HR professional competencies vs HR department capabilities

HR should focus on building a capable HR department, according to Wayne Brockbank, who says this approach yields better financial performance and long-term stakeholder value

The 2016 results from the Human Resource Competency Study from the University of Michigan and the RBL Group provide important insights into how to enhance the effectiveness of HR. Among the most remarkable findings is that the impact of the integrated HR department practices has substantially greater impact on short-term business performance and stakeholder value creation than does the competencies of individual HR professionals. To be specific, when compared with the competencies of individual HR professionals, integrated HR department activities have four times more impact on short-term (3 years) business performance and value created for investors, line managers and employees and more than twice the impact on external customer value.

To a great degree, these findings are intuitive. When all HR activities integrate around a few but critical business issues, their impact on business performance and stakeholder value creation makes much sense. Integrating the core HR activities of staffing, performance management, rewards, training and development, communications, and organisation development around the firm’s required capabilities enhances both short-term financial performance and long-term stakeholder value.

“The impact of the integrated HR department practices has substantially greater impact on short-term business performance and stakeholder value creation”

Two obstacles stand in the way.

First, since the emergence of competency modelling three decades ago, HR departments and professional associations have focused considerable attention building HR competency frameworks and models. They have provided training programs and certification examinations that are designed to enhance the skills, knowledge and behaviours of individual HR professionals. Such has been the case for every major HR association around the world.

Given the importance of the growing the number of individual dues paying members, the focus on individual competence development is understandable. Plus individual HR professionals are motivated to enhance their individual competence so as to contribute to their respective HR functional areas and also to enhance their personal marketability.

Continually developing the competencies of individual HR professionals is an important agenda. However, the focus on individual competency certification and development might have a tendency to displace the substantially more important agenda of building and sustaining well-integrated HR departments.

“When all HR activities integrate around a few but critical business issues, their impact on business performance and stakeholder value creation makes much sense”

Second, it is clearly easier to develop skills, knowledge and behaviours for individuals than it is to integrate the disparate parts of HR into an effectively functioning department. Pulling the pieces of HR into a cohesive whole can indeed be a formidable challenge. Each functional area within HR tends to develop its unique logic and approach. They emphasise different time frames with some focusing on short-term business results and some focusing on long-term results. Some focus on output results; other focus on behavioural or ethical inputs. Some emphasise individual performance while others focus on institutional results.

It is, therefore, understandable for training and development, measurement and rewards, organisation development, hiring and promotions and communications might tend to go in somewhat different directions. This tendency is partially underscored by HR consulting firms whose practices frequently focus on functional specialisation rather than comprehensive integration across all HR functional areas.

Regardless of the challenges, the data is clear. The focus within HR should be on building capable HR departments. This is the agenda that should receive the intellectual and operation focus of HR leaders.

4 action items for HR

  1. Recognise that having HR department capability is significantly more important than having competent individual HR professionals.
  2. Have a clearly defined set of business outcomes and organisational capabilities on which each HR functional area can focus.
  3. Regularly examine the shared mission and focus of the HR department and its constituent parts.
  4. Ensure that operational points of each HR functional area are clearly identified, integrated and collectively leveraged.

How important is design thinking in HR?

How does design thinking help HR? Can we re-orient HR designs to get better performance results?

How important is design thinking in HR?

A creative approach to solving a problem that puts the customer's experience in the center is called design thinking. As the HR function is rapidly evolving and adapting to new ways of engaging the workforce, design thinking can be very helpful in figuring out improvement areas in recruiting and hiring strategies. 


“Companies that have already adopted design thinking have a massive advantage over their competitors. HR needs to put themselves in an employee’s or candidate’s shoes to understand how they compare jobs, evaluate positions and apply for jobs to provide better strategies for recruiting and attracting potential candidates.” 

Design thinking was initially used in product design companies only. However, due to technological advances and rapid changes in every field, using design thinking principles has become a game changer.

These are some of the aspects of design thinking that give a simplified path to revamp HR processes to suit the changing workforce dynamics:

  • Human-centric designs

Gone are the days when an institution would decide as per their convenience and needs. The market today offers enormous opportunity, and potential candidates choose according to their preferences. Today, we are driven by a labor market where an employee’s needs, requirements, and comfort are taken into consideration. Any organization that understands what a candidate is looking for has a winning hand compared to their competitors.

