Posts

Talent Calibration Can Rise Above Politics. But How?

/, , , , /by

Are you involved in your organization’s talent calibration process? Think back to the last session you attended with executives. Did they mostly stay quiet? Perhaps experience taught them that opening up about employees exposes them to career-damaging shoot-from-the-hip criticism. Or they may think it reflects poorly on them as leaders if staff members’ ratings are less than stellar.

Unfortunately, this is a common situation. And too often, it leads to needless bias in talent ratings. Hyperbolic statements like “She’s fantastic!” or “He’s a superstar!” don’t help. Actually, leaders’ talent calibration input can be distorted by many factors — territorial issues, inflated egos, unconscious bias, a lack of exposure to employees, and more.

How can you minimize the impact of these variables? After working with many senior leadership teams who’ve faced these challenges, we’ve developed an approach that removes politics from the equation. It’s a two-step process:

  1. Capture leadership behaviors on a scorecard.
  2. Rely on data-based decision-making to drive calibration.

Here’s how it works…

The Behavior Scorecard: Measuring Means and Ends

Some executives are wildly successful, yet they’re notorious for leaving a “trail of bodies” behind them. When the end always justifies the means, it sends a negative message that can seriously damage your organization’s culture.

Before executives calibrate talent, they need a way to manage “ends” and “means” that avoids in-the-moment bias. The answer? Emphasize observable behaviors that reflect your cultural mindset and values. Rather than relying on a standard off-the-shelf competency model, focus on real behaviors that are valued in your organization.

Partnering an in-house team with an external challenger can provide a more balanced perspective. Also, expand your interviews beyond top executives. Perspectives from across the organization help create a realistic and authentic framework. Use focus groups, surveys, and other instruments to help illuminate the nature of leadership at all levels of the organization.

Most companies have already performed much of this work, and the evidence is located in multiple places. Start by analyzing verbatim comments from engagement surveys. Review consultant reports based on employee interviews. Interview people at all levels to understand what is valued currently, and what will help the organization advance. Using this data, you can construct a simple set of leadership priorities, including specific behaviors that can shape assessments and learning opportunities.

Assessments based on these behaviors can be one data point in an executive leadership scorecard. Others might include mobility, diversity goals, engagement survey data, ethical conduct, and participation in employee resource groups. Clearly define measures of leadership behavior that will move your organization in the right direction.

Data-Based Decision-Making: 4 Steps

We suggest a simple 4-step, data-driven decision methodology. We call it the “STAR” process — survey, talent card, assessment, and review. This encourages ongoing conversations about executive talent between peers. It also ensures visibility of organizational talent and breaks down silos to increase mobility, career development and advancement.

1. Survey

Understand a leader’s ‘brand’ before calibration.

Conduct a survey based on the potential and visibility of the “brand” each executive has developed with their peers. To promote a robust discussion, compare each executive’s pre-calibration response with responses from peers. This exercise can be especially helpful for succession planning and development.

2. Talent Card

Show a full view of the leader and their organization.

Use this card to aggregate data about leaders and how they manage their teams. Ideally, it features scorecard data, performance data, risk data, and ethical data. It can also include other relevant organizational data such as spans, layers, diversity, and profit and loss responsibility. To offer a broader perspective, you may also want to add responses from employee surveys.

3. Assess

Weight each item to determine a starting score.

For all talent card data, assign a relative weighting based on importance. This creates a set of “scores” based solely on data. These scores are your calibration starting point. Stack rank the list of leaders by score to identify top, middle, and bottom ranges. A leader’s manager can keep the ranking, or challenge it and add commentary. This balances manager reviews and data-based reviews of executive talent.

4. Review

Prep for calibration.

A review period gives executives a starting point to calibrate talent based on available data. Differences between ratings reveal where the “heat” of conversations should focus during a calibration meeting. This review cycle encourages dialogue about gaps before a calibration session. Encourage participants to stay curious and check their biases. Also, prompt them to ask questions that will deepen their understanding, rather than to explain or defend.

The Calibration Session

After completing the pre-work, you can focus on the gaps between data and manager review as a starting point for talent discussions. It also creates opportunities to ask useful probative questions about each leader. For example:

  • Were appropriate goals established?
  • Is this a “how” or “what” issue?
  • Are they seen as a “blocker” for other talent?
  • How do they interact with peers?
  • Are they visible enough?
  • Do they need to move on to a new role?

The calibration team does more than simply determine an appropriate rating. It also makes data-driven decisions around talent actions. Next steps and plans for both struggling and high-potential talent can be recorded during the session.

