The Need to Lead

Artificial Intelligence is revolutionizing how analytics are used. However, among many benefits lie many complications.

The Need to Lead
Artificial Intelligence in AnalyticsAnalytics were formerly used for simple tasks, such as measuring cost and performance on various business initiatives. In the past few years, some companies have gained a competitive advantage with their use of artificial intelligence (AI) in analytics. The use of AI for analytics in health technology has created significant space for innovation. However, as space for innovation rises, the need for management to adjust, and new talent to fill positions rises as well.
 
Some benefits of using AI in health-related analytics include:

  1. Bringing intelligence to medical devices
  2. Turning electronic health records (EHRs) into a reliable risk predictor
  3. Monitoring health through wearables/personal devices

Among many benefits, there are also many complications. IBM predicts that the demand for data scientists and analytics (DSA) will increase approximately 30 percent by 2020. In terms of overall data professionals, the number of job openings will increase from 364K to 2.72M by 2020. Similarly, IDC, a premier global market intelligence firm, indicated that the data and analytics industries will grow at a compound annual growth rate of 11.7 percent, reaching $203B in 2020. Alarmingly, DSA jobs are currently the most difficult positions to fill, averaging 5 days longer than the market average. With rapid growth in terms of demand coupled with extremely low unemployment rates, business leaders must develop strategies to address these trends.
 
According to a recent McKinsey Institute survey on the need to lead in data and analytics, even when analytics are top of mind for company leaders, only a quarter of them report to have communicated clear vision throughout the company.
With the increasing potential of AI for analytics in health technology, the shortage of qualified talent and the apparent lack of a clear corporate vision by the vast majority of leaders, how do leaders succeed?
 

Leadership and organization are key.

Before jumping into tactical activities, communicate clear priorities and vision. The same McKinsey Institute survey compared high performing companies to low performing companies. The largest qualitative difference between the high and low performing companies related to the leadership behind analytic activities. While leadership in low performing companies struggled to develop an organizational structure to support analytics, the higher performing companies reported that senior-management involvement was the greatest contributor to their success. Ensure that your leadership can develop organizational structure that fosters growth.
 

Invest and Find the Data Talent You Need.

Multiple factors, including the low nationwide unemployment rate, are challenges in finding top talent to suit your needs. Ensure your HR department is supporting you effectively. Additionally, establish a partnersip with an esteemed staffing agency, such as Talencio. Allow us to find solutions for your team so you can focus on your organizational goals.
 
For more solutions to address the talent shortage, reference our recent articles “What is 8X More Productive than Typical Talent” and “A Short-Term Strategy for Long-Term Success.”
 
Written by: Isaac Pirk, Talencio intern and student at North Central University, Minneapolis, MN.
 
About Talencio: We help the Health Technology community make progress by putting the right people in the right place to solve problems and identify opportunities to move healthcare forward. To learn more about career opportunities in health technology, or to hear how other companies have partnered with Talencio to tap into our skilled professional talent pool, contact us at 612.703.4236 or email. Talencio has been the preferred provider of vetted, accomplished professionals to the Health Technology Community for over 10 years.
 
Sources:
What’s Now and Next | McKinsey
AI Impacting Healthcare | Health IT Analytics
DSA Demand | Forbes
Big Data and Analytics | Forbes
Data & Anlaytics | McKinsey

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