› Data driven HR. Top trends in People & Work Analytics
› Networked company: agility, learning and engagement
› Organizational Network Analysis (ONA) as a tool of People & Work Analytics
› Organizational Chart Reinvented with Organizational Network Analysis (ONA)
› Complexity management in HR
› Building a culture of cooperation with advanced analytics
› What works and what doesn’t work when organizing company around teams and projects
› Social capital in a company – how to measure and manage it?
Intelligent automation of HR processes based on the analysis of large data sets on employees and their interactions as well as predictive algorithms supported by ML and AI is a strong HR trend. According to Deloitte research, the use of this type of analytics by HR teams around the world has increased from 16% in 2016 to almost 60% in 2018. What data is used for analysis? In what areas are they used? What statistics make practical sense? What paid and non-paid software is available on the market? We will answer these questions by discussing, among others turnover prediction at IBM, retaining key talent at Nielsen, or analysis of engagement conducted in Shell.
Networked companies with flat team and project-based structures have the advantage in today’s world, because they learn and move faster than their competitors, better respond to consumer needs and better attract and retain best employees. What is a networked company? How do its structures and processes work? You will learn modern startups such as Spotify, but also stable corporations such as GM, Decathlon or Thomson Reuters transform through network companies: what they’re doing, how they’re doing it, and why it works.
Organizational Network Analysis (ONA) allows a company to measure collaboration and communication between teams and employees based on data from company systems (e.g. calendar, e-mails, project management system). In the network, a dot represents an employee or team and the line represents connection between employees or teams. Algorithms and network visualizations based on such data allow you to measure many key HR metrics automatically and in real time: processes in which the team is involved, the level of overwork or employee availability, area of work, work-life balance, degree of isolation in the group or quality of contact with the manager. It is the basis for measuring HR areas that have been elusive so far, automating many management processes and describing the work of people and teams automatically. You will learn basic network interpretations and analyzes and will get to know how they are used in companies such as: GM, Thomson Reuters, mBank or Samsung.
The organizational chart we know is 100 years old and does not fulfill most of its functions, especially for companies that organize in flat structures focused around the work of teams and project groups. Research indicates that the hierarchical tree we know does not show the work of over 50% of teams in the company, does not show how 90% of work is actually done and usually does not keep up with real changes in the structure. At the same time, it is often still the main source of knowledge that informs employees how work is done and how to navigate the organization. Research shows that the lack of a good org chart results in a sense of chaos, communication and collaboration problems, and lower work efficiency. The networked org chart is the answer to these challenges. It is created by embedding data on collaboration (and not only a subordinate-supervisor relationship), data on teamwork and project work, and network analysis into the org chart. You will learn how such an org chart looks and works and how visualizing a company as a network of cooperation between people and teams reduces organizational chaos, simplifies organizational complexity and shortens the time needed to search for information and knowledge. You will count what real savings this can generate in your company and learn on the example of real companies such as Beumer Group or SCANFIL how such an org chart works.
It’s getting more and more difficult for companies to handle complexity: increasing customer needs for more customization, more convenience, lower costs and faster innovation. At some point the machine breaks down and companies just can’t handle it. Operating in conditions of variability, uncertainty, complexity and ambiguity (VUCA) is often associated with a sense of chaos and requires the management of complexity. How to manage the company as an emergent organism that is subject to self-organization? Stanford University research shows that processes are more important than strategies and the software plays the managerial role of white collars. You will learn what is complexity management in HR, what processes are optimized and what software is used. We’ll talk about how the best companies in the world such as Netflix or GitLab are doing this today.
A company employing 200 people spends about 5 million PLN annually on cooperation. Hence, it’s worth knowing how to manage, measure and improve this area. Organizational network analysis (ONA) comes in handy as a people analytics method. You will find out how network analysis serves for precise measurement of cooperation (including e.g. lack of cooperation, cooperation overload, key people for cooperation), and what free and paid software is used for such analyzes. You’ll find out how network perspective can be built into the organizational chart and how it supports company-wide agility, self-learning and engagement—in both dynamically growing startups and large stable corporations on an example of such companies as mBank, Samsung, Burda International or BEUMER Group.
Companies organizing work in flat team and project-based structures have the advantage in today’s world, because they learn and move faster than their competitors, better respond to consumer needs and better attract and retain best employees. However, the complexity of management processes is growing, and at the same time there is a lack of HR tools that can support them. The effects are amazing, such as the fact that more than 50% of teams are hidden for companies, it is not known exactly who works in what team and who was involved in what projects. You will find out how manage work organized around teams. While learning what processes and habits are implemented by the best companies in the world, e.g. Spotify, Medium, Valve or GitHub you’ll learn what, how and why it works and what does not work so far.
Not only individual contributors create business results. It is the entire system of relations and interaction between employees – one that facilitates or hinders work. In developed economies, social capital accounts for over 50% of the growth rate. Social capital consists of social networks and employee interactions, the quality of these relationships and their diversity. It is harder to manage social than human capital and this is where the management of networks, cooperation, diversity, values, a sense of belonging and organizational culture appeared in HR areas. Key to HR departments become system-based and automated data-based solutions that bring local, bottom-up changes, and increase overall coordination. You will learn how to measure social capital and manage it. On the examples of real companies, you will find out what data and analysis are used for measurement, what software are used and how it affects the business of: Netflix, Spotify, Beumer Group or GitHub.
Anita Zbieg – Expert with experience in Work & People Analytics and management practice. Network analyst, collaboration and communication analyst. Author of over a dozen scientific papers on organizational network analysis (ONA). PhD thesis on ONA as a method of evolution for organizational structures. She built her experience into the https://networkperspective.io/ software that visualizes how people and teams cooperate and makes real-time analytics on people, work and collaboration gathered from the tools a company uses. For over 7 years she has been advising medium- and large-sized companies, e.g., mBank, SAMSUNG, Burda, TAURON, Danone czy BEUMER Group. She also shares knowledge as a lecturer at Warsaw University and as an author in the Harvard Business Review.