Benefits of a Better Talent Calibration Process

We’ve worked with many senior leadership teams who’ve faced serious talent calibration challenges. When one firm used this process to deepen their talent discussion, it helped them create more effective development plans and design more confident action plans during the calibration session.

This planning process enabled executives to conduct more fruitful conversations with their most talented leaders. And these conversations about strengths, opportunities, and career paths within the company resulted in increased mobility through promotions, retirements, and resignations. As a result, the company made way for new talent, while increasing the visibility and mobility of diverse talent.

By relying on available data and linking evaluations to transparent behaviors, you too can reduce bias and improve the conversation about enterprise executive talent. Ultimately, you can minimize the unwanted influence of politics in discussions and decisions about your organization’s most precious resource — talent.

 

EDITOR’S NOTE: In developing this article, Jennifer Tice collaborated with Andy Atkins, VP, Executive and Team Performance Practice at BTS, a global consultancy. For more than three decades, BTS has been designing powerful experiences that have a profound and lasting impact on businesses and their people.

Want to Improve HR? Ask Better Questions First

/ /by

Boston got hit with its third snowstorm in two weeks recently, and more than a few work initiatives overseen by nearby colleagues got lost in the blizzard — including a high-level meeting on workforce planning. Today was supposed to be a big roundtable where senior HR people set their crystal ball on the table to discuss new hiring initiatives and succession strategies.

The organization (I’ll call them Company X) is scaling up rapidly, and has meanwhile been hit with a nasty wave of voluntary departures. It’s a common one-two punch that can knock the wind out of the sturdiest HR teams. So how can HR leaders react?

Use Tech Tools to Get the Big Picture

No, people aren’t leaving because of the snow — necessarily. Actually, no one knows why they’re leaving: there are no exit surveys to help find out why. Work is different from love: when a relationship ends, no matter how you unpack it, the love is gone. But debriefing matters at work. It’s worth getting the data on why someone leaves. To get that data, you have to ask for it.

That means that every organization needs a powerful, easy to use feedback tool and well-constructed analytics to shape the answers.

Make Data Accessible

Back to the big meeting: Company X employs some 1,800 people in the Boston area — and most of those couldn’t come to work in the blizzard, so the meeting was postponed. The HR summit depended on looking at spreadsheets, the rationale went, which we can’t really do remotely. So instead of spreadsheets, they’re looking at snow banks. It’s a textbook lesson in the need for better tools — including talent analytics. If they already had the data they needed, they’d be able to push ahead with a plan, weather or not.

Build an Analytics-Focused Culture

My colleague is a silver lining type. He used the snow day to do what he’s wanted to do for months: Analyze the available data to create a better hiring plan. We’ve been talking about the power of analytics for some time now, but it’s not yet part of universal work culture, and it’s certainly not part of Company X. The company views itself as a legacy firm with a rather buttoned-up HR approach (which may also be something to look at in terms of losing talent). Its top people are beset with that “he/she went to a good school” bias. True, Boston has as many college students around as it does snow these days, and we all like smart coworkers. But the theory that brains and education equals great work ethic and potential for growth has been long disproved.

Consider the Competition

We’re also working with a labor market that’s tighter than it has been in decades. Most of us can’t compete with big tech companies like Google and Facebook. Google famously offered a staff engineer $3.5 million of restricted stock to turn down an offer by Facebook; carrot accepted. Frontrunner organizations are leveraging great candidate and employee experiences into better engagement and a stronger employer brand. A global IBM survey of more than 1,700 CEOs found that 71 percent see their people as critical to their competitive advantage.

Use the Data to Make a Case

The good news: We’re committed to putting data to work. In 2013, only 5 percent of big-data investments were in human resources, according to a global study by a tech consultancy. Five years later, 63 percent of companies are investing in tech to boost hiring and retention.

Yet in that same survey, 60 percent of respondents saw turnover rates of 20 percent, and 25 percent were losing up to half their people.

We’re not using the new technology that’s available to actually fix our HR woes. Only 35 percent were using tech tools for hiring. The data is there — but not the tools to drill into it and craft a vision for the future. And there’s the irony. If we’re not yet asking the right questions, we’re not going to get the answers we need — which is going to give the old guard at Company X more ammunition to argue that data doesn’t work.

Insist on Asking Better Questions

Once the snow is gone, my colleague has decided he’s going to suggest a trip away from the stuffy office to revisit their non-use of data — and chart a way to get the data they need. To power his case, he’ll ask:

  1. How many people are we going to need to hire in the next year? And in the next five years?
  2. How much is it going to cost to hire them?
  3. How many of those open positions are new?
  4. Is there anything in common with the talent we lost in the past 12 months?
  5. How do candidates feel about the hiring process now?
  6. Which locations and which departments are experiencing the lowest retention?
  7. Is there a point on each employee journey when disengagement sets in, and if so, why?
  8. How long does it take to onboard a new hire? Is that process effective, and can we shorten that period?

