How Cornerstone Insights Will Unlock Big Data Potential in HR
April 2, 2019
Cornerstone recently announced Cornerstone Insights, a suite of predictive analytics dashboards that a applies sophisticated data science to workforce data, enabling business leaders to answer burning questions about how to use data to better hire, train, manage, and retain top talent. Max Simkoff, VP of Analytics at Cornerstone OnDemand, answers a few questions on how why this is an important announcement and why analytics will transform the state of talent management.
How will analytics transform talent management and business as a whole?
The term "talent management" was conceived 15-20 years ago. Since then, there has been a constant focus on automating key processes such as recruiting, onboarding, learning, succession, and performance management, as well as just getting all of the key transactional talent data in one place. Now that massive volumes of this talent data sit in the cloud with large enterprise talent management providers, analytics will be used to transform talent management from the world of process automation to intelligent decision support.
For example, whereas five years ago the focus was on automating the application process within the recruiting realm, with analytics the focus will now become automatically identifying the key attributes of individuals such as behaviors, competencies, and even keywords on a resume that statistically correlate to higher performing, longer-tenured employees.
This will have far-reaching, significantly positive implications for business in general because it will mean much more consistent and data-supported decisions that result in higher performing teams who drive better bottom-line results.
What is the most interesting use case of analytics you have seen implemented to date?
One use case that I believe is going to change the field of professional development in a very fast period of time is one that we have developed and deployed at Cornerstone, "predictive career-pathing." We have developed an algorithm powered by our machine learning engine that can show what the most successful career paths within any organization look like via a visual succession path diagram—using any employee or position as a starting point.
Every employee within a company can now explore what their own individual ideal career path might be, based on the experience of people who were previously in their position. They can now see what other jobs or roles they took on from that position and what their promotion track within the organization looked like. Using this has uncovered some very uncommon career paths that are unique to certain organizations.
For the first time employees have complete transparency and accuracy around how to achieve their ideal destination within their company. What is really amazing about this particular use case is that it also links career paths to associated actions and learning courses so that an employee can not only see what a potential career path is—but what courses they can self-register for in order to get there faster.
What is a common misconception of what analytics can/cannot do?
Perhaps the most common misconception around analytics is confusing correlation with causation. Most often, analytics is uncovering correlations that are statistically significant enough to demonstrate that two or more items are related—but it’s an entirely different thing altogether to say that one is actually causing the other. In order to determine causation, you need to make sure that your analytics algorithms have some unique and important quantitative methods built-in and additionally that you test them using A/B or randomized methods to separate correlations from causative factors.
What do you think businesses will be doing with analytics five years from now?
With all of the progress we’ve seen in the past five years, it’s almost impossible to imagine how far and fast the analytics world is going to advance in another five years. Based on the current foundation that has been built, we can expect to see advances in natural linguistic processing and semantic analytics to be able to automatically mine online profiles like LinkedIn and resumes to identify collections of experience or keyword phrases that identify high performers. Additionally, with the large volume of data being produced by employees every day we will likely be in a world where the performance review moves from an annual event to a continuous set of iterative interactions with employees that enables true iterative feedback based on observed patterns of data. Ultimately we’ll see HR and Talent Professionals get more focused on interpreting data and analytics and less focused on putting processes in place.
What are you most excited about with the release of Cornerstone Analytics?
It is extremely exciting that we are now able to immediately tap into over 15 years’ worth of valuable talent data and what we’ll be able to do with that data, especially in the area of learning and development. Cornerstone has a massive amount of highly granular, accurate data about how people learn. Our ability to mine this data and produce actionable recommendations will likely change the face of professional development in a way that both accelerates how people learn as well as where they choose to explore new knowledge.