Organizational interest in enterprise blockchain is tightly correlated with the rise and fall in Bitcoin prices. No surprise, this finding is supported by Gartner’s correlation analysis of social media conversations on enterprise blockchain with the price of Bitcoin. See Figure 1.
(Study covered period between April 1, 2017 and March 31 2019 – see notes below for methodology).
The highly correlated interest in enterprise blockchain with Bitcoin’s prices supports the theory that the bitcoin bubble drove the hype around enterprise blockchain. Still, emerging from the dust of cryptocurrency fortunes gained and lost, are transformational use cases based on blockchain and IoT integration.
Blockchain and IoT Integration
My colleagues, Benoit Lheureux, Alex Pradhan and I just published a research note on previously unattainable digital business benefits that are available by integrating IoT with Blockchain networks. (See Integrating Blockchain with IoT Strengthens Trust in Multiparty Processes). Our research note delves into the architectural and security options for this integration, and also presents two interesting case studies of organizations with limited production implementations. We also refer to other early-stage experimentations with the technology that we discovered.
Integrating IoT and Blockchain supports trusted multi-party processes that bridge physical world things to business process computing environments.
The combined environment:
- Enables an immutable audit trail of key IoT data and related business events that is shared across multiple participants and which can be independently verified by each party, and
- Supports smart contracts and distributed applications (known as dapps) that drive process automation across network participants often by referencing information represented in digital twins.
IoT digital twins provide the visibility and monitoring of things and related events (e.g., using IoT devices to automatically capture the origin of a product), and blockchain enables the shared single version of truth as to the state of these ‘things’ across their life cycles and associated business events.
Blockchain and IoT integration introduce new complexity, risks and vulnerabilities into organizational systems and processes. System scalability, security and out of the box integration are still works-in-progress. Organizations are therefore left with a hodgepodge of technical options and a good deal of customization to stitch Blockchain and IoT networks securely together, as shown below in Figure 2.
Figure 2; Sample Architectural Framework on this type of technical integration
Fake Olive Oil – Problem Solved?
Did you know that up to 70% of all store-bought extra virgin olive oil in the US is fake? And you probably know that romaine lettuce is highly susceptible to dangerous pathogens that cause food poisoning; hence the massive lettuce recalls we have seen over the past few years.
I am a huge fan of romaine lettuce salads and eat them at least once or twice a day. I dress them with the best (reasonably priced) olive oil and vinegar I can find. But I’m always leery of the olive oil I buy because I know most of it is fake – it’s usually corn or vegetable oil colored and flavored to look and smell like olive oil.
So it’s not an understatement to say that I really look forward to the day when I can buy organic extra virgin olive oil at the grocery store and be assured that it is indeed what the label purports it to be. That is — organic extra virgin olive oil that has been properly handled at the right temperature on the long trek from Sicily to my local grocery store.
That’s an experience that as far as I know, only blockchain combined with IoT networks, can give me. I’m not saying it’s perfect and 100% trustworthy as I’m sure some fraudsters will find ways to beat the systems. But it will be much harder for the criminals to interject counterfeit olive oil into the supply chain, and trust in quality will be significantly and justifiably raised.
Buying Extra Virgin Olive Oil I can trust is what I call my own personal digital transformation…
Notes on Methodology of Social Media Analytics study:
Additional Research Contributions: Ayush Saxena and Ritesh Kumar Srivastava from the Gartner Social Media Analytics Team
- Source of Social Media Analytics Data: Automated Social Media Listening Tools were used to track user responses on social media and public discussion forums as a leading indicator for consumer sentiment, preferences and activities. The data tracked is specific to quantifiable keywords (below) and phrases, as well as qualitative assessments and evaluations of results and use cases.
- Sources Covered: By default social media sources considered for analysis include Twitter, Facebook (publicly available information only), aggregator websites, blogs, news, mainstream media, forums and videos (comments only); unless and until specified.
- Geography Covered: All geographical regions of the world were analyzed for the study
- Languages Used: All languages recognized by the tool were used for the study.
Below are the Sample set of Keywords that were used to cover ‘Enterprise Blockchain’ conversations from Social Media
- (Blockchain OR “Distributed ledger” OR “Smart contracts” OR “shared ledger”) AND (enterprise OR business OR company OR organization OR corporation OR establishment)
First published on Gartner Network Blog