On a sultry day somewhere in rural India, three individuals are hard at work. A field salesperson employed by a Fast-Moving Consumer Goods (FMCG) major is on her smartphone - checking promotional offers, scanning sales tips, reviewing inventory and planning her day. The ASHA (Accredited Social Health Activist) worker fills her diary to enter data from her daily household visits where she meets and counsels village women. A teacher in the local Government school reconciles attendance information in her register and mobile application, as it is due for submission the same day.
Data pervades our society. In May 2017, The Economist did a much-discussed cover story on how 'data is the new oil'. Are public services like health, nutrition and education in rural India geared up to use this resource to optimise service delivery?
Let's start with health and nutrition. In our villages, these services are primarily delivered by the three Government frontline workers - ASHA, Anganwadi Worker (AWW) and Auxiliary Nurse Midwife (ANM). They collect and store a lot of data in multiple, voluminous registers and in some cases on mobile applications - surveys of households and residents, health status, antenatal care services, rations, attendance at the Anganwadi, immunisation details, child growth over time and more.
Consider education. Teachers in Government-run schools maintain records related to demographic information, attendance, lesson plans, mid-day meals. Student marks and progress are also collected, recorded and forwarded to the relevant authorities. Again, some mobile-application solutions have begun to facilitate this process.
In both cases, one notices that data is viewed from a collection lens. Ultimate service providers (frontline health workers, teachers etc.) see data as something to be obtained simply to meet reporting requirements. It is not unusual for data collection to be prioritised over service provision. They also tell you that the data collected is used by senior officials. However, there is hardly any conversation on data usage by the frontline workers themselves at the village-level, where services are delivered. While data collected flows upwards through the system, it seldom returns to the grassroots in the form of information or market intelligence that will enable providers to better serve their constituents.
Now, consider the FMCG sector. Customer satisfaction is all-important, competition is high, and organisations need routine feedback to get a competitive advantage. Field salespersons play a key role in obtaining data and feedback from retailers and consumers. However, their role goes beyond collection. Data reported by them is analysed and returned to them as insights that enable them to better target and serve potential geographies and channels. They are routinely fed information on promotional offers, target geographies and partners, inventories, competition's moves and the like. Thus, data flow here is two-way: salespeople report data and receive insights to do their jobs better.
Field data informs decision making in business and Government services. However, there is a key difference. In business, it takes place through the system. For instance, field salespeople are usually assigned a beat plan - a route map of stores that they must visit - by their local managers. Data collected by sales people is thus helping them plan their day better. In Government, data analysis is largely at the senior levels. Supervisors from various departments could be fed in insights to explore the possibility of creating data-driven dynamic beat plans for themselves and their teams. Frontline workers could be fed insights to prioritise services on high risk beneficiaries.
"Can village-level service providers really understand and work with data? Several of them are not even well-educated!" - one often encounters such scepticism. My experience has been different. In Rajasthan, The Antara Foundation (TAF) works with ASHAs - community mobilisers in each village (serving 1000 people) responsible for mobilising the community to the Government health system. ASHAs are expected to visit ten houses each day to counsel beneficiaries and families on health needs and events - they typically visit houses in a serial order: 1-10 on first day of a month, 11-20 on the second day and so on. In this system, it is quite likely that someone in say, house 136, wouldn't be visited for two weeks even if they needed it more than someone in say, house 27. We worked with ASHAs to create an algorithm representing a hierarchy of services in order of criticality using data from their diaries - for instance, houses of new born children (first six weeks), malnourished children, pregnant women at high risk would be visited on priority and more frequently. This algorithm feeds into a monthly household visit scheduler for the ASHA. While ASHAs initially required handholding for a few months to grasp the new system, many are now adept at preparing and working by micro-plans they create using the data they collect.
Success of Government programs and schemes is contingent on frontline service providers at the village level. Across departments, India has an enlightened structure with service providers in practically every village. Training apparatus also exists. It is time for the Government to take a leaf out of the FMCG sector's book and upskill frontline workers to use data. Let data collected from the field go back to the field as insight. Go back to the three women mentioned in the first paragraph - why should the ASHA and teacher be mere data collectors when they can be users like their FMCG field salesperson friend?
(The writer is the CEO, Antara Foundation. He has worked in management consulting with Arthur D Little and KPMG)
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