Multimodel research Assignment about Gun Control

Gun control is a controversial topic that has been around for a while but resurfaces every time there is a mass shooting or some type of shooting. The topic is very split, and people are either for…


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Hiring Without Confidence Is The Norm!

Thinking outside the box to expand interview methods within Data Science & Analytics

Evaluating strangers over the course of several hours with the intent of investing tens of thousands of dollars per year is a high stakes game of chance. How much can truly be understood about a person’s experience, capabilities, ethics, and overall fit in such a short period of time. Essentially, employers are making decisions with a compromised level of information. This outcome is the product of an outdated model for candidate evaluation which includes four key components; resume, ATS (Applicant Tracking System), interview, and assessment.

In today’s employment market majority of resumes are sourced through a handful of methods. Those include services such as professional social networks (i.e. LinkedIn), job boards (i.e. Indeed), career sites, recruitment firms, networking events, and internal referrals. Each of these methods has its own pros and cons associated with the types of candidates produced and supporting information.

Once candidates have been identified screening criteria is applied to identify only those that are considered the best fit for the position. This typically involves searching resumes for keywords and other indicators.

Now that the pool of candidates has been reduced employers conduct interviews to gather information on cultural fit, experience, ethics, problem solving skills, soft skills, technical abilities, analytical thinking, and so much more. Interviewers have a number of techniques at their disposal:

The intended purpose of assessments is validation. Employers are seeking as much information as possible to confirm what’s documented in the resume and what’s been stated throughout the interview. In many cases employers are also attempting to quantify cultural fit.

This method of sourcing and evaluating candidates for hire has been static for generations. The only thing that’s changed is the technology. Unfortunately the information gathered through this entire process is only a snapshot of a candidates abilities.

Selecting a candidate that falls short of expectations quickly becomes a huge waste of funds. This not only includes what’s been spent so far but also the cost of moving forward to find and hire a new candidate. Employers are in need of an improvement to this hiring equation that provides more information for decision making.

Innovation is required to solve for this challenge. Employers need a method to discover more data about candidates. If there were a measurement of insight into a candidates skills and abilities the current evaluation methods would only capture 5% of the necessary information. For this metric only experience and capacity to perform the functional aspects of the job are being measured; cultural fit is not included.

In order for such a measurement to be optimized, employers would need to evaluate candidates in an actual job function. Employers would need the ability to observe and measure candidates as they were performing. In some ways this is similar to internships. Interns spend between 3–6 months with a company working within a team on actual projects. This creates the opportunity for a thorough assessment of an individual’s experience, skills capacity, and growth potential.

Sadly offering all candidates a 3–6 month trial period is not realistic. Instead the next best thing would be to create a simulation that accurately represents the business. The more realistic the simulation the higher the assessment capabilities. The realism would need to accurately represent all aspects of the businesses model. Simulations designed to this degree foster the opportunity to create scenarios where candidates must apply the full scope of skills required for the available position. Candidates will be required to perform discovery of realistic data systems, develop a deep understanding of the business processes that generate data, create systems of data organization, analyze the outputs to arrive at determinations, and finally synthesize findings in support of outcomes and communication.

Simulation interviews, although more condensed than an internship, serves the purpose of delivering a full view of a candidates experience, skills, and analytic capabilities. When compared to the interview techniques that have been around for generations simulations make it possible for employers to have greater than 5% visibility into a candidates experience and analytic capability. Employers will have more data available on each candidate to make a data driven decision.

Simulation interviews also offer more opportunity to candidates. Those who otherwise might have underperformed during the traditional interview portions would have the chance to demonstrate abilities in realistic settings. Again, the more information available to employers only serves to improve the end decision.

Thanks for reading.

This article is a reflection of my opinion with additional information gathered from the sources referenced below:

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