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“Data and analytics are propelling organisations into the future”, says Vijaya Deepti, in the Leadership Series EDGE Webinar

Published on September 04, 2020

In the Leadership Series EDGE Webinar titled ‘Embracing Data and Analytics to Build the Enterprise of the Future’ on September 2, 2020, P H Vijaya Deepti, CEO of Tata Insights and Quants (Tata iQ), shared her point of view on how newer business models and newer ways of working are being built around data as an asset. Ms Vijaya Deepti, known affectionately within the Tata Group as Deepti, spoke about ways in which organisations are evolving their culture to become data-driven enterprises and how a new mindset of agility needs to emerge – taking thoughts and ideas to quick tests and scaling up successful initiatives. She stressed upon the need to build capabilities of the future – not only focused on data, digital and analytics, but also on governance and responsibly using the power that data can unleash.

Here are the key highlights of the session:

Deepti shared how global companies, which have been leaders in their industries are quickly adapting to the use of data and analytics to augment their proven business acumen and processes. The recent adoption of analytics is so pervasive that it has changed the way we bank, we travel, we get our energy and the way we shop.

Deepti spoke of three themes, which in her opinion, are driving data and analytics adoption and propelling companies into data-driven enterprises of the future:

1. Chase complex problems: Fail, but fast and cheap

Organisations are building cultures where there is freedom to fail. A culture of hypothesising, quickly testing, learning and putting efforts behind validated outcomes helps in prioritising the right initiatives for the context. Building minimum viable products is a great way to gain insights on the significant risks and validate assumptions on the solutions efficacy as one moves along the journey.

Organisations must also build and structure themselves to take rapid prototypes to scale. The skillsets and mindset required is very different, and losing focus on the ability to scale will hinder large scale adoptions.

2. Rethinking processes and metrics

Organisations would do well to integrate the model outcomes of the data analytics exercise with their existing processes, to truly unlock value. A successful analytics initiative is one that is deployed in the process and closely integrated with the systems and people that form the process. Further, it is also critical to ensure that the KRAs and incentives of the stakeholders are aligned to the desired behaviour of consuming the analytics to drive the relevant business outcomes.

3. No company is too small

Size is no excuse. Each company has the ability and the imperative to transform itself into a data-driven enterprise through adoption of digital and analytics. Flexible and scalable infrastructure solutions and capabilities being built on open source tools enable quick adoption in today’s world. Further, companies may also leverage a multi-hop architecture, with a careful selection of systems and processes that need to be in-house, complemented with those external to the enterprise.

Deepti also shared learnings from entities that focus on building and leveraging an ecosystem of partners – to stitch together complementing skill sets and abilities in crafting solutions to large scale or complex problems.

Capabilities of the future – A wider net than we think

Deepti wrapped up the session by stressing that the capabilities of the future go beyond the obvious ones of data, analytics and digital. Enterprise security in the digital world is of evermore importance, with a comprehensive security strategy and risk assessment framework warranted.

The explosion of data has brought privacy into focus, and while regulatory compliance is a given, companies will need to go above and beyond in gaining customer trust – possibly even using privacy as a competitive advantage.

The discussions on the ethics of Artificial Intelligence (AI) are creeping into mainstream conversations, and companies implementing AI need to start being mindful of the implications their models may have. At the very least, it is time to recognise possible biases in models being built, and strive to eliminate them.

The webinar concluded with Deepti responding to several interesting questions from enthusiastic participants on the use of analytics in specific functions and industries, capability and skill development for competencies of the future, and the role of leadership in building data-driven organisations.

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