Learn a new word: The Optimal Stopping Problem

I caught an interview over the weekend with one of the authors of Algorithms to Live By (can't recall which of the two co-authors I heard, but it doesn't matter. Kind of like it doesn't matter which of the two guys in Daft Punk plays a particular instrument on any given track. But that is another story.), and wanted to share a new word I learned from the interview that has some relevance to HR/Recruiting.

For this installment of Learn a new word I submit The Optimal Stopping Problem.

From our pals at Wikipedia:

In mathematics, the theory of optimal stopping or early stopping is concerned with the problem of choosing a time to take a particular action, in order to maximise an expected reward or minimise an expected cost. Optimal stopping problems can be found in areas of statistics, economics, and mathematical finance (related to the pricing of American options). A key example of an optimal stopping problem is the secretary problem. Optimal stopping problems can often be written in the form of a Bellman equation, and are therefore often solved using dynamic programming.

I bolded the 'secretary problem' which, despite its dated-sounding kind of name, is the example most commonly cited when discussing optimal stopping, and as luck would have it, is directly tied to HR/Recruiting.

The secretary problem is essentially, the question of 'Given X number of job candidates for a given position, and also given you have to make a 'hire/decline' decision on each candidate before moving to the next one, how many candidates do you need to interview in order to maximize your probability of identifying the best candidate, while minimizing the risk of making a 'bad' hire, (say by waiting too long, rejecting too many candidates, and having to settle for a candidate that is left).

Let's say you have 10 candidates for a position. You probably wouldn’t offer the job to the first candidate you interview, because you have no idea how that candidate compares to anyone else, or the general caliber of the candidates overall . But you probably don't want to wait until the 10th candidate, because if they’re the only one left you’re going to be forced to offer them the job (or keep it unfilled), regardless of how strong a candidate they are. Somewhere in the middle of the process there must be an ideal place to stop interviewing more candidates just to see what they’re like, and make a selection. But where to stop?

Enter the Optimal Stopping Problem. You can dig into the math here, but it turns out there is an ideal place to stop interviewing candidates, (or dating different people in order to try and choose who to marry), and it's after you have interviewed (or dated), 37% of the contenders. After you get to 37%, make a note of the 'best' candidate you have seen so far, (let's call her Mary Jane). Then, continue interviewing candidates and when you find the first one that is 'better" than Mary Jane, stop all further interviews and immediately offer that person the job.

How it works is related to the math behind estimating where the best candidate could be in the lineup. This number, expressed as 1/e, where 1/e eventually approaches 0.368, or about 37%. By analyzing the possible distribution of talent, it also turns out that if you interview the first 37 percent of candidates then pick the next one who is better than all the people you’ve interviewed so far, you have a 37 percent chance of getting the best candidate. 

It's a really interesting way of looking at the hiring decision making process, (as well as other processes that involve trying to make the 'best' choice amongst a number of alternative). But it makes sense somehow, even if only on an anecdotal level.

How many times have you slogged endlessly through an interview process where after some point candidate after candidate seem the same, and certainly no better than one you saw two weeks ago?

Or how many of us have, (maybe even privately), thought about a past boyfriend or girlfriend that 'got away' and for some reason has never been eclipsed by the series of people that you have subsequently dated?

Knowing when to stop, and understanding the probability that you have seen the best, or close enough to it, in any decision process is an enormously valuable thing.

In the secretary problem, and in probably a bunch of other problems too, the answer seems pretty clear - once you hit 37% you have seen enough, you won't learn much if anything else useful, and you know how to make your decision.

It is easy to apply in a job vacancy with 10 candidates. 

It is a little tougher to estimate just how many people you are willing/able to date in order to know when to apply the 37% cutoff.

Have a great week!

It's better to have a job when you're looking for a job

As the 2007-2008 financial crisis and subsequent economic recession fade further and further into the distance, we don't in 2017 talk about unemployment all that much. The sustained recovery in the labor market has pushed unemployment to near "full employment" levels of about 4.5% in the US, and in many sectors and job roles most employers would report 'good help is hard to find'. Until the robots take over. But that is a different story for another time.

Back to unemployment though. In 2008 and 2009, there was plenty of discussion about the best ways to help the many, many folks who were out of work to get back into the labor force. Lots of job search gurus appeared online, plenty of networking and support groups were created, and certainly significant governmental support, (cars, banking, insurance), was marshalled to try and stop the bleeding in the labor markets and help get people back to work (or keep them in work).