The only way to find these answers is leveraging the data — and everyone knows that. The trick, if you can call it that, is to insist on asking the questions. Can’t wait to see what they find out.

HR Data Won’t Make You Less Human

/ /by

With all the talk and rush toward people analytics (or talent analytics), there is some justifiable angst today that the H just might be taken away from HR – numbers will make everyone less human.

Everywhere we look, there’s a new article, webinar, conference or seminar imploring us to get with the program, that program being big HR data and the use of analytics in managing HR and the workforce. Analytics is being used across the board in HR, including talent acquisition, performance management, succession planning and more.

Is there a downside? By using data and analytics across HR functions, will HR and the people that make up HR become just machines, with no humanity, no compassion and no common sense?

No.

Not that there isn’t an opposing view to accompany the angst. Writing in Forbes, Liz Ryan goes all in on the inhumanity of analytics:

“A typical ridiculous, unquestioned business adage is “If you can’t measure it, you can’t manage it.” That’s BS on the face of it, because the vast majority of important things we manage at work aren’t measurable, from the quality of our new hires to the confidence we instill in a fledgling manager.”

Whoa – relax, Liz.

People are the backbone of any organization, and the most successful ones recognize that. It’s the reason talent management is such a hot topic and high priority now. Especially coming off the global recession, with top talent at a premium…the best organizations get this!

Liz goes on:

“Measurement requires stopping the action, getting outside of it and holding it up against a yardstick, exactly the opposite of the activity that would create products or ship them, make customers happy or move our business forward in any way…Measurement is our favorite CYA activity.”

That’s simply not true at successful organizations.

At successful organizations, the action doesn’t stop, the creativity doesn’t stop and the innovation doesn’t stop – the people in these organizations are on fire and they stay on fire, from top to bottom. The measurement is all about improving the business, and making the business better for its people…which will make the business better.

That’s a never-ending, iterative cycle that makes the organization better.

When leading HR industry analyst Josh Bersin claims that, through the use of analytics, “high tech companies now know why top engineers quit and how to build compensation and work environments to get people to stay,” he’s not saying numbers magically appear in some algorithm, get crunched and then get spit out. He’s saying that as part of an ongoing evaluation of an organization and the quest for improvement, this is an area that analytics can shine a spotlight on to improve how the organization betters its people management.

And the HR data comes from people. It comes from employees talking to and engaging with their managers, which comes about from smart executives working closely with and engaging their people managers. In successful organizations, it’s not about CYA and finger pointing – it’s about making everyone better – and making the organization better as a result.

Here’s another real-world example of a large, complex organization that has used people analytics to improve its operations, in conjunction with making its people happier, more productive and more fulfilled. The U.S. Department of Agriculture (USDA) employs many people to assist in the hiring of tens of thousands of applicants in it 29 agencies. People analytics was used to improve a wide range of talent acquisition functions – it led to a better allocation of resources, better candidates and improved communication between HR and hiring managers.  Analytics improved the morale of the people in HR and the people hiring candidates. And oh, by the way, the people applying for jobs now have a much better experience based on data provided by analytics. All this happened without stopping the wheel.

CYA? No. Organizational improvements? Yes.

As Bersin says, the geeks have arrived. But don’t let that scare you.

Most topics are not black and white. With all numbers and no people, HR can’t function. With just people and no data, HR is a lot less effective in doing the people part of its jobs.

While noted data scientist W. Edwards Deming is often credited with saying “you can’t manage what you can’t measure,” he also said “the most important things cannot be measured.”

Embrace analytics, even just a little bit. You’ll see how it can help the people side of your job.

 

Image: bigstock

#TChat Recap: The Talent Science Of Cultural Change

/1 Comment/ /by

The Talent Science Of Cultural Change

Every week our #TChat Community takes an in-depth social look at what’s going on in the World of Work. This week was particularly interesting because we discussed how data and analytics are shaping organizational culture. Our guests: Brent Daily, Founder of RoundPegg, employee engagement software that increases business performance through applied culture science; and Natalie Baumgartner, a Ph.D. in Clinical Psychology with a specific focus on assessment and additional training in strength-based psychology, know closely how talent science can affect the way employees change their perception about organizational culture. The revolution in HR technology has paved the way for organizations to realize how great company culture rewards them with employee engagement and workplace productivity. Before we can begin to understand the makeup of company culture, we must start to:


