Lessons from the SF Giants, 2012 World Series Champions

I don't use a whole lot of sports metaphors.  Heck, I like sports (especially baseball and soccer), but I find they're overused when it comes to HR, especially in team building.  Most teams in organizations don't have a defined individual competitor like sports teams do, and their metrics are much harder to pin down.

But in thinking about the dominating performance of the San Francisco Giants during the post-season, culminating in their 4-0 World Series shellacking of Detroit (sorry, Tigers fans), several themes emerged which I think are illustrative.  This post won't be about research and it may not immediately seem like it's about recruitment or assessment, but we can extrapolate back from these points to see the implications for selection.

First, workforce planning:  it's not always the case (and I know ardent baseball fans will come up with examples) but in the majority of games, certain positions--pitchers--are more important than the others.  That's not to say that you can win games without getting runs, but you can come darn close.  It's an important reminder that certain positions in an organization/team simply have more leverage and deserve more attention.  Bruce Bochy, the Giants' manager, recognized that, leading us to...

Point two: bench strength.  It's important to have broad skills across the team, but particularly in your key positions.  It speaks volumes about the depth of talent Bochy and the other coaches developed on the Giants that they lost their best closer (Wilson) early on and their former star (Lincecum) never hit his stride as a starter (but more on that in a second), yet they had several talented pitchers they could rely on to step up in these roles.  Imagine the flexibility this gives a manager, not only to replace unexpected vacancies but the hand you get to choose from on any given day.

Third: flexibility.  Aside from the aforementioned unexpected replacements (not to mention one of their sluggers being lost to a positive drug test), Bochy had to be ready to use people in different ways.  When he recognized that a certain catcher worked better with a certain pitcher, he moved the normal catcher (and batting champion, Posey) to first base.  When their former ace (Lincecum) couldn't perform as a starter, Bochy found a new role for him as reliever.

Fourth: trust.  Bochy kept at least one particular individual (Pence) in the lineup even though he wasn't consistent.  Why?  Because of his impact on the other players.  Bochy was willing to give him some time, and his patience was rewarded with some clutch playing later on--as well as a key motivational impact on the rest of the team, which leads us to...

Point five: fluid leadership roles.  Bochy wasn't the only one giving pre-game motivational speeches.  In fact the speech most credited with turning the Giants around was delivered by the aforementioned Hunter Pence.  Players revved each other up and helped own their team spirit rather than being told to have it.  A good manager allows this to happen, doesn't micro-manage, and doesn't have their ego bruised.  In fact good leaders will tell you they're happy when they blend into the background of a successful team.

Last but not least: patience.  For baseball teams, like all teams, there are rarely simple, quick solutions--this is especially the case in complex organizations with overlapping layers of management, politics, shifting priorities, etc.  Sustained success takes years of consistent management with a clear vision.  It's been said, but bear's repeating: hiring the best is not good enough.  Repeat that five times.  It's one of the reasons why assessments don't perfectly correlate with performance, and why a narrow view of selection won't cut it.

So, back to staffing.  What are the take home lessons?

1) Certain positions are more important to fill consistently right than others.  Does your organization know which ones these are?  Is your organization spending its resources acccordingly?

2) Bench strength isn't just important for sports teams.  Can your organization withstand the loss of a few key players (no pun intended)?  How many people can step up when needed and how quickly will you run out of talent?

3) How flexible is your organization when it comes to putting people in the right place?  Are you focused on position statements or on team and organizational success?

4) How much time do you give someone to start performing, and how quick is your organization to judge someone poorly?  This has implications not only for things like utility analysis but for organizational culture (and in turn, recruitment...it's a big cycle).

5) When it comes to judging your recruitment and assessment efforts, how integrated is this view with a broader perspective on team and organizational culture?  Your organization may be broken into silos but that doesn't mean your perspective has to be.

I promise: limited sports metaphors in the future.  But when the cleat fits...

