Mariana Gómez de la Villa, Program Director Distributed Ledger Technology, ING
In 2020, enterprises are no longer strangers to the business benefits of distributed ledger technology (DLT) solutions. Eighty-eight percent of senior executives think blockchain will eventually achieve mainstream adoption (Deloitte, 2020) and 79% of financial institutions say they dedicate resources to DLT (Accenture, Digital Asset 2020 ). So why do only 1.6% of financial institutions go live with their DLT solutions? (Accenture, Digital Asset 2020).
Over the past four years, ING’s DLT team have gathered learnings about what is holding enterprise DLT back from being widely adopted? Common challenges known to the whole enterprise DLT ecosystem include privacy, interoperability, regulation and standardization issues. However, significant developments to overcome most of these well-known challenges are underway. ING’s DLT team went ‘under-the-hood’ of enterprise DLT to research less-known ‘hidden’ issues that might be challenging the wide-scale adoption of enterprise DLT. Here’s what we found out:
1) Unreliable and non-standardised data management
Eighty-eight percent of companies mention data standards across networks as an important requirement for joining an industry-wide blockchain network (IBM 2020). However, DLT data quality is an issue. Currently, there are no standards for DLT data management and no processes for DLT data input. DLT cannot solve business problems with underlying issues, such as dirty data. Dirty data is inaccurate, incomplete and/or inconsistent data. DLT is immutable, so if a ledger is populated with dirty data, this cannot be changed. Most enterprises that adopt DLT do not usually consider data quality parameters.
2) Unclear metrics for DLT success
The duration of DLT initiatives getting to go-live stage can make it hard for enterprises to forecast the true value that DLT will bring when it is in full-scale production. At ING, we believe that DLT unlocks value in various areas, besides return on investment (ROI). A recent report by IBM found that 41% of organizations are interested in blockchain for more than outright profitability(IBM 2020).Customer success, partner profitability and community engagement could be used as alternative measurements of DLT success (IBM 2020).
3) DLT implementation challenges
IBM’s recent report on Advancing Trade with Blockchain highlighted three main DLT implementation challenges: integration, interconnectivity and interoperability (IBM 2020).
These implementation challenges relate to data connection complexities enterprises face when transferring existing data from old systems to new, DLT systems. It gets more complicated when DLT data needs to be communicated or transferred back to other systems within an enterprise. DLTs can create information silos so it remains difficult for enterprises to transfer existing data onto DLTs – a big impediment in the mass-adoption of DLT solutions.
4) Poor clarity on DLT use-cases
One of the top challenges when it comes to extracting value from blockchain is complexity: understanding what participants you need, what data you need from them, and what incentive models will drive participation (KPMG 2020). DLT is nascent, therefore it is experimental. A lot of DLT experiments are being done irrespective of the business problem they are trying to solve. This is herd behaviour, which is why DLT is often called a ‘hype’ (Pautasso et al 2020). It’s crucial to stay focused on the needs of your business and have regular feedback loops with customers. At ING, we first want to make sure there is a big problem to solve. We carefully analyse business cases by using DLT scoring frameworks and only after the DLT model is validated with the business, we apply the bank’s innovation method called PACE to scale up our most successful projects.
5) Negative preconceptions of the technology
Companies, including financial institutions, have negative preconceptions about DLT. In retail, there is a lack of trust in DLT because of negative media coverage on cryptocurrencies (Pautasso et al, 2020). Management teams are reluctant to examine DLT because of their poor understanding of the technology’s benefits and a high visibility of cryptocurrency scams and hacks (UCL 2019). Lastly, financial institutions have a negative preconception of tokens. This is largely the result of a misunderstanding of how blockchain can help to facilitate rather than hinder payments processes (UCL 2019).
6) Unexploited synergies with emerging technology
There is an intense volume of data collected, analyzed, and made actionable today across organizations through IoT, analytics, and AI. To extract better value from DLT, synergies must be found with other emerging technologies. For example, in supply chains with many participants, DLT will become valuable once a larger mass of data is obtained (e.g.from IoT).
7) Lack of institutional support for retail offerings
Seventy-one percent of millennials would invest in cryptocurrencies if it was offered by a traditional financial institution (eToro 2019). Currently, most enterprise DLT initiatives in banking are produced for wholesale banking clients rather than retail clients. Cryptocurrencies exist on permissionless DLT, which enterprise have been hesitant to experiment with because of the risks. However, there is some enterprise demand to use permissionless DLT (EY 2020).The global DLT in retail market size was valued at $83 million in 2018, and is projected to reach $11.18 billion by 2026, registering a CAGR of 84.6% from 2019 to 2026 (Researchandmarkets.com). Additional DLT retail offerings could be critical to enterprise DLT adoption.
8) Non-standardized developer tools
In DLT, developers need to master non-industry-standard programming languages in order to build quality applications. Being able to develop apps on DLT using common programming languages such as GoLang and Java would facilitate faster application creation.
Overcoming these challenges is crucialinunlocking the full-scale adoption of enterprise DLT in the future. Acknowledgments:
To AnnerieVreugdenhil for asking the question and for being the source of inspiration for this article and to Xavier Meegan for resiliently finding the answers.