You can’t begin to form and understand culture until you know what your employees truly value. You have to learn what matters to them. If you want to walk into an office full of organic creativity and passion, then start by asking the right questions. Begin to:

Melissa is right about listening to employees. She’s also right about getting employees involved in shaping company culture. Who better than employees to understand what their organizational culture looks and feels like? Employees carry with them the data to uncovering what organizational culture should be. Of course:

Yes, data and analytics can help light the way for our talent science. It can shed light on what can’t be seen clearly without technology. It can even shed light on paths we did not know are available for us to take. Great company culture comes from understanding the makeup of employees. It’s not about presenting employees with flashiness and disillusionment of what you’re selling. Employees know what they crave. Brent reminded us that:

The key to realizing what your culture is and what it can be comes from having meaningful conversations with employees. Remember, they carry the data to uncovering what your organizational culture can be. HR technology helps remind us of this, and teaches us to recognize the obvious about company culture. You need to get employees involved in shaping company culture by strategically implementing ways for them to add feedback and grow within the organization. Cultivating culture is a science, not a cheap magic trick. Data and analytics gives us the insights we need to understand our organizations, but it’s finding the will to change is what makes it all worth it.

Want To See The #TChat Replay?


 

Closing Notes & What’s Ahead

Thanks again to our guests: Brent Daily, Founder of RoundPegg, employee engagement software that increases business performance through applied culture science; and Natalie Baumgartner, a Ph.D. in Clinical Psychology with a specific focus on assessment and additional training in strength-based psychology.

#TChat Events: The Talent Science Of Cultural Change

TChatRadio_logo_020813 #TChat Radio — Are you plugged in to #TChat radio? Did you know you can listen live to ANY of our shows ANY time? Now you know. Click the box to head on over to our channel or listen to The Talent Science Of Cultural Change.

Note To Bloggers: Did this week’s events prompt you to write about trends on the engagement experience?

We welcome your thoughts. Post a link on Twitter (include #TChat or @TalentCulture), or insert a comment below, and we may feature it! If you recap #TChat make sure to let us know so we can find you!

Contributor CTA

Save The Date: Wednesday, August 20th!

Join us next week, as we talk about Surviving a Bad Workplace Culture during #TChat Events. The TalentCulture conversation continues daily on #TChat Twitter, in our LinkedIn group, and on our new Google+ community. So join us anytime on your favorite social channels! Passive-Recruiting photo credit: Andrew Morrell Photography via photopin cc

What Do Interns Really Want? [Infographic]

/ /by

Developing an extraordinary internship program can be a long and winding journey. You’ll face plenty of bumps in the road, and perhaps lots of trial and error. And as we’ve seen in the news recently, you may even discover some controversy.

But overall, internships can be very beneficial for organizations — not just because enthusiastic young workers are contributing to your business goals. Internship programs can also open the door to a more diverse workforce, help add fresh perspectives to your brand, attract other young talent to your organization, and more.

Of course, employers aren’t the only ones who benefit. Although the state of the internship has shifted over time, its overarching goal remains the same — students and recent grads should gain something educational from their work experience. So, what do today’s interns really want to accomplish, and what else should employers know about them?

The following infographic, based on student employment data from InternMatch, offers insights to help employers map out a more effective internship program. Here are some highlights:

•  38% of interns want better pay
•  30% want opportunities to perform meaningful work
•  47% are interested in access to executives and mentorship
•  California, New York, and Florida are three of the top states for finding college talent

Do any of these statistics surprise you? Check out the full infographic below, and share your thoughts in the comments area.

What are your thoughts? Have you experienced these trends — as an intern or as an employer?

Image Credit: Stock.xchng

HR Data: What's The Big Deal? #TChat Preview

/ /by

(Editor’s Note: Are you looking for a full overview of this week’s events and resources? See “HR Data: What Really Counts? #TChat Recap.”)

(Also Note: Have you heard the news? Now there’s another reason to look forward to Wednesdays!  STARTING THIS WEEK #TChat Radio moves to Wednesday nights at 6:30pmET — just prior to our popular #TChat Twitter event at 7pmET. So tune-in live, and then join us on stream!)

Better Data = Smarter Choices

Past performance can be a good indicator of future performance, right? Well, when it comes to HR decisions, not necessarily — according to a recent New York Times profile of workforce science practices.

