Yes, people analytics is on the rise, and rightfully so. HR becomes an increasingly data-driven function. The biggest obstacle: When it comes to people analytics, business leaders ‘don’t know what they don’t know’, since there is no naturally grown demand for people analytics (for various reasons, disappointment with HR data being one of them). To convince business leaders, people analytics needs to prove substantial value fast. The biggest conventional value lever for HR is its impact on engagement. And the biggest emerging value lever is that people analytics supports an agile organization. If people analytics is applied to these fields two recently underleveraged data sources are required: Skill and experience. Skill data is the currency of skill management: It enables the workforce of the future, with productivity gains of up to 9%. Experience data fuels the active management of employee experience at scale in large organizations, with the potential to drive employee engagement improvements of 26%. That’s reason enough to look more closely at these underrated data points: Experience data is a new and emerging people data point. The background story: Companies are aware that employee experience (EX) is an important field. It drives the engagement of employees, and hence, performance. Yet 87% of HR functions are not actively managing EX. The primary cause is in plain view: HR is – regarding its data in this respect – blindfolded. Neither HR’s feedback tools (employee surveys, pulse checks, exit interviews, HR ‘voice of the customer’ etc.) nor their IT systems are actually measuring the experience of employees. Experience happens at touchpoints of employee journeys. Marketing, sales, and service functions started to manage the Customer Experience (CX) 15 years ago. They can prove that companies managing CX effectively yield a 35% higher shareholder return than the average large company. They should be able to teach HR how to manage experiences. The key lesson for HR to learn: If you don’t have experience data, you don’t know which touch-points to fix and you can’t hold anyone accountable for it. In other words: Only if HR measures direct, touchpoint-level experience feedback of employees we will know where to direct the scarce resources to drive people engagement. And only then will we be able to make ‘touchpoint owners’ responsible for improving the employee experience. Skill data is underleveraged for one major reason: Skill detection is hard. Traditional ways (skill catalogues) have largely failed. New platforms for maintaining skill profiles are not sufficiently used. And sophisticated models predicting skills based on social data are much harder to bring to reliable levels than we earlier anticipated. To overcome these issues, we need a new paradigm for skill management: Let’s focus on two critical talent groups for skill management – the ‘experience seeker’ and the ‘unaware & unemployable’. A 70/20/10 skill building model is key for both groups: 10% formal (e-) learning, 20% informal coaching and mentoring, and 70% on the job training, organized in projects. To get there, HR (and people analytics) must offer three services: A skill analysis service, making current skills transparent and evaluating them especially in regards to employability and volatility in a new world of work. A skill neighborhood service to show to people the skills they should develop – derived from their current skills, future skill demand and personal preferences. Finally a skill building service, based on formal, informal, and – first and foremost – project learning. When these three services are clearly focused on the talent groups ‘on fire’ they will bring noticeable personal value for individuals thereby encouraging them to adopt the idea and share their skills and aspiration openly. In summary: Only by managing skill and experience data professionally will HR be able to provide enough business value for business leaders to make people analytics the service to improve people decision making. Let’s go for it!