It's advisable to come early, as there are 300 delegates to be registered. The conferences will commence at 09:00 sharp, in order to meet the event schedule.

Location: In front of the main Conference Hall

Who runs the show?
Julia Altenburg
Julia is a founding member of the Rhein-Main People Analytics Meet-up and as one of the „first movers“ involved in the People Analytics scene Germany since 2013.

She is a frequent international speaker, panelist and advisor. Julia has worked as a scientist, psychologist and progressive HR professional and is an experienced coach and consultant for private individuals and corporations.

About the Speaker:
Luk Smeyers
Luk is an experienced CHRO who has lead complex transition projects for compelling blue chip companies.

He has an enviable background performing strategic and operational roles for dynamic, change-oriented companies and has managed at board level through business start-ups, turnarounds, acquisitions, divestitures, joint-venture creation, down-sizing and restructuring on a pan-European basis.

With his result and people oriented focus, he has made substantial difference everywhere and established deep shifts in perspectives and strategies.

In 2008, Luk started as a Human Capital entrepreneur and established a cutting-edge HC Analytics consultancy, together with academic partner Dr. Jeroen Delmotte (www.linkedin.com/in/jeroendelmotte).

Luk is passionate about quantifying and predicting the business impact of people investments. Predictive workforce Analytics is all he does and he is widely recognized as one of the few European top HR intelligence experts.

Luk is revered as a leading thinker, educator, influencer and is a well-known content contributor, blogger, columnist and author of many articles. He is an invited speaker at international conferences and helps clients set a higher ambition for strategic HR intelligence, leading consultative projects and strategy meetings with such organizations as Ahold, Deloitte, BNP Paribas, Zurich, ING, KPN, ABN-AMRO, AXA, Philips, Rabobank, UWV, RealDolmen, Acerta, NS, BASF, Besix, Strukton, Bekaert, Randstad, Eandis, AG, Postnl, AON, Raet, to name a few.

Presentation focus:
Sharing learnings from executing over 100 projects in the past 5 years with regards to implementing the People Analytics function.

Overview:
In our projects, we are seeing that many organizations are starting with People Analytics without thinking of an operating model. We have experienced many times that organizations get stuck after a while and are not making (analytical maturity) progress anymore because the lacking 'rules of the game' (= operating model). I will take the participants thru my experiences and learnings in working with organizations that got stuck after a few initial experiments.

Key take-aways:
1. Understanding the critical necessity to invest in an operating model to become successful with People Analytics
2. How to start using the 4 pillars of a People Analytics Operating Model: People, Organization, Data & Technology
3. How to design a roadmap to implement the People Analytics Operating Model

Panelists:

Moderator:

Candid & controversial - not "just another" round-table

The coffee-break makes for a great occasion to mingle around some 300 delegates, share instant feedback about presentations you enjoyed the most, engage in casual chat and naturally visit the sponsors exhibition area.

Location: HR Tech Expo in front of the main conference hall

Presentation focus:
· People Analytics as a user centered approach
· Start People Analytics without data
· People Analytics can deliver consumer products
· People Analytics will change HR
· AI instead of classical HR approaches
· New roles and tasks for HR

Overview:
Many People Analytics projects start with data. Bosch goes another way. Together with business leaders, the project team identified the most relevant issues they are facing. The team is running the project with design-thinking approaches, focusing on end user needs and not starting with a data perspective. Join to see how this does work.

Key take-aways:
1. People Analytics has different ways to start, just do it your way
2. People Analytics supports employability and business needs
3. People Analytics will change HR

Speaker: Steffen Riesenbeck · Global Head of People Analytics · Robert Bosch GmbH

Presentation focus:
· What is data based employer branding?
· How to choose the right metrics to assess and optimize the employer brand
· Different maturity stages of people analytics usage in employer branding
· Integrating over 500 HR metrics into one employer brand model

