Organization Horsepower

Thinking Like a Motorcycle Racing Team

Category: Blog (page 2 of 4)

3 Ways People Analytics Go Beyond Talent Acquisition

The Atlantic – They’re Watching You Work

Last week The Atlantic published “They’re Watching You at Work.” by Don Peck. It’s a catchy title that implies that your employer is spying on you, watching your every move. But the subtitle is much more Insightful: “What happens when Big Data meets human resources?” The result is probably the most complete look at people people analyticsanalytics that’s been published today. The article paints an excellent picture of how analytics can help in the Talent Management process, especially in helping identify potential and overcome bias. It also features some very good examples where people analytics were applied with a positive result. The article is not brief, but it is worthy of your time.

What Happens After Talent Aquistion and How Can People Analytics Help?

Most of the article deals with the Talent Acquisition portion of the Talent Management cycle. As you read the article, consider this: What if we do use people analytics and we recruit the best people with the highest statistical potential, but then the one of these three things happens?

  1. They don’t accept the job
  2. They fail to meet business metrics
  3. They leave (when you don’t want them to)

How can Big Data help human resources if any of those three things happen? The truth is that Big Data still can help quite a bit, but we have to develop and push how people analytics can help us all the way through the talent management and the career cycle.

Examine the first proposition, “They don’t accept the job.” It may be that the person was the right fit for you, but you may not be the right fit for them. This happens to some extent today, but as people analytics becomes more open and transparent, the door will swing both ways. As you gain more insight into your candidates, people will increasingly gain more insight into your company. The companies that will thrive over time will use analytics to look at themselves and make changes so their top picks return the love.

What about the second proposition: “They fail to meet business metrics”? In that case, the first thing you have to consider is whether you hired the right person but for the wrong job. And by that we mean;

Does the design of the position actually take advantage of the strengths your data supported recruiting hired for?

People Analytics can tell us a lot, not only about that person, but also whether or not our business process and job design actually allow people to succeed and thrive. What good is hiring for a behavioral attribute if the person you put that position in only gets to exercise that muscle on rare occasions?

Finally, imagine if we do use great people analytics as part of our talent acquisition strategy. We save a lot of money by hiring the right person and realize greater profit by having high performance, but then that person quits? We will have spent more on acquisition, and the loss realized from attrition of a high performer is huge. People Analytics can and must help us predict—and ideally prevent or reduce—high-cost turnover.

The bottom line is that People Analytics will have a huge impact on HR well beyond Talent Acquisition. In fact, if we only pay attention to the acquisition side of the equation, it will actually expose shortcomings in other areas of the employee life cycle. A balanced approach to the use of analytics is the right course to take.

Return On People: Why It’s Good for Employees

We all understand from a business perspective the concept of getting returns. We spend dollars in order to make more dollars. However, as an employee of a business sometimes the concept of “returns” gets a little cloudier. Sure, we all earn a paycheck but sometimes it’s hard to see in the “here and now” how helping our organization makes more, benefits us and it rarely shows immediate returns in our paycheck. So when we talk about “Return On People”, it’s really easy for employees to relate that concept with just another way for employers to make more money off harder work, more hours, or fewer benefits.

As much as adopting a Return On People mindset is about making more back from your investments in people, it doesn’t work if those people can’t see or don’t understand where they fit in, or what they will get out of it.

A huge component of getting better Returns on People is increasing the amount of time spent on activities that generate profit, as well as decreasing or eliminating activities that have no measurable, or even a negative impact (more cost), on profitability. While the benefits to the employer of better job design are obvious, the net effect for employees is better, more meaningful jobs.

If you asked one of your employees how much time they spent doing actual work in a day (and they answered honestly), what would they say?

It is safe to say the answer would be less than you would like, but the real challenge is identifying what they did with the remaining time and why they didn’t consider it “real” work. Chances are at least some of the time is doing activities that is a requirement of their job that they just don’t see value in.

We all want employees that are engaged with work. It’s much easier to get that level of engagement when the majority of the time spent at work is on activities that have meaningful outcomes and align with that individual’s skill sets. It creates an atmosphere of value. It says to the employee that you value what they are good at far more than the activities that don’t produce returns. You have involved them in something larger than just themselves, and have shown the relationship between work and the success of the company.

Conversely, if we treat employees as costs and draw direct-line relationships between that cost and productivity, that productivity will be limited to the spend associated with it. If they don’t see you trying to make meaningful work for them, your get just what you paid for, labor in exchange for money.

Paying attention to Return On People isn’t just the right thing to do for your business, it’s the right thing to do for your people.

