Embracing Non-Linearity: Moving Beyond ‘Business as Usual’


The world is moving beyond simple and linear automation required for carrying out basic transactions. A more complex, non-linear and converged world driven by data is taking shape. And it is happening quite rapidly.

The need of the hour is to build a holistic approach towards creating a system where even smaller events can lead to bigger implications. New wave of digital can do that and if not exploited in the right way, it will be a gross waste of its potential.

– Shri Vishnu Chandra, DDG, NIC

Government is not immune to this new reality that is disrupting the ‘business as usual’ approach and forcing policy makers to come to terms with it. New technologies like Artificial Intelligence and Machine Learning are exposing the areas of unpreparedness in exploiting data meaningfully and steering us towards a more contemporary and nonlinear version of eGovernance. The realization may be latent as of now, but it will dawn upon us very fast. That’s the way the world is evolving today. We need to be ready when that happens and the time for preparing ourselves is NOW.

The new paradigm makes it quite imperative to build a data layer that can be enhanced by using cloud computing, is amenable for broader and deeper analytics, and can drive micro services in the form of apps. In the current scheme of things, it may be extremely difficult for a single entity to handle all the four essential aspects i.e. data layer, cloud enhancement, analytics and apps. Capacity building as we know today may be apt for a linear world, but innovative ways may be required for coping with the demands of a non-linear reality.

The article was published in the Best of Tech Report, 2019

Building upon the learnings from the GIS domain, I think there are three key areas to focus upon for building capacity for handling and exploiting data.

Breaking the Walls of Data Siloes– AI, ML, Big Data Analytics are forcing government entities to standardize the data for it be uniformly understood across application domains. Take for example, in an outreach drive in the MSME sector, we found variety of industry classifications by different government departments. Nothing much can be done without building a common or standard classification across the concerned departments/ ministries/ stakeholders. The problem is present in almost all the initiatives that involve multiple entities to provide a unified and converged service to the end users.

Conceptualizing Capacity as an Integral Part – It is almost an established fact that IT teams alone cannot drive eGovernance. It may have a bigger role in defining guidelines, driving adherence and ensuring security of data. But beyond that a more open approach to handle and analyse data and drive micro services for the citizens may be required. Let me elaborate upon one area, that of capacity building. Technology can help in capturing the tacit knowledge of process owners, both government and non-government, which may be used meaningfully. Conceptualizing capacity as separate structures of consultants may be relevant as a add on approach in the ‘business as usual’ linear thinking, but it must become an integral part of the core governance structures in the nonlinear reality that is emerging. How can that be done? Can platform-thinking help in encoding policy and processes as integral parts ensuring adherence and security yet involving all. Without taking a holistic approach, government may always lag the technology curve, losing the potential for better governance.

Defining Policies that Support the New Reality – New policies that allow for both sharing of data and ensuring its security and privacy is the need of the hour. What must also be addressed is the flow of data across governance siloes, a common data language and ability to combine or recombine data to form new data points.

The GIS platforms today are in a way driving lot of convergence yet may need impetus in the form of the three essential aspects as discussed, for the user departments/ ministries/ stakeholders to meaningfully exploit data.

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