The Shell example shows just how big of a transformation that enterprises can undertake using digital technology. However, any business of any size can benefit from removing inefficiencies in their processes and increasing agility. In turn, this means any business can benefit from digital transformation.
Data foundations must drive data strategy
When it comes to using analytics to drive better business outcomes, Shell has a reached a level of success that inspires envy from many other enterprises. According to Anu, the team at Shell has been successful across more than a decade of advanced analytics work because they’ve focused on getting their data in order first—before they worry about turning that data into insights.
“My journey with data started as early as 2012 or 2013,” said Anu. “At that point, we were starting to get into advanced analytics and predictive analytics. The thing that it taught us in the early days was that it’s all about data, and it’s about getting your data in good shape, having good data platforms, and having a data strategy behind what data you collect, how you collect it, how you govern it, who owns it, who manages the quality of it. There’s a whole bunch of stuff that I call ‘data foundations’ that you need to have in place before you start driving the insights and the data science/machine learning/AI use cases.”
Digital transformation is a journey, not a destination
What does it truly mean for a business to be “digital?” In the session, I argue it’s hard to say for sure, because no organization ever reaches the point where it’s fully digital. No matter what you’re doing, there’s always opportunity to do it with greater efficiency and agility. This is why it’s so important to reassess your journey in progress and focus on new opportunities as they arise, instead of viewing digital transformation as a fixed target to pursue.
According to Anu, the thing that truly separates digital businesses from traditional ones is the speed at which they make decisions. As an example, she shared how Shell deploys AI-powered sensors at the edge to monitor pipes for corrosion and leaks, and uses the data from those sensors to enable real-time maintenance decision-making.
“You’ve got an operator sitting there with an iPad who’s immediately getting data at the edge fed to him, which gives him the information to make the immediate decision whether or not that pipe needs cleaning,” said Anu. “In the previous world, he would get the data, the data would get uploaded, it would go to some machine somewhere, it would get crunched 48 hours later, and he’d have to come back all over again. The cycle time with which he’d have to make that decision would be much, much longer.”