By Ben Wohl
This is the third of a three-part series about COE Forum’s upcoming Data Analytics Industry Futures study. The first and second parts of this series respectively concern how to appeal to the rapidly growing citizen data scientist market and how to quickly test and fund new electives and certificates.
Bootcamps’ business model necessitates staying on the bleeding edge
Ongoing advancements in artificial intelligence undermine the viability of skilled occupations formerly safe from automation. In one widely cited 2013 Oxford University study, 47% of American jobs were found to be at risk of automation. Even jobs that survive will be transformed.
Data analytics programs are not exempt from automation’s transformative effects. Deans and program directors must take steps to ensure their analytics programs remain relevant and attuned to changes in high-demand skills. To stay ahead of the curve, take cues from how bootcamps keep up with rapid technological change.
Bootcamps position themselves as the leading source for up-to-the-minute job skills. To continue to grow, bootcamps must stay at the forefront of analytics to provide the in-demand skills that ensure graduates can attain their desired jobs. Known as a “career transformation academy,” General Assembly is the largest bootcamp in the United States by enrollment and market value.
This particular bootcamp needs to grow even more to ensure a successful 2018 IPO and repay its early investors, including Jeff Bezos, Amazon's CEO. From new tools to hot skills, bootcamps can act as “canaries in the coalmine” for universities by providing advance notice of what is happening at the frontier of analytics. Analytics program administrators can get insight on the pace of technological change by tracking their non-traditional competitors.
Learn from bootcamps: 3 steps to prepare your analytics program for continuous change
Learning from the strategic and operational behaviors of the bootcamps involves three steps:
Monitor bootcamps’ market performance.
Perform periodic curriculum comparisons to determine whether their curricula are keeping pace with a rapidly changing field.
Mimic bootcamps by capturing a non-traditional review of the market through examining the skill and hiring profiles of both traditional and leading edge employers.
EAB’s upcoming data analytics study, “Data Analytics: Capitalizing on Creative Disruption,” will cover all three steps in detail. In the interim, focusing on the third step leads to understanding the “voice of the market” (pinpointing the emerging in-demand skills sought by employers) and promises the biggest ROI.
Capture a non-traditional view of the market
In a fast-changing field like analytics, program directors need to accurately and holistically monitor changes in employer requirements and hiring. EAB research identified two key steps for bootcamps to capture insight quickly and accurately on high-demand and emerging skillsets:
Gather bottom-up insight. Conversations with executives on an advisory board and company recruiters should be complemented by talking to analytics practitioners and managers. These individuals typically know more than anyone in the firm about hiring needs and the most relevant analytics skills.
Avoid traditional market myopia. Local employers provide useful perspective, but programs should supplement these insights by talking with leading edge employers whose skill needs are ahead of the analytics curve.
Program directors should compare these insights to their current curricula. This comparison should reveal how the program matches up with employer expectations and also help guide program directors toward how to better align education with emerging job requirements.
Of course, outside of analytics, many other COE programs will be disrupted by automation. Therefore, this two-pronged approach to keeping up with market demand can certainly be applied to other COE degree programs, too.
Learn more by registering for our Capitalizing on the Rise of Data Analytics series
These represent only a handful of strategies to infuse adaptability in your current or future data analytics portfolio. Ultimately, as automation continues to change the nature of work in North America and beyond, constant program adaption will become ever more important.