Why graphs will form the basis for a new HR industry

Global HR influencer Josh Bersin recently singled out graph databases as the basis for a new wave of HCM technology over the next 5-10 years. Neo4j’s Amy Hodler examines the claim and considers some real-world examples.

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HR relies on clear structures to manage reporting processes, authorisations and tasks, and role allocation smoothly across an organisation. As a result, having an overview of complex org charts and a flexible framework to respond to change is indispensable.

Something that will assist in this vision is graph technology. The technology, which is primed to find connections between datapoints, was identified as the potential basis of a new wave of human-centric HR applications by respected HR analyst Josh Bersin in his latest annual report on HR technology.

Bersin identifies people analytics as the fastest-growing sub-domain of the HR profession—he says 25% of companies are hiring into this role. People analytics means creating an HR database that reflects relationships and roles, not just an org chart, and Bersin has called out graph technology as a promising way to achieve that:

“In today’s businesses, people have jobs and job descriptions, but these don’t typically reflect the work that is actually done. More and more of the focus today is on role and project, which leads to the need to look at someone’s real business capabilities, not just their job title, level, or experience… every individual in the company is no longer a node on the hierarchy. We are each nodes in a network, connected to many other people, projects, information, and history.

“[Graph databases] are vastly more powerful for modeling how people work in networks, how people search for data and objects, how people communicate and build different types of relationships (peers, team-mates, bosses, subordinates). These products essentially store this information into a graph of the company, which can evolve over time.”

Graph 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 theory was the brainchild of Leonhard Euler, perhaps the greatest mathematician of the 18th century. Graph technology became famous when The Panama Papers used the tech to expose financial wrongdoing, exposing the tracks public officials and executives had tried to keep hidden.

Data modeled in the form of graph data structure encodes interconnectivity, making graph-based models a powerful way to reason about large volumes of interconnected data. Graph databases efficiently model complex networks of entities and their interrelationships—which is why they are increasingly being used to make sense of HR relationships.

Mapping personnel structures to get an overall perspective

A perfect example is carmaker Daimler’s use of graph database technology. With 250,000 employees in multiple locations and interdisciplinary teams worldwide, diarising and scheduling time for project availability can be a challenge: managers work with team members on leave, temporary workers, and resource from partners and service providers. To manage, Daimler built a graph-powered HR platform to provide insight into these personnel structures.

The solution had to adapt to regular changes in personnel in a user-friendly and transparent way. At the back end, it needed to map personnel structures to provide an overall view or new perspectives on data and uncover new connections. Finally, the software needed to maintain data integrity and quality when making structural changes.

A graph database solves these issues and grants Daimler the possibility to gain deeper insight into different structural levels. Nodes such as ‘Employee’ or ‘Expertise’ and the connections between them (for example, ‘active’, ‘reports’, ‘participates’) can be assigned any number of qualitative or quantitative characteristics, such as the duration or type of employment.

The result is a complex network of data and data relationships that can be navigated and provide real-time insight into relationships, such as team affiliation. Users can move from node to node in the graph database and quickly traverse the hierarchy network.

The graph database gives the HR team deeper insight into the structural levels. Often, interesting aspects are visible only through the analysis of relationships at the second and third levels. In the graph database, users can go deeper into the data structure, gaining new insights into data relationships that are not obvious at first glance.

Skills gaps in space exploration

Let’s look at another use case in a different industry, space exploration. NASA needed to build a skills analysis system to cater to the organisation’s fast-changing occupations and work roles. Its Acting Branch Chief of People Analytics and Sr. Data Scientist David Meza explains why:

“As we are trying to get back to the Moon and onto Mars, we've going to not only regenerate the skills we used to get to the Moon before but look at new skills and new programmes and projects and the new technology we have to incorporate to do that. So we need to have a good understanding of our workforce to achieve that.”

The agency wanted to create a database that covered core and adjacent skills, cross-functional skills, training certifications, educational credentials, and career path information. The database also needed to capture where skills are located geographically, and within which programmes and projects.

Using a graph database, 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. Graph data science algorithms can easily be applied to extract insight about skills and L&D trends.

As a result, complex data about employees, departments, programmes, locations, skills, career paths can be queried by NASA project managers in real-time, contributing to succession planning and a strategic alignment model for any project to meet strategic

targets.

So is graph technology going to change the whole HR and human capital management market? Graph databases are, in essence, about managing relationships, so it seems like a very natural fit and one that HR leaders should look into.

Amy Hodler is Director, Analytics and AI Program at Neo4j, the world’s leading graph database company. She is also co-author of Graph Algorithms: Practical Examples in Apache Spark & Neo4j, published by O’Reilly Media