MCBASSI & COMPANY

How to Grow Your HR Analytics Budget

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If you’re like many HR professionals, you share two characteristics:
  • You know you should be making more progress on HR analytics
  • You also don’t know where to get the money to do it

And yet, some organizations – admittedly a minority – report that they have sufficient HR analytics budgets.

So we set out to determine what distinguishes those HR functions that report having an ample budget for analytics.  To answer this question we analyzed McBassi’s HR analytics maturity benchmarking database. (If you would like a free customized benchmarking report on how your company’s current HR analytics maturity stacks up, click here.)

Our analysis showed that the following attributes distinguish HR functions that have a sufficient HR analytics budget from those that don’t:

1.  They have a strategy in place ensuring that their HR analytics initiatives are aligned with the organization’s strategic objectives.

2.  They get the basics right. They have reports/dashboards making it possible to determine whether goals are being met for each of HR’s key responsibilities (recruiting and selection, training and development, compensation and benefits, retention and promotion).

3. They have developed the capacity to link together disparate pieces of information on people and business outcomes to produce actionable, executive-level insights.

Now we know what you may be thinking – “We can’t possibly do these things because we don’t have the budget to get them done.” Classic chicken-and-egg problem. But what we’ve learned is that it doesn’t take a lot of money to make a good, running start at each of these issues. It does take being clever and resourceful – and committed.

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Applying HR Analytics to Leadership Development

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HR analytics has wide applicability to a broad spectrum of people-related issues within organizations.  Within the HR universe, analytic methods are most typically applied to identifying factors that drive employee engagement or employee turnover.

There are many other applications as well that are far less commonly used.  This month we’ll explore the use of analytics in leadership development, a common (and often quite expensive) investment organizations regularly make in key employees.  Nonetheless, we’ve found that most organizations know very little about the impact or effectiveness of those investments.

We have four key lessons about how to apply analytics to better understand – and improve – an organization’s return on its leadership development:

  1. Make sure the leadership competencies in which you’re investing are, in fact, the ones that will drive better organizational performance.  Rather than investing in generic, one-size-fits-all competencies from external vendors, consider creating your own competencies, so you can develop leaders with the characteristics to be successful in your organization.
  2. Tap the wisdom of your workforce to determine what leadership development has actually occurred.  Ask the people who see your leaders in action every day: your employees!  How?  Ensure that detailed leadership questions are included in your employee surveys and/or 180-degree (or 360-degree) feedback assessments.  This will make it possible to properly evaluate and improve your leadership development initiatives.
  3. Link together key (and disparate) pieces of data to yield actionable insights for improving the return on your leadership development investment.  Look at the relationship between various leadership characteristics and competencies and your organization’s outcomes.  See which ones are most closely associated with more successful outcomes, and focus on those in the future.
  4. We’ve said it before, but don’t let the perfect be the enemy of the good!  You won’t accomplish all of the above right away – it will take some time and some hard work.  But that’s not a reason not to get started.  Even the most basic early insights can be powerful catalysts for change – and your insights will only improve with more time (and more data).

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How To Get More Value Out Of Your Employee Engagement Survey: Part 2

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Cleverly Analyzing Your Survey Data

Any employee engagement survey should help your organization drive better business results through more effective management of its employees.  When done properly, an engagement survey helps your organization operate in “the sweet spot” – the intersection of enlightened and sustainably profitable management of people.

Employee engagement surveys often fall far short of this potential because data from surveys is not properly analyzed, and the resultant report therefore has little impact.

There are three steps you must take to ensure that your employee engagement survey has maximum positive impact:

Part 1 – Ask the right questions (see our August newsletter)
Part 2 – Analyze the data cleverly (see the guiding principles outlined below)
Part 3 – Create insightful reports (coming up in next month’s newsletter)

The five principles that should guide your analysis of employee survey data are listed below.

1.  Design your analysis to identify statistically the most important drivers of your organization’s employee engagement and ability to achieve its business goals.  The analysis needs to go far beyond benchmarking and measuring high and low scores.

2.  Use correlation analysis as a primary tool for identifying the drivers of each of the outcomes questions separately.  (Click here for a discussion of diagnostic vs. outcome questions.)

3.  Systematically combine the findings from the correlation analyses with measures of organizational strength and weakness on each of your survey’s diagnostic questions to create a rank ordering of areas of opportunity.

4.  Simultaneously examine the rank ordering of areas of opportunity for each business outcome to create a “short list” of the most important areas of opportunity.

