CHART OF THE DAY: Which matters more, Google or Facebook?

Apologies for not being more clear on the question in the post title, a better way to phrase it would be this:

Which source send the most/best referral traffic to your online content - Google or Facebook?

The answer, and the consultant in me loves this, is really 'It depends.'

And what it depends on is the kind/type of content you are publishing, and is the subject of today's Chart of the Day.

As always, and by popular demand, first the data, then some pithy, wise, and FREE comments from me:

Here goes...

Interesting, no?

(Let's pretend it is interesting and proceed).

1. I have to admit being a little surprised at the edge Facebook has over Google as a source of referral traffic for many of these categories. This surprise is driven and clouded by my own personal media consumption habits I guess. I would never imagine using or relying on Facebook as a source of information for anything other than family/close friend news. And I barely use it for that. Said differently, it is a good reminder that the way you/me consume content may not be the way most people consume content. I barely use Facebook, but I have to remember most of the rest of the world does.

2. If you are pushing any kind of mainstream, general consumption type content, and you care about how many folks consume said content, you might need to think more about how you can up your presence/reach on Facebook, and maybe be a little less concerned about SEO, (which you never really understood anyway, but that is another story).

3. BUT... Take a look at the last content category on the above chart - Job postings. In this category Google still dominates with 7x the referral traffic as Facebook. And it even dominates 'other' (sorry other). It seems like if you are in the Recruiting business you still do need to worry about SEO after all. And you probably need to get a handle of what Google is up to with its recent and early forays into the recruiting and job search space.

This is totally fascinating data I think. And a reminder that job postings are not (yet) the same as the rest of the content on the internet. People look for them, and find them, much, much differently than many of the other forms of content that are all over your Facebook feed.

Interesting stuff for sure.

Have a great week!

PODCAST - #HRHappyHour 285 - Discovering the Next Great HR Technology Company

HR Happy Hour 285 - Discovering the Next Great HR Technology Company

Host: Steve Boese

Guest Co-host: George LaRocque

Listen to the show HERE

This week on the HR Happy Hour Show, Steve Boese is joined by George LaRocque to talk about the process for Discovering the Next Great HR Technology Company at the HR Technology Conference in October. Steve and George talk about the process for companies to submit,and how George and the other expert coaches will work with the selected contenders. Plus, we talk about how HR leaders and the HR community can get involved in the process. 

Also, we discuss some tips and ideas for HR leaders when working with startups, where innovation is happening in HR Tech, and what are some of the exciting new technology innovations we see coming in the future.

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

This was a fun show, thanks George for sitting in. 

Thanks as always to show sponsor Virgin Pulse - learn more about them at www.virginpulse.com.

Be sure to subscribe to the HR Happy Hour on iTunes, Stitcher, or wherever you get your podcasts.

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!

Google and the interface of everywhere

Google's big I/O event happened this week, and in customary fashion the search and technology giant made a bunch of interesting product announcements and made public for the first time some brand new solutions and innovations. Folks in the HR/Recruiting space will largely be most interested in and perhaps concerned by Google's announcement that it intends to launch 'Google for Jobs', a consolidated job search tool (powered by Google's search technology at the core), for job seekers that will surface job listing from a number of sources like LinkedIn, Facebook, and CareerBuilder. And while that announcement certainly was interesting, and needs to be top of mind for folks who run or heavily promote their jobs on job boards like Indeed, to me, it was not the most interesting thing to come out of I/O.

First, Google announced the forthcoming Lens app, a tool that essentially makes a smart phone camera more intelligent by allowing you to learn about a product by taking a picture of it, find out information about a performance by taking a photo of the name of the band, or connect to a wifi network by snapping a photo of the login and password information. This app is a nod to the increasing use of the camera/photo as not just a means of recording an image, but as a method for navigating the world and its objects and experiences around us.