Advances in data collection and analysis are shattering preconceived notions about how to find and manage talent. Increasingly, HR practitioners are looking to data for answers to important business questions. The possibilities span a broad spectrum:

  • Talent Pool Viability
  • Skills + Competency Analysis
  • Hire Quality + Cultural Fit
  • Employee + Contingent Engagement
  • Hiring vs. Workforce Development
  • Workforce Growth Rates + Costs
  • Talent Retention + Turnover
  • Overall Business Impact

So how can you effectively apply data to HR practices? That’s a question we’ll discuss at #TChat forums with two HR data experts:

#TChat Sneak Peek Video

To kick-off this week’s conversation, Christene joined me for a quick G+ Hangout, where she helped clarify the meaning of “Big Data” and its relationship to HR management:

#TChat Events: The Big Deal with HR Data

What do you think about workforce data and its role in business management? Whether you’re an organizational leader, an HR practitioner, or a job-seeker who wonders how data analysis will influence your career, data is increasingly relevant to professional life. So bring your point of view, and join us to share your questions, ideas and opinions to the table this week!

TChatRadio_logo_020813

Tune-in to the #TChat Radio show

#TChat Radio — Wed, June 26 at 6:30pmET / 3:30pmPT

Christene and Andrew join our hosts, Meghan M. Biro and Kevin W. Grossman, for a LIVE 30-minute discussion to examine this topic up-close.

#TChat Twitter — Wed, June 26 at 7pmET / 4pmPT

We welcome anyone with a Twitter handle to join our open, online community, as we exchange ideas live on the #TChat stream to explore this week’s questions:

Q1: Why is Big Data a bit of a misnomer when it comes to HR analytics?

Q2: What’s the difference between data, metrics and analytics?

Q3: What metrics and analytics should HR focus on, and why?

Q4: What can HR leaders do to make a business case for predictive analytics?

Q5: Why should we stop using spreadsheets to analyze talent management data?

Throughout the week, we’ll keep the discussion going on the #TChat Twitter feed and on our new LinkedIn Discussion Group. So please join us share your questions, ideas and opinions.

We’ll see you on the stream!

HR Data: What’s The Big Deal? #TChat Preview

/3 Comments/ /by

(Editor’s Note: Are you looking for a full overview of this week’s events and resources? See “HR Data: What Really Counts? #TChat Recap.”)

(Also Note: Have you heard the news? Now there’s another reason to look forward to Wednesdays!  STARTING THIS WEEK #TChat Radio moves to Wednesday nights at 6:30pmET — just prior to our popular #TChat Twitter event at 7pmET. So tune-in live, and then join us on stream!)

Better Data = Smarter Choices

Past performance can be a good indicator of future performance, right? Well, when it comes to HR decisions, not necessarily — according to a recent New York Times profile of workforce science practices.

Advances in data collection and analysis are shattering preconceived notions about how to find and manage talent. Increasingly, HR practitioners are looking to data for answers to important business questions. The possibilities span a broad spectrum:

  • Talent Pool Viability
  • Skills + Competency Analysis
  • Hire Quality + Cultural Fit
  • Employee + Contingent Engagement
  • Hiring vs. Workforce Development
  • Workforce Growth Rates + Costs
  • Talent Retention + Turnover
  • Overall Business Impact

So how can you effectively apply data to HR practices? That’s a question we’ll discuss at #TChat forums with two HR data experts:

#TChat Sneak Peek Video

To kick-off this week’s conversation, Christene joined me for a quick G+ Hangout, where she helped clarify the meaning of “Big Data” and its relationship to HR management:

#TChat Events: The Big Deal with HR Data

What do you think about workforce data and its role in business management? Whether you’re an organizational leader, an HR practitioner, or a job-seeker who wonders how data analysis will influence your career, data is increasingly relevant to professional life. So bring your point of view, and join us to share your questions, ideas and opinions to the table this week!

TChatRadio_logo_020813

Tune-in to the #TChat Radio show

#TChat Radio — Wed, June 26 at 6:30pmET / 3:30pmPT

Christene and Andrew join our hosts, Meghan M. Biro and Kevin W. Grossman, for a LIVE 30-minute discussion to examine this topic up-close.

#TChat Twitter — Wed, June 26 at 7pmET / 4pmPT

We welcome anyone with a Twitter handle to join our open, online community, as we exchange ideas live on the #TChat stream to explore this week’s questions:

Q1: Why is Big Data a bit of a misnomer when it comes to HR analytics?

Q2: What’s the difference between data, metrics and analytics?

Q3: What metrics and analytics should HR focus on, and why?

Q4: What can HR leaders do to make a business case for predictive analytics?

Q5: Why should we stop using spreadsheets to analyze talent management data?

Throughout the week, we’ll keep the discussion going on the #TChat Twitter feed and on our new LinkedIn Discussion Group. So please join us share your questions, ideas and opinions.

We’ll see you on the stream!