EMERGING TECHNOLOGIES | BDO LLP
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11 EMERGING TECHNOLOGIES | BDO LLP
BUSINESS INTELLIGENCE | DATA ANALYTICS
INTELLIGENT AUTOMATION (IA)
While often treated as broadly interchangeable terms, business intelligence can be seen as past-facing, analysing historic data for insights, while data analytics is more future-focused, using data science to make inferences about future outcomes. Globally, the big data market has been forecast to grow to $103 billion by 2027 , over double its 2018 size. Software is likely to account for almost half of that figure. In of a survey of late 2018, some 45% of market research professionals reported using big data analytics in their work.
for analysis. According to Dening, an optical character recognition (OCR) engine struggles to get more than 50% to 60% accuracy across a typical invoice data set from multiple suppliers. However, an AI-driven system such as Automation Anywhere IQ Bot uses both supervised and unsupervised learning to get past 90% to 95% precision. As Dening says, ‘The more data it processes, the better it gets.’ As with all these emerging technologies, the potential applications are myriad, among them improving back-end operations, optimising customer experience, de-risking regulated processes, driving product innovation, and improving workplace productivity. Here again, quick wins and strong business cases are the order of the day: ‘On paper the world needs more intelligent automation, but right now there has to be a very clear need and a short-term ROI,’ says James Duez, citing
Rapidly developing technologies like AI and IoT, along with cloud and mobile traffic, are all contributing to the complexity of the data that businesses have at their disposal. While big data is of course a valuable asset for businesses, it is of course only as good as the quality of the insights you can derive from it. Business intelligence software tools help organisations to extract value from big data, for example via data warehouses, data discovery tools and cloud data services. Data analysis tools similarly mine raw data for actionable conclusions to help a business optimise its performance, for example for supply chain efficiency, product innovation, risk management, service personalisation, and customer retention and acquisition.
Intelligent Automation (IA) sits at the intersection between the automation of software (RPA) and artificial intelligence (AI), to deliver end-to-end business process automation and accelerate digital transformation. Where RPA can help automate rule-based, process-led tasks, intelligent automation can harness AI to start to recognise semi-structured and unstructured data – and do so, crucially, at scale. ‘That combination [of RPA with AI], driven by advances in machine learning (ML) techniques, computational power, and more advanced cognitive engines, is starting to be applied to a wide range of business problems,’ writes James Dening . ‘Voice recognition, natural language processing, document analysis, and classification — these are everyday, real-world applications.’ Businesses are capturing more and more data, but much of it is unstructured or inconsistent. This ‘dark data’ – which lives
AS WITH ALL THESE EMERGING TECHNOLOGIES, THE POTENTIAL APPLICATIONS ARE MYRIAD , AMONG THEM IMPROVING BACK- END OPERATIONS , OPTIMISING CUSTOMER EXPERIENCE, DE- RISKING REGULATED PROCESSES ...
in emails, voicemail, video, dockets and invoices in multiple formats, PDFs and the rest – is useless if it can’t be processed
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