In a recent post, we examined the idea of a “21st-century career”—what it is and steps organizations will need to take to enable this new model of work. In the post, we noted the disparity between the critical need for new learning approaches and the lack of decisive action being taken by companies, and provided steps organizations can take to achieve business goals and meet the workforce’s changing expectations.
Today we take a closer look at one of those suggestions—the role of data in determining learning needs.
The use of data to analyze, predict, and improve employee performance has increased significantly in recent years—both in practice and perception. Among respondents to the Deloitte 2018 Global Human Capital Trends survey, 70 percent note that they have begun major projects to analyze and integrate data into their decision making. Additionally, 84 percent of respondents view “people analytics1” as important or very important, making it the second-highest-ranked trend in terms of importance.
Data-driven learning, which is a component of people analytics, is an approach that considers multiple factors to determine a person’s learning requirements. It means looking at evidence, such as actual proficiency assessments (direct), surveys about what employees think they need to learn (indirect), and knowledge about the skills employees in similar job functions and industries need to be productive.
When working with clients on learning approaches, we base recommendations on multiple sources. We look at experience we have had with companies of similar size and in the same industry—for example, the topics that caused the most disruption during migrations, specific applications and features that required more intense training, etc. We factor in company culture and client-specific data—Which applications or features are employees calling about the most? Which topics are getting the most traffic in our Help Me kNow Hub?
Several factors are driving the use and importance of data in organizational learning (and in all aspects of HR strategy). Among them:
Smaller, more frequent updates and releases are changing the way learning happens. Just a few years ago, software changes were sweeping, disruptive events that occurred every three to five years. For example, switching to a newer version of Office meant dozens of new features to learn and widespread downtime. Companies usually provided one-size-fits-all training, regardless of an employee’s job responsibilities, with the principal goal of returning to pre-migration productivity levels as quickly as possible. Advanced and job-specific training came later, if at all.
But smaller doesn’t mean simpler. Today’s rapid-fire updates deliver significant new and changed functionality on a continual basis. Since the first quarter of 2017, Microsoft launched 160 Office updates, 91 of which were released in the first quarter of 2018 alone. In addition, Microsoft currently has 189 updates in development and 75 that are beginning to roll out.2 To ensure employees can keep up, organizations need to provide targeted, effective training and support.
Skills have a shorter shelf-life. Experts predict that almost half of subject knowledge learned during the first year of a four-year technical degree will be outdated by the time students graduate.3 In addition, by 2020, more than a third of the desired core skill sets of most occupations will include capabilities that are not yet considered crucial to the job today.4 Keeping up is critical. Upskilling and reskilling will become critical in coming years.
Learning needs differ according to industry, company size, job function and other factors. Employees in one industry—healthcare, for example—will not use Office 365 the same way people who work in a field such as oil and gas do.
Using data in all aspects of business can deliver enormous benefits to both the organization and the employee. However, business leaders should keep in mind that data is not a cure-all—you cannot reliably determine a person’s learning needs with just one reference point. To create rich, effective learning and development, organizations need to rely on a combination of data, knowledge and human expertise.
1. “People analytics” is the application of math, statistics and modeling to employee-related data to see and predict patterns. Also referred to as HR analytics and talent analytics, people analytics is used to make better decisions about all aspects of HR strategy with the goal of improving business performance. Source: “Essential Guide: A guide to HR analytics,” by TechTarget, https://searchhrsoftware.techtarget.com/definition/human-resources-analytics-talent-analytics.