More Data for HR Geeks: Wow, it's getting old around here

Last week Kris over at the HR Capitalist ran a cool piece titled Economics for HR Geeks: The Quitter's Index, where he called out the BLS data indicating that more Americans are now quitting their jobs than being fired/laid off/downsized.  There are lots of possible reasons for this shift, but the takeaway for the talent pro is that more people are open to a voluntary move than in the last few, recessionary years. The climate for recruiting and retention is starting to shift.

In the spirit of KD's piece, I thought I'd offer a similar, geeky chart for your perusal, first spotted over at Business Insider last week. Have a look at the below graph, that shows the total US employment level for two age cohorts, those from 25-34, and those 55+, and I'll make some (obvious) observations after the data sinks in. 

 

Yep, really soon, and for the first time since anyone started keeping track, the number of workers 55 and older will exceed those aged 25-34, typically the next generation of talent that so many firms are trying to recruit, develop, and retain.

Many workers north of 55 have seen their retirement plans put on hold, some for a few years, many for longer, as the combination of recession, slowly recovering equity markets, and lots of 20-something kids still living at home as they remain persistently unemployed or underemployed themselves.

Have you walked around the office lately and thought to yourself, 'Wow, when did everyone start to look so old?'. If you haven't noticed, don't worry, you probably will soon. And after you take note, maybe its time to think about the makeup of your specific workforce, in total and in important segments, to see whether or not you are seeing this trend play out for your company, industry, and region.

And then maybe take a few minutes more to think about what that all means for your 3, 5, and 10 year plans for recruiting, retention, benefits, work assignments, facilities, management succession, and more.

Gettind old can be a drag. It can be a real drag when it happens to everyone at once.

FYI - the chart was originally created on the FRED site, which is an absolute gold mine of information. Check it out sometime.

Big Data, coming to a staff meeting near you

Big Data is probably the latest buzzworthy term to enter into the discussions amongst technology solution providers, pundits, and enterprise information technology types, all of whom are jockeying to variously understand, explain, and offer insights as to all the fantastic opportunities, (and challenges) that Big Data presents. In case you may be late to the Big Data party, (maybe you've been goofing off too long on Pinterest to keep up), let's take a look at a basic definition of the concept from Wikipedia:

In information technology, big data consists of datasets that grow so large that they become awkward to work with using on-hand database management tools. Difficulties include capture, storage, search, sharing, analytics, and visualizing. This trend continues because of the benefits of working with larger and larger datasets allowing analysts to "spot business trends, prevent diseases, combat crime."

 Scientists regularly encounter this problem in meteorology,genomics, connectomics, complex physics simulations, biological and environmental research, Internet search, finance and business informatics. Data sets also grow in size because they are increasingly being gathered by ubiquitous information-sensing mobile devices, aerial sensory technologies (remote sensing), software logs, cameras, microphones, Radio-frequency identificationreaders, and wireless sensor networks.

Got all that?

Essentially, our ability to generate and store massive amounts of data, from disparate, always-on, and almost unlimited sources, is surpassing our ability to understand, analyze, interpret, and take actions based on said data.

Where there is an identified problem with data, (massive amounts of it that don't fit traditional tools and methods of interpretation), we can expect more and better technology solutions to continue to be developed to help organizations and institutions. Doing a quick search on 'Big Data tools' already yields thousands of results, ranging from technologies and processes from some of the largest information technology companies in the world, to new ideas from start-ups trying to innovate and get a toe-hold in this emerging domain.

But like any other new technology trend, the trouble that Human Resources professionals could fall victim to is thinking that the problem of 'Big Data' is fundamentally a technical one, and that with the right or new or more powerful computing resources that suddenly 'Big Data' will start spitting out all kinds of actionable insights into their business and talent.  Data has always been just that, data, and possessing more and more of it just makes it more apparent that without the ability to ask the right questions, propose the right theories, and the capability to implement the strategies suggested by all this data, then all the Big Data in the world won't mean all that much to the HR professional.