5.  Use that short list to create fact-based, directional recommendations.

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7 Steps to Using Analytics to Improve the Evaluation of Learning

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A recent CLO article reported that a growing number – nearly 60 percent – of CLOs are dissatisfied with their internal learning analytics capability.  The article states that, “This reflects an ongoing trend: The state of measurement in learning and development is falling behind other areas of the business. CLOs are more dissatisfied with their organizational approach to measurement this year than last, continuing a trend of the past three years.”

In short, in most organizations a different approach is needed.  More of the same (which typically means using Kirkpatrick levels 1-5, with an emphasis on the lower levels) won’t get CLOs where they want to be – understanding what’s working (and what isn’t) in learning and development initiatives and targeting resources at the most fruitful areas for improving business results.  Instead, a more modern, “analytics-enhanced” approach is necessary.

Here’s what we’ve learned about how to transform an organization’s learning analytics:

1.  Create an “authentic” learning impact evaluation by embedding it in a more holistic framework.

The fundamental problem with traditional (Kirkpatrick) learning evaluation is that it’s done in a vacuum.  While some Kirkpatrick evaluations definitely have their place, a more authentic way to evaluate the impact of learning is to embed it in the larger context of measuring the overall management and development of a company’s people.  In particular, companies should seek to identify opportunities to learn from “naturally occurring variations” in people’s work, learning, and leadership environments.   All of those variations – not just learning-related ones – should be used to assess and predict variations in business outcomes.  This requires that the CLO’s office collaborate with – or take the lead to create, if necessary – an analytics “center of excellence” within the organization.

2.  Stop waiting for the perfect data warehouse.  Instead, create a “data hut.”

At their core, data warehouses are designed for reporting – not analytics.  So the sooner you realize that your organization’s data warehouse (whether current, pending, or hoped-for) is never going to enable you to do the learning analytics that you need, the better off you’ll be.  To undertake analytics, you need to start by putting together heretofore disparate pieces of data (see Figure 1).   This will enable you to do the following:

  • Take a big step toward embedding your learning evaluation in the larger context of evaluating people management and development (step #1 above).
  • Analyze why you are getting the impact that you are getting (not just what the impact is).
  • Produce actionable insights about what levers to pull to create better business results through learning.

Figure 1. Build a HR Analytics “Data Hut”

 

3.  Don’t let the perfect become the enemy of the good.

Generalizing #2 above, in the early days of creating an analytics-enhanced learning evaluation, you will almost certainly not be able to obtain all of these disparate pieces of data and integrate them into a unified analysis file.  But don’t let that become an excuse for inaction.  Start by putting two of these pieces of information together – for example, data from your LMS with employee engagement, or turnover data, or customer satisfaction data, or sales data.  The important point is to begin to make progress, rather than to continue with the (unsatisfying) status quo.

4.  Choose your initial analytics project carefully.

The best place to start is with a burning business issue.  Examples might include one or more of the following:

  • Customer satisfaction problems
  • Lackluster sales
  • Safety
  • High levels of regretted turnover
  • Failure to achieve diversity and inclusion goals
  • Stagnant or declining employee engagement

Design your initial analytics project to provide actionable insight on issues that are front-and-center for senior executives, and you will find yourself in a much better place.

5.  Start under the radar.

Making progress towards better, more powerful, analytics-enhanced learning measurement does not have to take a lot of time or money.  Choose the right initial project (#4) without fanfare.  Just go do it.  Use the findings from your first project, and the enthusiasm that it will engender, when properly presented (see #6), to bootstrap up your learning analytics budget and capability.

6.  Remember: insightful reporting trumps data dumps.

Learning analytics is both a science and an art.  The art comes in how you present the findings from your analysis.  Less is often more.  So focus on what executives need to know to drive better business results, and avoid the temptation to share every nuance and cool thing you might have learned in the course of the analysis.

7.  Use learning evaluation to improve the effectiveness of learning.

It will also be tempting to use your newfound analytics capability to prove that “learning is working.”  It’s far better, however, to use it to develop actionable insights for improving the business impact of learning.  Doing so will generate significant returns in terms of the enhanced credibility and support that learning enjoys within your organization.

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HR Analytics: Get Started By Thinking Big

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HR Analytics holds the promise of helping organizations operate in the “sweet spot’ – the intersection of sustainably profitable and enlightened management of people.  Aspiring to achieve this outcome is a powerful impetus for designing, executing and sustaining your organization’s HR Analytics strategy.

It’s always important to start with the end goal in mind.  And ideally, it should be a BHAG – a big hairy audacious goal. Otherwise, your HR Analytics efforts run the risk of devolving into another HR-check-the-box reporting initiative long on activity and short on value.

