How to Fix Blockchain’s Missing Link to Cross the Data Chasm

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In this contributed 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 gathered in the first place – and harnessed 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. Prior to founding Entopy, Toby held multiple management positions in retail.

Digitalization is seen as key to ensuring agility and robustness 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 firm data foundation, their efforts are doomed to failure. Unless organizations gather the right data in the first place – and harness 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 interconnecting, the latest next-generation technologies are extremely attractive. Blockchain offers the ability to provide many stakeholders with access to trusted data across a supply chain network, and AI provides a path to predictive, autonomous decision making.

There is certainly no shortage of data. However, there is a huge chasm between the amount of data being generated and businesses being able to harness that data. Blockchain and AI are not capable of bridging this gap – it is not what they are designed to do.

Accessing data in the supply chain is easier said than done, as relevant data could reside in a separate business unit or an external organization. And, without the whole picture, it is difficult to maximize value.

Many approach the data challenge by looking at the data as the key. They collect that data, store it on a blockchain so it is ‘trusted’, and then expect technologies like AI to magically deliver the insights they need. But using centralized infrastructure, comprizing things like data lakes and data warehouses that consume the vast amounts of data being generated, and just submitting this data to the aforementioned technologies does not work. 

That’s why the real key to bridging the data chasm is to look at data through the lens of the entity, not the data. Looking at the world through this lens – looking at real-world objects and using data to describe those objects digitally – allows much more comprehensive and intricate pictures to emerge. This is why digital twin technology holds the key to unlocking the next wave of digital transformation. 

By enabling real-time models of real-world objects to be created in the digital world, it makes them accessible by all participants in a supply chain via a central platform. These digital entities comprise all relevant data for a consignment, dynamically updating in real time with new data as the consignment progresses through the supply chain.

Intelligent data orchestration creates relationships between those entities, unlocking highly complex, real-time, multi-dimensional insights with the data that is generated across the supply chain. Relationships between entities are dynamic, changing over time, reflecting the real world. The questions being asked of the data can be easily changed and new entities can be introduced. The resulting digital twin provides a real-time, reflective picture of what is happening, from which insights can be generated. 

What’s more, this approach provides a foundation, a map, a framework that enables targeted data capture, ensuring only relevant data is sourced from connected systems – with little or no effort required from the respective domains. The automated technology brings the disparate data together, structuring it to form a complete data product and dissolving it at the end of its operational lifecycle – providing a firm 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 intelligent data orchestration provides can also fuel machine learning and AI models to provide predictive analysis 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 correct way, playing to their respective strengths, helping to drive the next wave of change across modern-day supply chains. 

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