Overview:
Employer branding is a complex construct that requires integrating different actions and metrics through the entire candidate-employee lifecycle. How to overcome this challenge when shaping the attrition and retention strategy, setting KPI and measuring the effects? Can it be based on single measures? Should we benchmark towards the other brands? How to integrate the people data to employer brand strategy? Presentation showing different maturity stages of people analytics usage in employer branding based on case studies from well-known big companies operating on the polish demanding market (from the banking to construction sector) such as:
∙ Shaping the salesforce recruitment communication based on performance based research
∙ Optimizing the recruitment campaigns based on performance based marketing
∙ Assessing and crafting the employer brand strategy based on 500 HR metrics

Key take-aways:
1. Choosing and integrating HR metrics is the most challenging task when we do data based employer – branding
2. Using people analytics to asses and optimize the employer brand can have different stages of maturity
3. Benchmarking is not the opposite to people analytics, it is a must have stage when applying it correctly

Speaker: Barbara Zych, PhD. · CEO · Employer Branding Institute

Presentation focus:
∙ The Challenges of Large, Dynamic Organizations
∙ Getting our Analytics Act together: Why did it take so long?
∙ Moving into the Analytics Fast Lane
∙ Our People Analytics Operating Models
∙ How People Analytics is making and Impact

Overview:
At Nokia we develop Big Data Platforms for the telecom industry for a living! Why did it take so long for HR to start utilizing People Analytics for more strategic value? This presentation will focus on the challenges to getting started in a large dynamic organization, evolving a more structured approach and operating model for People Analytics and our current environment. It takes time and is a journey! This will be about our growth in People Analytics capability from the perspectives of People, Processes, Technology & Future Aspirations - Analytics in the Fast Lane!

Key take-aways:
1. How Nokia advanced in People Analytics Maturity
2. Operating Models depend on what Matters Most
3. Use Cases: There is so much Value to explore!

Speaker: David Shontz · Head of HR Reporting & Workforce Analytics · Nokia

A great opportunity to engage in a casual chat with speakers and your fellow delegates. Lunch will be served at the main hotel restaurant, providing a variety of specialties ranging from traditional German food to best international cuisine.

Location: Main hotel restaurant

Presentation focus:
∙ People analytics: from a hot topic to a sustainable discipline
∙ Tips for purposeful and sustainable people analytics
∙ Viewing people analytics as a step towards evidence-based management
∙ Treating organizations as unfinished prototypes that we continuously develop over time

Overview:
People analytics is a hot topic that has the potential to transform how HR as a function is operating. However, starting with people analytics seems often easier said than done. In this talk, I would like to show that people analytics does not need to be rocket science. We will talk about some misconceptions of people analytics and how to ensure that people analytics is purposeful and sustainable.

I will highlight 1) that people analytics does not need to be fancy, but effective 2) that we often do not have to reinvent the wheel, but can use existing scientific evidence as a starting point 3) that we should treat our organizations as unfinished prototypes – and people analytics can help us to develop them over time.

Finally, I will talk about why now is the right time for starting with sustainable people analytics.

Key take-aways:
1. People analytics does not need to be rocket science
2. You don't have to reinvent the wheel - use existing scientific evidence as a starting point
3. Experimental designs can be simple, but powerful approaches

Speaker: Chris Kaibel · Project Lead People Analytics · University of Mannheim Business School

Presentation focus:
∙ Ensuring data governance through a centralized analytics function
∙ Creating a People Analytics function embedded within HR who will serve as translator between HR business priorities and analytical capabilities
∙ Understanding the business demands to develop platforms for self-service data reporting and data visualization
∙ Enabling the HR business to utilize people analytics assets to create a culture of data-driven decision making
Leveraging technological capabilities such as predictive analytics and machine learning to advance analytical insights

Overview:
In this talk, we would like to present our transformation journey and share the learning experiences that we had in setting-up a people analytics function.

We will cover our transformation journey - from operational metrics and manual reporting to strategic business partnering and steering of data driven insights. We will highlight the three most important facets in building the people analytics function: (1) setting-up data governance through a centralized analytics function (2) partnering with the business to understand and respond to their analytical needs (3) developing a culture of data-driven decision making through enablement.

