Challenges around the skills crisis, or “war for talent”, have been made more prominent in today’s evolving workforce. Instead of narrowing the impossible talent gap, organisations are moving their focus towards maximising and retaining the skills employees already possess.
When it comes to the IT industry, there is an added complexity given the rapid pace at which technology is progressing. Tech organisations, large or small, need people who are willing to learn, transfer skills, and adapt to these changing requirements.
According to the Equinix 2022 Global Tech Trends Survey, 63 per cent of IT decision-makers view a shortage of personnel with IT skills as one of the main threats to their business. Organisations who try to rehire former employees or seek new talent may need more time to re-skill and upskill these employees.
Leveraging the power of graph technology
Beyond training and redeploying people, it is becoming imperative to help employees reach their personal career goals. Employees are quite often confused by the complex ecosystem of platforms, systems and processes that have been deployed within their organisations. Whilst employees simply want to know what in-demand skills they should have for career development opportunities, managers may not always have the necessary data to provide this advice.
Organisations maintain large amounts of data about their employees and in most cases that data resides in siloed systems that are difficult to connect. Graph databases and graph data science allows organisations to connect siloed data and determine the complex relationships within this data which can then be applied to various use cases for workforce planning analytics and career development recommendations for employees.
To untangle this complex ecosystem of siloed data, DXC Technology is using a combination of the Neo4j Graph Database and the Neo4j Graph Data Science Library (GDS) for its Career Navigator platform. As explained in the recent International Data Corporation (IDC) InfoBrief on The Power of Graph Data Science, graph technology uses a more sophisticated way of structuring data as it contain nodes and relationships as its primary structure, compared to tables in a traditional relational database, which contains rows and columns. On the other hand, graph data science is a scientific approach to gain knowledge using the structures of connected data to power predictions, answer questions, and explain outcomes.
The first release of DXC’s Career Navigator is currently being piloted by 10,000 employees across the APAC and EMEA regions. Employees receive automated and personalised recommendations for career development and mobility, based on in-demand roles and skills. At the same time, they also receive recommendations based on the skills and learning of their peers and the role that they are currently in, their aspirational role, open roles and project assignments.
To be successful in developing employee career opportunities, organisations need a view of what is likely to occur in the next six to 12 months to allow enough time to upskill their employees. Using the graph database to determine external demand and supply patterns will enable organisations to look “beyond the horizon” for trends on where they should be upskilling employees.
By anticipating forward skill demand, organisations can ensure that their people are trained and ready for the next wave of technological change, without constantly having to go back to the market in search of new talent.
Using data to drive career development
With data, leaders also gain a better understanding of the complex relationships between their people, skills, learning gaps, and business resources. It also enables them to better guide employees towards career opportunities and pathways available within their organisation. If done right, graph technology can be a very powerful tool for organisations to benefit from a more diverse talent pool and be more effective in redeploying their workforce.
A forecast by Gartner shows that graph technology will be used in 80% of data and analytics innovations by 2025. Being able to analyse employee-related data can effectively bring more value to an organisation. It allows for more informed decision-making regarding employee development and career mobility, builds better employee experiences and fosters meaningful relationships. Employees become more empowered to drive their own career development as they have a clearer career plan and at the same time, connect with individuals within the organisation for mentorship and peer learning opportunities.
While traditional analytic approaches struggle to extract important relationships between entities, leaving useful datasets neglected and underleveraged, graph-based models can analyse large volumes of interconnected data and uncover hidden connections, hence providing organisations with a clear view of all the relationships and roles within the workforce.
Graph technology set to transform HR functions and management
With today’s remote workforce, leaders are faced with changing expectations in working environments, shifting mindsets, market demands and challenges when managing career pathways for employees. Organisations need better tools to help retain employees and upskill them to high-demand opportunities, while keeping their skill sets within the organisation. On all counts, graph technology is set to transform HR functions and management, offering real-time data to solve the rapidly changing skills demand.