Power to your people with graph databases
Human relations departments used to process people data in a similar way that finance departments process fiscal data: the role was administrative, and people were company assets
How Sense HR is leading the next generation of HR software solutions
Human relations departments used to process people data in a similar way that finance departments process fiscal data: the role was administrative, and people were company assets. That role, not to mention the expectations of personnel, have evolved beyond all recognition but the architecture behind most HR software is the same as it was decades ago.
At SenseHR, we’re changing that. We want to support HR and human capital management professionals with precision tools to perform the strategic, analytical, and supportive functions that are now expected of them. And we want the people who they’re managing to feel valued, empowered, secure, and even understood. What’s more, we’ve got the technology to achieve it.
Graphs, glorious graphs!
Legacy HR systems—and you can go ahead and put nearly every existing product in that category—are built on relational databases, which are carefully modelled, predefined data tables. The relational model has many applications—it can be great for accounting applications, for example—but when it comes to the living, breathing, relationship-based world of people data, it’s seriously limited.
Unlike legacy systems, SenseHR uses graph databases to achieve a relationship-centric approach to people analytics. Using our software, companies and their people can map, analyse, and benefit from the more complicated and flexible relationships between different team members, their work, skills, talents, experience, and much more.
Industry analyst Josh Bersin, confirmed in his 2021 industry report that people analytics is the fastest growing sub-domain of the HR industry, with 25% of firms now hiring into this role. He goes on to identify graph databases as “vastly more powerful for modelling 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),” and he notes, “In today’s businesses, people have jobs and job descriptions, but these don’t typically reflect the work that is actually done,” instead he identifies people as “nodes in a network, connected to many other people, projects, information, and history.” And this is exactly how graph databases store people data.
Hang on, not so fast! What’s a graph database?
We’re glad you asked.
Let’s visualise how one employee in an organisation—let’s call them Rachel Jones—could be mapped in a graph database. It’s an exercise that can begin to reveal the significance and ROI in using company-wide, next-generation HR systems. In a graph database for HR functions, a person would become a node and would have properties like a name, email address, and date of birth. They can be connected to other nodes, which can be other people, locations, departments, skills, and so on, according to their relationships. For example, Rachel is connected to David because they’re colleagues in the marketing department, friends, and worked at another company together for 3 years prior to their current employment. Yes, you read that right—the relationships themselves can include properties too, which leads to a fuller, data-rich, understanding of how everyone in a company is interconnected, in ever-evolving, real time.
The following graphic is a basic example of what kind of data a graph database could store for Rachel and what that might look like.
Graphs empower everyone
One of the major benefits of the graph model is that people can be viewed by the system as individuals, with unique talents, skills, networks, and histories. Coupled with the relevant analytics tools, graph databases could make it less likely that individual contributions are overlooked, or emerging skills and talents are wasted. More fluid roles and career paths could be easily managed and even encouraged, leading to a more satisfying, productive, and largely autonomous workplace.
As teams and people become more spread out and mobile, both geographically and organisationally, effective people and knowledge management becomes exponentially harder using legacy systems. Imagine a global company wanted to find the right team to head up an international marketing campaign for a new product. It might require system searches for similar historic marketing campaigns, the success rates of those campaigns, the different teams that have worked on them, and their individual availability for a new project. Using a relational database, this would mean making several different searches through campaign, employee, and schedule data tables, then collating the data, before building the team. But because of the relationship-based structure of graph databases, companies could implement tools to upload a brief for a project or use the brief criteria to conduct a single search, then receive automated recommendations on which teams would be best to carry out the project based on real world connections, company hierarchies, schedules, and historical analyses. Any decisions could be tracked and fed back into the system for further analysis.
And that real-time feedback can highlight useful patterns. For example, showing that staff engagement has reduced after the introduction of a new policy. Or productivity is suffering after the appointment of a new manager. Or that a project is taking longer when compared to similar past projects.
The future is… graphy
We’re with Josh Bersin on this one—the future of human capital management is probably going to be built on graphs. So, naturally, we wanted to get ahead of the crowd. Here’s just a few of the things that you can do with SenseHR.
- Support goals, workflow, training, compensation, and multiple reporting models within the HR system, to successfully model people working on multiple teams.
- Seamlessly manage contractors, part-time employees, gig workers, and any other alternative employment type you want to throw our way, including modelling them in the system.
- Understand that people are often managed, paid, and trained based on their relationships and influence, so connections are part of their value.
- The core HR system is highly flexible and scales naturally, so third-party apps with different data models can plug in easily. That’s hard, if not impossible, to do with traditional systems.
And we don’t like to brag (OK, we do a bit… but only occasionally… like now), but this kind of functionality is never going to be available on legacy systems, because it’s not feasible to update traditional relational HR systems to the graph model without going back to the beginning and redeveloping the whole system architecture. Afterall, databases are the foundation of any HR system.