I've got some suggestions for your screenplay

Not really, and unless you are up to something on the side, you probably don't even have a screenplay (or a short story or a book for that matter). But what you might have, still, is that problem of folks in the HR and even IT game have been lamenting just about forever - no 'real' business people take you all that seriously.

For whatever reason the people in the organization that get to decide the 'what' of what people do are more important and 'strategic' than the people that (largely) are responsible for finding and hiring those people in the first place (HR), and identifying, procuring, deploying, and maintaining all the technologies that the people rely on every day (IT). That is probably true in most organizations and it's also true that it's unlikely to change unless HR and IT start to think a little differently about the problem.

I was thinking about this over the weekend when I read this piece in the New York Times, Solving the Equation of a Hit Film Script, With Data, about a new method or process where Hollywood film scripts are evaluated, and suggestions for improvement given, based on data-driven analysis. How does the process work? From the NYT piece:

Netflix tells customers what to rent based on algorithms that analyze previous selections, Pandora does the same with music, and studios have started using Facebook “likes” and online trailer views to mold advertising and even films.

Now, the slicing and dicing is seeping into one of the last corners of Hollywood where creativity and old-fashioned instinct still hold sway: the screenplay

A chain-smoking former statistics professor named Vinny Bruzzese — “the reigning mad scientist of Hollywood,” in the words of one studio customer — has started to aggressively pitch a service he calls script evaluation. For as much as $20,000 per script, Mr. Bruzzese and a team of analysts compare the story structure and genre of a draft script with those of released movies, looking for clues to box-office success. His company, Worldwide Motion Picture Group, also digs into an extensive database of focus group results for similar films and surveys 1,500 potential moviegoers. What do you like? What should be changed?

Pretty interesting and still in this age of data trumping everything kind of unusual. Although even as I recently wrote about here, data and algorithms and machine learning approaches encroaching on formerly 'creative' endeavors are starting to pop up more and more.

Applying intelligence, Big Data, and more powerful technologies for improving movie screenplays does more than just fix up the dramatic scene in Act III, it allows a guy like Vinny Bruzzese, who as far as we can tell had no 'real' movie experience, to become an influential participant in the movie-making process.

His data, team of analysts, and statistically-backed conclusions and suggestions, now put him more and more 'at the table' (sorry), where formerly only writers and movie producers used to meet. It doesn't really matter that he didn't go to film school or he didn't spend the 80s directing episodes of Full House, his data-driven solutions make him a Hollywood player.

Influence in business seems to be becoming more about who can gather, assess, and make data actionable, than who has the 'right' degree or experience. And the background of the people who can do that might be a lot different than who normally used to have that kind of influence. 

Follow-up: Big Data for HR - what do you make of this?

Yesterday I took about 550 words to say essentially this : Once your CEO decides that 'Big Data' is the next big thing to upskill your organization's talent level it is on you as an HR or Talent pro to make that happen. (It was in the Times you know).

One of the ways, besides the more obvious ones like 'Invest in some new technology' or 'Take a statistics course' is to challenge yourself to starting thinking differently about information and data (and not the typical data you might be used to considering) and what it might or might not mean for your organization and your talent game.

Here's an example of what I mean pulled from a recent Business Insider piece on some data around student loan debt load and default rates by State, (and let's assume for the purposes of this exercise that college recruiting and hiring is an important part of your workforce planning).

Chart 1 - Average Student Loan Debt

Dang, that doesn't look good anywhwere, but student debt loads seem particularly high in certain states and regions. Let's take this one more step.

Chart 2 - Average Student Loan Delinquency Rates

Interesting - not perfect alignment between the states with the highest average student loan levels and the highest default rates. But nevertheless, there are some pretty large sections of the country with average default rates at 15% or more. So the exercise is this - what, if anything would or should you do with data like this, (incomplete as it is, bear with me, it's just an example to make us think).

What if you are recruiting college grads or soon-to-be grads in the parts of the country with the highest debt loads and default rates?

Would that change your approach at all to things like signing bonuses or retention schemes that have an element of student loan repayment built in?

Would you formulate a plan for more strategic counter-offers for your younger talent that is likely to be much more receptive to make a jump to a competitor for even a small bump in salary?

Would you consider overpaying in the first few years for the best college grads knowing that some or even most of them have pretty significant financial worries outside of work?

Would you make access to a financial planner or accountant part of your signing package?

