How to Fix Blockchain’s Missing Link to Cross the Data Abyss
In this article, Toby Mills, CEO of Entopy, looks at the trend for organizations to turn to technologies such as artificial intelligence and blockchain in an attempt to find a “silver bullet” to unlock the next wave of business transformation. But unless the right data is collected in the first place – and used effectively – even the best new technologies will fall victim to the age-old “garbage in, garbage out”. Toby started his entrepreneurial journey in 2016 with domestic IoT products before launching Entopy in 2017. Since then, he has overseen the evolution of the company from a hardware-centric business to the intelligent data orchestration platform it is today. Before founding Entopy, Toby held several leadership positions in retail.
Digitization is seen as key to ensuring agility and resilience across operations to cope with today’s rapidly changing landscape. Businesses are drawn to technologies such as artificial intelligence (AI) and blockchain in an attempt to find a “silver bullet” to unlock the next wave of transformation.
But without a solid data base, their efforts are doomed to failure. Unless organizations collect the right data in the first place – and use it effectively – even the best new technologies will fall victim to the age-old “garbage in, garbage out”.
The supply chain industry is a good example. Given the complexity of modern supply chains, the number of influencing factors and the number of separate organizations being connected, the latest next generation technology is extremely attractive. Blockchain offers the ability to give many stakeholders access to reliable data across a supply chain network, and AI provides a path to predictive, autonomous decision-making.
There is absolutely no shortage of data. However, there is a large gap between the amount of data that is generated and companies that can leverage this data. Blockchain and AI are not capable of bridging this gap – that is not what they were designed to do.
Gaining access to data in the supply chain is easier said than done, as relevant data may reside in a separate business unit or an external organisation. And without the whole picture, it’s hard to maximize value.
Many approach the data challenge by seeing the data as the key. They collect this data, store it on a blockchain so that it is “trusted,” and then expect technologies like AI to magically deliver the insights they need. But using centralized infrastructure, which includes things like data lakes and data warehouses that consume the vast amounts of data generated, and just feed that data into the aforementioned technologies, doesn’t work.
That’s why the real key to bridging the data chasm is looking at data through the lens of the device, not the data. Looking at the world through this lens—looking at objects in the real world and using data to describe those objects digitally—allows much more comprehensive and intricate images to emerge. This is why digital twin technology holds the key to unlocking the next wave of digital transformation.
By making it possible to create real-time models of real objects in the digital world, it makes them available to all participants in a supply chain via a central platform. These digital devices include all relevant data for a shipment, and are dynamically updated in real time with new data as the shipment moves through the supply chain.
Intelligent data orchestration creates relationships between these entities, unlocking highly complex, real-time, multidimensional insights with the data generated across the supply chain. Relationships between entities are dynamic, change over time, and reflect the real world. The questions asked of the data can be easily changed and new units can be introduced. The resulting digital twin provides a real-time reflective image of what is happening, from which insights can be generated.
Moreover, this approach provides a foundation, a map, a framework that enables targeted data capture, ensuring that only relevant data is retrieved from connected systems – with little or no effort required from the respective domains. The automated technology brings the disparate data together, structures it to form a complete data product and dissolves it at the end of its operational life cycle – providing a solid data foundation to unlock the next generation of digital transformation.
Intelligent data orchestration can feed data into a blockchain, providing long-term trust in the data and ensuring integrity. The foundation for intelligent data orchestration can also power machine learning and AI models to provide predictive analytics across operations.
There is no single answer to unlocking digital transformation. It will be a combination of technologies, each playing an important role. What is critical is that these technologies are used in the right way, leveraging their respective strengths, and help drive the next wave of change across modern supply chains.
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