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Monday, May 21, 2012

HR Tech and Classic Rock: Open Arms

As the Summer concert tours began to take shape, I couldn't help but notice Journey would shortly kick off their 2012 tour this July. I certainly wasn't surprised to see them heading back out on the road as they've experienced a definite resurgence over the last decade along with the likes of other power rockers such as STYX and REO. 

What got me thinking though was this wasn't the same Journey, nor had it been for quite some time. In fact, most of these legendary groups have undergone key personnel changes over the years primarily as a result of band members no longer able to coexist as a group. Just as remaining members of the band undertake the search for a replacement lead vocalist or bass player, organizations are going through similar selection processes- looking for their new lead singer (system of engagement) or new rhythm section (system of record) as a result of their current group (applications) not working as well together as expected. These new systems must ultimately welcome each others' data with open arms.

Yeah, I know. That was a stretch, but we can all agree it's more critical than ever for enterprise systems, regardless of function, to be open and able to share and consume data from other applications. Closed systems have no place in our world today. Solutions providers must demonstrate openness and the ability to integrate across the organization.

The HR Tech landscape has been in constant flux as a result of recent acquisitions. Niche players and best-of-breeds are finding their way into the organization. Unified solution providers are working diligently to expand partner networks and grow their ecosystems. Software delivery models have expanded the options the business now has in making technology decisions and changes in the way people engage with each other mean new types of data that can't be ignored.

Each of these trends is even more the reason why the systems you choose to run your business with must provide for multiple options to interface and share data with each other.

First, let's consider what this means for those organizations whose solution of choice recently fell victim to some level of acquisition within the market place. What do recent moves such as Salesforce's purchase of Rypple and Oracle's purchase of Taleo tell us about the need for a system's ability to be open. There weren't a whole lot of folks, outside of Benioff maybe, that were forward thinking enough to see that Rypple's social performance platform could have anything to do with CRM. And what would Oracle decide to do with it's new cloud purchase? The task at hand for these vendors is to determine how to provide integration points for their new band mates- both for their existing fans as well as new ones. As a consumer of these offerings, I'm looking for useful integrations that drive strategic value and not just done for the sake of saying we integrated the two solutions.

Secondly, the adoption of the social enterprise is changing the way we work and interact with others. An increasing number of organizations are now leveraging some form of enterprise collaboration tool to improve the connectedness of their employees. Whether it's a social goal in Rypple or employees giving praise to one another in Yammer, we're seeing new types of people performance data emerge within the workplace. This data, and it's ability to be consumed by your performance management system, is becoming increasingly critical if you're going to achieve a holistic view of your people. Many HR Tech providers have acknowledged the importance of this data and are now partnering with enterprise collaboration providers to deliver integrations between HCM and these new social tools. 

Finally, the ease of which organizations can adopt and leverage new technology has forced providers' hands in ensuring openness of their solutions. Lines of business are now more empowered than ever to make their own decisions when it comes to the software they use to run their departments. Upgrades, rip and replace strategies and moves to the cloud could eventually mean organizations are left with a group of disparate systems still very much in need of sharing data with one another. 

So what should you be looking for from your HR Tech vendors to ensure they're welcoming data from other systems with open arms:

1) Check out the partner pages on the web sites of solutions providers you're currently evaluating as well as those already in use within your organization. Vendors should be able to demonstrate a developing ecosystem around their solutions incorporating technology partners from various disciplines.

2) Ask about pre-packaged integrations and connectors to other commonly used solutions. This prevents you from having to build and maintain custom interfaces on your own. 

3) Ensure the vendor offers an API library for which to programatically share data between applications. Web services are an efficient way for different applications to interact with each other and can automate the movement of data between multiple systems. Web services should be made available at no additional cost and be packaged with application programming interface guides and sample code to help get you started.

It's time for your HR Tech to integrate it's new band mates with the same open arms Journey welcomed lead singer Arnel Pineda . Those that fail to forge these new relationships early on might find themselves playing to empty arenas.

Predictive Analytics: March Madness Style

This post was originally posted on in April 2012. Re-posting here for archival purposes.

