MCBASSI & COMPANY

How to Become Better at HR Analytics

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In many HR departments, the heat is on – or soon will be.

Senior executives are increasingly demanding that HR provide actionable insights for driving better business results through targeted improvements in the management and development of people.

The insights that are now increasingly expected from HR go far beyond traditional HR reporting on headcount, time-to-fill vacancies, and employee engagement benchmarking.  Instead, there is a growing demand that HR provide analysis about how to cost-effectively improve outcomes such as the following:

  • Sales productivity
  • Customer service
  • Managerial effectiveness
  • Employee well-being
  • Workforce diversity and inclusion

It’s clear: the bar is being raised quickly.  So how do you get from where you are currently to where you need to be?

In the end, advanced HR analytics capabilities can’t just be parachuted into your organization – you have to build it through the following steps:

1.  Create organizational and broad-based executive support by beginning to produce insightful, succinct reports and analyses.  Ensure they’re presented from an executive’s perspective – not HR’s.

2.  Develop an analytics strategy that’s aligned with your organization’s overall business strategy.  This should lead to the production of business intelligence and actionable insights that help leaders at all levels in your organization drive better business results through focused, targeted and achievable improvements in the management and development of people.

3.  Grow the size and skills of your analytics staff within HR (or find a trusted external analytics consultant).  Don’t focus exclusively on technical skills.  The business acumen, collaboration, consulting and presentation skills of your analysts (and HR generalists!) are all critical elements as well.

4.  Expand the scope of your HR analytics initiatives to encompass all of the essential aspects of people management and development.  This includes the following:

  • Recruiting and onboarding
  • Learning and development
  • Performance and career management
  • Rewards and recognition
  • Engagement and retention

Where to start?  If you’re like most HR departments, you have limited resources, but your executives have high expectations.  So you need a plan that enables you to focus on the right things and to get them done in the right order.  And that, of course, will be shaped by your organization’s current HR analytics capability.

So we’ve designed a quick (and free!) online assessment tool to objectively measure your current level of HR analytics maturity along with recommendations on the most important areas for focus in light of your relative strengths and weaknesses.  The assessment takes fewer than 10 minutes to complete, so why not give it a try right now? Click here to begin the analytics self-assessment.

We hope you find it useful.  And if you’d like to have a quick call to discuss your assessment and feedback and think through next steps, don’t hesitate to be in touch with us. We’d love to hear from you!

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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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Why HR Analytics? A Look at the Numbers

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There’s a lot of buzz around HR analytics.  Advances in software, newly-available data sources, and how-to manuals have made it easier than ever to dive right into HR analytics.

This month, we thought we’d take a step back and ask “Why?”  Why should organizations care about this?  Why should executives be devoting more time to people matters than they’ve ever done before?  And why should HR professionals be learning the necessary new analytic skills?  Looking at a few numbers helps to answer those questions.

Let’s start with intangibles – organizational assets that are not physical in nature.  Intangibles include intellectual property, knowledge, reputation, etc.  These sorts of assets represent an ever-growing percentage of the average organization’s market value, increasing dramatically from 9 percent of market value in 1980 to 65 percent today.

And what do all forms of intangibles have in common?  They’re created by people.  A few decades ago, if you wanted to increase your company’s value, you focused on managing your physical assets – plants, equipment, etc.  Today, if you want to increase value, you need to manage your people – your human capital.

This, more than anything else, explains why analytics is now an essential HR competence.  Executives and boards of directors are always focused on company value.  Today, that means they need to be focused on their people.

Some companies recognized this earlier than others, and some companies have done a better job managing their people.  How have those companies fared?

Extraordinarily well.

A Boston Consulting Group study from 2012 found that companies appearing on the Fortune “100 Best Companies to Work For” list at least three times in a ten-year period cumulatively outperformed the market by an average of over seven percentage points per year for ten straight years.

And our own live portfolios, through which we’ve invested in a basket of companies that invest in their employees and/or embrace Good Company principles, have outperformed the market by an average of almost eight percentage points per year for twelve years running.

All told, the numbers certainly support the world’s current fascination with HR analytics – and suggest that focus will continue to intensify in the years to come.  Are you on board?

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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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