HR: Applying Business Judgment to Data Science
Most organizations place too much emphasis on data science and data management at the expense of driving business decisions and actions.
To improve the impact of talent data, HR is increasingly seeking individuals with advanced statistical degrees and experience working with statistical tools and models.
However, analytics expertise is only part of the equation. Business judgment— the ability to use business and organizational knowledge to draw conclusions from talent data—is far more influential on business outcomes.
CEB research has shown that, on average, business judgment activities have up to a 32% analytic impact compared to 18% for data science activities. (‘Analytic impact’ is defined as the extent to which talent analytics improves decisions and provides actionable support to key stakeholders.)
HR executives at the best organizations focus less on advocating for talent analytics and more on building the function’s ability to:
- Set a clear vision and objectives for analytics staff that are oriented around business judgment;
- Hold all HR staff accountable for applying data to business challenges; and
- Establish accountability and connections between analytics staff and the business.
For example, Telefonica Europe, a telecommunications company, has refocused the role of the HR analytics function toward inspiring, influencing, and shaping business decisions using three key steps:
Step 1: Align the hiring process to overall analytics goals. Although Telefonica hires candidates with advanced degrees, they assess for strong judgment skills critical to driving business decisions, as shown in real-world simulation tasks.
Step 2: Reinforce the need for analytics to support action. Telefonica ensures HR analytics employees have opportunities for internal networking and best practice sharing at every step of the HR analytics project cycle.
Step 3: Establish mutual accountability for analytics results. Telefonica’s HR analytics team lead engages with business stakeholders before the start of any project to establish clear business expectations—what HR analytics will do for the business and what the business unit will do to support the HR analytics team. Early collaboration and consensus ensures HR analytics will be trusted and used by the business.