villages in Uttar Pradesh leveraged the already established e-Choupal network to improve the availability of partner manufacturing firms’ health products for diarrhoea management. The VHCs’ marketing campaigns, under the supervision of “Channel Health Champions” (CHCs), heavily influenced the rural purchase of a range of primary health products by the rural population.
The Arogya Parivar programme (Novartis, 2014), a for-profit initiative by Novartis, also became an essential public health tool operating in 10 states across India. Each “Health Educator” covered a few villages every day and ensured timely availability and public awareness of primary health products. These health products were packaged in small and affordable size, ensuring the affordability and adaptability from the rural public’s perspective.
In the Hindustan Unilever’s Project Shakti (Narsalay, Coffey, & Sen, 2012), local women or “Shakti Ammas,” who were recruited as salespeople, purchased the products from central locations and distributed to thousands of villages. With help from their husbands (called “Shaktimaans”), the 45,000 Shakti Ammas were able to reach approximately 3 million households every month.
However, there is a lack of detailed evidence on how these models modified the incentives of supply chain entities and what was their impact on product availability at the retail outlets. We, therefore, studied a similar alternate distribution model (termed as the carry and delivery distribution model) for Oral Rehydration Solution (ORS) and Zinc tablets and syrups, which is the recommended treatment for acute diarrhoea in children from 2 months to 4 years of age. The intervention was implemented over two years across two northern states of India (Uttar Pradesh and Bihar) by three independent agencies promoting and distributing ORS and Zinc and was funded by an international foundation.
Figure 1: Value chain comparison of Traditional Pharma model with carry and delivery model Note: The number in the rectangular box upstream of a supply chain entity is the cost incurred by that entity, and the one downstream is the price obtained upon selling. Values in square brackets represent margins for the corresponding supply chain entity and the values in green represent the percentage margin. Percentage margin (at a supply chain entity) is calculated using selling price as the base. The margin numbers (& percentages) at the centres of the arrows are corresponding to the supply chain entities present at the same lateral level. |
In this carry and delivery distribution model, a designated pharmaceutical partner procured the health products from manufacturers and marketed as well as distributed them to retail outlets through field representatives (commonly called Field Officers or FOs). We conducted key informant interviews and surveys to understand the underlying economics at various stages of the supply chains and to draw a comparison between the traditional pharma model and the carry and delivery model. Figure 1 below captures the comparison between the two models and highlights unit margins for various players across the distribution chains.
We see that the margins for retailers were higher under the carry and delivery distribution model to incentivize them to order larger quantities and thereby improve availability. Despite the slightly lower margins to the pharma partners in the carry and delivery model (refer Figure 1), the higher volume ordered by the retailers was meant to compensate the per unit lower margin for the pharma companies. Adopting this model removed the dependency on the wholesalers and eliminated a bulk of operational hassles, such as wholesalers’ discretion-based supply to “favoured” retailers and unnecessary travel for the retailers to pick up products themselves from warehouses. Moreover, the FOs being the direct point of contact with the retail outlets are well-placed to gain a thorough understanding of the end-consumers’ healthcare product needs. As seen in the Novartis Arogya Parivar Programme, a sound understanding of low disposable income in the rural areas helped tailor the health products to the needs of the underserved rural population by introducing the same products in smaller quantity packaging.
Despite these merits, we found that the actual performance of the carry and delivery model may not be substantially better than traditional pharma models. The increased dependency on the carriers (FOs) and the thin margins for the pharma partners pose certain limitations. There are, however, specific ways that can be explored to increase the overall availability and sales of health products in the carry and delivery model.
Increasing FO productivity: Figure 1 does not illustrate the additional operational costs of “carry and delivery” activities in the carry and delivery model, which have to be conducted by FOs instead of the retailers. Improving FO productivity, therefore, plays a significant role in driving down the unit delivery cost. In the ORS and Zinc intervention, we found that the FOs waste about one-third of the total working time in a day in non-productive activities. Significant improvement in FO productivity may be brought about by organizing FO deployment in a more organized manner. If the FOs visit retail outlets as per accurately prepared daily beat plans, then not only can the travelling time be reduced, but unproductive visits can also be minimized. Efficient planning can lead to optimal routes, more productive visits, and thus, more sales per visit. This, in turn, requires the ability to estimate demand at retail outlets, which is not necessarily the same as sales due to stockouts (stockouts do not necessarily represent high demand; low availability can also lead to fast stockouts at retail outlets).
Introducing Basket of Goods (BOG): Since the travel cost associated with distribution to an area is fixed, a higher volume can reduce the average unit distribution cost. A way to achieve this higher volume is to include multiple products in each transaction of the FOs with the retailers. The BOG concept could be introduced, in which FOs would sell additional health products along with the primary health products to generate more profits. In addition, layering the primary BOG with other secondary health products would help further improve the commercial viability of the last mile distribution chain due to the apportioning of the delivery cost among multiple products (Verma, 2011). In the case of the ORS and Zinc intervention, the BOG concept prompted retailers to buy ORS and Zinc products in addition to the other products that they were already buying from the FOs, resulting in more ORS and Zinc sales per visit on an average. BOG design needs to be informed by a combination of analytics and local knowledge of the FOs through feedback from retailers. Analytics, in this context, needs to include various competitive characteristics of different products, including unit margin, weight per unit volume (higher the weight per unit volume, higher the unit transportation cost!), and the scale of demand.
In summary, we find that no one distribution model seems to clearly dominate over the others in an absolute sense in terms of performance and product availability. However, each of these models may have several components that can be optimally designed to improve their performance. This will require, rigorous evidence obtained through carefully designed field experiments instead of ad hoc pilot implementations.
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References
Batliboi, S. M., & Tambe, S. (2014). Conceptualizing a Model for Improving Access to Medicines in Rural India. https://doi.org/10.1177/0972063414548556
Madhavan, K., Saharia, A., & Malhotra, A. (2019). Indian Pharma Companies Need Supply Chain Transformation. Retrieved 30 August 2019, from Pharma Focus Asia website: https://www.pharmafocusasia.com/strategy/supply-chain-transformation
Maiti, R., Bhatia, V., Padhy, B. M., & Hota, D. (2015, October 1). Essential medicines: An Indian perspective. Indian Journal of Community Medicine, Vol. 40, pp. 223–232. https://doi.org/10.4103/0970-0218.164382
Ministry of Home Affairs, & Government of India. (2011). Census of India Website: Office of the Registrar General & Census Commissioner, India. Retrieved 1 October 2019, from Office of the Registrar General & Census Commissioner, India website: http://censusindia.gov.in/2011-Common/CensusData2011.html
Narsalay, R., Coffey, R. T., & Sen, A. (2012). Hindustan Unilever: Scaling a cost-efficient distribution and sales network in remote markets. Retrieved from https://www.accenture.com/_acnmedia/accenture/conversion-assets/dotcom/documents/global/pdf/dualpub_23/accenture-unilever-case-study.pdf
Novartis. (2014). Arogya Parivar: healthy family in rural India. Retrieved from https://www.novartis.com/sites/www.novartis.com/files/Arogya-Parivar-fact-sheet_2014_final.pdf
Verma, G. G. ITC eChoupal Rural Health Initiative: End of Project Report. , (2011).
