It’s time to integrate data within municipalities
Excerpts of an interview with Dr Anjali Karol Mohan
There is a lot of excitement around urban data and its merits are visible; yet, there is a gap between what is being discussed as potential and, what is being practised, says Dr Anjali Karol Mohan, an expert in urban e-governance. In over two and a half decades of practise and research, Dr Mohan has engaged with various urban planning and urban management exercises, evolved planning tools, and evaluated plans to provide inputs to policies and effective planning exercises. Currently, Dr Mohan is curating a two part seminar series (at the EAFIT University in Medellin, Colombia and NLSUI, Bangalore, India) that aims to address planning challenges faced by cities in the global south. Dr Mohan is a visiting Faculty at the National Law School University of India, Bangalore, International Institute of Information Technology Bangalore, and Takshashila Institution.
1. Recent governance dialogues revolve around data driven governance and its benefits. What in your opinion are the main challenges in implementing data-driven governance in the urban or rural space?
In my opinion, there are two challenges; one is the data itself and second, the people who will be using that data.
The first challenge lies in the lens through which data is viewed by different scales of governments and, by extension, the manner in which the data will get utilised. Therefore, although large datasets are being produced and collated by various governments, departments, and hierarchies, the scale, granularity, and periodicity of that data is from a particular lens. This might make it not so useful for other stakeholders. For instance data produced by State departments, for instance, to monitor local governments, may not be required by municipalities and panchayats whose roles and responsibilities are different. The second challenge is, who are the people using this data. There is a gap in capacity in terms of using data in a consistent and lucid manner so that it enables decision-making.
While the first challenge might be resolved if we unpack and understand the requirements of different lenses, but the second is a much more daunting challenge. This is where one needs to get functionaries and managers in various arms of the government into the habit of looking at data to inform their decisions. This not only requires building their capacity, but also increasing their will power for the same.
2. Is there a greater possibility of data usage by different stakeholders if data culture is institutionalised to some extent by target-oriented reforms?
Data generation, capture, analytics (as we understand it today in the context of the technology revolution), and its utilisation are not systemically embedded in governance structures and processes. There is a lot of excitement around data and perhaps people are beginning to see the merits of it. But there is still a gap between what is being discussed as potential and what is being practised. There are arguments that technology-driven data culture demands a generational change, i.e. next generation of city managers are more likely to be tech savvy and hence, better equipped to appreciate the relevance of technology in generating and collating data, converting that data into information, and eventually to knowledge. But I think that the new generation will only be able to do it if they are capacitated in a manner where data-driven decision making is the only choice. This requires not just conventional approaches through training programmes, but also a change in work culture, habits, and practices.
Having said that, I have come across several municipalities where data entry operators, typically from a younger generation have begun to comprehend the efficiency that a computer brings in, and are taking to technology even if it requires them to leverage their own personal resources.
From your experience, how do cities perceive capacity building efforts, especially efforts that emphasise the creation of new positions in municipalities, such as city data officers?
Historically, within the states, skill sets that can engage with technology and tech-enabled data are lacking. Attempts have been made to implement municipal reforms in various states — Karnataka has been a front runner in this. Similarly, there is a digital presence in Panchayats too. Commensurate with these reforms, is the hiring of data-entry operators/programmers and setting up of data cells. This is an ongoing effort. Notably, in several places, staff associated with the data cells are employed on a contract basis (although I am given to understand that recruitment and cadre rules are being modified to embed these skills within the state). While it may serve the purpose of initiating technology driven reforms, in the long run, my experience (and research) shows that the data cells do not get integrated within the municipalities. In effect, these emerge as parallel systems. It is about time that measures are initiated to ensure integration of data and data-related functioning within the municipality. This has far reaching implications on accountability mechanisms, which tend to get compromised in the presence of parallel systems.
3. Do you think that the Smart Cities Mission and other technology-focussed initiatives are able to bring convergence between the State’s perspective of why they need data and the municipality’s perspective of how efficiently they can use the data?
That the Smart City Mission has foregrounded the need for data (incl. data-cells, observatories, etc.) as critical to urban development and management cannot be denied. There is a flurry, at times incomprehensible, around data production and collation. It is happening at several points. However, I maintain that data requirements from various lenses need not necessarily converge. The need for varying data-sets at different scales of government cannot be questioned. There can be multiple points of data generation, collation, and utilisation, as long as there is clarity on the purpose for which data is being generated and analysed. For instance, in cities, data generated at ward level needs to reach the municipality to facilitate decision making. The State government may apply its own lens to view/collate this data — like seeing how one city is performing in comparison to the other.
We need to understand that technology has this inherent tendency to centralise actions. I am not for a moment arguing for or against centralisation or decentralisation. Both are required. One to the exclusion of the other is not advisable. However, where centralisation is appropriate and where decentralised interventions/actions are more relevant, needs to be unpacked carefully. For example, beneficiary selection for welfare programme in rural areas is a function best performed at the lowest level of governance. Usually, selection is based on the Socio-Economic and Caste Census (SECC), 2011, followed by Gram Sabha verification. Yet, of late, we see State Governments using technology to directly select or indirectly impact beneficiary selection processes. This is dangerous.
4. There is an increasing emphasis on data for decision making, whereas entirely data-driven decisions can have their own biases. How should the discourse position itself so that we have enough checks and balances built into the system itself?
Institutionalisation of data can start to, in some sense, institutionalise decision-making. There will be a record of why a certain decision was taken and what the implications would be if we were to reverse this. The precaution that needs to be taken here, is that the data needs to be very relevant and context specific. That can only happen if we align principles of decision making with the idea of subsidiarity. That is what the decentralisation agenda is all about.
If the local government has to take an informed decision, the most relevant data is what is generated within its jurisdiction. It is a hugely positive step if a decision-maker is able to visualise data and then utilise it, to frame problems and challenges, and seek appropriate solutions / redressal mechanisms. In the discourse about data, observatories, and decision making, the lack of emphasis on the need for contextualisation, is the reason many cities are not able to move ahead on data-driven decision making.
5. Do you see the National Urban Policy Framework, currently being finalised, likely to emerge as an enabling tool facilitating data-driven urban governance?
The NUPF is still in its making. Notably, it recognises the prerogative of the State as far as local governance is concerned. It can provide a critical space for data-driven decision making by triggering the need, incentivising it, and further creating opportunities for State policies to do the same. While planning and governance are viewed as two different processes, these are intrinsically connected. The NUPF attempts to bring these together, but I don’t think it goes far enough. The NUPF should ideally incentivise proactive planning, and make data-driven decision-making a part of that narrative. How exactly it would be implemented should be left to State policies, as contexts vary across states. The NUPF needs to create this space by providing a broader framework for proactive planning with data as one of the dimensions which will inform both planning and governance.