Second, Google announced additional places (beyond its Home device and its Pixel phone) and tools where its 'Assitant' app will be available - on iPhones for the first time, on more Android devices, and soon, in cars, refrigerators, and more. Google's near-term vision is to make Assistant available essentially everywhere, and to (ultimately), disconnect or break the bond between the smart phone, (and Android for that matter), and the Assistant capabilities.

These two announcements combine to form the basis and the beginnings of a powerful service (Assistant), that eventually will seem "interface-less", or said differently, will be accessed via a variety of devices and methods - voice, images, touch screens, and sure, if you must, by typing commands into a keyboard. Who knows, maybe the next iteration of Google Glass, (remember that?), will be to largely function as a lens and continuous input stream to the Assistant. As you stroll around with Glass you can ask it for advice and information about where you are, the restaurant you are walking by, and who knows - maybe see a list of open jobs at the Cafe you are sitting in having a coffee.

What is interesting about all this, to me, is the longer term implications it has for the tools and technologies that we use at the workplace. Consumer-driven technology innovation has been driving enterprise tech for a while now. You were using a smart phone or a tablet at home, before you ever did so for work. And I think the same thing will become true for this future world of the 'everywhere' interface to smart tools and services designed to help us navigate the world, and get things done.

Smart phones exploded for work applications because (in part), we didn't want or need to be trapped to a desk and a computer in an office in order to get things done. Now, we are beginning to see what is coming 'next' - after the smart phone, when the technologies are all around us, in our ears, in the devices we interact with, and never more than a spoken 'Ok Google' away. What will be the first HR system to be fully integrated and accessible via voice, image, and even wearable tech? 

I think it is tremendously exciting and fun. And way more interesting and powerful than a new website that aggregates online job listings. But if you have to talk about that, it is ok. I get it.

Have a great day!

The half-life of technology-based advantage

... keeps getting shorter and shorter.

Take a look at the chart below which tracks the daily active users of the most recent 'next big thing', Snapchat, against the DAUs for a slightly older 'next big thing', Instagram - specifically Instagram's "Stories" feature, one designed as a pretty blatant copy of Snapchat's core use case.

Here's the data then three quick points about what it reminds us about technology-driven competitive advantage.

The chart is a couple of months old, especially for the Snapchat data, but the trends are holding up. Instagram essentially was able to surpass the DAUs of Snapchat's primary feature in less than one year. It is kind of hard to say what this means for Snapchat in the longer term, I imagine they will try and continue to innovate, (and I confess to not being a user of Snapchat, I tried two or three times and could never understand it), and perhaps reverse or at least slow these trends.

But bigger picture, what does this 'story' (pun intended), remind us of?

1. Almost every technological advantage can be copied by competitors, and sometimes copied very quickly. Snapchat had a 5-year or so head start and within months that advantage or distinction has disappeared. Technology, consumer or enterprise, is moving, adapting, innovating faster than ever.

2. When considering/selecting/implementing enterprise tech, (like a new HR Tech solution), "features" or capability probably should not be the most important differentiating criteria. The HR solution providers across a wide range of domains are developing similar capabilities and features and even user experiences. I probably saw demos of four or five new enterprise learning management solutions in the last 18 months and they all look, feel, and act really similarly. In fact, if I had to do a 'blind' test, like the old Pepsi Challenge, I am not sure I would be able to tell them apart. 

3. So if technological advantage, i.e. features should not be the most important criteria when evaluating technology then what should it be? Well, I know I have opined on this before, but I still submit HR leaders should be carefully evaluating the things that can't be as easily copied across providers. Elements like the implementation experience, customer service and support, the provider's vision of the future, and the extent to which the solution provider sees you as a true partner - in innovation and in business success. These are all critical elements, hard for competitors to copy, and admittedly, harder to assess on an RFP than a list of feature/functions.

Ok, that's it - I'm out. Going to fire up Instagram. I heard today they copied the 'koala ears' filter from Snapchat. 

That's what my selfies have been needing.

Have a great day!