March Madness has the unfortunate reputation as being one of the most productivity draining events of the entire year for many organizations. Instead of focusing on this phenomenon, which many others have already so eloquently done, (here’s a great one this post is about the underlying data and capabilities of it to predict a team’s success in the tournament and how analytics is as important for those of us filling out our brackets as it is for the success of our organizations.

Each year, as NCAA tournament time rolls around, millions of college hoops fans, inclusive of myself, try to predict which lower seeds will upset a higher seed, which school will make a Cinderella run and who will ultimately make the final four.

I bleed Orange and Blue. This means my beloved Florida Gators are a lock for the final four every year and traditionally, I’ve always put them through to the championship game in my bracket.

However, as the landscape was dominated this year by the likes of Kentucky (who we as Gator fans endured three painful loses to), Syracuse and Missouri, which received an untimely exit compliment of Cinderella Norfolk State, I decided to take a more objective approach to filling out my brackets. I did a side-by-side comparison of how teams would perform in the tournament based on two key data items used by the NCAA men’s basketball selection committee. 

The first was RPI which is a computer ranking of a team based on the opponents it has played during the season. The RPI is made up of a complex formula assigning weightings to things such as winning percentage, strength-of-schedule, wins at home vs. road wins, and opponents winning percentage. Fortunately for college basketball fans, the RPI rankings play much less significance (or do they?) in determining the overall national champion than that other infamous computer ranking system we all love to hate. Yes, I’m talking about you BCS!

The second was the team’s won/loss record over their last 10 games.  Those we consider experts believe how a team performed over their last 10 contests, conference tournaments included, is as good a predictor as any as to whether a team is deserving of being selected for the tournament field. The thought process here is a team who won 7 of their last 10 has a much better chance of going deeper in the tournament than one who may have lost 5 of 6 down the stretch.

And so I began to fill out my brackets, putting my love for my Alma Mater aside-giving way to the numbers and higher rationale. As we always say, the numbers don’t lie. In my RPI bracket, the team with the higher RPI went through to the next round.  In other words, the higher seeded team advanced.  The “last 10” proved  a bit more of a challenge with many teams recording the same won/loss records over their last ten games.  If this was the case, my tiebreaker was overall number of wins.

Now before we get to which was a better predictor of who would eventually be crowned champion, let’s discuss how using your company’s own data can help identify those employees in your organization who may become champions and those who may make an early exit.

If I told you that out of your most recent group of new hires, I could predict with high levels of accuracy which of those employees would no longer be with your organization after 1 year, what you would say? How about if I could predict which of your high performers might consider leaving their current position with your company, what would you do? I expect you would say “Heath, show me how I can use my organization’s data to predict employee behavior. “ I’d be happy to. By creating models that leverage key data points in our HCM systems, such as salary, length of service, location, job, performance data, we can successfully predict an individual’s behavior with greater than 80% accuracy. This is exactly what the selection committee is trying to do when building the tournament field, creating a model and using readily available data to determine a team’s success. Although in this case we’re dealing with individuals and your organization instead of a team and a tournament.

Imagine the value this type of tool would provide to your organization. Think about reducing employee churn and the cost savings associated with replacing an employee (estimated in the thousands of dollars).  And how about the ability to recognize flight risk of a high performer and the potential opportunities gained if you were ultimately able to retain that individual. The possibilities are endless. As an HR practitioner,  demonstrating these capabilities to your C-level execs will definitely earn you a seat at the table.

So how’d my brackets do? (ignoring the inherent flaws in my model) RPI turned out to be a better predictor of success then won/loss record. A team’s RPI successfully predicted the game winner 62% of the time, including the overall national champion, the Kentucky Wildcats. Using “last 10” as a predictor was only accurate in selecting the winner 30% of the time. And my Florida Gators, who were a dismal 4-6 in their last 10, well they defied the odds making it through to the Elite 8.

Fortune tellers have their crystal ball, the selection committee has their RPI. As professionals, we have access to powerful  business intelligence tools and data to help us predict the future. Harness that power to ensure the ongoing success of your organization. Like we always say, the numbers don’t lie.