Around that time, as the unemployment rate topped at about 10%, one peculiar storyline emerged, and pretty consistently as well - namely that folks who were unemployed, and 'actively' looking for work, were often characterized as less desirable candidates than say someone who was currently employed, and may not even be actively looking for something new. The dream 'passive' candidate if you prefer that term. Lots of anecdotes about hiring managers passing on any candidate who was out of work were shared, and plenty of folks, (I possibly was one of them), opined about how unfair that this kind of (for lack of a better word) discrimination against the unemployed was seemingly more and more prevalent. And anecdotal or not, it certainly seemed that looking for a job when you did not have a job was much, much tougher than looking for one when you were already employed.

But just how much tougher is it, really?

A recent study by the Federal Reserve Bank of New York looks to put at least some data around these anecdotes by looking at job search activity by unemployed workers, by employed workers, (both passive and active), and people out of the workforce. The entire report is interesting and worth a read but I thought I would tease out two of the report's most interesting findings about job search, and more importantly, job search outcomes.

1 - Lots of employed people are actively looking for work - almost one quarter of them 'actively' searched in the trailing four weeks of the survey period

Not shocking I guess, but also the 23.3% doesn't account for the probably much larger number of employed workers that would be open to at least discussing new opportunities, even if they were not in active search. Said differently, one of the reasons contributing to a bias in favor of employed workers is the fact that just about all employed workers are still in the candidate pool anyway. At least partially in.

So how does this perceived bias influence outcomes? Here's the money chart from the study, depicting how search behavior and application intensity translate into positive outcomes, i.e. job offers.

I will help you with the fine print here. Unemployed workers make up about 7 percent of the survey sample. They send out 40 percent of the total job applications, but receive only about 16 percent of the total job offers.

In contrast, folks who were employed and were actively looking for work make up about 20 percent of the sample but receive almost half of all offers. Further, the employed not looking for work (and who do not apply for any jobs), receive about one‑fourth of all the offers in our sample—more than the unemployed who are the most active searchers and applicants.

So how much better is it to be employed when looking, (or in many cases not looking) for a new role?

Well, according to this data, much, much better. Roughly it takes eight times the effort in terms of time spent and four times the application rate for unemployed folks to generate a similar rate of job offers that employed workers realize - many of whom are not looking for work at all.

Hopefully we won't have another dramatic economic or market shifting incident like the financial crisis that drives up unemployment and will make these findings and their impacts top of mind again. But it is good food for thought for any of us who may not love the job we have now, and are looking for something better.

We just might want to hold on to that crappy job as long as we can, because having it makes our odds of finding the next (hopefully less crappy) job that much better.

Understanding your competition for talent

There is a old adage, (not sure when and from whom this was first attributed to), that ascribes a breakthrough in an auto manufacturer's business strategy to them realizing that they were not in the 'car building' business, but rather they were in the 'helping people to get where they want to go' business. 

This restatement in their fundamental purpose as a business became the key to thinking differently or more expansively about the business, their products, and the talent attraction and retention programs they would have to employ. This kind of thing is happening once again in the auto industry, as described in a piece I read over the weekend from Business Insider titled 'There's a raging talent war for AI experts and it's costing automakers millons'.

Most of the major auto makers are now playing at some level or another in the nascent self-driving vehicle space - continuing the evolution of their business purpose and their strategy towards personal transport and away from just making cars. But, as you would expect, and the BI piece points out, these shifts have important implications for talent attraction and retention - most importantly even for those of us not in auto making, and are driving changes in the talent competition marketplace.

From the BI piece:

But automakers, in particular, are making massive investments in (AI) experts because they’ve begun their AI efforts late compared to traditional tech companies.

Because deep learning has applications far beyond just self-driving cars, manufacturers are having to compete with each other and traditional tech companies.

Only 28 companies have more than 10 deep learning specialists on staff, accounting firm KPMG wrote in a 2016 report. What's more, only six technology companies employ 54% of all deep learning specialists: Google, Microsoft, NVIDIA, IBM, Intel, and Samsung.

