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Must-watch trends to stay ahead of competitors and keep audiences tuned in -
How big is Big Data? The World Economic Forum says we’re approaching 44 zettabytes - and that number will only continue to grow. -
Whether your organisation wants to meet Environmental, Social & Governance standards to satisfy investor pressure or establish a Corporate Social Responsibility programme to meet consumer expectations, one fact remains the same: Addressing forced labour risk falls squarely in the ‘Social‘ realm in any organisation’s ESG or CSR efforts. -
Artificial intelligence, machine learning, predictive and prescriptive analytics, natural language processing and robotic process automation—whatever your industry, you’ve likely heard these words with increasing frequency over the last year. -
Intelligent Automation combines the automation of repetitive tasks through Robotic Process Automation (RPA) with the learning, analysis and decision making capabilities of Machine Learning and Artificial Intelligence, enabling automation of a much wider range of tasks. Intelligent Automation has the potential to transform the way companies carry out a number of key tasks -
We look at the growing risks to companies from their supply chains, and suggest how they should overcome them by using data and technology to gain supply chain intelligence. -
Predictive analytics models are only as good as the data that goes into them. When your data sample is too small, your models may be influenced too heavily by anomalies, which can skew results. -
The current patchwork of voluntary and mandatory human rights due diligence regulations means that many organisations are not required to meet more stringent standards yet. -
2020 is a key year for Anti-Money Laundering regulation. The European Union’s Fifth Anti-Money Laundering Directive (5AMLD) came into force in January, and the Sixth Anti-Money Laundering Directive (6AMLD) will come into force in December. What do companies need to know about complying with the regulations -
We look at the growing risks to companies from their supply chains, and suggest how they should overcome them by using data and technology to gain supply chain intelligence.
