Building a data-driven business: Lessons from open data master – Ram Kumar, CDAO, Cigna

Ram Kumar Cigna

Today’s technology is tomorrow’s legacy. There is no silver bullet or a single vendor that can solve all challenges around data and analytics. A hybrid technology environment is therefore a must.

Ram Kumar has a sixth sense for data. For more than two decades, he has been the industry’s go-to data strategist and stalwart for data-driven cultural change. As a long-time advocate for open data, Kumar has also extended his hand to setting global data standards in order, taking a lead role in the development of the OASIS protocol – used by the likes of Google and other bigtechs.

Serving as Chief Data and Analytics Officer at global health insurance and health services giant, Cigna International Markets, Kumar sat down with FST to explore the ethical challenges of unfettered consumer data use, maximising business buy-in for blue-sky data initiatives, and lessons for aspiring digital leaders in building a truly data-driven enterprise.


FST Media: As the tide of data swells within organisations, questions remain as to how insurers can and should utilise sensitive consumer data. While still advancing business objectives, how can insurers ensure they remain ethically above board when using consumer data?

Kumar: Ethics will play a very important role in determining the future of artificial intelligence (AI) and data science, which has been a heavily discussed subject in recent years. You may be compliant with legal privacy regulations when using customer data to develop products or solutions, but ethically it may not be the right thing to do. Ultimately, ethics lie in the eyes of the beholder – in this case, organisations.

Having access to customer data is a privilege that customers give us. They trust that we’ll use it in an appropriate, acceptable, and meaningful manner; we cannot break that trust.


It is important for organisations that are serious about data-driven value creation and monetisation to have a comprehensive and well-thought-out data and AI ethical framework – one that ensures informed decision-making. Finding the right balance between ethics, privacy, and value creation through innovation, data science or AI is very important. It is therefore essential that the core values of the organisation should reflect ethical behaviour as a key value to drive the right culture and mindset.


FST Media: What is Cigna doing to clamp down on unethical practice and ensure algorithmic bias does not compromise or invalidate data insights?

Kumar: As we deal with health data, data ethics and privacy protection is a top priority for Cigna. Reputational damage due to data exposure and misuse is a major risk for us – and history has shown that when a lack of priority is given to ethics, it has destroyed companies and the careers of many executives. We have a sound data and analytics governance framework that incorporates ethical, privacy, legal and regulatory aspects to proactively identify and manage risks and make informed decisions about how to deal with data across the organisation.


FST Media: You were a key contributor to the development of the OASIS global open data standard, widely adopted across the tech sector (including by the likes of Google Maps). What has this experience taught you about creating a universally accepted data standard? 

Kumar: I spent close to 16 years voluntarily contributing to the development of global, open, vendor-independent, and royalty-free data standards by working closely with many organisations, vendors, and independent contributors globally; these are standards that have been implemented globally for various purposes. It was truly an amazing and rewarding experience.

Data is the lifeblood of the business and, to create seamless flows of data across processes and technology systems, data interoperability is key.


It is important to understand that today’s technology is tomorrow’s legacy. There is no silver bullet or a single vendor that can solve all challenges around data and analytics. A hybrid technology environment is therefore a must. This is why it is very important to invest effort in developing a solid technology architecture foundation supported by a data architecture built for data analytics. The architecture patterns should be developed based on a clear set of requirements – business, technical, as well as functional and non-functional capabilities – and should also be independent of technology tools and products to create a plug and play technology ecosystem. The design of such an architecture will prevent technology lock-in and provide the flexibility to replace technology components as required.

FST Media: What else did the OASIS process teach you about delivering an organisation-wide data standardisation program?

Kumar: Data standards are documented agreements on representation, format, definition, structuring, tagging, transmission, manipulation, use, and management of data. They provide the means to promote the efficient sharing of information among different systems and processes in a consistent manner. Data standards also provide vendor-independent interfaces to enable loose coupling of data from technology. This enables reusability of data elements and their metadata that can reduce redundancy between systems, thereby improving reliability and often reducing cost.

Organisation-wide adoption and implementation of data standards – while also ensuring compliance – is critical. The challenge in implementing data standards in organisations is the discipline that is required when ensuring standards are implemented by all programs or projects and that all implementations comply with current and future standards.


FST Media: Your session at the Future of Insurance conference offers guidance to insurers on building data-driven organisations. What does a successful data-driven culture translate to in the day-to-day functioning of a business?

Kumar: It is unfortunate that many in the industry still believe that creating value out of data through analytics, AI, machine learning etc. means an organisation has a data-driven culture. A true data-driven organisational culture is not just about creating value out of data alone. It is about how the ‘lifecycle of data’ is managed and governed effectively and efficiently – one that enables an organisation to organise, enable and democratise its data for consumption to drive activities in an acceptable manner to make informed decisions, create measurable value, resolve conflicts, and manage risks.

If an organisation is able to achieve these, then it has a true data-driven culture. In a data lifecycle, it is only in the “use” component of that lifecycle where you’ll find the role of analytics.

