How Chief Data Officers are reshaping the future of work
A recent McKinsey article analyzing workplace automation trends highlights the growing unease over the displacement of workers by technology. In the coming years, McKinsey predicts data collection and data processing will be two of the top three job activities replaced by machines. (The top activity, by the way, is “predictable physical work,” like drilling.)
For data-oriented job activities, machine learning, robotics, and artificial intelligence applications will augment and/or complement the work of humans who currently collect and process data. As research and advisory firm Outsell has chronicled in its Future of Work research, these rapidly maturing technologies enable businesses to utilize advanced (and economical) computing power to seamlessly integrate natural language, predictive and prescriptive analytics into their everyday activities.
Yet as the workplace continues to evolve, so too will the role people play collecting and processing data.
Automated data collection has come a long way, particularly with the rise of Internet-based technologies from web-based forms to site scraping and machine-learning applications. But there are sobering (and somewhat surprising) statistics about how often humans are still spending too much time doing what automation should be doing.
For all jobs in the US economy, one-third of the time spent at work involves workers collecting or processing data. Mortgage brokers spend up to 90% of their time processing applications, and financial sector workers as a whole spend 50% of their time on data collection and processing activities. And if you think this work is concentrated among lower-wage employees, consider that senior management — defined as earning $200,000 and above — spends 31% of their time engaged with collecting or processing data.
Beyond the growing potential for job automation, the ways these changes will actually impact business depends on multiple factors: cost-benefit (i.e. business case), regulatory and social elements, and labor market dynamics. These factors, combined with technical opportunities, will ultimately be the forces reshaping the nature of work.
Enterprises gain competitive advantages through innovation and efficiency, and automation is transforming the workplace from top to bottom. Chief Data Officers (CDOs) are driving these changes at all levels. They’re raising standards for data accuracy, comprehensiveness, and velocity. And they’re making data a foundational asset of the business and product-development lifecycle.
Contrary to the ‘threat’ aspects of disrupting the future of work, CDOs have a positive role in this transformation: They are eliminating routinized, monotonous tasks for employees, clearing the way for greater satisfaction/productivity with fewer errors. Automation of the future is less about displacing workers and more about changing the nature of work and ultimately improving quality of life.
Taken a step further, data executives are fueling the rise of a different type of data-related job: storytellers.
For CDOs, the common thread in more effective Business Intelligence (BI) teams is improving and evolving skill sets. Instead of focusing on the technical or development skills required to build data dashboards, CDOs are cultivating BI managers who better understand the operational objectives associated with their work. Greater insight into business objectives — coupled with greater emphasis on communication skills — ensures that this new breed of BI manager builds platforms and interface, with better analytics and insights to drive business performance.
But why limit focus simply on automation and the role of workers in the future?
CDOs and data executives can improve the quality of life for workers today by employing data already embedded within their enterprise systems, providing insights into employee satisfaction and revealing factors that accelerate attrition.
Combining traditional data inputs — such as compensation, tenure, and promotion history with secondary factors such as the departure of a teammate, re-org histories, or recent M&A — can help identify who’s safe and who’s at risk today. Alongside these existing data streams are more sophisticated sociometric tools such as Humanyze, which can reveal social patterns that help companies modify office layouts, policies, and org charts to maximize employee performance.
Leveraging new technologies to automate data collection and analysis are less about displacing workers than about improving the quality of work.
Hugh Byrne covers the business of data for Outsell Inc. Find out more about how data executives are reshaping the future of work at Outsell’s DataMoney conference, Feb 1–2 2017 in NYC.
