The industrial sector is undergoing a digital transformation driven by artificial intelligence (AI) and the Industrial Internet of Things (IIoT). At the same time, the manufacturing workforce is shifting as retiring domain experts are being replaced with tech-savvy hires who may lack the same level of operational expertise. From this backdrop emerges the Chief Data Officer (CDO) and the industrial data scientist, a new breed of data experts with access to more industrial data than ever before.
In 2021, PricewaterhouseCoopers (PwC) published a first-of-its-kind, quantitative, global study of Chief Data Officers. In the report, they explain that, while the CDO role has emerged as a senior executive role over the last five years and much has been written about the role, there is not sufficient data tracking the evolution of the CDO within an organization. After surveying the role at 2,500 of the largest publicly traded companies, there were four key findings:
- Companies are talking the talk about data. The survey showed that two-thirds of companies are talking more about data than five years ago.
- Companies are not yet walking the walk with CDOs. In fact, only 21% of the top 2,500 companies have a CDO in place.
- 80% of CDOs are based in North American or European companies and are most likely to be found in companies with more than 10,000 employees and more than $5B in sales.
- The presence of a CDO influences how companies talk about data — companies with a CDO mention data ~30% more frequently than those without a CDO.
Number of CDOs hired by year (SOURCE: PwC Chief Data Officer Study)
Heiko Claussen, SVP of Artificial Intelligence at AspenTech, says that there’s growing importance placed on data and the core function of the CDO is to create value from all the data that is being gathered at a record pace today.
Volume of data/information created, captured, copied, and consumed worldwide from 2010 to 2025 (in zettabytes) SOURCE: Statista
With this level of data growth, it’s important to take that “Big Data” and turn it into actionable, smart data for the organization. Heiko points out that you need to determine how you are going to store the data to make it accessible to different functions across the organization. For example, when an organization wants to do automated testing on customer use cases or simulation data for data science purposes, this can require collaboration between the CIO and the CDO functions, as well as collaboration between the software experts and the operations domain experts within industrial organizations.
Heiko has found that simply having a data science background isn’t enough to ensure success as a CDO — it also takes industry expertise. The CDO needs to collaborate with customers, partners, suppliers and within their organization. This requires a well-rounded combination of domain and AI expertise.
In the video below, Heiko speaks with Jim Harris, one of the foremost thinkers on disruptive innovation and author of international bestseller Blindsided, to discuss the “Rise of the Industrial CDO.”
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