The Future is Here

The below is a chapter from Predict Book 4 - Notes from the Predict Conference 2018. Predict Book 4 is written by Ian Campbell and published by Creme Global. In eight chapters in summarizes main discussion points from Predict Conference 2018. This book is available to anyone who purchases a Predict Conference ticket. To secure your Predict Tickets at amazing value during our Super Early Bird offer - go to our website.

Predict Book 4 - The Future is Here

Predictive analytics and AI are already a source of competitive advantage so there’s a strategic imperative to adopt them now and use them correctly.

Speaker after speaker confirmed what Creme Global’s Cronan McNamara suggested in his opening address at 2018’s Predict conference, that analytics is no longer the sole preserve of large corporates and every organisation needs to become data driven. That means focusing on the widespread adoption of analytics by different users across a business, rather than getting bogged down in the technology. 

Accenture’s Medb Corcoran left delegates in no doubt about the need to take these actions, saying that the consultancy has never in its history seen a technology adopted so quickly with the potential to affect so much – our work, our home life and our society. Although AI has been around in various forms for 60 years, the unprecedented transformation we’re now going through is because of a combination of more data and cheaper processing power. 

Garry Connolly, from Host in Ireland, describes it as a two-prong technological revolution that gathered pace over the last twelve years. At one end you have people walking around with much smarter devices, kick-started by the Apple iPhone in 2007; at the other are huge cloud platforms pioneered by Amazon, providing globally available compute power and storage. 

Thanks to Steve Jobs and Jeff Bezos, argued Connolly, the handheld device is now the window to a seemingly infinite world of data. He was one of many speakers to drop statistics that reminded us that we are only experiencing the first ripples from the Big Data explosion. By 2025, he said, every month will generate seven or eight times more data than all the data that was created up until 2010. 

More data, accelerating compute power and increasingly accessible tools have brought predictive analytics and AI projects into the mainstream. Cronan McNamara described how the four years of the Predict conference have captured the change, how projects that once sat on shelves are now being undertaken and successfully delivered.

Projects and outcomes

Head of Accenture analytics in Ireland, Paul Pierotti, had a similar first hand account of the shift. He recalled client meetings where he presented elaborate strategies for analytics projects that were rarely implemented. That’s all changed and he’s now seeing a real appetite among organisations to take action and deliver data science insights. 

 Accenture speakers were among many presenters who had here-and-now evidence that well executed projects are already delivering results and driving business advantage. In the highly competitive insurance market, Accenture has helped a company realise a 15 per cent improvement in their bottom line by using big data, advanced analytics and AI to deliver a personalised micro service to individual customers. 

Another financial services client, a health insurer, uses Robotic Process Automation with advanced analytics to fully automate 520,000 claims a year with near 100 per cent accuracy. Combined with AI and machine learning, the technology delivers over $3 billion in savings in claims non-compliance. 

“This is now the new normal,” said Pierotti. “The people in this room, the people seeing analytics and data science as the career path they want to take are not tomorrow’s CIOs, they are tomorrow’s CEOs. And the organisations that win in this new digital world are the ones that are digitally and analytics led.” 

His colleague Barry Heavey talked about the impact of analytics on Industry 4.0 and the supply chain, areas where some of the first gains have been most evident. Using various combinations of robotic automation, AI, industrial IoT and embedded analytics, Accenture has delivered a 5 per cent cost reduction in the food and drink industry, for example, and a 19 per cent reduction in quality issues for an automotive supplier.

Another real world example was the way Accenture helped Schneider Electric develop a ‘virtual factory’ to rapidly build and scale new offerings in areas such as predictive maintenance, asset monitoring and energy optimisation. Predictive asset maintenance is already quite mature in what’s often described as the fourth industrial revolution, where machine data and AI combine to reduce the risk of production line downtime. 

“We see a huge appetite for this at the moment,” said Heavey, “especially in discreet manufacturing, and in areas like oil and gas where there is a very heavy utilisation of assets and downtime of an asset can have huge negative implications on the supply chain.” 

The people seeing analytics and data science as the career path they want to take are not tomorrow’s CIOs, they are tomorrow’s CEOs.”

Paul Pierotti, Accenture

Learning from lean

Analytics has become a day-to-day to reality for many organisations, but big challenges remain, including a hype-driven enthusiasm that can give rise to the wrong kind of projects. “Quite simply,” said Paul Pierotti, “if it’s not going to change what your back office or your front line are doing on a cold Tuesday afternoon, don’t bother creating the insight.” 

 Michael Phelan, from DePuy Synthes (part of Johnson & Johnson), had similarly sobering words. “Just collecting data for data’s sake is a fool’s errand,” he said, urging organisations to focus only on actionable outcomes. “Because if you’re not going to take any actions, why look for the insight and why bother collecting the data? It’s a waste of resources and time.”

After you’re clear on what you want from your insights, you have to go back to the beginning and make sure you have stabilised and clean data. “You’ve got all these beautiful lean processes, but the data flowing through your lean processes is anything but lean, and instead of filling data lakes you’re filling data sewers because you have data everywhere,” said Phelan. 

His area of expertise is the supply chain, which has been transformed by lean manufacturing. He believes that lean-type practices could be used for more effective data analytics, because they both rely on implementing a specialist set of tools and techniques. 

Along the way you also have to up-skill employees. In the case of analytics, it’s about deploying new applications across data flows, moving from Excel spreadsheets to more sophisticated BI (Business Intelligence) dashboards, and then stepping up to full-blown predictive analytics solutions. 

He warned against signing up to vendors who come in with “a big red button”, a magic fix that promises instant analytics and insights. Unless the groundwork is done on the data, it’s never going to work. And if you haven’t reinvented yourself as a responsive and agile organisation, you are not ready. But you better get ready or face a stark reality.

“Analytics in the supply chain is a journey and you’ve got to get on-board sometime because digitalisation is steam rolling ahead, and if you’re not on-board you will perish. You will not survive the next wave of the technical revolution,” he said. 

Inherent challenges around analysing data are not just technical, as Phelan reminded the audience when he quoted management consultant Peter Drucker, “Culture eats strategy for breakfast”. 

He then elaborated on how hard it is to adopt new practices in an organisation that is resistant to them: “All the analytics in the world isn’t going to help if your organisation isn’t ready to adapt to digitalisation, doesn’t see it coming down the line, and doesn’t have the right culture in place.”

“All the analytics in the world isn’t going to help if your organisation isn’t ready to adapt to digitalisation, doesn’t see it coming down the line, and doesn’t have the right culture in place.”

Michael Phelan, DePuy Synthes