Digital Transformation Need: Strong Tech Base10.09.2018
Buzz continues apace around digital transformation. But no matter which firm offers the most agile IT, the most whiz-bang IoT, or the smartest AI, one critical determinant of success remains: the underlying technology infrastructure.
“All of this new, latency-sensitive business transformation that’s happening must be built on a strong foundation,” said Bill Fenick, Vice President Enterprise at Interxion, a provider of co-location and data-center services. “If the foundation is not a proper bedrock, newfangled technologies and digital-transformation initiatives will not succeed.”
A bank may offer its customers chat support powered by artificial intelligence, but if the system suffers significant downtime, that AI won’t learn the correct lessons. Similarly, a technology company can roll out an efficient, flexible and scalable cloud, but a distant location and/or a paucity of network connections would limit the performance and therefore the utility of the offering.
“The core has to be solid,” said Feargal O’Sullivan, CEO at USAM Group, a New York-based sales outsourcing firm focused on financial technology.
“In financial services, the fact that you’re dealing with people’s money means you have to ensure rock-solid privacy, and you have to ensure rock-solid reliability,” O’Sullivan said. “This goes above and beyond the normal performance and scalability of underlying infrastructure for less-critical applications.”
In cloud computing, companies benefit most from a hybrid arrangement of on-premises and cloud — the former being the foundation needed to optimize the latter.
“For the things you keep on-premise, it’s very important that that platform is well-connected and has the right specifications,” Fenick said. “If your IT infrastructure is not in a data center that is well-connected, close to the city, and close to internet exchanges, then you won’t really get the benefit of using cloud, because it will take too long for the workloads to move between the different services.”
Cloud, Data, AI
For AI specifically, companies need a strong foundation of digital capabilities to compete, according to a July 2018 McKinsey report.
“It appears that AI adopters can’t flourish without a solid base of core and advanced digital technologies,” McKinsey Senior Partner Jacques Bughin, lead author of the report, wrote. “Companies that can assemble this bundle of capabilities are starting to pull away from the pack and will probably be AI’s ultimate winners.”
McKinsey noted that the adoption of AI is part of a continuum, a stage of investment that comes after the establishment of core digital technologies (cloud computing, mobile, and the web), and more advanced technologies (‘big data’ and advanced analytics). Of more than 1,300 companies surveyed in 2017, 75% of firms that adopted AI leveraged knowledge gained from applying and mastering existing digital capabilities.
Only one in three organizations have a solid base of underlying technologies. “This digital substructure is still lacking in many companies,” the report said. “The biggest gaps were in more recent tools, such as big data, analytics, and the cloud.”
Leading-edge technologies such as AI and Internet of Things have cache to the extent that companies may feel the need to get involved, if only because everybody else seems to be. A rush to adoption introduces the risk, not only of the new technology not adding value, but also of underlying quality control and customer service deteriorating.
“From the IT failures and outages you see in the news, the pitfalls are enormous,” Fenick said. “A day of downtime simply cost too much these days. Your IT solution is a chain, starting with the data center as the foundation for the IT stack. If that foundation is not compliant, secure and well-connected, you will not succeed with your IT cloud solutions.”
A proper foundation is to a leading-edge technology implementation, what a 101-level course is to a 102-level course. “It is required, but not sufficient” for success, said Vasant Dhar, Professor of Information Systems at NYU Stern School of Business.
Beyond the infrastructure, human leadership and vision at the CEO and CFO level, and connecting data to business thinking, is most critical, according to Dhar.
“The most important thing is CxO-level involvement to link business thinking to AI instead of leaving it all to the CTO or business units to make it happen,” Dhar told Markets Media. “Some of this requires harnessing the brains, skills, and experiences of the employees to define the potential projects they could be doing. The job of the CEO is to prioritize these potential initiatives.”
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With Eugene Kanevsky, James Redbourn, and Joanna Wong, CLSA
AI/ML on the buy-side trading desk is a long-term program with short- and mid-term deliverables.