Hiring right: It's about relationships, not technology

"I'm sorry, Dave.  I'm afraid I can't do that." - HAL 9000, 2001: A Space Odyssey

Remember the Wall Street Journal article I told you I was interviewed for?  Yeah, well turns out I wasn't quoted, probably because I was a big wet blanket on the topic.  But that doesn't matter--what does matter is continuing the conversation that has been sparked by the piece.

The WSJ article talks about using analytics and computers to hone in on what makes for good hiring decisions.  In particular, using computers to develop models for the best hiring algorithm.  Nothing wrong with that (well, conceptually)--I/O psychologists have been doing that for a long time.  I just thought it was sorta old news.  But other writers have taken interesting approaches, talking about the implications of "big data" and, well, "big computers", on hiring.

Charles Handler makes some great points in his article on this (including the importance of human judgment and process), as does Joe Murphy in his (e.g., a focus on validation), but I'm going to take a slightly different approach.

Good hiring doesn't hinge on technology.  Or validity (bear with me).  Or job analysis.

In the practical world, at least in mid- and large-size organizations, good hiring is about the quality of relationship between the HR consultant/recruiter and the hiring supervisor.  Because without it, you're guaranteed to introduce bias and lower your success rate.

Why?  Because most supervisors aren't experts in hiring.  They are, hopefully, experts in their business.  But left to their own devices, they WILL ask stupid questions like what animal do you wish you could be.  They will make assumptions about things like short job tenure (bad) and attending the same alma mater (good).  And they will hamstring the organization from being as effective as it can be as a result of middling talent decisions.  But ya know what?  I don't blame them--I don't expect them to be good at hiring.  That's where HR comes in.  HR consultants, like good mechanics, are tasked with diagnosing the situation and coming up with effective, efficient solutions.

The power--and if necessary, blame--lies with the HR function.  It controls the relationship and should be held accountable for it.  Not sure how well an organization is doing?  Here are a few ways of diagnosing how well this relationship is working:

1) How well do the hiring consultants know the business they support?  (Yes, this comes first)

2) How well do the consultants know hiring research and best practices?

3) How much are the consultants trusted by their customers?

4) How often do supervisors contact HR about new issues, simply to get their advice?

5) How much unsolicited positive feedback is given to the consultants?

None of this is new.  So why am I talking about it?  Because it needs to be emphasized.  Again and again and again.  I've discovered that every time something "new" is discovered in hiring technology, I have to remind folks to go back to the basics.

Technology, or more accurately, good analysis, is essential to ensuring the best ROI on hiring.  And as much as I like technology, as much as I have wished sometimes that certain supervisors weren't involved in hiring, they are, and that's the world we live in.  And that's not going to change any time soon.  Why?  Primarily control and arrogance.

First, control.  In some organizations, the culture is such that big data may be given priority status over human decision making.  But I'm guessing in most it won't (particularly those with merit systems).  Because supervisors will not relinquish control over hiring--at least the final decision, and not without a lot of resistance.

Go ahead, take this exercise: think about hiring someone to report directly to you on a daily basis.  If I told you I had the perfect algorithm that predicts performance, that you don't even need to meet the person before they start...would you agree to hire them, sight unseen?  If you would, kudos: you're unlike 99% of the people I've asked that question.

On to the second part: arrogance.  Even after years and years of research with large data sets indicating otherwise, most hiring supervisors believe they know how to judge people and make good hiring decisions.  They don't.  One thing the focus on big data and the I/O research have in common is a recognition that the more "objective", consistent, and standardized (i.e., less influenced by human biases and decision limitations) you make the decisions, the better they tend to be.

Put these two factors together and you get the status quo, at least for now.  Rapidly evolving organizations are more likely to adapt computer-assisted decision making.  But in the end, we're unlikely to remove human decision-makers from controlling final hiring decisions in many organizations.  For now. 

But perhaps that's not a bad thing.  As bad as our biases can be, the errors that entire computer systems can cause are much more serious.  If only I could think of an overblown example...

"The system goes on-line August 4th, 1997. Human decisions are removed from strategic defense. Skynet begins to learn at a geometric rate. It becomes self-aware at 2:14 a.m. Eastern time, August 29th." - Terminator 2, Judgment Day