People Analytics For Dummies
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Analytics, specifically people analytics, can be applied to an array of decisions from within the talent acquisition function. When a company is just starting out, the work of talent acquisition often is performed by a key founder or ends up being shared by everyone on the team. As a company grows, the demands of talent acquisition become more complex. Eventually, the company must hire people to take responsibility for the work of acquiring more people. Historically, this highly specialized role within an organization has been called either Staffing or Recruiting — increasingly, it's being called Talent Acquisition.

Whatever you call it, it isn’t unusual for a growing company to have dozens (if not hundreds) of people doing this work. I have worked in some companies — Merck and Google are two prominent examples — that have over 300 recruiters. Talent acquisition is like a business within a business. And, with its high volume of activity, the inputs, activity, and outputs can seem difficult to see, manage, and control.

The operative word here is seem. The fact of the matter is that talent acquisition, like sales or supply chain management, is a production-oriented function for which there are straightforward ways to measure success — there are, in other words, clear inputs (applicants) and clear outputs (hires) and start and end time stamps. In this respect, you’re dealing with a classic throughput funnel, where a large initial pool is whittled down to a relatively small final result.

analytics talent acquisition Talent acquisition professionals find candidates and then work those candidates through stages until a hire is made.

As the figure illustrates, first you have a lot of activity and eventually a hire is made — and it's this activity that needs to be managed correctly. Talent acquisition measurement isn’t limited to the number of hires that come out the other side of a funnel. You can use a variety of metrics and analysis to wrangle better control over what is going on in that funnel. Important measurement categories include volume, efficiency, speed, cost, quality, and the experience of candidates and hiring managers.

Measurement helps you see what is working well, what isn’t (and why), and how to make it work better. In some cases, you'll have to use measurements to justify making the best decision possible under the circumstances.

The case for talent acquisition analytics

The design and day-to-day running of a company involves a lot of decisions — not just decisions made by the CEO but also those countless decisions made every day throughout the command structure of an organization. The aggregate quality of these decisions determines success or failure. Talent acquisition is a job function that facilitates decisions that have great consequences for companies.

Making the right decisions means asking the right questions. For example: How do you attract to your company the best candidates in each field or discipline? How do you determine what “best” even looks like? Where do you find these stars? How do you get them to agree to leave where they are and come to you? How much should you offer? Should you pay for quality and let the pros do their thing, or should you hire upstarts for less and bring them into a system that makes them high quality over time? When you need to defend your hiring decisions, how can you convince others that you made the best choices?

Answering these questions correctly determines whether your company consists of the best band of people out there who are committed to excellence or is a mismatched collection of mediocrities just trying to muddle through the best way they can. Measurement and analysis are designed to help you systematically improve your chances of getting the right answers and thus improving your decision-making process. And what is it that can actually be measured and analyzed when it comes to talent acquisition? I thought you'd never ask.

Potential employee data that can be measured and track

Analytics can be applied to an array of decisions from within the talent acquisition function. The following examples show the types of decisions that can be made better with data:
  • Priorities: Which jobs and candidates should you focus resources on, in what order should you focus on them, and how much of your resources should be directed to each one?
  • Goals: Should you optimize the talent acquisition process for speed of hire, cost of hire, quality of hire, candidate experience, or a balance?
  • Candidate characteristics: Which candidate characteristics should you favor in the talent acquisition process (generally and per job) in order to produce higher-quality hires, stimulate a more efficient process, support company culture, or help a hiring manager solve a specific problem on a team?
  • Screening and selection instruments: Which screening and selection instruments (methods of thinning applicant pools and rating candidates) should you apply? These are some examples of frequently used selection instruments:
    • Unstructured interviews: In an unstructured interview, the format and the questions asked are left to the direction of the interviewers.
    • Structured interviews: A structured interview uses a predetermined list of questions that are asked of every person who applies for a particular job. For example, a situational interview focuses not on personal characteristics or work experience, but rather on the behaviors needed for successful job performance.
    • Sample job tasks: These tasks can include performance tests, simulations, work samples, and realistic job previews that assess performance and aptitude on particular tasks.
    • Personality tests and integrity tests: These assess the degree to which a person has certain traits or dispositions (dependability, cooperativeness, and safety awareness, for example) or aim to predict the likelihood that a person will engage in certain conduct (theft or absenteeism, for example).
    • Cognitive tests: These assess reasoning, memory, perceptual speed and accuracy, skills in arithmetic and reading comprehension, as well as knowledge of a particular function or job.
    • Criminal background checks: These provide information on arrest and conviction history.
    • Credit checks: These provide information on credit and financial history.
    • Physical ability tests: These measure the physical ability to perform a particular task or the strength of specific muscle groups, as well as strength and stamina in general.
    • Medical inquiries and physical examinations: Such exams could include psychological tests designed to assess current mental health.
  • Resources: There are substantial options for applying resources (money, time, materials) to talent acquisition strategy and tactics.

Where and when should you invest resources (and which ones) in talent acquisition channels, staff, technology, training, incentives, new selection techniques, and other supports?

All these “people decisions” add up and over time impact the long-term success or failure of every company. Superior talent acquisition can lead to competitive advantages. If your company had an attrition rate of 25 percent per year and its talent acquisition efforts produce below industry average hires, it will take only two years for 50 percent or more of employees at your company to be below industry average. 25% turnover may be an extreme example, but even with a 10% turnover rate any company can go from great to below industry average in 5 to 10 years if they don’t have hiring quality figured out. Conversely, in the same scenario, if the talent acquisition function produced exceptional hires, it could quickly change the talent profile and trajectory of the company in a short time as well.

About This Article

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Mike West was a founding member of the first people analytics teams at Merck, PetSmart, Google, and Children's Health Dallas before starting his own firm, PeopleAnalyst, LLC. He has helped companies large and small design people analytics applications and start their own people analytics teams. Mike brings a unique perspective about how to use data to create winning companies and great places to work.

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