The Resourcing function in Human Resources has undergone transformational changes over the last decade. From a traditional way of recruitment where job vacancies are posted in the local newspaper, to the now sophisticated online tools that are used to attract talent. Technology today has rapidly transformed the way we work and communicate, and it has also transformed the way we recruit and retain talent. In this article, I would like to share 3 skills in the use of analytic tools that HR professionals can employ to manage their recruitment and talent sourcing function more effectively. Analytics has a great impact on business outcomes and by leveraging on it, recruiters can transform their image from being “reactive” to a “pro-active” business partner who possesses the foresight to make better and faster talent acquisition decisions and outcomes. The 3 skills are:
1. Proactive Hiring Using Data And Models
In today’s competitive labour landscape, being able to pro-actively anticipate business needs and provide the talent pipeline needed to achieve short and long term goals, is vital to the growth of organisations. Many large companies which have multiple teams scattered in different locations are already benefiting greatly by using data to predict areas where staffing require shoring up of resources and areas that might need down-sizing.
In my experience working for a large security company with thousands of workers in multiple locations, I employed a supply chain model to predict and project manpower needs six to 9 months before the need arises. This is done through integrating HR data with sales pipelines and deployment data. It resulted in the HR Department being able to develop a constant talent pipeline to meet business needs and to slow down in areas where demand is tapering. Figure 1 gives a quick illustration of how the model works.
The Recruitment supply function projects manpower needs through sales pipelines for the next 6 months. This is translated into recruitment targets for the different business units. Predictive analytics is used to develop the manpower funnel that will eventually feed into the deployment system. Recruiters are given daily and weekly targets to meet and specific market segments for candidate resourcing. This systematic model enabled the HR Team to help the sales team win a big project and successfully deploying more than 2000 employees within a short span of 9 months. It’s an instance where the HR Division gave the company a strong competitive advantage to meet the people demands of the business.
2. Tracking Hiring Data To Improve Efficiency
In today’s competitive labour landscape, being able to pro-actively anticipate business needs and provide the talent pipeline needed to achieve short and long term goals, is vital to the growth of organisations. Many large companies which have multiple teams scattered in different locations are already benefiting greatly by using data to predict areas where staffing require shoring up of resources and areas that might need down-sizing.
Analytics help you to improve the efficiency of your resourcing function by offering a high-level view of your whole hiring effort and answers the following questions:
1. Where are your hiring bottlenecks?
2. Which hiring managers need help?
3. Which positions need urgent attention?
4. Which are your best sources for hire?
Let me share a few tools you can use.
a) Time-per-status: How long are you spending on each step of the process?
This simple analytic can make a real difference for a hiring team trying to figure out how they currently allocate their time during the hiring process and how they can better redirect their efforts. For instance, perhaps your candidates are spending far too long in the initial application stage before being either rejected or moved on to the interview stage. By statistical tools such as ANOVAs, you can identify the areas that are causing bottle necks and thus improve your recruitment speed and time.
b) Source-of-hire: Where are your best candidates coming from?
Looking critically at candidate sources can be a great way to tailor your recruitment strategy to tap into the best talent pools. For example, perhaps you’ve been spending time and energy making sure your positions are posted on the biggest job boards. Your hiring team thinks this is a good strategy because the best candidates are obsessively checking these boards for the newest positions. However, your recruitment analytics tell a different story. Turns out all your best candidates are coming from Twitter and Facebook. Now you know to tailor your strategy to focus on social media instead of spending so much time on job boards.
c) Referral rates: How many of your hires are thanks to current employees?
Employee referrals are essential because they often lead to better quality candidates. Your current employees personally know the individuals they are referring and can explain to you how they would fit into the position and overall company culture. They are unlikely to refer someone they truly feel would not fit because this would reflect poorly on their own judgement. Using data analytics, you can see just how many of your new hires have come from your current employees. It might be time to rethink your incentive program if the rate is too low. Perhaps you have been using cash bonuses when what employees actually desire are added vacation days. An attractive incentive program will help you get the right candidates.
3. Using Big Data To Gain Insights
Josh Bersin shared in a recent article on Forbes.com of how a client improved sales performance by $4 million in 6 months simply by implementing a new candidate screening process based on insights gathered from data the company always had. Similarly, a simple analysis of your turnover data can give you insights as to the type and profile of employees that might not fit the culture of your organisation, thus assisting recruiters to be more effective in their next candidate selection. At SUTD, an analysis of high turnover in a particular year revealed that location and accessibility to public transportation were key areas of concern for employees who left. This enabled the recruiters to re-adjust their efforts to hire employees who were living closer to the East Coast campus, thus reducing turnover.
In another study done by “World at work” where they went through thousands of data sources, it was discovered that better quality of leadership resulted in lower turnover of key talent, as compared to paying higher salaries. Information like this can help recruiters focus their efforts on recruiting more high quality managers, thus eventually reducing compensation cost.
Conclusion
Using data analytics require skills and competence in different disciplines. These include: data analysis, statistics, visualisation and problem-solving. Most HR professionals currently lack these skills, and finding such individuals and getting them to work on HR data becomes important. Finally, it is important that recruiters ask themselves fundamental questions as to what they are trying to solve, and the type of data they will need to help them make better hiring decisions. Once that is identified, data analytics will complement the function by drawing out important information to support hiring decisions.
I hope you found this article useful and that it has given you insights on how you can improve your resourcing process. Do you have any other thoughts or suggestions to add on to the 3 points that I have mentioned? Are you currently using such tools in your resourcing function?
I welcome comments, thoughts and ideas as we move along in this journey to adapting analytics, systems and models to refine the hiring process!
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