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!

If Yahoo doesn't kill remote working, then Big Data will

A little bit lost in the continuing fallout from the decisions by Yahoo to end remote working arrangements for their staff, and Best Buy's move to end ROWE (Results Only Work Environment), at its corporate headquarters was this much more interesting, (and potentially more important), report in the Wall Street Journal, 'Tracking Sensors Invade the Workplace', that hints at a data-powered future workplace where 'being physically together' is not just mandated, but is tracked, recorded, and interpreted by algorithms and leveraged by management.

How exactly does Big Data, (which usually sounds kind of benign, or at least non-threatening), play a role in the future of telework?  Take a look at this excerpt from the WSJ piece:

As Big Data becomes a fixture of office life, companies are turning to tracking devices to gather real-time information on how teams of employees work and interact. Sensors, worn on lanyards or placed on office furniture, record how often staffers get up from their desks, consult other teams and hold meetings.

Businesses say the data offer otherwise hard-to-glean insights about how workers do their jobs, and are using the information to make changes large and small, ranging from the timing of coffee breaks to how work groups are composed, to spur collaboration and productivity.

"Surveys measure a point in time—what's happening right now with my emotions. [Sensors] measure actual behavior in an objective way,"

The next step in figuring out how people work, communicate, and interact in the workplace and with their colleagues involves wearing an always-on tracking device, (bathroom breaks optional), and harnessing all the data the device collects about who a worker talks to and for how long, how often they get up, when they hit the coffee room and vending machine, how long they stand waiting outside a conference room because the prior meeting ran long - all of this and more.  Mash up that 'experience' data with other electronic data trails (email, IM, internal collaboration tools, etc.), and boom - the data will be able to prescribe optimal amounts of employee interaction, recommend the timing and duration of breaks, send push notifications alerting you that the guy you need to connect with about the Penske account is two stalls away from you, and crucially - keep your managers informed about just what the heck you are up to all day.

But it seems really likely to me that if these workplace tracking sensors gain more well, traction, that organizations will quickly realize that the only way to really exploit them, and the data they collect to its fullest potential, will be in a traditional workplace environment - with all employees together in a physical location and 'on-duty' at the same time. Let's face it, for a remote worker wearing a tracking sensor probably won't produce much valuable data - unless its to try to 'prove' to a suspicious manager that a remote worker is slacking off.

The tracking sensors, if they catch on, will change the anti-telework argument from 'We need you to come in to the office so we can keep an eye on you' to 'We need you to come in to the office so we can track everything you do, say, touch, and feel all day.'

It's a brave new world out there my friends...

Lessons from an Ad Man #3 - On Judgment and Research

Note: Over the holidays I finished off an old book that had been on my 'I really should read that' list for ages - Confessions of an Advertising Man by ad industry legend David Ogilvy. The 'Confessions', first issued in 1963, provide a little bit of a glimpse into the Mad Men world of advertising in the 50s and 60s.

This will be the last submission I think in the 'Ad Man' series, not because there aren't plenty more nuggets of insight from Confessions of an Advertising Man, but more that if I haven't convinced you by now you should score a copy and read it for yourself you probably never will.

I pulled this last lesson for its increasing relevance today - this new age of information, metrics, and Big Data, where we seem to be continually told, pushed, and cajoled into taking a much more analytical view of the world. Data, statistics, relationships, algorithms - these for many are the new coin of the realm and should be used to inform all kinds of decisions we make as HR and Talent pros.

Data can tell us where we should post our job ads to generate the best candidates, which of these candidates 'match' the job requirement, who might be a culture fit, what questions we should ask them in the interview, and how we should score their answers.  Even more data can tells us how much (or little) we should compensate our employees, how much we need to reward out top performers to convince them to stay, and which ones are likely to progress in the organization - making increased attention and investment in them pay off. And still more data can tell us where we should expand - what locations and markets have the 'right' supply of talent that fits our talent success profiles - and where we need to consider contingent staff or outsourcing to fill in the gaps.

In 2013 and beyond you as an HR and Talent pro will simply have to get more comfortable with data, (big or otherwise), and taking a data-driven approach to workforce planning, staffing, performance management, and rewards. This reality seems clear, and few would dispute the impact and influence that data and analytics will have on HR.

There was plenty of data back in Mr. Ogilvy's day as well. Sure, maybe not the voluminous amounts that we capture today, but still lots of data, and with the more crude tools available back then to aggregate, analyze, and derive insights - it is quite likely than business leaders of that age might also have felt they had a 'Big Data' problem.  Back then Ogilvy sensed a growing tendency for many in his field to become over-reliant on data and research - at the expense of reasoned and experienced judgment. Here is Ogilvy's take on the matter, from a section of the book subtitled 'The Image and the Brand' -

How do you decide what kind of image to build? There is no short answer. Research cannot help you much here. You have actually got to use judgment. I notice increasing reluctance on the part of marketing executives to use judgment; they are coming to rely too much on research, and they use it as a drunkard uses a lamp post, for support rather than illumination. 

Nice shot from the Ad Man, and certainly one that will continue to resonate more and more as the available amount of data and information that will be available to us at almost every part of the talent management process will only increase.

The data, as Ogilvy suggests, has to illuminate, it has to lead us into making the best decisions and even into dreaming up brand new ideas. It can't only be a prop or a justification for a lack of imagination or of daring. If we let data and data alone drive our actions, well then we can easily be replaced by it, and by technology that can process it much faster and more efficiently than we ever could.

The data will consume us if we allow it to I think. 

Use your best judgment on this...

The true goals of HR Big Data projects

Buried near the end of this fairly standard but still pretty interesting piece on how software giant SAP is deploying Human Capital workforce analytics solutions in their internal organization from their recently acquired SuccessFactors product suite is perhaps one of the most clear, coherent, and instructive observations about the goals (or what should be the goals), of any HR organization embarking on an analytics or (buzz work blog police look the other way) 'Big Data' project.

Here's the quote from SAP's Helen Poitevin:

We see this (the implementation of modern workforce analytics solutions) as a transformation for us first, moving from being specialists in extracting data from our systems, to being specialists in answering workforce related business questions.

I know that this seems like a kind of overly simple and somewhat of an obvious point of emphasis, but I think it is one that serves to remind those of us that like to talk, read, or prognosticate about how Big Data will have a truly transformative impact on HR professionals, workforce planning, and human capital management need to remain mindful that collecting more data, and even making the extraction and presentation of that data simpler and even more beautiful, is only the first step in the journey to realizing better business outcomes.

The goal of these analytics and Big Data projects, as the SAP article makes plain, is not just the ability to organize, describe, extract, and present workforce data (which in truth are necessary and important steps), but to leverage that data, to have the data lead to the asking of the right questions, to illuminate a path towards answering these questions, and to help the organization understand and relate the story that their human capital data wants to tell.

Again, the SAP piece makes it clear what their goals are, and what has to be the end-state for HR analytics and data projects:

(the analytics projects) represents a transformation for our business, by virtue of leveraging data-based insights and analysis about our workforce to make better, more sustainable decisions

Again, you probably already know this. Probably.

But it is a telling reminder just in case you've let your goals slip a little, or if you want to (or feel like you have to) claim victory with the initial successes in your analytics programs. 'Look we have reports!'

You're not really there, (and hardly anyone is yet), until the workforce data becomes an essential part of how your business makes decisions, and is not just a set of cool dashboards or a slick set of charts on an iPad app.

Have a great week all!