Every company has to deal with the recruitment and onboarding processes. We covered this topic in another blog post highlighting the monetary investment involved, but with the emergence of big data and analytics we are able to considerably reduce the time and costs.
The other concern companies face is the current candidate driven market, where most candidates find multiple offers from different companies, it’s important to target certain demographics that will be right for your organisation. But how can you do that with hundreds and sometimes thousands of people applying for a job opening?
The answer is data and lots of it.
I’m sure everyone has had this term thrown around, it has dominated headlines in the last decade as the next big analytical tool, its being used in every industry. Big data is essentially just a collection of structured or unstructured data, but what does that mean? Unstructured data could be anything from e-mail messages, word processing documents, videos, photos, audio files, presentations, web pages and many other kinds of business documents. For recruiting, resumes would fall under unstructured data.
For structured data it has a predefined data model, like an excel spreadsheet or a SQL table.
The magic here is using tools to connect the unstructured with the structured to find your golden goose.
Having so much access to information about someone allows you to gauge their productivity, likelihood of turnover and their projected career path in your company even before you hire them.
How its done
In the age of the internet everything you have ever said or done online leaves a record and a standard one page resume just doesn’t cut it. Companies can use tools to mine candidate’s social media profiles and sort through thousands of resumes looking for keywords that meet their job requirements. The end result gives you a complete 360 view of an applicant, allowing you to make an informed hiring decision.
What most companies get wrong is how they design these searches, it’s important to properly define what an ideal candidate is to your organisation. Create filters for personality type and skills based on the each job opening and finding the right tools designed for this job.
Data that you should be looking for
The very first step would be to collect a pre employment assessment of a candidate.
This isn’t something new, companies have been doing this for decades but in 2020 you should be looking to automate this process, allowing you to free up time and resources from your HR department and to get a bearing on a candidate’s personality and skills.
Next, look into their resumes and make sure that the skills and achievements match with their pre employment assessments. Also use tools to find keywords that match with your job opening to ensure that they are the right fit.
Finally, the social media mining, what people say and do in their personal lives is no longer personal, there have been countless scandals involving employee’s actions that have damaged and sometimes destroyed a company’s brand image. It is absolutely essential that you conduct a thorough screening of each candidate’s online behavior and also implement conditions stating that anything they say and do online is of their own volition and has nothing to do with the company.
The Candidate Experience
With people analytics making such a splash in recruiting, candidates are also privy to this knowledge. The company BrandYourself which appeared on the popular investor show Shark Tank acknowledged that recruiters are indeed scrutinizing every single online interaction and offered a solution to purge any bad posts or social media interactions across all the popular platforms for their customers.
They have recently started incorporating AI based searches to further customise and help their users to have a 5 star social media presence.
In closing, the use of people analytics and big data allows you to :
- Removes bias in hiring because the hire won’t be based on subjective factors.
- Helps manage large volumes of applications in a short time.
- Streamlines the recruitment process, making it more efficient, thus reducing the cost per hire and the average time needed to fill open positions.
- Has the ability to predict talent needs by analyzing trends in the voluminous data.
- Has the ability to predict the success of applicants by combining data mining with predictive analytics.
By using statistical methods and techniques recruiters can forecast the probability of an occurrence using historical data. For example, they can make predictions about a candidate’s likely tenure with the firm should they be hired.
Social networks are an invaluable source because they reveal whether a candidate might be a good fit for the culture of the firm. For instance, a social network might show that a candidate enjoys pastimes that might impair their productivity, such as excessive drinking or high-risk hobbies – red flags to any discerning recruiter.