In the world of data analytics, the role of chief analytics officer is being shone down on. The current position of a CAO is to report to the CEO with the analysis of data within a company, and it’s currently changing to accommodate the rise of artificial intelligence technology. As improvements continue to be made, artificial intelligence analytics is in the spotlight as being an advanced option for analytics. CEOs are, therefore asking their Chief Analytics Officers to scale artificial intelligence advancements and deploy advanced analytics.

It’s an excellent opportunity for a business, but even more significant challenge for CAOs. Chief Analytics Officers face a lot of stumbling blocks ahead in their efforts, and while they are hired to scale the data and analytics function for growth purposes, progress is not always linear. Most teams have their focus pulled toward general business operations instead. Business CEOs need to be more open-minded to the opportunities that CAOs could take in AI, capturing the bigger prize in advanced analytics than their competitors do. What has to happen is the Chief Analytics Officer needs to assume the leadership role, the Catalyst – which will be a whole new business persona for deploying advanced analytics at artificial intelligence scale.

Three Types Of Organisation

In the past successful CAOs have been pushed by analytically minded CEOs. The organizations that are pushing analytics include three types:

  • Pure digital, analytics as to the lifeblood of the organization. These have CAOs in the thick of their C-suite, leading the way.
  • CEO is analytically driven, putting analytics at the top of their priority list and is pushing every executive in the business toward analytics.
  • Organisations that require analytics to compete. They put the CAOs in charge of the way their business is due to transform.

In the early 2000s, there was an increase in data generation. This was because of the social media boom and the rise in internet-based businesses. The emergence of better data capture and analytics technologies pushed the bar for success and leaders in analytics had more pressure and expectations on their shoulders. As the analytics leaders gained more recognition and pressure in their roles, the CAO role was born. People could see data analytics usage through their organisations. The next decade brought a little more urgency to digital natives who were becoming even more successful, which upped the intensity of their competition.

Data-generating smartphones have grown in popularity and in numbers, surpassing how many humans there are on the planet. This means that data-hungry machine learning techniques are more commercially viable and to be able to get this right, an aggressive CAO is a must. They can then embed analytics across an organization way more consistently. The problem is that the strong push from aggressive CAOs means that the role itself needs to be rebranded as a leader to encourage further change.

A Demanding Role

In the present day, CAOs are sought after to capture the AI opportunities ahead. This allows for a degree of scale for a business that was not required before and in an environment that is far more demanding. There is a massive need for the competition from the digital natives, and it’s being pushed throughout all sectors to increase wallet share. Analytics and artificial intelligence use have become the stakes on the table when it comes to the delivery of personalized attention. Analytics tools are expanding and becoming more widely available because of the cloud, and this is allowing demand to be met. Analytics and artificial intelligence delivery are now high stakes due to these reasons, and with almost a third of the value that these technologies are expected to drive coming from marketing and sales use, it’s essential!

While all this has happened, the risks have grown alongside the benefits. There have been concerns around data privacy and IT security and organizations are expected to balance these concerns with their projects. Most analytics projects are running into massive delays due to security requirements being on the up. CAOs are therefore facing challenges within the organizations that they are working, and they are doing their best to push scalable analytics functions. There are long-standing processes to be navigated and data silos that must be stitched together. There should also be analytics structures in place at the back of the business to keep it going.

With all of this pressure, CAOs often find themselves pulling the weight of analytics and AI on their own. This is accompanied by limited influence, and they don’t have the profit and loss accountability that would give them the power that they need. Similar to chief marketing officers ten years ago, a CAO lacks a seat at the C-suite table, much as they need one! This puts CAOs at a substantial disadvantage when it comes to getting funding or necessary resources.

In today’s digital landscape, the previous CAO personas couldn’t have found success. However, we are in a time now where the CAO has to be a leader and no longer in disguise. They need to embrace a new style of leadership that is pushed toward addressing the demands of today – including the deployment of AI and advanced, scaled analytics. Catalysts have to approach their role differently compared to CAOs of old.

There are five critical areas in which CAOs need to lead the charge, and these include:

An Equal Coalition

Catalysts have to work closely with IT, business and the CAO themselves, creating a coalition of equals.

Enterprise Capability Building

Playing a leadership role in analytics equals capability building across the whole business.

Advanced Analytics Integration

CAOs have to lead and advise on how your business should integrate those advanced analytics insights into decision making.

Change Agent

Catalysts are change agents. They are able to navigate barriers in the organization and change them to analytics adoption.

Board & CEO Advice

All catalysts support and advise their CEOs and boards, helping with the foundational knowledge on the artificial intelligence role. This then allows members to understand the journey compared to the competitors and learning about governance issues.