I was thinking about this after reading a recent piece titled 'Can Big Data Replace Domain Expertise?', a review of some recent articles and discussions among leading academics and data scientists debating whether or not if one possessed the data, the needed technology, and some core 'data science' skills, that actual domain experiences, (e.g. for HR or Talent data, actual experience in HR or Recruiting), would not be necessary to extract insight and actionable information from the data. In other words, "given the right data set, a data scientist with no domain expertise can out-perform experts that have been working in the field for decades."

For domain experts, this kind of a conclusion would certainly be disputed, after all, how can a techie or a statistician know more about my business, or more pointedly, my people, than I do? How can simply crunching the data take the place of the knowledge I can bring to the table?

Personally, I tend to side with the domain experts on this one, perhaps it stems from watching so many NBA games and seeing the increasing importance statistical analysis is playing in the sport and in how coaches, teams, and players are managed and evaluated. Often when I read detailed statistical analysis of a player or team that seems to be at odds with my unscientific (and likely biased) views, I often want to ask, 'But did you actually watch the games?'

But eventually the data will get to be too much, too universally known, understood, and accepted, and some of my opinions and biases might have to change if I want to continue to be seen as a relevant, or even astute judge of the NBA and its talent.

Eventually just watching the games won't be enough.

And I suspect the same thing is going to happen for managers and judges of talent inside organizations as well.

Before You Know You Want One

Did you catch this fantastic piece from the New York Times last week - 'How Companies Learn Your Secrets', an inside look at how the major retailer Target has combined it's extensive data collection efforts with insight into shopper's tendencies and habits in order to better tailor promotions and outreach efforts, and match them more accurately with with what products that shoppers are likely to want? The focus of the Times article was Target's work around using data and analytics to attempt to predict which shoppers might be pregnant, and with that knowledge, send them more focused ads and offers for things like prenatal vitamins and maternity clothing.

It is an incredibly interesting piece, and I'd encourage everyone to read it, as it offers not just a peek behind the curtain at a multi-billion dollar merchandising machine, but also suggests other ways that the ability to capture, analyze, interpret, and make actionable copious amounts of data presents an area of opportunity for organizations and disciplines of all kinds. A quick read provides three important takeaways from the piece that are worth remembering:

1. Timing is everything. From the Times: 

Consumers going through major life events often don’t notice, or care, that their shopping habits have shifted, but retailers notice, and they care quite a bit. At those unique moments, Andreasen wrote, customers are “vulnerable to intervention by marketers.” In other words, a precisely timed advertisement, sent to a recent divorcee or new homebuyer, can change someone’s shopping patterns for years.

2. If you're not thinking about how to manage and derive value out of all this data, you might be already a step behind your competition.

Almost every major retailer, from grocery chains to investment banks to the U.S. Postal Service, has a “predictive analytics” department devoted to understanding not just consumers’ shopping habits but also their personal habits, so as to more efficiently market to them. “But Target has always been one of the smartest at this,” says Eric Siegel, a consultant and the chairman of a conference called Predictive Analytics World. “We’re living through a golden age of behavioral research. It’s amazing how much we can figure out about how people think now.”

3. But having all this data, and ability to extract meaning and opportunity from the data, doesn't absolve an organization of thinking hard about how it has collected the data, and the expectations and possible reactions of the consumers, (or candidates), about how the data is used.

At which point someone asked an important question: How are women going to react when they figure out how much Target knows?

“If we send someone a catalog and say, ‘Congratulations on your first child!’ and they’ve never told us they’re pregnant, that’s going to make some people uncomfortable,” Pole told me. “We are very conservative about compliance with all privacy laws. But even if you’re following the law, you can do things where people get queasy.”

Is there an equivalent or at least approximate set of takeaways for the HR and Talent professional?

Definitely. Hitting a top performer with a high-profile and challenging assignment before they drop their two-weeks on your desk, understanding where the next set of company stars and leaders are likely to come from based on your assessment of the data on the current team, while making sure the data you're digging up on employee, candidates, and competitors doesn't make you too uncomfortable are all applicable takes from the Times story on Target.

It's all Predictive Analytics these days. Maybe you need a refresher course.