Or would you do nothing at all?

The point to all this is not really the student loan data, but rather to raise just one possibility of the potential and challenge that big data holds for you as a Talent pro, and to try and illustrate that using data to your advantage is likely going to require not just technical skills, but the ability to think differently about what drives your business.

And like we established yesterday, since it hit the Times, you can't pretend it doesn't matter for much longer.

Big Data for hiring - now everyone knows, (including the CEO)

While it can be cool to say and think that old or traditional media is dead or at least dying, (witness CNN's Keystone Cops-like coverage of the Boston Bombings and their wall-to-wall coverage of the Carnival 'poop cruise', interesting only to the people on the actual ship), it is still pretty remarkable to witness, at least in our little HR and HR Tech corner of the world, the sheer power to drive conversation the big, mainstream outlets still wield.

The latest example? The NY Times piece over the weekend titled How Big Data is Playing Recruiter for Specialized Workers, that did admittedly a fine job of covering some HR Tech startups like Gild, TalentBin, and Entelo, and how data, algorithms, and smart machine learning are combining with traditional sourcing methods in attempts to help organizations make better hires faster, and less expensively than in the past.Robert Rauschenberg, Yoicks 1953

It is a good piece and I recommend you checking it out, if you follow this space at all chances are you have already read the article, as it seemed to me over the weekend everyone Tweeted out the link (I did too). Even though these solutions have been out for some time - I just wrote about Gild myself here - once news like this hits the mainstream, you can bet you'll have some explaining to do back in your office about how you and the HR organization plans to leverage this kind of data in hiring and talent management decisions. Let's face it - even though people like me have written about these new technologies, and some of them have been featured at the HR Tech Conference, it's still the rare CEO or COO that has heard about them.  

But drop a feature about these cool new technologies in the Times, on the weekend no less, when Mr. or Ms. CEO is kicking back over brunch with their iPad and has a few minutes to read and think about a piece like this - well some of you are getting an email (maybe it already arrived, 'sent from my iPad') from the CEO with the link and a question along the lines of 'What can we do with this? or 'Are we using Big Data in hiring?'

It is pretty fun to stay on top of the latest trends and catch demos or webinars from the coolest new technologies. It is also fun to be sort of 'in the know', to be the only one in your office or in your local HR community to have some insight and savvy about the latest solutions and tools. You (mostly) get respect and cred from just knowing about them. 

But that position of 'person who knows all about the technology' will only take you so far once everyone else starts catching on too - especially the C-suite types that really only take notice of something until it hits the Times of the Wall St. Journal.  And that is happening my friends.

We're coming up fast to the point where 'awareness' is simply the ante that lets you play in the game. Your bluff is about to be called, by a CEO in a fancy suit, and iPad, and a link to the Times article.

Stay thirsty my friends... 

On phone calls and productivity

Yesterday I took a fairly easy shot at everyone's favorite communication whipping boy, email, comparing the typical send/receive ratios of email to SMS, which continues to be the most engaging two-way communication medium. Today I want to think about another method of communication that perhaps is not examined nearly as much as the many electronic means of communication at our disposal - the old-school phone call.

Yes, the phone call, a real live one person talking to one other person conversation, that (normally) requires just about 100% attention and concentration from the two participants.  The phone call - that personal connection and interaction that many of our social media and networking 'experts' exhort upon us to pursue with our online personal and professional connections - ostensibly to make the connections more 'real', (as if the millions of emails, texts, Tweets, and status updates we are sending are somehow 'unreal').

Regardless, I caught a really interesting piece recently on the Big Picture blog, where the author Bob Lefsetz calls out the phone call as a colossal waste of time for anyone whose business is information or data or even 'Big Data'.  Here are the key passages from the piece I want you to think about:

Prior to the Internet era, an entertainment titan would make in excess of a hundred phone calls a day. Do you think he was making deals? No, he was learning things. Extracting information that would help him proceed.

Now most of this information is available to everyone.

Yes, I’ve established a Grand Central of information. If you say you talked to me on the phone, you’re lying. Because I almost never do. Maybe one business call every other week. Usually to an oldster who is not net-savvy. You see just like the Wall Street traders I know it’s about speed. I haven’t got the time to waste on the phone, where you take twenty minutes to talk sports, kiss my butt and then ask for the favor. Let me know in an e-mail, instantly.

'If you say you talked to me on the phone, you're lying.' That is probably my favorite line of 2013 so far.