For the above to happen, the culture should be driven from the top, by the board and executives leading from the front and investing in building data foundations that enable and democratise data (e.g. data management, data governance, etc.) for value creation and in building analytics capabilities. Data monetisation (or value creation) should be a critical KPI in an organisation’s balance scorecard supported by data risk management.

Effective management and use of data should also be in the balance scorecard of employees who create, consume, and use data on a daily basis.


It is important to note that building a data-driven culture is not a project or a program, as it does not have an end date. It is a journey and investment that should be seen as building and managing a strategic asset for value creation. Hence, it should not be regarded as a cost.

Data literacy is about the ability to read, understand, create, and communicate data in a business context that is digestible and easy to understand.

While many organisations aim to have a data-driven culture, they often lack an understanding of what it means and how to achieve the objective.


This is where the role of data literacy is an integral component of building a data-driven culture. It’s a skill that empowers all level of employees to ask the right questions of data and machines, build knowledge, make decisions, and communicate its meaning to others. Data storytelling is a key skill as part of data literacy – effectively, explaining the data context in business language. Having people with data storytelling capabilities is becoming integral to any business as we look to leverage data to build strategies for success.


FST Media: With Covid-19 putting a proverbial spanner in the gears of the global economy and business, data insights have become a beacon for organisations navigating their way through the crisis. How has Cigna’s data strategy evolved in response to the pandemic?

Kumar: Cigna was able to leverage its rich data assets accumulated through its healthcare programs, covering domains such as network, clinical, providers, and clients, as well as with our partnership with data providers, to develop and rollout Covid-related insights dashboards with various KPIs to our businesses globally. Using data collected from virtual care programs during the pandemic, Cigna has revamped its business priorities, increasing our focus on affordability by delivering better, more efficient and cost-effective services to our customers and partners.

This includes revamping our digital offerings. During the pandemic, Cigna launched its new health services business, Evernorth, which brings together our vast array of health services capabilities, as well as partners from across the healthcare system – in pharmacy solutions, benefits management, and care solutions. Data and analytics are critical enablers of this business. We believe that this kind of care coordination ecosystem can be effectively deployed, and generate incremental value, by generating insights from data, to understand future healthcare risks for insurers, providers and customers.


FST Media: Serving in a keystone role with cross-functional relevance, you will, at times, encounter resistance to certain blue-sky initiatives. How do you ensure maximum business buy-in for those more out-of-the-box data projects?

Kumar: One of Cigna’s core strategic priorities is to build data and analytics capabilities to drive value creation for the business; it is one area the business has been heavily investing in over the last few years. This is driven by the board and the executive team.

Cigna’s data and analytics strategy covers the following key components: data foundations, analytics, data governance, data culture, talent management, capability development and data value measurement. Globally, Cigna has over 800 analytics professionals who work closely with IT and business to execute this strategy.

As the chief data and analytics officer for Cigna International Markets, I cover more than 30 jurisdictions globally. Identifying and prioritising use cases has become an interesting challenge but a great opportunity to focus on what really matters. I have the full support of my stakeholders who clearly understand the need for strong data foundations coupled with analytics-driven value creation for the business. It is natural that every country chief executive or regional CEO wants to focus on use cases that would create value for their business. However, the CEOs also understand the importance of contributing to the strategic priorities of the division.

To help meet the expectation of our various CEOs, and the executive team of our international markets division, we have built a comprehensive data and analytics use case prioritisation framework.

This applies several key decision-enabling filters specific to businesses and international markets to help us make informed decisions, ensuring a balance between business specifics and our strategic priorities. Any use-case my team executes, the business works with us to operationalise, monitor it, and measure value creation.


FST Media: As a seasoned data executive, what advice would you offer to aspiring data leaders to get the most out of their teams and digital assets?

Kumar: The following are a few key points that aspiring data leaders should consider:

  • Don’t get carried away by the hype created around data analytics, AI, machine learning etc. They’re only a few components of a data-driven culture. Data leaders have a key role in contributing to the creation of an organisation’s true data-driven culture. This is an organisational transformation journey and requires patience, persistence, practical and proactive approaches to drive data-driven value creation by taking the business stakeholders, partners and employees through the journey.
  • Take the business and your stakeholders through the data and analytics capability and competencies development journey. Understand the business priorities well and work with the business closely to identify key focus areas to create value for the business – short, medium or long term, and ensure that while it is critical to focus on value creation use cases, it is also very important to focus on data foundational areas (e.g. data access, data quality, data governance, data risk management) that would enable the use of data to create value. This is an area where business leaders need to be coached to understand that building data foundations is an investment into enabling corporate data assets for value creation.
  • Have a good vision and solid data and analytics strategy. But do not implement the strategy as a ‘big bang’. Go for an incremental approach to implementation by demonstrating data-driven value creation to the business, get the business buy-in and then slowly increase the scope as excitement grows.
  • Continuously push data literacy initiatives in the organisation to educate employees of the organisation. Data storytelling should be a key skill of data literacy – explaining the data and analytics context in business language.
  • Lead by example when leading your team by inspiring them and by providing an environment to bring the best out of them and by investing in their career, capability, talent development and growth.

Ram Kumar was a featured keynote speaker at FST’s Future of Insurance, Sydney 2021 eConference revealing strategies to building a data-driven organisation.