Hi, and welcome to the sixth module, which is dedicated to recruiting. Recruiting can be both fun and exhausting, but as cliche as it may sound, it is always the most important process in any business. In this module, we will cover the basics of workforce planning analytics, recruiting technologies, and candidate assessment tools. Basically, workforce planning encompasses everything the organization does to identify its talent needs now and in the future, in terms of skills, numbers, quality, and so on, assess how internal and external events can affect those needs, predict turnover, and plan talent sourcing to satisfy organizational needs. Analytics boils down to being able to incorporate and integrate internal and external data to go beyond traditional workforce planning, which emphasized head count. Workforce planning analytics looks at strategic and operational business metrics, behavioral and engagement data, and uncovers hidden causes of attrition, absenteeism, low performance, and so on. Proper workforce analytics is future oriented and prescriptive in nature, informing recruiting and development strategy decisions. Many enterprise analytics platforms provide comprehensive talent analytics, which include all aspects of human capital management and integrate with finance and performance metrics. Most small businesses cannot afford such systems, and even for large companies, integration can take a long time. Being honest to the promise of making this course as practical as possible, we will talk further about some of the things you can do quickly to gain insights into attrition, recruiting, and planning your talent needs. Identifying skill gaps is directly connected with your business strategy. It's fairly simple to conduct skills audit to identify today's needs, but it is much harder to predict what skills will be needed as your business grows, expands, or pivots. Having regular skill and competency assessments, and individual and team development plans tied to business objectives, would help you understand what you currently have. This is the starting point which would help you uncover what skills you need to develop and what skills you need to buy. There are various ways to predict attrition. One way is to use historic data. Another is to apply data analysis to historic data to identify patterns which lead to employees quitting and then apply these patterns to the existing population. There are various ways to predict attrition. One way is to use historic data. Another is to apply data analysis to historic data to identify patterns which lead to employees quitting. And then apply these patterns to the existing population. Ideally, your system would continuously monitor this data to highlight employees that are at risk of leaving at organizational, team and individual levels. Moreover, an advanced analytics engine would also analyze which measures were successful in retaining the top performers and high-potential employees. Finally, some systems like Joberate analyze external data, including social media and networking systems, to provide the so-called job seeking behavior scores which gives the probability that someone is looking for a job. Using Joberate, and tools like that, could be accessible to SMEs as much, both in terms of the cost and in terms of the amount of data. Because it utilizes its own algorithms and big data, it would work even if you're trying to assess job seeking behavior of just one employee. Building your pattern model to identify potential quitters or paying for tools developed by companies like SAS or Visier might be more expensive, but may pay for itself given your cost of replacement. Before making decisions on how much to invest in retaining your employees, both in terms of retention measures, and investment in expensive predictive analytics, it makes sense to understand what your replacement costs are. Oftentimes managers think that replacement costs are limited to recruiting costs. For example, paying for executive search firm or posting an ad on Craigslist and so on. However the greatest part of replacement cost are associated with time devoted to identifying, interviewing, selecting and onboarding potential employees. And with lost productivity, almost always resulting from the need for a new employee to reach her potential. Even if you find a replacement before the incumbent leaves and has the ability to train the newcomer. On top of that, there are elements which are extremely hard to quantify, like expertise and organizational or cultural knowledge, that your employee takes with her when she leaves. And team dynamics that breaks up when one of the critical links are missing. Greg Willard from Boston-based Cangrade gives a great overview of most costs associated with employee turnover on the ERE Media website. Replacement cost analysis, though, is never complete without proper risk assessment. Retention investment has to be allocated where the risk of losing someone who is valuable to the company is higher. In the most basic terms, which would be much more complex in real life, your decision making would be based on comparing the product of replacement cost times risk of losing the employee. This is where predictive analytics plays a crucial role. Recruiting can take many forms, depending on company size, growth patterns, and the skills it requires. In this module, we will talk mostly about recruiting technologies that would apply both to small and large companies. On this slide you can see the universe of talent acquisition technology, on the map developed by Talent Tech Labs, an incubator for HR tech companies in New York. It is possibly the most crowded HR tech site plan. Regardless of the company's size, recruiting process includes the following, defining job or roles descriptions, sourcing and identifying candidates, engaging candidates, filtering applications and assessing candidates through interviews, tests, assessment centers, and onboarding candidates.