But think about it, maybe your job or most jobs even are not completely about gathering, categorizing, analyzing and making decisions based just on data. But as the level, complexity, volume, and speed of data about business, people, markets, customers, candidates, etc. continues to accelerate it makes at least logical sense that time carved out of your schedule to talk on the phone, (or sit in a meeting) with only one other person is going to impact and possibly detract from your ability to see, gather, and understand all this data.

The person you are talking with might have something you need, or, you might have something they need, but can you afford in the words or Mr. Lefsetz the 'twenty minutes to talk sports' in order to get to those needs?

Data might kill the phone call I suppose, if more people take Lefsetz' 'I don't have time to talk to you because I might miss something' approach, but then I suppose better tools to automate and synthesize the oceans of data that are important to us today then it might actually save the phone call as well.

I'd have the time to spend with you one-on-one if after I hung up the phone and could look at a dashboard or a consolidated activity stream or a report that told me exactly what I just missed, what I need to look at, what actions I should take, and why it's important to me.

If you know of that kind of a tool and how I can get access to it, give me a call.

I promise I will pick up.

Employee Tracking Data and the Inevitable Pushback

Last week I had a piece about the development of a new set of technologies that are effectively designed to collect, aggregate, synthesize, and help management interpret every interaction, activity, and action that employees take in the workplace. The idea being that this ocean of data about employee activity - who they meet with, for how long, how many emails they send and to whom, even how often and where they take smoke/coffee/Instagram breaks - can be mashed up with other more traditional workplace measurements about productivity, revenue, performance reviews, etc. to arrive at a more enlightened if not optimal set of recommendations, (and possibly rules) to optimize work and worker activity.

Of course collecting this level and type of data about employee activity, if it indeed catches on in the workplace, will inevitably collide with employee notions about privacy first, and then once most if not all employees accede to this nature of data collection, (perhaps under threat as a condition of employment), to concerns about the 'fair' or proper interpretation of the data. What employee actions and activities are 'good' or 'beneficial' to overall performance of the organization as opposed to the individual's own performance will also be a bone of contention - it really is a big data version of the classic 'results vs. how those results are obtained' conundrum.

It is hard to say how these issues will develop in traditional workplaces, but to catch a glimpse of how it might work out, (and the potential for management vs. employee conflict), I naturally look to the world of sports, in this case NBA basketball.  In the league these days the collection and use of more and more advanced statistics and data about player and team performance are changing the way teams and fans evaluate player performance and attempt to optimize the use of their talent to improve results.

The specific example I want to call out is about David Lee of the Golden State Warriors. By traditional and historical measures, (points, rebounds, assists), Lee is a superior player - as evidenced by his selection to the NBA All-Star team earlier this season. But to those who closely observe the league, and supplemented by more advanced statistical and player movement video technology, Lee's poor play on defense all but cancels out his fine offensive performance - essentially rendering him about an average player on balance.

Lee, to his credit, admits his defensive play has not always been stellar, but his comments about the recent attention being placed on the use of newer data sets and analyses to question his overall contribution is interesting and perhaps a bit instructive -

“At this point I could care less. I’ve worked hard to improve my defense. I think I’m a much better defensive player today than I was a year ago and definitely to start my career. There’s a lot of different numbers to support a lot of different things. You can’t have it both ways. You can’t say me putting up 20 and 10 doesn’t matter because ‘numbers don’t matter,’ but at the same time, ‘charts at MIT matter.’ You can’t have it both ways.”

And that part of the quote in bold above - 'You can't have it both ways' - is really at the heart of the problem for the Big Data in the workplace movement as it marches inexorably into the future, (and as in the NBA, the present), of the workplace.

Having more data about employees doesn't necessarily make us any smarter or able to understand that data, and how it might be applied to improve workplace performance. And it definitely doesn't make us any wiser as to how to handle the inevitable employee pushback when our interpretation of performance, backed with the data we think is important, doesn't align with theirs.

With more data we can tell more stories, but we can also find data to justify any story we want to be heard.

David Lee wants us to emphasize the data the paints him in an All-Star light - 20 points and 10 rebounds a night. His detractors want to point out that he is an ineffective interior defensive player - and can point to a new, hardly understood set of charts and graphs to back that up.

The truth is probably somewhere in between, along with one other truth - more data about your employees probably won't make your job as a Talent pro any easier.

Have a great week!