As businesses grow, the need to be competitive, innovative, relevant and agile also grows, therefore the need for deeper insight, faster information, greater collaboration and new commercial ideas become a high priority. This said, trying to analyze this type of diverse IoT data is physically impossible for a human, hence the association and need for Artificial Intelligence (AI) becomes synonymous with IoT. The link between these new challenges is advanced analytics.
With more than 55 billion IoT devices by 2025 – more than four devices for every person on earth - meaning Big Data is only getting bigger. The need to use high frequency, high velocity data for some sort of benefit is the purpose of connecting the physical world with the digital world, but not analyzing this data effectively is a missed opportunity to drive the outcomes your business needs to thrive. To unlock the value of the pervasive nature of IoT data, a strategy is needed, and the ability to digest high volumes of data from multiple sources is required. Taking a platform approach provides a flexible framework to allow a business to extract the value from IoT initiatives to deliver the outcomes business are looking for.
As certain buzz words gain more momentum, the Chief Analytical Officer (CAO) gains more credibility in the work place. As covered in a recent McKinsey study, this role has morphed into the catalyst for business change and driver for greater efficiencies. But behind the hype, how can the CAO and Chief Technology Officer (CTO), who drive the innovation strategy, conspire to do this? The first battle must be the common understanding of the language used in analytics, one person’s AI is another person’s ‘black magic’ when reviewing technology; should you buy or build? Best-in-class or single vendor strategy? Decisions, decisions…
Strategic decisions and answers to these questions are very subjective and relative to the business issue being addressed, but when you look deeper into the required ecosystems that define an IoT strategy, analytics highlights the question around how the CAO and CTO interlink with all these other partners and capabilities to support this complimentary strategy.
As McKinsey wrote, the key roles for CAOs need to focus on:
Ref: McKinsey – Rebooting analytics leadership: Time to move beyond the math
Integrating these key focus areas into IoT projects is critical to surface the hidden value in IoT data. In figure 1, I have simplified what I believe to be the key elements in an IoT capability covering; data, connectivity, people, process and insight. Therefore, the CAO provides the skills and knowledge of how to unlock this value of integrating, visualizing and transforming diverse and voluminous IoT data from different processes sources by applying advanced analytics, AI and capabilities to share the insights and democratize analytics via their platforms. This goes beyond the simple analytics, statistical models, and business rules that most ‘IoT platforms’ boast today.