It's only the next big thing if you've never thought about it much. Then it might be the latest thing you just missed.

Are Pictures Better than Words?

Here's a question for a Friday: Have infographics already jumped the shark?

If you spend even moderate time and energy reading online news, blogs, commentary, etc.; no doubts you've ran into your fair share of infographics in the last couple of years. And like any other art form/data presentation medium some of these infographics are awesome, and some are, well, kind of sad attempts and enlivening thin data sets that would be better communicated in a simple data table, or even a paragraph.

And while infographics may now seem kind of familiar and even a little played out on the web, they have not really entered the day-to-day flow inside most organizations. I bet no one reading this post has ever responded to the boss' request for some HR or Financial data with an infographic, even if we think that when well executed, the infographic form might help us not only present the data, but tell the story as well.

Might infographics begin to enter the world of work and become as typical as the Excel-based pie chart copied onto a PowerPoint slide?

Maybe.

A new company called Visual.ly is building out a service that will allow people to create custom infographics using information from their own databases and APIs. The service will be automated, which means users will only need to indicate the kind of information they want to display visually to produce the infographic. You can see some samples of what these infographics look like here.

Pretty neat right? And even the most jaded web natives among us would probably admit that even the simplest of these infographics are often an improvement in presentation and 'interestingness' than the spreadsheets and data tables we have all been working from for ages.

Visual.ly has produced thousands of infographics to date, mostly for big media companies and online news services like the Wall Street Journal and The Economist; and has plans to go public with its service in December. Until then, you can experiment a bit with the self-creation process by creating a simple infographic of your own Twitter persona, (mine is below).

What do you think - do you see a time where simple, created with a few points and clicks type infographic presentations of enterprise data will become as common place as the pie chart?

Should enterprise systems build in this kind of capability, or is this better left for getting attention on the web?

FYI - Here is my little infographic experiment:

 

 Have a great weekend!

Need better information for business decisions? It might not be a technology problem

Recently the MIT Sloan Management Review in partnership with the IBM Institute for Business Value released some preliminary results from a project called 'The New Intelligent Enterprise'. The MIT and IBM researchers conducted an inquiry into how organizations are using analytics for competitive business advantage. The study was comprised of a survey of more than 4,000 executives, managers and analysts from around the world and across a wide range of industries.

Understanding how peers and competitors are leveraging analytics and new tools and technologies to increase competitiveness and make better business decisions has long been a concern of leaders across the organization, certainly in process-heavy aspects of the business like supply chain management, but increasingly in the Human Capital Management space as well. And while there are lots of tools and solutions that are on the market that can help organizations in these efforts to better capture and assess analytical data, some of the MIT/IBM study results suggest focusing on the technology alone may be a mistake.

While the full report and analysis of the research findings are still to be released, several of the study's raw data points were shared by the researchers, and I think the most interesting results were the first and last chart from the piece on Sloan Review site:

Figure 1 - Access to Data Needs Improvement

Source - MIT/IBM

Nice. Most of your key players, the ones you are counting on to make the right decisions, and make them quickly, and often under pressure probably don't have easy access to all the information they need. and almost 20% claim limited or no access to the data they need to success. Ouch. But you know that right? And that's why you are trolling the web, attending webinars, talking to consultants, and hitting the trade shows to find a software solution to address this problem. Sounds simple, get the right tools in, get them in the hands of the right people, and bam! - problem solved.

Except it might not be that easy.

Figure 2 - Technology is not the problem

Source - MIT/IBM

This chart is a little busy, but essentially says that when considering the deployment of better analytics solutions in the enterprise, the survey respondents felt organizational and company culture issues were perceived to be twice as hard to resolve as technology issues. Or perhaps said differently, finding and purchasing a technology solution might only 'solve' about a third of the overall problem.

Perhaps not ground-breaking findings, but worth remembering no matter what workplace technology solutions we try to apply to help solve business problems. We can recognize we have a problem, buy a solution to address the problem, but until and only when the organization is committed to making the kinds of important changes that these projects often require, we will not realize the full potential of the technologies and more importantly, of our people.