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Tag: human capital analytics (page 1 of 2)

Return On People: Why It’s Good for Employees

October 10, 2013 / / 0 Comments

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)

September 19, 2013 / / 0 Comments

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

September 12, 2013 / / 0 Comments

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

September 10, 2013 / / 0 Comments

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

September 5, 2013 / / 0 Comments

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

August 22, 2013 / / 0 Comments

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.

What is Return on People?

May 10, 2013 / / 0 Comments

The largest expense on any enterprise P&L is the money it spends on combined wages, payroll taxes, paid benefits, and unpaid benefits. This is fitting since most companies at least pay lip service to people being the most important and valuable asset that company has. While many will go to exhaustive lengths to calculate return on investment in software, hardware, and real estate, surprisingly few companies measure the return they get as a result of their spend on people.

Return on People is a philosophy and practice of calculating and projecting cost, revenue, and profit that is a result of a company’s spend on people. Return on People is measured using Human Capital Analytics. Human Capital Analytics is designed to measure people on an unemotional and equal business footing with other business measurements such as financial, operations, inventory and facilities. Management and improvement of Human Capital is the mechanism used to maximize Return on People.

For a snapshot of how well your organization is utilizing its most valuable (and costly) asset, a free version of our ROP Maturity Assessment will be available shortly. You can sign up to be notified as soon as it is available. Your ROP score gauges your organization’s readiness to make strategic use of Human Capital information. A high ROP score indicates your ability to earn high returns on your Human Capital Investment – your Return on People.

Bersin IMPACT 2013 – Day 2 Recap

April 30, 2013 / / 0 Comments

I recently attended the Bersin by Deloitte Impact conference in Ft. Lauderdale Florida. We’ve been following Bersin for quite few years and have used Bersin research with client engagements in the past. I chose to attend this particular conference because of its concentration on HR and data analytics in predictive ways. There were four tracks: Manage Develop, Attract and Retain, and Predict and Plan. I spent almost all of my time looking through the Predict and Plan lens since that is where the use of analytics are most prevalent. My comments here will reflect that perspective.

While there was not clarity around how the acquisition of Bersin by Deloitte will affect the service offering, one benefit that was evident at the Bersin IMPACT conference was that Deloitte will contribute its best people and thought around talent management. Cathy Benko is Vice Chairman and a Managing Principle at Deloitte, and wrote The Corporate Lattice. Cathy delivered a keynote on “The Shifting Ethos and What It Means for Talent Leadership”. We all must face the truth that talent leadership is changing, and we need to have the data and analytics to help steer the ship. But we also need to adapt to a continuously changing workforce that values corporate citizenship. How we change, plan and react is critical to the “engagement” that we all claim to seek.  According to Cathy in order to succeed we need to address three key principles:

  1. Dismantle the corporate ladder
  2. Connect the dots
  3. Forge a co-operative

The principles tie back to her model of the corporate lattice. Linearity gives way to flexibility and work is encompassed in interconnected ways. She highlighted 3 applications of the lattice in this diagram.

To embrace the lattice model, and fundamentally change the way we lead work and function in HR, we will need to be more agile. Gloria Stinson from Adobe presented a session on the topic of agility. Gloria laid out how her team adapted the principles of agile software development when addressing human-based work issues and flows. Deloitte threw in their agile manifesto for good measure. Looking at their service delivery model through an agile view point, Adobe learned that while they had a great team, the physical and organizational structure was holding that team back. Adobe learned 5 key lessons along the way:

  1. Transformation is a journey
  2. Leadership is needed
  3. Equipping is essential
  4. Communicate & leverage
  5. Always be cognizant global/legal considerations

When data, systems, tools, agility, and attitude all align at the top of the organization, new ways of work become possible. Imagine a company where PTO doesn’t exist and people take time off when they need it. In fact, the 8 hour workday is even a thing of the past. Ryan is a global tax services firm that, under the direction of EVP Delta Emerson, blew away all traditional interpretations of work life balance. They created accountability for work while allowing the flexibility for life. Enabled by a system of dashboards on both the employee and management levels, productivity is measured not in terms of hours but by goals related to revenue or support tasks that agreed to in regular collaborations. Low performers are quickly identified, and predictive modeling is enabled through projected productivity.