To achieve your BHAG, you’ve got to start by asking the right questions. What would any potential investor want to know about the people side of your business? How could your strategic HR measurement and analysis inform an investor’s perspective?

Of course, your Board of Directors should want to know everything investors want to know, and then some.  Similarly, your CEO, CFO and the executive team should want to know everything the Board wants to know, and more.  And senior HR leaders should want to know everything the executive team wants to know, plus still more.  You get the idea.

Now here’s the thing.  Investors, boards and executive teams currently only ask for (demand) a very limited set of HR metrics.  That’s because they don’t know more is possible.  Your job is to help educate them so they know they can, and should, expect actionable insights that provide them with the facts and analyses they need to make better business decisions.  And these facts and analyses need to go far beyond executive comp and executive-level succession planning.  That is the essence of HR analytics.  (See our ATD post from last month for more detail on this.)

Here’s our advice: incorporate into the narrative perspective on the critical risks that your work mitigates.  Risk is, in fact, the other side of value creation.  One very important lesson we’ve learned in our work with clients of all sizes and industries is that “risk sells” – all decision-makers are concerned about it and want to understand better how to minimize it.

So here’s a human capital risk framework to get your creative juices flowing:

  • Capability Risk: Do your people have the knowledge, skills, resources, and business processes that will enable them to perform effectively?
  • Alignment Risk: Do your people really understand your business strategy and goals and do their day-to-day jobs in alignment with those goals?
  • Turnover/Demographic Risk: Are you retaining key people?  Do you have a pipeline sufficient to replace departing employees?
  • Labor Market Risk: Are you able to find and acquire the right people?
  • Health/Well-being Risk: Are your people healthy and able to contribute to the organization at their maximum capacity?
  • Leadership Risk:  Do you have the leadership depth or quality needed to ensure that key initiatives will be successful?

By shifting or expanding your thinking, language, metrics, and analysis from value creation to risk mitigation, you will lay the foundation for a sustainable HR Analytics strategy worthy of sustained, high-level executive and organizational support.

The most appropriate risk-based BHAG for your organization will depend on your organization’s specific people-related challenges. The only limit is your imagination – and having the available data!

Remember HR Analytics is not about generating piles of reports.  It’s about generating insights in areas of risk affecting the very life-blood of your organization.

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4 Axioms of HR Analytics

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HR analytics is a hot topic these days.  With new conferences, books, and software emerging at a dizzying pace, it’s easy to feel like you’re scrambling not to fall behind.  And with all the hype, it’s easy to lose sight of what’s really important in this realm.  What can HR analytics really do for your organization, and what traps do you need to avoid?

Here are McBassi’s 4 axioms of HR analytics:

1.  HR analytics is more than predicting turnover.

Multiple times, we’ve asked for a show of hands at conferences on who’s using HR analytics in their organization.  Many hands always go up.  Then we ask who’s using it for something other than analyzing and predicting turnover.  Almost all the hands go down.

Don’t get us wrong — predicting turnover is a worthy goal and a fantastic use of the principles and tools of HR analytics.  But it’s far from the only thing to look at.  Try using the same concepts to assess differences in sales across offices, or safety records across plants, or how to identify key issues to address after a merger/acquisition, or how to report to the board of directors.  The list goes on and on.

2. The importance of a problem is inversely related to the sophistication of the statistics available.

Sad but true: multivariate regressions, factor analysis, simultaneous equations, complex neural networks – all impressive quantitative techniques, but rarely the right tools to answer the most important questions facing a business. For example, what do we need to do to become more innovative?  How can we increase sales?  What would make our stock price grow sustainably faster than our competitors’?

The problem is that the most sophisticated statistical methods also need lots of comparable units for analysis.  They might work well if you have the necessary data on a million consumers or a thousand plant locations, but they’re much less likely to work on big questions, where the data’s usually a lot more limited.  But other, more basic, methods can still provide key insights.  Don’t shy away from comparison of means or correlations just because other methods look more impressive.

3. Risk sells better than value creation.

HR analytics can provide key insights into both risk and value creation in your organization.  But which one is much more likely to get the attention of your executives?  Risk.  Executives are keenly aware of the multiple types of risk faced by your organization, and anything that can help them quantify it – especially in a not-typically-quantified area like your organization’s people – is going to be welcomed enthusiastically.

4. Don’t forget about the forest.

Data analysts are masterful at drilling into big data sets and identifying all sorts of relationships and other interesting findings.  But that should be just the start.  More important is the next step: sorting through all those findings to determine what’s really going on.  What’s the big picture or pattern that emerges from all of these smaller pieces?  Remember that’s what your ultimate goal is, and don’t let yourself miss the forest because you’re distracted by all the interesting trees.

