Saberr, a London-based start-up company, has been successful in designing a pre-emptive and predictive model used for hiring decisions. This system can be a great help for companies that have trouble finding the right candidate for a job. The models it creates can help predict the characteristics of the candidate who will be perfect for a specific position.
The predictive recruitment algorithm started with a gamble.
A couple of years ago, Alistair Shepherd was trying to determine the relationship between the qualities of people by observing the variables on a dating site. He wanted to find out what makes people like each other. This data helped him with his future research for finding the perfect candidate for a job. He founded Saberr with one of his university friends in 2013 and is now helping companies by providing them with highly-customized tech solutions for their hiring needs.
The idea for this algorithm started with predictive exercises, and after founding Saberr, Alistair started visiting entrepreneurial competitors, but not with the aim of competing but instead to predict winners. Shepherd explained his tests in one of his blog posts:
“Our first test of the algorithm was at the University of Bristol. They were hosting a business plan competition as part of their Spark course. We wanted to see if we could predict which team would win without any knowledge of their skills, their experience, their demographic, nor the idea they were working on. We were hoping to be roughly right, roughly the teams with better relationship quality would rank higher than those with lower relationship quality. But instead we got the precise ranking of all eight teams spot on. The probability of getting this correct is 1 in 40,320.”
Although the company is very young, they have a good reputation for satisfying clients, which has helped them develop a strong portfolio and referral customers. However, there is one challenge they are facing: They don’t have a data bank of their own, so they have to rely on information provided by customers. Although Saberr’s algorithm is very effective, the lack of data points can hinder future predictive analysis for hiring and recruitment purposes.
But Shepherd is hopeful that even though the company is new and lacks the sophistication found in internet giants like Insidesales, there are vast opportunities for them. He emphasized his point by saying, “We are seeing good take up in the enterprise space. There is a real desire to change and innovate their practices, and they have the resources to make that change, so selling into this works extremely well for us. Unsurprisingly, the tech world is very open to using data about people to make business decisions. Probably because they are pushing that narrative in other areas: that tech and data will change your life.”