While much of the talk about predictive analytics at the conference was directly related to projecting and reducing attrition, Lowe’s, the home improvement giant, presented a case study on leveraging analytics to improve end to end process with their store development teams. The result was that Lowe’s was able to cut almost in half the time it took to open a store, improved the accuracy of the projected cost, and even produced workforce planning models for stores that hadn’t even opened yet. One issue I have with Lowe’s model was their characterization of HRBPs as generalists. I agree that HRBPs need to be consulted and worked closely with. But HRBPs need to be so much more than generalists. HRBPs should be your organization’s internal consultants that have tangible expertise that they can bring to bear strategically.

The conference wrapped up with Dr. Paula Caligiuri on “Cultural Agility“. She spoke on the importance of agility, and how to build, attract, and retain talent that can help you operate in the new global talent model. She referenced a 2010 IBM CHRO study which can be found here. She had some great tips on where to look for globally agile talent, and how to recognize the skills and abilities that are common among these people. She has a book on the subject, which can be found here.

We are now in a time where HR transformation is no longer optional but a business-based requirement. We no longer have the luxury of waiting for seat at the table. We need to embed ourselves in the core business of our companies and provide real value through strategic and predictive data-backed initiatives. In short, we will provide value by transcending our delivery models and cost-cutting efficiencies, and begin to directly engage our lines of business for meaningful and sustainable improvement.

Read my recap of day 1.

Bersin IMPACT 2013 – Day 1 Recap

April 26, 2013 / / 0 Comments

I recently attended the Bersin by Deloitte Impact conference in Ft. Lauderdale Florida. We’ve been following Bersin for quite a few years and have used Bersin research with client engagements in the past. I chose to attend this particular conference because of its concentration on HR and data analytics in predictive ways. There were four tracks: Manage, Develop, Attract and Retain, and Predict and Plan. I spent almost all of my time looking through the Predict and Plan lens since that is where the use of analytics are most prevalent. My comments here will reflect that perspective.

In many ways the topics at this conference are the same topics people in both L&D and HR spaces have been talking about for ten years:

  • How do we get people to be better?
  • How do we get “a seat at the table?”
  • How do we show return on investment?

But who asks the question (and the way the questions are answered) is undergoing a monumental shift.

Instead of asking, “How can my department have a greater impact on my little segment of the business?” we are now asking holistically, on behalf of the entire enterprise, “How can we reach and affect the fundamental ways we do business?” with the full realization we are talking about people. We still call them cryptic names, like talent assets and human capital, but as a whole we understand more what those terms actually mean.

For the world’s best companies, looking holistically at people means looking globally and trying to understand what it takes to operate our people-fuelled and dependent enterprises across cultures. This global theme was pervasive throughout the conference and started off with Josh Bersin’s The World is Local: A New Model for Human Resources article that was released just prior to the kickoff keynote. It’s an excellent paper that I encourage you to read. My favorite snippet from the article:

So while companies spend a lot of time focused on reducing HR costs and improving service delivery efficiency, the big value occurs when the HR team directly engages with managers and leaders to help the business run better.

Directly engaging with line of business becomes immediately evident when you start talking about analytics that matter. The business rarely cares about the measures that HR uses to measure itself. The numbers that really matter are the ones that directly link to the business.

Jonathan Ferrar from IBM presented a session on “Big Data in HR” that addressed making connections between business data and HR Strategies. The data maturity model from the book Competing on Analytics was explained, as was how it fit into IBM’s five pillar data source model which consists of Social, External, Internal, Predictive, and Enterprise-wide. IBM used a predictive model to project $9M in savings by strategically reducing attrition by 2.7%. This represents a significant shift in how the enterprise leverages HR and how HR can respond by transforming from a retrospective reporting model and showing real value in a predictive sense.

The theme of using predictive analysis was carried into the next session with representatives from Pfizer. In this case, Pfizer analyzed attrition from a socio economic lens and the predictive models were able to project factors that correlated with high attrition. One of the clearest indicators, rehire status, confirmed a long held cultural belief – if they left you once, they’ll do it again. However, as someone in the crowd aptly recognized, correlation is not the same thing as causation. Predictive data gives us insight, but not absolute truth. We need to be diligent and careful with its application.