 

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An Analytics-Enhanced Employee Survey

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Welcome back (at least to those of you in the northern hemisphere) to the new, even-more-frenzied, post-summer work reality!

For those of you beginning to be immersed in 2015 planning and budgeting, we’d like to offer some thoughts on how to get more bang for your buck from your next employee engagement survey.  In one sentence: you should use it as cornerstone for a strategic, analytics-enhanced HR measurement strategy.

When employee engagement data is properly designed and cleverly analyzed, it is an enormously powerful foundation for creating actionable, fact-based insights to drive better business results.  It is the single most important source of data enabling you to move beyond “descriptive” HR metrics to “predictive” human capital analytics.  By identifying the human drivers (and impediments) of business results, these analytics insights provide a strong evidence base both for guiding HR investments and documenting their impact.

Through linkage analysis – the mapping of employee engagement to important business outcomes­ – it is possible to develop insights into the HR strategies that will have the greatest positive impact on your organization’s greatest challenges, such as the following:

  • Revenues
  • Cost containment
  • Profitability
  • Customer service issues
  • Productivity
  • Safety
  • Managerial effectiveness
  • Training effectiveness
  • Employee engagement
  • Absenteeism
  • Regretted turnover

The bottom line – an analytics-enhanced employee survey is a far better investment than the traditional, HR check-the-box employee engagement survey!

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Do You Have the Ladder on the Right Wall?

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A generally accepted truism is that 80 percent of the work in an organization is accomplished by 20 percent of its employees.  But it is also true – at least based on the view of the world we see in our client work – that most people are working incredibly hard these days.  So how is it that both of these propositions could be simultaneously true?

The most likely answer is that lots of people are spending lots of effort placing and climbing their proverbial “ladders” on the wrong wall – or at least the wrong spot on the wall.  We see it all the time: employees and organizations working diligently, all to maximize the wrong outcome.  Attempting to maximize customer satisfaction is an example.  When you stop to think about it, achieving this objective should be very easy – just produce an acceptable product or service and give it away for free.  But, of course, that would be completely unsustainable.  (The HR equivalent is attempting to maximize, rather than optimize, employee engagement.)

And that is why people involved in this type of work find it so difficult – the organization pushes back to prevent the damage that would occur.

So ask yourself whether a part of the resistance you encounter in work might be the result of attempts to maximize the wrong objective?  In other words, do you sometimes attempt to put the ladder on the wrong wall? And if so, how would you know?

Having solid business acumen skills is the one sure-fire way to avoid this exhausting and career-limiting error.  And it is also why a key element of business acumen – HR analytics – is getting so much attention these days.

It helps ensure that you’ve got the ladder at the right spot on the right wall.

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Webinar on employee surveys and big data

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I’ll be joining forces with KnowledgeAdvisors for a terrific new webinar, “Employee Surveys and Big Data: Gaining Crucial Business Insights from Your Workforce,” on Thursday, April 11, 2013, at 11:00 am.

I’ll share what I’ve learned about using employee surveys and predictive analytics to understand employee culture and drive better business results.

Join us and come away with insight into getting started, best practices and pitfalls to avoid!

Register here: http://ow.ly/jkcRT

5 HR Analytics Mistakes to Avoid

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No matter what name you prefer – HR analytics, HC analytics, or talent analytics – more and more organizations are getting serious about applying analytics to the people side of the business.

Our work with clients over the past decade has taught us that analytics can be enormously powerful, but there are also many pitfalls to avoid along the path to becoming a more analytically-capable organization.

Here are some of the major missteps to avoid:

1.  Using analytics to “prove the worth of HR” – this may well be a byproduct of your efforts, but it should never be its primary purpose.  (If it is, you’ll lose your credibility.)

2.  Assigning responsibilities for analytics to a lower-level technician.   In order for the power of analytics to be realized, it must have executive-level support.  Otherwise, it will degenerate just into another pile of reports.

3.  Believing benchmarking is the same thing as analytics.  For most people-related issues, the actionable insight you gain from analytics completely eliminates any need for generic one-size-fits-all benchmarking.

4.  Confusing data dumps with actual insights.  While the process of analytics can involve lots of data, the reporting of results should not.  Reports should focus clearly on the major findings and implications, with supporting tables confined to an appendix.  No one wants to wade through dozens (or hundreds) of data tables trying to figure out what they all mean.

5.  Allowing the perfect to become the enemy of the good.  We have not yet worked with a client whose data is perfect.  But using the lack of perfection as an excuse for inaction ensures that your HR function will fall behind in analytics.  And analytics is one of the most important developments the profession has seen in the past few decades.

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