In each of these facets, we will share the lessons we learned that ultimately set the foundation of who we are today and what we bring to our organization – an excellent people analytics function helping create great employee experiences.

Key take-aways:
1. Centralization leads to Standardization: Accurate and Standardized data among business units is a pre-requisite in performing data analytics. To achieve scalable and sustainable data governance, centralizing the analytics function under one organization ensures that data, metrics, and KPIs across the organization are defined consistently.
2. Business Integration Drives Impact: The goal of the People Analytics Function is to help the business make informed decisions by looking at data. Partnering with the business, understanding the business need, and working on real problems are therefore crucial in performing relevant and impactful data analysis.
3. "A fool with a tool is still a fool": Enablement is an integral part of developing a data-driven culture and mindset. Data cannot and should not make decisions for people. Therefore, people should be enabled to use data in making decisions.

Speaker: Sarah Zelt, PhD · Senior Consultant HR Data and Insights · SAP AG

The coffee-break makes for a great occasion to mingle around some 300 delegates, share instant feedback about presentations you enjoyed the most, engage in casual chat and naturally visit the sponsors exhibition area.

Location: HR Tech Expo in front of the main conference hall

Presentation focus:
∙ Navigating complex labor-market using publicly available datasets
∙ Strategies for optimizing hiring decisions, based on particular skill-set and location
∙ Realizing ROI on talent management in distributed organizations

Overview:
Organizations are becoming increasingly distributed in the modern economy. Distributed organizations often find it more difficult to determine how well they should be doing with regards to hiring for specific skill sets in different locations. Publicly available datasets (census data) and other sources (like indeed, meetup, LinkedIn) can help identify geographic areas with skill sets of interest. These data sources can also serve as a guide for how well a company should be doing on hiring for certain roles in these locations. This information can also help inform targeted campaigns to recruit for specific roles in specific locations that are much more resource-efficient.

The presentation will cover how answering a CEO question helped starting HR Analytics journey. The challenges we faced and all the different things we did to resolve them, build a brand and credibility to the work we do and how we play a strategic role in scaling HR as a true strategic partner.

Key take-aways:
1. Geographies vary meaningfully in the density of specific skill sets
2. These variations provide an opportunity for organizations who are distributed / have multiple offices to gain strategic advantages
3. Organizations can combine internal and external/public data sets and information to determine the most desirable outcomes

Speaker: Jared Valdron · People Analytics Lead · GitHub

Presentation focus:
∙ People analytics is a hot topic and can get outsized results
∙ Most organizations do not do it well
∙ A holistic approach is most successful - going beyond tools, technologies, cool analytics or data scientists
∙ Giving insights back to each person can scale productivity and performance significantly

Overview:
ANALYTICS, BERSIN
Prediction: People analytics will augment the workforce and the workplace

Ninety percent of the data in the world has been created within the last two years alone, and the continued emergence of new technologies will likely increase that rate even more. HR leaders have been attempting for years to use people analytics to turn this vast amount of data into actionable insights, but many still struggle with how and where to apply people analytics to maximize the return on investment. In the coming year, more and more organizations will start to apply people analytics in a new way, with a direct focus on the individual, rather than through HR or leaders—a bottom-up approach, as opposed to just top-down.

Last year, Bersin’s High-Impact People Analytics research revealed that only 2 percent of surveyed organizations are highly mature in people analytics. That tiny percentage has granted us an advance look at how to put people analytics to work. The most mature functions not only integrate it throughout their enterprises but also focus it on addressing business problems, enhancing the quality of day-to-day decision-making, and expanding its accessibility and use through robust insight delivery systems. The purpose of people analytics in these few high-performing companies? Enhanced workforce productivity and performance.

Going forward, we predict people analytics will become a principal supporting factor in the growing autonomy (and productivity) of the individual, empowering each person with the insights to help them do their best work.

People analytics will support individuals in the flow of work.