Despite some excellent examples of how predictive HR analytics have been used at IBM and Pfizer, both of those companies cited that their analytics capabilities were very much early stage efforts that they were trying to expand and grow. On the theme of building capability, there was an excellent panel with representatives from Alliance Data, eBay, and Aleris. As these three companies have taken a head first approach to embracing analytics, it’s important to note that two of the three panelists did not come from HR roles within their companies, and none of them started their efforts by sitting down and asking what HR needed. They all started by sitting down with business leaders (engaged directly with the business) and digging into ways of measuring things that mattered.

Myank Jain from eBay said to start with the basics, Revenue per FTE. But I have to add, don’t underestimate what it will take to get that data. With multiple systems and varying definitions of roles within the business, it might be a bit of a process to define FTE, revenue, or even a definite headcount for the enterprise as a whole until your data maturity gets to a point where you have reliable data. However, it’s worth it, and as Jeff Buchmiller from Alliance Data put it, “The big wins are not usually exclusive to HR data.”

As important as analytics are becoming in the HR landscape, these efforts are not being driven up through the organization. They are intentional top-down efforts led by a new breed of C-level HR executives that are fully engaged with the business that they lead – not the “business” of HR. Another panel at the conference was called “the bold new CHRO,” but I found it interesting to note that only one of the four actually had the job title CHRO. The market is moving so fast, and this new HR is so important, that there is no time to wait for job titles to catch up. The panelists were:

  • Bruce Boucher, Extra Space Storage, CHRO
  • Richard Hughes, United Health, SVP
  • Garry Randall, Disney Consumer Products and Interactive HR, SVP
  • Steven Rice, Juniper Networks, EVP HR

What these gentlemen all had in common (other than being white males, but that’s another story) is that they all had bold new visions for HR. In their vision, HR is a partner to its business, an enabler of strategy, and a driver of business performance. All four speakers were highly engaged, charismatic, and knew that they were on a long path that would require continuous improvement. While all spoke with passion on their organizations, Steven Rice from Juniper Networks is someone to watch. His plain language approach to making things work and work right is highly admirable and will lead to great things in our industry.

Read my recap of day 2.

Bersin IMPACT 2013 – Day 2

April 24, 2013 / / 0 Comments

To keep up with the Bersin IMPACT conference in real time, follow Media1der Harrison Withers on Twitter at @harrisonwithers.

Here’s a summary of yesterday’s session, courtesy of Harrison’s twitter feed, in reverse chronological order. Make sure you take a look at his photos too!

thank you @CornerstoneInc for a great reception. Another Fort Lauderdale time elapse picture to celebrate. #impacthr pic.twitter.com/sQRNWD8u1p

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trying to think of something clever to say about big data and big boats, but brain is full… #impacthr pic.twitter.com/stjIrJ8Dog

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Finally the clouds break and we are enlightened with knowledge and warmth (and ideas about analytics) #impacthr pic.twitter.com/0mT8AHdbfD

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Congratulations to Bersin “What Works” award winners! #impacthr

Steven Rice “Benchmarking is interesting but not helpful” #impacthr

Steven Rice, Juniper networks, what a great down-to-earth no BS approach. #impacthr

Free Return On People maturity assessment. #impacthr

“Distinctly Disney, Authentically Chinese” -J. Bersin. Great characterization of Global/Local operating model that we aspire to. #impacthr

The best way to predict the future is to create it. So, what does your business need tomorrow to be? #IMPACTHR

“entrepreneurs of talent” sounds like the makings of reality tv show. Part joking, but it might actually help #impacthr

Only one of the four on the panel has the title of CHRO, is the title important or the mindset? #impacthr

the BOLD CHRO panel with Disney, Extra Space Storage, United Health, and Juniper Networks #impacthr

the business will see HR as a cost until HR shows a profit. #impacthr

Revenue Per Employee, simple measurement that can be deceptively hard to get. #impacthr

My personal hobby of building guitars and HR Measurement meet in this blog post: http://www.media1.us/measure-twice-cut-once … #impacthr

Which system would you go to for an employee count? Is there more than one? Would you get the same answer? #impacthr

the big wins are not usually exclusive to hr data – Jeff Buchmiller, Alliance Data #impacthr

Analytics starts with the business and not the needs of HR. Who do you talk to first? #impacthr

