It's always exciting to plan digital transformation, AI, & actionable analytics but- so boring to have to go back to that staple of success- data.
Unless enterprises and public sector organisations can join and analyse data in disparate data silos inherited over years of acquisitions they are doomed to relative failure.
AI, machine learning and robotic process automation (RPA) needs massive amounts of data to have a chance of success. It is said that insurance companies can only access 10% to 20% of their data! They can only innovate if they can access 90% plus. What is the situation in other industries.
To keep up with unpredictable customers and audiences this is a "must do" before seeking new technology answers. Retrieve the insightsin the data you already have and blatantly ignore before trying to be clever.
A common challenge for brands is getting real, actionable insights from data and using it to deliver engaging customer experiences. Data sources are often not properly integrated within organisations, sitting in siloes. The Google Analytics Suite addresses this problem by using AI in its platform to connect and analyse data. “Companies need to join up the data. It’s the key to unlocking opportunities in reaching customers,” she said. “Our priorities should be shifting from ‘mobile first’ to ‘AI first’.” Does this mean that humans will no longer be needed? Not so, argued Sam Olsen, director at SI Partners. “The rise of machines doesn’t mean humans are suddenly redundant,” he said. “It’s all about intelligence amplification and an effective use of information technology in augmenting human intelligence.”
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