Measurement and Trust for HR (2013 Remix)

Back in 2011 I wrote series of articles on measurement that focused in performance-based measurement for training professionals. At the time, Media 1 was focused in on the transformation of the training function to a performance mindset. In subsequent years, we’ve reframed that performance mindset for the HR professional. The following is an update on my thoughts from the original post.

Far be it for me to hold back on how I really feel about something. So, here goes:

Measuring HR as a justification for HR is an utter waste of time.

It’s like giving style points to the 50-yard dash. It may be interesting, but the only thing that matters is who crossed the finish line first. In other words, the performance or result mattered; the style in which it was achieved is barely noteworthy. Yet, when you measure HR in and of itself, that’s exactly what is happening.

I think Charles H. Green hits it on the head with this quote from his blog:

“The ubiquity of measurement inexorably leads people to mistake the measures themselves for the things they were intended to measure.”

Why do we keep using measures instead of actual performance as justification to ourselves and our organizations? The answer to that question in many cases is rooted in why we are asked to measure HR in the first place… that is, to prove that it has some kind of meaningful, measurable impact on the organization’s results.

Many of our organizations do not believe that HR as it is currently defined contributes to profitability. Or they do not trust that you or your immediate organization can execute HR in an impactful way. The requirement for measurement comes from a place of distrust—not from a defined need to measure results. Consequently, measurement is demanded to “prove” HR has value. Trust is not impacted or improved through this exercise, but regardless, time and effort is spent generating measurements that don’t really tell us anything about the business.

It is not my intent to write a primer on the effects of trust in business. I think Stephen M.R. Covey has done a good job with that in his book the Speed of Trust and the follow-up Smart Trust. The point is that a lack of trust affects our relationships and results in demands for measurements based on volume that are intended to justify the existence of HR in an organization. It’s a closed loop with no obvious business value. That’s why old-school HR departments are usually viewed as a cost centers, not as a strategic business partners or even a source of predictive intelligence.

So how do we as HR professionals earn trust and show that HR can be a source or profitability within the enterprise?

In short we have to make the paradigm shift into measurements that help the business make better, faster decisions based on the analytics of human performance. When business sees we are measuring things that concern them and aren’t self-serving, then that’s a great first step in assuring the business that we’re all in this together.

What to Measure First, Key Performance Indicators for Supporting the Business Case

It’s easy enough to come up with meaningful HR generated data that should be meaningful to business stakeholders.  After all who wouldn’t want to know revenue and/or profit by FTE, loaded costs by function, or engagement levels? The problem is that those measures while valuable may not align to what is most important right now. The first step in aligning the measurement of HR to the needs of the business is to align to corporate goals and initiatives. From there we should be able to identify specific measurements or Key Performance Indicators (KPIs) when building the case for an initiative.

Resist the temptation to use measures based and volume and time alone. These metrics generally serve as justification indicators, but fall short of a true performance benchmark.  Good KPI’s rely on multiple sources of data that allow for calculating true costs and profitability. At minimum good KPIs support direct correlation to cost and profitability.

Once your KPIs have been identified, you are well on your way to generating a measurement of your current operational state, also known as a baseline.  Now all you need to do is figure where you left all that elusive data…

Don’t Confuse a Benchmark with a Goal: Video Blog

The following is a video perspective on the blog post “Don’t Confuse a Benchmark with a Goal,” released last week:

Don’t Confuse a Benchmark with a Goal

I recently worked with a client that was very insistent on getting benchmarks from a fairly narrow scope of companies on a specific set of cost measures.  I found out that getting benchmarks from the really high performing companies is often difficult because they believe that they have achieved something with their measurements and that it is a competitive advantage that they don’t necessarily want to let out of the bag. I also found that companies don’t like to disclose cost information unless it’s a pretty nebulous range.

However the good news is that the benchmark isn’t the end-all-be-all. Don’t get me wrong, a benchmark can be important, but don’t get it confused with a goal. Benchmarks are best used as indicators; they can tell you how you compare to other companies, and if the gap is wide enough, it may help you prioritize an initiative. However, while it’s a good start it should never be used as an indicator of the end.

You don’t stop when you hit average, so don’t stop when you hit a benchmark. No one would ever be “best-in-class” if they just shot for a benchmark.  That doesn’t mean chase perfection without payback either, last time I checked best-in-class didn’t come with a guaranteed paycheck. Performance improvement has to always be scaled to match the potential return and the investment needed to get there.

It’s OK to look at a wider range or larger sample size for your benchmarks; they are only one indicator of many you’ll use in evaluating potential opportunities for improvement. Ultimately you’ll need to set achievable goals that meet your internal capability, that’s the measurement that will matter.

