Opportunities and challenges in creating a data-driven, connected, and intelligent digital ecosystem

Data plays a significant role in our decision-making, particularly in business. Statista estimates that global data will reach 180 zettabytes by 2025. But how well are we prepared to harness this data? A survey conducted by MIT Technology Review in partnership with Infosys(that reached out to 255 business leaders) found that 45% of the respondents used data only for fundamental insights and decision-making. This leaves a lot to be desired when it comes to making the most out of data.

Modern organizations feel the need to be able to predict and respond to new and emerging opportunities with agility. Relying on traditional methods of data analysis is no longer bringing in the success they seek. Business leaders are building new AI-driven solutions by partnering with non-conventional partners and the ecosystem with a view to delivering new value-chains.

The highly connected and always-on business environment is conducive to building a digital economy that weaves together unconnected data from different industries and creates a network of collaborators. Such a data economy can support new data-driven products and services and create opportunities for new revenue streams and business models.

The many applications of data ecosystems

Fortunately, the cost of collecting and analysing data are no longer prohibitive. The cloud offers both the technical infrastructure and the business model that makes it cost effective and viable to mine and connect vast amounts of datafrom different sources and build an ecosystem that supports the creation of new solutions that extends the value of data beyond imagination. In other words, it helps monetise data, opening new revenue streams and opportunities.

Let us illustrate this through an example. One of the largest rail transport companies in the US discovered that they were under-utilizingtheir rail network capacity by 40%. To monetize the unused resource, they studied the market and found there was a demand for end-to-end logistic operators. They created an opportunity for themselves by building a transportation hub working with partners and competitors to become a value chain orchestrator for the first and middle mile. This is a good example of a symbiotic data economy.

Ecosystem partnerships can overcome the barriers of disparate data sets found commonly in traditional organizations by enabling a unified and real-time view of data. For instance, during COVID-19, the government and the healthcare industry partnered to track, monitor, and assist patients by sharing relevant data.

Modern companies and are under pressure to prepare their data for ESG reporting and decision making. A data economy provides the necessary access to relevant metrics across the value chain and help in building the ESG data.

Leveraging the data economy

Primaryobjectives of building a data economy are to overcome data silos and finding the path to discovering valuable insights. The executive must believe in the idea and put in place an organizational structure that can support the following key steps to building a data economy.

Move to new technology and infrastructure

Legacy IT infrastructure can pull down an organisation from moving on the innovation path. Companies must invest in new architecture, digital technologies and capabilities that help build secure data exchange, managed data products, and AI/ML-based solutions.

Build a data-driven organisation

The only way to beat competition, particularly the new-age digitally natives, is to view and use data as a strategic asset. Connecting data from different sources both within and outside the organization to discover new opportunities and models is the first step to building a data-centric organization.

Keep the data aligned to your business goals

A data strategy must align with the larger business goals of a company to ensure that the business leaders are solving the right problems with the data they own and manage.

Educating about data and managing micro changes

An organization will fail to deliver on its data projects unless its employees are literate enough about data and its various dimensions. Understanding the ethical, privacy guidelines or the regulatory compliance as well as the capabilities of the different technologies that are used to work with data are essential. The education also helps prepare employees for handling data and working with it effectively.

Data once captured, processed, and linked, can be explored for finding new opportunities, such as building a varied portfolio or to design a new product or drive a new business model. It can be monetized by sharing data and collaborating with partners. For instance, a motor insurance company can extend their data to automobile companies for them to work on automotive features around safety and convenience.

Data economy is the future

If data is allowed to flow freely between industries and markets, it can empower enterprises to create new value-chains and build novel ecosystems that will succeed in the digital environment. The fact that the Cloud, AI, 5G and now the Metaverse are all coming together to drive the possibility of data doing more is something that every enterprise must take note of. With the amount of data being generated today, the only way for organizations to succeed is to build a “managed data ecosystem” that rests on a strong foundation of Trust, Ethics, Privacy, and Governance to drive their sustained competitive advantage and growth.

Authored By: Sunil Senan, Senior Vice President and Business Head, Data and Analytics, Infosys