As organisations generate more data than ever, the real challenge is no longer gaining insights—it’s turning those insights into timely, effective action. Self-Service Analytics 2.0 represents the next evolution in analytics, moving beyond static dashboards and manual reporting to intelligent, AI-driven platforms that actively support and automate decision-making. By combining predictive modelling, machine learning, simulation-based forecasting, and AI-powered recommendations, Self-Service Analytics 2.0 bridges the gap between data discovery and execution. Business users can monitor performance in real time, optimise operations through automated workflows, predict future trends, and proactively mitigate risks—without heavy reliance on IT teams. This approach enables organisations to improve operational efficiency, reduce costs, accelerate decision cycles, and achieve greater forecasting accuracy, all while minimising disruption to existing processes. Its value spans industries, from manufacturing and supply chain to finance, healthcare, real estate, and retail, helping teams become more agile, data-driven, and resilient. Most importantly, Self-Service Analytics 2.0 empowers people with intelligent automation that augments human judgement rather than replacing it, delivering faster ROI and sustainable business impact. To clearly explain what Self-Service Analytics 2.0 is, how it works, and who can benefit from it, we’ve captured the full story visually in the infographic below.
