Today’s HR needs clear structures to manage reporting processes, authorisations and role allocation smoothly across the organisation. As a result, having an overview of complex organisational charts and a framework that’s flexible to change is indispensable.
Global HR analyst Josh Bersin identifies people analytics as the fastest-growing sub-domain of the HR profession — with 25% of companies hiring into this role. People analytics is a data-driven method to manage the workforce by creating an HR database that reflects relationships and roles, instead of merely an organisation chart. Bersin has called out graph data technology as a potential basis of a new wave of human-centric HR application.
With modern organisations increasingly focused on role and project – looking at an employee’s real business capabilities, and not just their job title, level, or experience – more complex data about employees, departments, programmes, locations, skills, career paths needs to be analysed. Traditional methods such as tables and spreadsheets have grown to become inefficient. Data must be modeled in the form of graph data structure to encode interconnectivity and graph-based models are a powerful way to examine large volumes of interconnected data.
A brainchild of Leonhard Euler, graph data technology efficiently models these vast networks of entities and their relationships. It offers an overview of complex organisational charts and creates a flexible framework to find information about an employee, their work, their skill sets across different projects and programs faster.
One example is the case of US aeronautics and space agency NASA with their effort to get back to the moon and onto Mars, new skills, new programmes, new projects and new technology were needed. NASA built a skills analysis system using graph data technology to cater to its fast-changing occupations and work roles and to expand the understanding of and access to talent from across the business and optimise its staffing. The agency needed an HR support tool that covered core and adjacent skills, cross-functional skills, training certifications, educational credentials, and career path information, but could also capture where skills are located geographically and within which programmes and projects.
Knowledge graphs and graph databases also make it easier to add and remove information compared with relational database systems. Users can move from node to node and traverse the skills matrices, and the nodes themselves can easily be moved and reoriented without having to change the entire data model. The gradually growing database will not slow down query time, either. Graph data science algorithms can easily be applied to extract insight about skills and L&D trends. Now, NASA project managers can access and query complex data about employees, departments, programmes, locations, skills, career paths, enabling them to contribute to succession planning and a strategic alignment model for any project to meet strategic targets in real-time.
In another instance, a global banking and financial services company uses knowledge graph to drive intelligence insights and empower risks analysts to grant or deny requests such as allowing a bank employee to get USB access, by giving them much better context about what that employee does and what critical information and systems they have access to. With the help of knowledge graph, the bank is able to trace employees’ actions to detect and prevent cyber breaches and fraud.
Graph data technology is used in everything from search engines, GPS navigation, to power social media and in contact tracing applications. Every time you use a search engine, knowledge graphs are used to enhance the accuracy of your results. Graph data technology became famous when The Panama Papers used the technology to expose financial wrongdoing, exposing the tracks public officials and executives had tried to keep hidden.
Graph-based databases are today being used to manage relationships of the modern workforce, even having the power to change the whole HR and human capital management market. With this technology, HR leaders should be able to hold leverage over the very element that holds the success of the company – its people.
By Nik Vora, Vice President (APAC) Neo4j
This article was first published by HR Asia