Tackling Data Complexity with AI

the challenges of dealing with different complexities of data and how AI can be applied to help

Business leaders know that data is as precious as currency and success relies in being able to realise value from the information and insights buried within it.

The challenge that organisations face is that 80% of the data that they gather is not structured and therefore not in a format that their systems can understand without significant manual effort.

Automation seeks to reduce or eliminate manual effort and technologies such as workflow and RPA are now leveraging OCR to extract key data from semi-structured documents such as invoices, sales orders and forms into the structured format they need to automate processing.

The structure of data can be described on a spectrum - the more unstructured it is the greater the level of manual effort required to handle it. Structured and semi-structured data are machine generated, by far the most complex data that an organisation must handle is unstructured because it is human generated. It's the enquiries, complaints, claims and correspondence that flow in every day from customers, suppliers and employees that are not only unstructured but descriptive, unpredictable, in multiple languages and received through different channels.

Whilst the 'Back office' can automate machine generated data that is structured or semi-structured, it is the front office in areas such as customer experience, which is the true driving force behind the idea of digital transformation and where understanding meaning and intent to achieve personalisation is key to digital customer experience.

The challenge in dealing with unstructured human generated data is that it demands the most human effort to process because of its highly complex nature. It is in the front office where artificial intelligence such as machine learning, natural language processing, neural networks and fuzzy logic can augment humans to deliver the greatest efficiencies.

It's essential to keep humans 'in the loop' not only to deal with exceptions but ensure that the software learns from their actions and decisions. This creates an 'AI lock in loop' that achieves continuous optimisation. Only through continuous learning is AI able to handle unstructured data in a way that humans might.

We now create over 2.5 Quintillion bytes of data every day and so organisations need to move beyond RPA, OCR and workflow so that organisations can make sense of this data regardless of its complexity in order achieve competitive advantage through better customer service, compliance and financial performance.

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