"The traditional power and talent of the auto industry was based in their product development group," Gary Silberg, the head of KPMG’s automotive unit, told Business Insider. "So they would hire these amazing mechanical and electrical engineers at the top schools of engineering and they would be part of product development."

"You can’t just turn on a dime and say, 'ok, now we are going to go recruit AI geniuses and computer scientists and expect them to come to work with us,'" Silberg continued.

A shift in strategy, leading to the increased demand for a (apologies to Liam Neeson) particular set of skills, is changing how and with whom the auto makers are having to compete with in order to find the talent they need for these AI initiatives.  And they are not finding it easy. Instead of a GM or a Ford more or less having to only worry about each other, and maybe Chrysler, for the cream of the crop of mechanical engineers and industrial designers, they now have to compete with Google, Uber, Microsoft, Tesla and more for the really, really scarce pool of AI experts.

In fact, as the BI piece points out, the pool of AI experts is so small at least in part due to the best AI professors themselves being recruited out of academia and into industry, leaving universities unable to meet the demand for educating more AI students.

Want a great example of how a business strategy shift impacts your talent strategy, and requires that the talent strategy undergo a complete re-think? Look no further than this example from the auto makers. The lesson here? The next question your company needs to ask when assessing a business strategy shift, after 'Can we really do this?' is 'Can we find, attract, hire, and retain the kinds of people we need to do this?'

Competing for talent against one or two competitors that do about the same thing as you do is fairly straightforward.

Competing for talent against an ever-growing, deep pocketed, and fast moving ecosystem of often dissimilar companies is another thing entirely.

Have a great week!

PODCAST - #HRHappyHour 275 - Employer Branding on a Global Scale at GE

HR Happy Hour 275 - Employer Branding on a Global Scale at GE

Hosts: Steve Boese, Trish McFarlane

Guest: Shaunda Zilich, Global Employer Brand Leader, GE

Listen HERE

This week on the HR Happy Hour Show, hosts Steve Boese and Trish McFarlane are joined by Shaunda Zilich, Global Employment Brand Leader for GE to talk about employer branding, recruitment marketing, and working with employees and the marketing staff to achieve employer branding goals. 

Shaunda shared some key insights about GE's approach to employer branding, how to engage employees, hiring managers, and business leaders to help spread important employer brand messages, and to best position GE as well as communicate, support and align with business strategy. She also shares some ideas about how to get employer branding and recruitment marketing programs off and running, even with limited, (or maybe even no) budget, staff, or resources.

You can learn more about GE at www.ge.com/careers where you can learn about GE's new initiative to place 20,000 women in technical roles.

We also chatted about bourbon, snowstorms, and Trish and Shaunda both shared some incredibly important news of their respective company's recent announcements with the NBA. This is HUGE news (definitely to Steve anyway).

You can listen to the show on the show page HERE, or by using the widget player below:

This was a fun and interesting show, thanks so much to Shaunda for joining us!

Remember to subscribe to the HR Happy Hour Show on iTunes, Stitcher Radio, and all the podcast apps - just search for 'HR Happy Hour' to subscribe and never miss a show.

PODCAST - #HRHappyHour 274 - The Evolving Role of the Recruiter

HR Happy Hour 274 - The Evolving Role of the Recruiter

Host: Steve Boese

Guest: Dan Finnigan, CEO & President, Jobvite

Listen to the show HERE

This week on the HR Happy Hour Show, host Steve Boese is joined by guest Dan Finnigan, CEO and President of Jobvite, a leading provider of Recruitment technology to talk about how tech, automation, and marketing are evolving the role of the recruiter and presenting both opportunities and challenges for the modern recruiter.

Dan shared some perspective of how recruiting technology has grown and evolved as well, and how these changes in technology, capability, and the increased availability of recruiting data are impacting recruiting today and in the future. Marketing and marketing software played a key role in these evolutions, and Dan shared some interesting perspective on the marketing/recruitment relationship.

We also talked about some Rochester, NY delicacies, the current slate of Oscar contenders, and more.

You can listen to the show on the show page HERE or using the widget player below, (Email and RSS subscribers click through)

This was a fun show, thanks to Dan for joining us. And many thanks to show sponsor Virgin Pulse - www.virginpulse.com.

Remember to subscribe to the show on iTunes, Stitcher Radio, or your favorite podcast app - just search for 'HR Happy Hour' to subscribe and never miss a show.