Good Baselines Come from Good Data

The first programming class I ever took, I was introduced to the acronym G.I.G.O. For those of you who have never had the distinct pleasure of such a course, it stands for Garbage In, Garbage out. The premise is that if you input bad data, the only result you can get out is similarly flawed.

Traditional HR does not have a heavy emphasis on data or statistics. We ask finance for numbers, or we run a report and generally trust what is there. Or we like and trust people, so we ask them for numbers. However, as we strive to strategic if not enabled business drivers, we need to pay more attention to where our numbers come from and how those data sources affect the baselines that we use to measure progress against.

I recently had a client provide me with baseline cost data that clearly showed a disproportionate spend on one particular area of operations. Without getting into a lot of detail, it turns out that baseline cost included quite a bit of misplaced expense that significantly bloated the baseline. After removing the added expense, the project couldn’t be justified on a cost basis alone. It was still critical that the client generated a true baseline, but not having an accurate picture up front really took the wind out of everyone’s sails.

The reliability of your baseline data can be directly linked to the maturity of your data analytics culture and the tools you use. There are four primary sources of baseline data listed here from least reliable and mature to most.

Conjecture, anecdote, and correlation – probably the most utilized source of baselines, this method involves making educated guesses about the metrics you use for baseline calculations. This approach is best characterized by using very small sample sizes, and applying logic. If it takes this long to do a known quantity, then this other target quantity is x% of that time. While useful for napkin calculations, this type of data is highly subjective and has credibility problems. At some point someone will question the validity of numbers and it becomes a trust game.

Survey/poll – When you don’t know something you think you should, its human nature to reach out and ask someone that you think should know. In HR terms that means asking a group of employees about the activities they perform. This can be as simple as an email or complex as a survey. When using this type of data to form a baseline you have the benefit of a larger sample size (assuming you get enough responses), but you are essentially either asking an employee how they feel about something or what they imagine something is. There is no way to validate the data and it leads to interventions that are centered on changing the way some one feels instead of changing the way they think and consequently act.

Activity logs – If you aren’t measuring something that you really want to measure, the best way to fix that problem is to start. If you wait to measure until you’ve already changed something you missed out on a lot of good data and it really didn’t help you generate a baseline. In the simplest terms, start asking people to track what you want to measure. Think of it as a naturally occurring experiment. If you want to know the data state of the current state, start logging some data. It will take a while to generate enough of a sample size for it to be reliable data, which means it’s not a great technique to use when you’re already under the gun. However, more mature organizations anticipate and proactively measure.

Enterprise systematic – Of course the best way to generate a baseline is on reliable data that is tracked systematically across your entire sample size over a long period of time. Look for sources of this type of data in your organization first, ERP, timekeeping systems, and payroll are all rich centers of reliable baseline information, but typically require set-up and configuration to get exactly the type of data you need for good baselines.

At the end of the day, having one singular source of truth for your baselines is something to aspire to. If you’ve already got it figured out, my guess is that you haven’t read enough of this post to get to this point. The reality is that as we get started with measurements, metrics, and analytics we have to develop and plan for our baseline data sources. The better the data we get in, there better data out puts we’ll be able to produce, and the more we can help our companies move forward.

Measure Twice, Cut Once

Cigar box guitar

My biggest hobby outside of work is building musical instruments. I don’t have a woodworking or lutherie background. In fact, I’ve never taken a single class on either, and my dad is more shade tree mechanic than wood worker. So my instruments are generally pretty primitive.

I started building instruments out of cigar boxes. The practice of building instruments out of found objects is nothing new, in fact there is a long history of improvising to create something that you couldn’t afford for less than the cost to acquire that item. If you don’t have anything good to work from, then use what you have and improvise.

While this is a rewarding hobby for me, and it keeps me sharp in a lot of areas in my business life, my HR clients are not dealing with “found objects”. They don’t need to, and can’t afford to improvise on their talent to meet the needs of their companies. They are more mature at the practice of HR than a proverbial cigar box guitar.

The thing about learning slowly through experience alone is that while it takes a while, the journey is fairly rewarding. But the costs to get the experience are astronomical. Part of that cost is time, some of it is materials, tools have been a major expense, and some of it is lost to mistakes made.
As my skills have improved, the instruments I build take more time,
and the cost of materials I used have escalated rapidly.

Maple guitar

Measure twice, cut once is an over-used cliché, especially when we are talking about ruining a 99 cent 2×4 that is part of the unseen interior hidden by drywall. But when I’m using a $100 set of spalted curly maple (as seen in the picture to the right), that over-used cliché suddenly means something. I measure multiple times from multiple directions because there are real consequences if I make a mistake. But it’s more than the cost of wood. That piece of wood directly determines how the instrument sounds, how it plays, and how attractive the end result is. It also determines, if I choose to sell it, how much I can sell that finished instrument for.

