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Collective intelligence - Moving from data silos to data networks

15 minute read


Our ability to leverage technology to extract knowledge from data is evolving. In the first of our article series on collective intelligence, we explore the game-changing shift from data silos to data networks.


What is collective intelligence?

Data has become the most valuable asset for organizations globally to improve their services and operations. The information economy is growing as organizations make substantial investments to unlock an edge. Over the next decade, the success of an organization in an increasingly competitive global economy will depend on its ability to effectively harness the power of data and information. The best estimates suggest that globally, we are collectively creating more than 300 million terabytes of data every day – and this number is only rising.1

Simultaneously, the abundance of data and information sources presents great opportunities to discover valuable insights pertaining to customer and employee experiences, product pricing, cost dynamics, operational performance, risk analysis and more. In the era of customer-centricity, the transformation of data into an asset is the crucial factor that enable organizations to unlock novel business models and thrive in a competitive market.

Companies are often unable to realize the true value of the large volumes of data that they produce. This data frequently resides within a company’s internal database, providing some limited benefits for internal processes and decision making, but not much more. For the rest of the time, it just sits there, idle like a car parked in long-term storage. Why not apply the same principles from the emergence of the sharing economy? What happens if you move the car from long-term storage to a ride-sharing app?

That’s where collective intelligence comes in. Collective intelligence is possible when a network of participants shares information in a secure and controlled manner, allowing it to be used and interpreted outside of its organization of origin. Done right, the potential benefits of sharing data are significant. Not only can companies monetize their data assets, but the shared information can drive better decision-making, innovation and benefit entire industries, creating a whole that is more than the sum of its parts.

Encouraging companies to release what can be highly sensitive or even competitive information requires secure data sharing systems, robust data privacy, and greater control over where the information is going and how it is being used. In the first of this article series, we will explore this evolutionary journey from data silos to the future of data networks.


The original model of intelligence: Data silos

Many companies only rely on their own internal data during the decision-making process. An aversion to sharing internal data stems from a tendency for companies to create data silos. This often is not intentional: it is simply a symptom of the way data infrastructure grows organically, and without inter-company standardization. Different data owners use incompatible applications and formats that make exchanging information technically difficult. These incompatibilities mean that companies that want to share data often create complex bilateral data flows that cost time and money.

Limitations of data silos include:


Incomplete data sets: When data is in silos, it is hard to know if all the relevant information has been included. As a result, there could be reporting inaccuracies and organizations may be making decisions based on incomplete data.


Security and governance: Fragmented datasets and lack of visibility into information flows can make it hard to enact comprehensive data governance. This can also result in privacy and security issues. If you don’t know where data is stored, it is hard to safeguard it.


Inefficiency: Having to manually consolidate data from multiple sources is inefficient and time-consuming. Different departments or different companies all storing their own versions of the same data results in wasted resources. A recent study by Forrester shows that workers lose 12 hours a week searching for key information trapped in silos.2 Meanwhile, poor data quality costs businesses an average of $12.9 million annually, according to Gartner research.3


Missed opportunities: By failing to leverage operational, industry-wide data, companies are missing out on opportunities to develop new products or services or manage their businesses more effectively. A 2021 study by McKinsey & Company found that data silos cost businesses an average of $3.1 trillion annually in lost revenue and productivity.4 But when used well, prioritizing data and harnessing its results can be a powerful revenue driver.


Pooled intelligence through data intermediaries

One way to increase access to information is to use third-party aggregators that accrue data from multiple organizations – think aggregators such as flight price tracker Skyscanner or local search-and-discovery apps like Foursquare.

Data aggregators provide valuable services by pooling information and making it publicly available. Examples of these aggregators exist all around us, pooling data and providing services such as credit risk assessment, sanctions screening, fraud risk scoring and even identity verification. Pooling intelligence in this way helps to increase information flows, breaking down some of the data silos within an industry.

Using aggregators makes it easier for enterprises to monetize their data, by sending it to a small number of external providers, who integrate with many other data suppliers. It means that companies do not have to directly share data with their peers, some of whom may be competitors.

But this approach also comes with two primary drawbacks for data owners:


Loss of ownership: Once data is in an aggregator's hands, the supplier loses control of it. This risk prevents companies from sharing commercially or legally sensitive data, at all.


Limited scope: There are sectors of the economy where it is not financially viable for data aggregators to operate. Providing new ways to monetize data sharing could help to transform industries that currently lack access to pooled data resources.


Understanding collective intelligence

Companies can unlock the value of internal company data by removing the historical obstacles to effective data sharing. This is where collective intelligence brings value. Empowering organizations to share their data insights enables owners to capitalize freely on their information safely and securely. Instead of sitting idle, data can generate new revenue streams for its owners.

There’s also the realization that companies stand to make more than direct revenue by sharing internal knowledge. With more information out there, entire industries can grow. This distributed corpus of shared knowledge is the backbone of collective intelligence.

But this cannot be done without safeguards in place. Since data can be highly vulnerable to attack or misuse, collective intelligence must provide enhanced:


Sovereignty: Owners must retain control over how, when and where their data is used.


Security: Organizations must be able to share sensitive knowledge without risking it being compromised on another company's systems.


Privacy: The misuse – accidental or otherwise – of sensitive data is a key business risk, increasingly penalized under the law. Companies must be able to contribute to collective intelligence while protecting sensitive data.

If these three areas can be guaranteed, then businesses can start to maximize the value of their information assets. A 2019 survey from PwC found that businesses which developed plans for using data to make their operations run smarter and faster were three-times as likely to see a return on investment than those who lacked a plan.5

Using collective intelligence for decision-making

Data has and always will be a tool for better decision making. But in the digital era, we have not always had the tools to gather, store, share and maximize it fully. Collective intelligence unlocks the untapped potential of under-utilized data and transforms it into actionable insights.


Collective intelligence, through Liink by J.P. MorganSM

To remove the middleman and to capitalize on the powerful concept of collective intelligence, Onyx by J.P. Morgan has developed Liink by J.P. MorganSM (Liink), a scalable, peer-to-peer information exchange network that provides solutions to solve complex information sharing challenges.

Built on a private, permissioned blockchain-network, Liink enables participants to share information across its network, all while maintaining the three fundamental properties of information sharing: sovereignty, security and privacy. The advantage of a blockchain-based network such as Liink is that it prevents information from being altered or tampered, while ensuring full transparency on who the information is shared with. That means with Liink, network participants can exchange data privately while maintaining control over who they connect with, how the data is shared, and who can use it.

Liink fulfils the untapped potential of under-utilized data – the network represents the evolution of the information economy. Right now, we are breaking down silos within J.P. Morgan and other financial institutions and organizations, to build intelligence and share insights – however, this is just the beginning. As the benefits of smart knowledge sharing become more evident, we anticipate a shift in how organizations collaborate. We believe unlocking the latent value in our data will prove to be the catalyst for a new era of benefits for all.

By Sushil Raja

Global Head of Liink by J.P. Morgan,
Onyx by J.P. Morgan


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