If someone were to predict that in two years the departure rate in your business would be 20% because of stagnating wages or challenging economic conditions, you would find this prediction futuristic, maybe even impossible.
And yet the predictive analysis of human resources (HR) data is a technology that has gained momentum in recent years, with good reason: it enables HR directors and managers to interpret data quickly and look at numerous risk factors such as absenteeism and resignations, making it their best ally in strategic decision-making!
A focus on reliability and credibility
In 2015, Technomedia, a Canadian company and leader in HR management systems and professional training, approached the National Research Council of Canada (NRC) about adding predictive features to PeopleVision, its talent management platform. The specifications emphasized ergonomics, integration, agility and data security.
"We wanted to go further than our competitors by offering a data aggregator with a reliable predictive algorithm, which is crucial," said Julien Lemesre, Director of Business Intelligence (BI) projects at Technomedia.
HR predictive software has not been in use for very long, and the lack of expertise in analyzing these data is slowing development of management solutions.
"Technomedia doesn't have research and development skills in the area of machine learning; that's the domain of researchers. We needed these skills to be able to meet our users' expectations, to predict future trends and the rationale for behaviours. Partnering with the NRC struck us as the best way to achieve that objective," added Julien.
The NRC boasts researchers with first-rate expertise in information technologies, especially in competency framework engineering, competency extraction and performance prediction. This makes the NRC well positioned to meet technological challenges in the HR sector.
"The NRC has some of the finest expertise in the field, and collaborating with its researchers gives us credibility that sets us apart from the competition."
"It's also important to consider that the accuracy of the predictive analysis results can have a much greater impact than one might think on internal decisions, which is why we need to make sure our solution is reliable in every way," added William Neale, Marketing Director at Technomedia.
Expertise unparalleled in Canada
"We have a talent pool that represents added value for the client," explained Cyril Goutte, Research Officer at the NRC. "This partnership brought together a number of internal resources based in our Moncton, Fredericton and Ottawa laboratories and specializing in statistical modelling, computer science for education and training, and software development."
The NRC's team of experts supported Technomedia throughout its project. "The main challenges were transforming input data into structured information and interpreting output data using the algorithm, which is the cornerstone of analytics and of maximizing the potential of this intelligence," said Cyril. Guillaume Durand, Team Lead at the NRC, added, "The client was new to predictive analytics. To ensure that operations went smoothly, we worked with the client to help them identify and send us the information that would be interpreted by the algorithm."
After six months of development, the NRC delivered a functional technology that meets the needs of its target market.
"Today, our company is proud to offer a world-class talent management tool of the technological calibre we were aiming for."
To stay ahead of the competition, Technomedia must stay on top of technological trends and listen to its clients.
"HR needs and data evolve rapidly and will continue to do so. We want to remain current with the market, so we have to continue to adapt the tool. For example, one of our short-term objectives is to add input data on distance to the workplace, which is a reason why people resign," explained the Director of BI projects.
With data increasing, the methods for analyzing them should also increase and improve. Machine learning is therefore the key element in data preparation and predictive analysis in tomorrow's businesses.
It goes without saying that analytics has a promising future.