Today, most organizations that have adopted people analytics still use the insights it delivers for the benefit of the HR function: to help improve people processes, to better plan for needed workforce capacity and capabilities, and to effectively attract, manage, develop, retain, engage, and reward people. Tomorrow, more organizations will embed people analytics in the flow of work to enable people to increase their productivity and improve their performance on their own.

As the key user of people analytics shifts from HR or leaders to the individual, the personalized performance and development indicators, insights, and prescriptive actions it can deliver will come to the fore—raising the benefits exponentially. Organizations will still need to pay careful attention to data security, privacy, and ethical issues. But individuals may feel less concerned about their employers monitoring email and meeting behavior if they reap direct benefits of that activity—for instance, automatically generated suggestions about which meetings to attend or skip, and which people to meet with or avoid. Organizational network analysis and meeting metadata make this possible. These insights alone could result in enormous productivity enhancements, given the time spent in meetings.

Similarly, facial scanning and analysis delivers confidential and proactive behavioral nudges: your phone can tell you that you appear to be stressed and suggest a five-minute break before your upcoming team meeting.

Finally, individuals will benefit from tips on how to be more engaged and happy at work—using the same data organizations have been collecting for decades, with the individual as the beneficiary and owner. They’ll also receive learning suggestions based on real-time performance indicators. All of these are possible and available today.

This is not George Orwell’s “Big Brother.” This is individuals owning their own data—and productivity. People analytics will drive up the productivity of the entire enterprise by helping the workforce help itself become more effective and happier at work.

People analytics will free up leaders to enable the productive workplace.

When people analytics empowers individuals to manage their own work and engagement more effectively, the role of leaders at all levels shifts. Instead of devoting the lion’s share of their time and attention at the individual level, leaders will be able to apply their efforts to driving productivity at the group or team level.

People analytics will help leaders make the workplace a better place to work. It will enable them to determine which technologies and environmental features support productivity and which ones hinder it. In doing so, people analytics will help leaders remove obstacles to collective productivity.

Better yet, people analytics will deliver its benefits in real-time. Aggregated data feeds into people analytics systems will provide leaders with early warnings regarding workforce engagement issues, roadblocks to productivity, retention issues, and even burnout or safety signals. Leaders will get insights and suggested actions proactively, rather than having to dig for them. Today, most organizations require leaders to stop their work and go to a separate place to slice and dice data for actionable insights. Not surprisingly, many never find the time. In the coming year, prescriptive insights will become an expectation—real-time, work-embedded insights accompanied by suggested actions nudging the expected behavior.

The people analytics-enabled workplace will become a reality.

It will fall to HR, and particularly, the people analytics team, to thoroughly integrate people analytics with all people-related systems and embed them all in the flow of work. Rather than running reports and looking for insights, the people analytics team will create the environment in which people are equipped to take action quickly and seamlessly.

To accomplish that, vast amounts of structured and unstructured data—operational, people, financial, and customer, both internal and external—will be collected and correlated to identify what exactly drives business outcomes. Organizations will be able to accomplish this using various next-generation technologies such as AI, machine learning, and cognitive computing. This, in turn, will require the people analytics team to build closer and more intimate connections across and outside the enterprise, and to more rigorously monitor the use of people data to ensure it is ethical and secure.

Looking Ahead

HR leaders have talked about people analytics for years, and now we’re on the cusp of an explosion in its use and application. HR will certainly play a central role in attaining its long-promised and much-needed productivity benefits. Technologies are here to make this happen and are accessible and affordable to much broader populations than ever before. But, to really transform people analytics, the more savvy organizations will treat the workforce—not HR and not leaders—as the customer of people analytics. The opportunity ahead is vast: By understanding that the individual is at the heart of their business, organizations will turn people analytics from a backward-looking HR activity focused on reporting the past into a workforce and business benefit, and in doing so empower each person to do their best work and grow their career—and ultimately be more productive.

Key take-aways:
1. Sophisticated analytics, data science and technologies are not enough to make an impact
2. Scaling analytics for impact is challenging
3. Giving each person their own data can drive culture

Speaker: Kathi Enderes, PhD · Vice President Talent & Workforce Research · Bersin Deloitte Consulting

Closing