No CDO? Better Think about Getting One
Do you have a chief data officer? By 2019, you probably will -- if only because almost all your competitors will have one.
Do you have a chief data officer (CDO)? Do you need a CDO?
By 2019, you probably will -- if only because almost all your competitors will have one.
That's the conclusion of a recent report from Gartner, which estimates that a quarter of all organizations had already hired a CDO by the end of last year. By 2019, 90 percent of all organizations will have them.
According to Gartner, the rapid emergence of the CDO position has everything to do with increasing (let's be honest, exploding) interest in analytics. It's part of the still-coalescing shift toward digital business -- a shift that, in just the next two years, will change the way most companies do business.
Why a CDO? More Data and More Possibilities than Ever
By 2018, Gartner predicts, analytics and algorithms will inform the competitive decision making of more than half of all large organizations.
Analytics models and algorithms aren't magic, of course; they don't produce results without the right data. However, thanks to the proliferation of connected devices -- via both the Internet of Things (consumer or commercial connected devices and services) and the Industrial Internet of Things (the enterprise counterpart) -- organizations will have plenty of data to power their analytics.
In the report "Predicts 2017: Charting a Path to IoT Business Value," for example, Gartner projects that IoT endpoints will grow at a 32 percent compound annual growth rate from 2013 to 2020. Organizations that think they're awash in data today haven't seen anything yet.
The proliferation of devices or connected "things" -- and the general pervasiveness of IP connectivity and computing power -- will create more opportunities to collect, analyze, and monetize data. The imperative will be to ingest, manage, analyze, and use this data to improve efficiencies, reduce costs, improve strategic business planning, and permit organizations to develop new products, services, and business models. The CDO has a key role to play in all of these activities.
In the near term, Gartner says, organizations will use separate analytics engines to monitor and process signals from IoT and related streams. They'll primarily focus on improving efficiencies -- e.g., monitoring IoT feeds and using predictive analytics to predict impending failures or maintenance needs -- to reduce costs over the life of IoT-enabled signalers.
As companies get more sophisticated, Gartner predicts they'll integrate IoT analytics into their core business processes. This "will enable the transformation of business models from guarantee of performance to guarantee of outcome," according to the Gartner report. For example, this will permit a company to track and bill the amount of power consumed by upstream operators.
Over the long term, companies will use IoT analytics to improve the design, engineering, and manufacturing of products and services, resulting in additional efficiencies.
More than anything else, the digitalization of business -- a phenomenon that encompasses IoT and a number of other parallel or converging trends -- will help to popularize the role of the CDO, argues Ted Friedman, research vice president and distinguished analyst at Gartner.
"It represents a much deeper change occurring throughout most organizations. Practitioners of distinctive data and analytics disciplines will need to broaden their understanding and work more closely with others to realize the benefits of using data and analytics to capture transformative business opportunities and mitigate risks," Friedman argued in a prepared release.
The role of the CDO is to set the stage for the identification of candidate use cases, applications, and processes for digitalization, as well as to promote collaboration, sharing, and innovation between analytics practitioners at all levels and in all domains of the business.
"The modern data and analytics leader has an unprecedented chance to transform the organization on its journey into the world of digital business," Friedman concluded.
"[T]he course of action is clear: craft a strategy to overcome the data science skills gap, modernize data infrastructure and [analytics] platforms, govern and take advantage of diverse information sources, and spearhead data and [analytics] projects that have high-value payback."