Data and analytics leaders who promote both internal and external data sharing are more successful in demonstrating superior team and organisational performance, according to Gartner’s fifth annual chief data officer survey. In fact, Gartner predicts that by 2023, organisations that promote data sharing will outperform their peers on most business value metrics and generate three times more measurable economic benefit than those who do not.
Yet, at the same time, Gartner predicts that through 2022, less than 5% of data-sharing programmes will correctly identify trusted data and locate trusted data sources. Many organisations inhibit access to data, preserving data silos and discouraging data sharing. This unnecessarily undermines efforts to maximise business and social value from data and analytics at a time when Covid-19 is driving demand for data and analytics to unprecedented levels. The traditional “don’t share data unless” mindset has outlived its original purpose.
While it’s not easy to change the status quo, data and analytics (D&A) leaders must ask their teams to prioritise five areas to foster a data sharing mindset.
There is massive demand for data sharing, placing an enormous burden on businesses, governments and individuals worldwide. At the same time, meeting this demand presents positive business opportunities.
Prior to the Covid-19 pandemic, ten large pharmaceutical companies, including Johnson & Johnson, AstraZeneca and GSK, undertook collaborative efforts to train their drug discovery machine learning (ML) algorithms on each other’s data. The goal? To accelerate and reduce the cost of the discovery of drugs. They used digital trust technologies, including blockchain, to share data without compromising confidential or commercial secrets.
Today, that collaboration is paying dividends in helping find a Covid-19 vaccine. This rare example shows that organisations can deliver more value when they collaborate in sharing data externally - even with competitors - yielding comparatively increased value through efficiency and cost savings for each organisation.
To drive organisational enablement of data sharing, leaders should prioritise use cases in which increased data sharing will yield maximum alignment with business outcomes. The key is to collaborate with business leaders across your internal organisation and with partners to identify shared business goals.
By focusing on your shared goals, you can understand which data makes the most sense to share and quantify its impact on the achieving the goal. This can be increased costs savings, net new revenue or non-monetary value creation, like improved risk mitigation decision-making.
And if competitors and partners can do it, so can vendors and customers. As a vendor, sharing back customer data can create new value in the relationship instantly and regularly. Begin with an assumption that all customer data should be shared back to the customer - the opposite of most current thinking. The mere act of doing so will deepen trust, reduce resistance to your use of customer data and, once analysed together, a better understanding of customer expectations and preferences.
Executive conversations often focus on the risks of sharing data, without considering the risks of not sharing data. By defaulting to this perspective, organisations undervalue data sharing and miss scenarios to connect data insights with business outcomes. On the other hand, the risks of irresponsible data re-use are growing, from embarrassment resulting from downstream misuse, to regulatory fines, to shareholder disappointment and brand disloyalty.
As the D&A leader responsible for driving business value, you must promote the merits of data sharing for business value while managing executives’ anxiety of going against the grain. The best way to do this is to carve out the specific use cases applicable to your industry and business goals where you will not share data even if it is legally permissible to do so.
Look diligently for use cases that drive “win-win” outcomes from exchanging and sharing data to reduce the idea risk. For example, insurance data sharing for fraud prevention serves the economic interests of business, consumers and government. Develop the business case for “loss avoidance” outcomes, using D&A for increased loss prevention from wrongful conduct (such as by employees or customers).
Be sure to resist extremes within the data sharing spectrum - the zero-sum “never share” approach on one end and the disaster-waiting-to-happen “always share” approach on the other end (unless there is a good reason and a well-vetted business case for pursuing either of these models).
If you do not introduce trust throughout your data-sharing process, you cannot achieve business value from the data you collect. Gartner predicts that through 2023, organisations that can instil digital trust will be able to participate in 50% more eco-systems, significantly expanding revenue-generation opportunities.
It’s important to trust the quality of the data you collect, use and share to match your business context and requirements. However, through 2022, less than 5% of global organisations’ data sharing programs will both correctly identify trusted data and locate trusted data sources. It only makes sense that partners, vendors and customers must trust their data sources before they rely on them to achieve business goals. As such, D&A leaders on all sides need to implement trust-based mechanisms.
Use digital trust mechanisms, such as blockchain smart contracts which enable a trusted-data collection method, while also enabling the efficient transfer and sharing of any asset of monetary or non-monetary value. When you receive data, use responsible artificial intelligence (AI) to mitigate the risk of downstream nefarious data uses and unintended impacts, such as unwanted bias. That way, your data sources can trust that your use of their data is unlikely to result in a negative outcome.
To establish a data-sharing environment, work with business leaders across business units to create a data-sharing mindset. Foster a data sharing culture - not a data ownership culture - by identifying the emotional impacts and inherent biases that hamper data sharing.
Within your IT department, distinguish your data management strategy between data warehouses, data lakes and data hubs. Gartner predicts that through 2020, organisations that adopted data hub strategies will achieve outcomes dependent on shared and governed data with at least 60% lower cost.
Align your data architecture to data sharing - data hoarding or over-centralisation approaches limit the benefits of data sharing. Well-architected data sharing approaches manage risk and deliver significantly more benefits by matching the choice of data sharing architecture to the data sharing purpose and use case.
Once your data sharing programme is established, consider upgrading to a data fabric design that enables dynamic and augmented data integration in support of your data sharing strategy.
To meet the expectations of D&A teams delivering sustainable, repeatable business value from increased investments in data, leaders need to rewire their organisational culture for an AI-infused future. The term “augmented data eco-system” reflects the merging of organisations’ internal data with external data, with the application of AI or ML for optimisation or improvement. By continuously creating and engaging in augmented data eco-systems, you can locate diverse datasets.
To do so, leverage data marketplaces and exchanges by developing a strategy for your business to build its presence through supplying and buying data on these platforms. You can streamline the process by working with third-party partners that use AI, blockchain, and automation to securely share datasets and facilitate the seamless nature of these platforms.
Also consider joining industry and technology consortia where data sharing among participant members creates new insights and business value. This will allow you to explore opportunities to either build, or play a central role in your industry’s data sharing culture and position your company as a leader in the space with the ability to maximise the value from the contributed data.
Lydia Clougherty Jones is senior research director at Gartner