Josh Bersin offers new insights on how we can help our organizations become not just literate in data, but masters of it. This Resource, which was created in conjunction with our People Analytics Program, shares Josh’s four-stage analytics maturity model. When you sign up for the Josh Bersin Academy, you’ll gain access to our Programs as well as our library of 250+ Resources—to which we add three new Resources per week. Enjoy this exclusive sample, and join the Academy for more.
As our organizations acquire more data, Josh argues that the old maturity model for people analytics isn’t cutting it anymore. The four levels many organizations were (and still are) using to measure people analytics maturity from 2015 onward are: operational reporting, advanced reporting, advanced analytics, and predictive analytics.
The first two levels—the reporting levels—are merely operational. Josh found that in 2018, 84% of companies were still in operational mode and had not advanced to the more impactful, less administrative areas of people analytics. The need for progress is huge. So, here is the new maturity model Josh proposes to help us guide our organizations toward people analytics maturity:
Level 1: Trusted Reporting and Alerts This level is defined by reactive reporting of operational and compliance measures, plus a focus on data accuracy, consistency, and timeliness. The focus is on making HR and talent better, including ERP, talent, recruiting, learning, diversity, compensation, and rewards.
- Data management, integration, and shared data dictionary
- Governance of data definitions
- Reporting and integration tools
- Strong IT partnership
- Sound tool set for dashboards
- User access to data
Level 2: Management Insights and Action At this level, organizations engage in proactive reporting for decision-making, analysis of trends and benchmarks, and produce customizable, self-service dashboards. The focus is on identifying performance engagement, retention, and culture issues through feedback, conversations, and surveys; wellbeing, location, psychometric data assessments and 360 data; reskilling of HR business partners.
- Integration of analytics team with performance, talent, engagement, and other assessment offerings
- Ethics and trust standards for data privacy
- Clear communication to users
Level 3: Productivity and Work Redesign At this level, organizations produce statistical analysis, identify issues and actionable solutions, centralize staff, and integrate data. Organizations should take a consultative approach to individual business units, show expertise in network analysis, have an analytics team embedded in the business, and leverage tools for organizational network analysis (ONA).
- Understanding of how the organization works
- ONA and/or email metadata
- Map of database relationships that include understanding of organizational design, management practices, high-performer behaviors and misbehaviors
Level 4: AI-Enabled Action Platforms At this level, organizations are developing predictive models and data governance models, carrying out scenario planning, and analytics are integrated with business and workforce planning. Organizations at this top level should provide tools to help managers improve behaviors, leverage employee segmentation and journeys, and integrate AI-driven chatbots and other systems of employee engagement.
- Established process for delivering action and insights to managers and bringing data together into employee experience solutions, journeys, and problem-solving projects