Companies spend more on their people than any other expense on the balance sheet, yet too many of them treat people like a 99 cent 2×4 and not like a beautiful set of unique one-of-a-kind wood that directly affects their profitability. That’s not to say that they treat those employees poorly, it’s that they fail to measure, let alone twice, what the real value of that person to the organization really is.

This is also more than a “cut” metaphor; this isn’t about “staff reduction” as much as it’s about being smart about how people are applied to the end result.

I want to build better guitars. If you want a better HR function, measurement that means something
needs to be part of your approach. You will never improve without it.


Why Measure HR?

Think about this for a second. Are you measuring HR? What are the measurements you are tracking?

If you aren’t measuring HR, why would you want to start?

Many companies are trying to track employee satisfaction with HR services or transactions. Even more are capturing volumes of services.  Those are excellent measures if you are trying to diagnose efficiency of a specific function or process for targeted improvement, but do you send those numbers to your boss? Do those numbers reach the C-suite?

The brutal truth is that the only reason you would ever send volume or satisfaction numbers up the line is to justify your own existence, to “prove” you are doing work of value. The problem with that approach is that it is very transparent in an “emperor has no clothes” sort of way. If you are fighting to justify yourself, it casts a shadow of doubt on your numbers. It does nothing to show the value HR brings to the business. It doesn’t matter how insightful your take on the numbers is, the business has no reason to trust you.

If you are going to measure HR, and you really should, you need to pick metrics that speak directly to the function of the business. Or at bare minimum, ones that can be directly correlated to a business measure. An employee being happy with a process is valuable to that process, but the business wants to know if that happiness made the company more profitable.

If you’re measuring the wrong things for the wrong reasons, stop. You are part of the problem by adding costs (labor) to something that undermines your credibility and at the end of the day isn’t helping your company be better.

Thoughts from SHARE 2012: Three Drivers that Transcend SharePoint

I just got back from the SHARE conference in Atlanta, and while it’s true that the conference is built around SharePoint as a core technology, the conference is really intended to focus on business applications of SharePoint. I’m not going to do a blow-by-blow conference report; Kristian Kalsing did a pretty good one here. Instead, I’m going to pick out for you the three drivers that are not only critical to the success of SharePoint-based solutions but really to any business solution.
  1. It’s about the business not the technology. When is that last time you experienced or heard the tale of an executive who calls a meeting and says we need an “X”? Recent examples of “X” have included social networking, Kahn Academy, and even Angry Birds. The point being: if you simply take the order and implement your companies version of these tools, the chances of adoption are immediately in danger because nothing in the business is driving the initiative. For example, social networking in and of itself isn’t enough to merit attention, but “connecting the sales force to the engineering staff in near time or real time to shorten the sales cycle by 10 days” is something the organization and your leadership can get behind. The fact that it’s built in SharePoint or any other tool is inconsequential and may be detrimental depending on your organization’s prior experience with the tool (see #3). When it comes time to justify expense or measure ROI of your solution, having real business drivers will be critical.
  2. You’ll need a roadmap. Every project needs a plan, but a roadmap can be so much more. When attacking tough enterprise issues, you’ve got be certain about what the real problem is and how you are going to measure your fix for the problem. Your roadmap can even include governance for the organization or project and accurate requirements gathering and analysis. Susan Hanley was one of the speakers at the conference on governance and is a great resource on governance issues. Sarah Haase from Best Buy is also a great corporate practitioner; her blog can be found here. Our own John Chapin also has a blog post on roadmap creation.
  3. Branding is important (don’t call it SharePoint)! Unless your company sells SharePoint or somehow derives income from marketing SharePoint, you won’t do yourself or your users any good by naming your solution after the technology it was built in. This goes for any branded technology. In fact, if your users have a negative impression of that tool, it may actually interfere with user acceptance of the tool. Let’s face it; sometimes users cringe when they hear SharePoint but won’t bat an eye when you call it the “Sales Efficiency Accelerator.” The trick is this: when users visit this mythical application, it can’t contain the elements of poor user experience that caused them to hate the tool in the first place. Branding will get your users to overlook the underlying technology once or twice, but good user experiences will keep them coming back.

Overall, I’m glad I went to the SHARE conference. It’s nice to see a group of people who are focused on the business applications of SharePoint and not just the stability and scalability of a corporate technology platform. After all, the tools we use are only as good as what we use them for.

Older posts Newer posts