Reflecting on the changes that have occurred over the last 20 years in talent acquisition is a humbling activity. I don’t consider myself to be an old timer by any stretch of the imagination, but I have watched the changes happen and been very happy along the way. In the late 90’s we still had filing cabinets of resumes to flip through if the databases weren’t producing enough, and faxing a resume to a hiring manager was an everyday occurrence. This was in the midst of Monster’s disruption of the industry through their aggregation of resumes in one place leading to an explosion of resume databases.
As we continued into the new century, cell phones became more common and our ability to communicate started to become a 24/7 affair in conjunction with email. In the early 2000’s most of us were still tied to our desktops and bringing home our work every day wasn’t yet prolific. During this time, resume databases started to strangle print ads as companies saw the advantage of online job postings and people stopped reading the paper. Applicant tracking systems were making companies more efficient in their hiring and everyone began to fall in love with Managed Service Provider programs and mark up rate caps in contract labor.
Blackberry had been around for those people who liked to have access to email and the internet 24/7. However, the iPhone served as a model of convergence for recruiters, candidates, and hiring managers with essentially everything you need to consume data and communicate in the palm of your hand. Never mind the iPad, which was a performance enhancing drug.
Social networks changed the way we communicate and how we consume information. LinkedIn and Facebook gave us digital footprints which could be data mined by savvy sourcers who didn’t need to pay for resume database accesses. Tools began to change to focus on the new way we communicated through social networks and talent acquisition became integrated with the technology.
We are still seeing a proliferation of new tools coming available. It often feels like there is something new on the market to try every month. As I look forward, though, I haven’t seen the technology align much in the area of big data and predictive analytics. I once pleaded with my LinkedIn rep to investigate data mining their network to produce useful insights when I looked at a profile. Obviously, that didn’t go anywhere and I think talent acquisition providers are behind technology curve.
LinkedIn, CareerBuilder, Indeed, etc. have millions of data points for analysis that are not utilized. They could be providing tools for recruiters to make their lives easier and improve decision making. For example, they have enough data points to start correlating and making probability statements on whether a potential candidate will leave their position based on a profile. What is the probability that someone who has worked in a private company for 10 years in X,Y, and Z locations would consider B location in a public company? The data points exist within the confines of their proprietary database to provide that insight. The dozens of questions that recruiters ask themselves when reading a resume can be answered without requiring the need to rely on intuition or opening a new window for research. For instance, I’m looking at a resume that has some gaps or periods of short tenures. An overlay of the unemployment rate or sector economic performance would give me data to make an informed decision. A direct link to aggregated company news from public sites and search engines would allow me to deep dive further into company performance.
My dream is that someone brings the data under one platform to allow recruiters to make more informed decisions about resumes. Providing a robust level of data analysis and insights will allow recruiters to make reliable decisions and reduce the reliance on intuition and gut feelings when viewing a resume. The data is there in droves, but who is going to use it?Read more
by Rodney in Uncategorized
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Discretionary effort is usually described as the level of effort an employee gives beyond the required minimum for their job. It is the area where an employee is going beyond what they have to do for their job and potentially achieving greater productivity and results for the company. In a company with employees using maximum discretionary effort one would expect to see high achieving results and high engagement. Discretionary effort is directly linked to employee engagement because as engagement rises, so does discretionary effort. At least, that is the common thinking on the subject. Employee engagement scores measure how people feel in relation to their work and employer. It is not a direct measure of productivity, but is an indirect leading indicator of attrition, absenteeism, and productivity.
An organization which can measure the level of discretionary effort output of its employees has an amazing piece of data and differentiator. It is like the speed gauge in your car. However, the challenge is how to directly measure it. Employee engagement measures the sentiment in your organization which you can then use to extrapolate a wealth of additional data, discretionary effort being one of them. It has most famously been used to show highly engaged organizations perform better. For example, Gallup says EPS growth rates are 3.9 times higher for highly engaged companies. I suspect the problem remains for most C-Suites that correlational data is not compelling enough to invest a great deal in employee engagement programs.
I believe the data to measure discretionary effort is right there on a company’s server. It is entirely possible to data mine internet/intranet traffic, email, calendars, and time card information to develop and accurate picture of level of effort. Collecting data on the amount of time employees are in meetings, actively using their resources, and engaging with coworkers, customers, and contacts says everything about their discretionary effort. Direct observation is also the best way to get commitment from executives to act. There are no correlations involved or required. We could see actual behaviors throughout the day which tie directly to productivity.Read more
by Rodney in Uncategorized
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by Rodney in Uncategorized
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