2 of 3 panelists in predictive analysis didn’t come from HR roles. #impacthr

Step 1 to analytics: get smarter about the question. #impacthr

Thought I recognized Mayank Jain, IRC correctly he presented at #learning12 on behalf of amex, now with eBay. Mobile talent. #impacthr

building capability in predictive analytics at #impacthr with Alliance Data, eBay, and Aleris

Social people search is the new recruiting nirvana, is knowledge management next?How do we “recruit” internally for capability. #impacthr

from the crowd: correlation is not causation. true dat. #imapacthr

Return on People Analytics maturity is a slope not a step. Get what you can and utilize it to enable the next step. #impacthr

Dear CLO, read what the the CHRO reads, worry about what the CHRO worries about, or get called to the table on it. #impacthr

Distributed HR does not necessarily mean decentralized, does not mean disconnected, and absolutely does not mean inconsistent. #impacthr

Pfizer data shows rehire status is strong predictor #imapcthr

Being predictive with analytics requires a shift from being reactive to being proactive. #impacthr

71% of surveyed executives express very high (43%) or high concern (28%) about losing critical talent. (Deloitte) #impacthr

Whatever we say about “learning” almost always transcends into HR. Learning plans are annual, just as well be HR, Talent, Etc. #imapcthr

learning that doesn’t lead to performance = http://www.youtube.com/watch?v=bFEoMO0pc7k … #impacthr

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38% of respondents cite “lack of understanding of how to use analytics to improve the business” as barrier to adopting analytics #impacthr

Newsflash: Nobody has time for anything (including learning) they don’t derive value from. #impacthr

measurement inexorably leads people to mistake the measures themselves for the things they were intended to measure. -C. Green #impacthr

IBM used predictive model to project $9M in savings by strategically reducing attrition by 2.7% #impacthr

“Heat Map” hurts my head but clearly shows differentiation #impacthr pic.twitter.com/RqVkDwR56D

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Does your company have a set definition of what an FTE consists of? Most of my clients do not, and it is not uncommon. #impacthr

Waiting for somebody to do something about that? Wait … aren’t you somebody? #impacthr

5 levels of analytics: Social, External, Internal, Predictive, Enterprise-wide #impacthr

From book: Competing on Analytics, Davenport and Harris #impacthr pic.twitter.com/ZHliMsSTvQ

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According to IBM study 71% of companies cite human capital as a leading concern #impacthr

Waiting for somebody to do something about that? Wait … aren’t you somebody? #imapcthr

Analytics Driving Action with Jonathan Ferrar, IBM #impacthr

Agile Performance Management- Shift from competitive ranking to continuous coaching #impacthr

Social people search is the new recruiting nirvana, is knowledge management next?How do we “recruit” internally for capability. #imapacthr

30-35% higher returns on process when shift from annual performance reviews to quarterly. Agree, but how measuring “return” #impacthr

Agile Performance Management- Shift from competitive ranking to continuous coaching #imapcthr

changing from “learning” to “capability and performance” #impacthr

Experience design note: I sat in the middle so I could see Josh, screens are now too far away to read infographics. #imapacthr

Bersin drivers: 1. gaps in leadership, skills, and ed. 2. Explosive role of technology 3. Disparities in economic growth & opp. #impacthr

http://bit.ly/ZkYz0V  -very wise words from @Josh_Bersin #impacthr

Wise words from others:

@hirevuejosh Steven Rice, EVP HR at Juniper Networks – If I can’t deliver content on a mobile device, my execs won’t read it. #impacthr

‏@charlietierney #hranalytics 2 ways 2 do it. Small group doing cool stuff OR embed the analytics into hr culture…everything u do. #ImpactHR

@StaciaGarr #impacthr Speed of accessing info is most determined by having clear data definitions. #hranalytics

@emmajs24 HR orgs should build networks of expertise, not centers of excellence #impacthr

‏@bollinger Best quote today -Extra Space Storage – “our competition is the dumpster” – Bruce Boycher – CHRO #impacthr

@rgravelin #impacthr Metrics change based on the needs of the business partner. “If it’s not measured, it’s not real.” — Yetter

‏@rgravelin #impacthr We get locked into annual learning plans, but the business changes more frequently that annually.

@davidkoehn #impacthr …map the global local L&D model to the overall operating model of your business… CLO Fishbowl

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