  • Collaborative design

Future candidates and current employees play an equally important role in shaping your organization's employer brand. A higher number of satisfied employees ensure better reputation in the market. On your website, if you have your CEO articulate good things about the work environment, it might not be as effective as a video uploaded by your employees who talk about their experiences and the reasons that have motivated them to work hard to grow and stick around for long.


“Knowing your co-worker's feedback and their thoughts about a particular workplace sets an image which might help you pursue a job or search for other opportunities. Any organization that knows its employee and tries to improve their experience, can and will attract more potential candidates.”  

Get your marketing team to help you attract best resources for your brand, which will help you grow in the right direction.

  • Creative problem solving

Creativity is the need of the hour. There are so many new concepts that have been introduced for attracting the right talent - right from Recruitment Marketing, Inbound Recruiting, Social Media Recruiting, Candidate Relationship Management and Data-driven Recruiting. HR has gone through a tremendous transformation from what the recruiting process was five years back to how talent acquisition is now. 

Technology has helped raise the bar to the next level. However, it has created many obstacles as well. Recruits and candidates are more connected and aware of an organization's culture due to social and technological advances. Hence, it is crucial creating best candidate experience, branding strategies and implementing the latest HR technology to attract suitable people for the designated jobs.

  • Prototyping

Experiment with internal recruitment policies. Use different career site controls, videos, employee testimonials, employee career stories and team blogs to attract employees and recruits. Try and keep application forms short and keep the selection process shorter rather than making it tedious. Mix and match different types of questions in an interview that help you understand people's character, knowledge, and experience.

  • Testing

It's tough for an idea to be successful or give you expected results right away. Hence, it is essential to test your plans to see which one gives you the maximum output with minimum cost and effort. Try different strategies which keep employees satisfied while providing quality work. Once the idea is tested and applicable, you can measure time, cost and quality of your organization as well as employees.  As per inc.com companies like Airbnb and Pixar are one of the examples which show the difference caused by design thinking.

Airbnb has changed Chief HR Officer’s function as Chief Employee Experience Officer function, understanding that experience is the essence of any workplace.

At Pixar, The Employees Experience Manager provides outreach, consultation, and support to all. This also led to more face time conversation with managers which helps to understand the difficulties faced by employees and the expectations of the management.

The Truth About Digital HR Transformation

When surrounded by the energetic and inspiring talk of disruption and innovation at day one of UNLEASH London 2018, it would be easy to get overwhelmed and wonder how on earth your organisation is ever going to keep up. Jonas Kjellberg, a co-founder of Skype and disruptor extraordinaire, kicked us off with brilliant insights, hard-won from his failures as well as his successes.

Kjellberg talked about the need to re-imagine our organizations. Yes, some of the well-worn cliches were trotted out about Airbnb re-imagining hotels or Uber re-imagining taxis, but this is a guy who helped revolutionise how we communicate. He used some other examples, such as how Zara doesn’t see itself as a fashion retailer; it sees its business as a logistics operation — “first with the latest.” But he stressed that innovation can’t be achieved piecemeal, or by “three guys tapping away in your basement” while the rest of the organization carries on with business as usual. Innovation needs to become part of an organization’s DNA.

That’s easier said than done, right? In David Wilson’s session in the analysts track, he shared five truths about digital HR transformation. Based on data from Fosway Group’s joint research with UNLEASH, David talked about the realities of how HR is grappling with the changing world of work today.

Attending this event, you realise there is a very real gap between what gets discussed by speakers and the battles HR professionals are fighting back at their desks day to day. Obviously, I work for Fosway but I really believe it’s important to understand this gulf between where organisations are now and where they’re trying to get to in order to support the future of work.

Wilson’s points, summarised in this slide from the presentation, are key to helping HR move forward.

Fosway_UNLEASH London 2018

This isn’t about innovating technology for its own sake, but looking critically at how it can truly enable better business delivery. So video-based virtual recruiting might be cool (38 percent of organisations are already using it), but will it help achieve your talent-acquisition goals? Chatbots (45 percent are looking to adopt these in the next year) and AI are very much “flavor of the month” (although only 12 percent are currently using AI), but how can they support your functional HR shared services? So in plain English, don’t go buy shiny new things and call it innovating it if isn’t going to add anything for your people and how they work (or how you work in HR).

Vendors also have an important role to play here. They are (or should be) in the innovation business. They have R&D teams developing their solutions all the time. But Wilson stressed that they should not just talk about their own innovation. They need to help corporates innovate too in order to be in a position to take advantage of what’s available. And what’s innovative in one context might be business as usual in another, or pie in the sky somewhere else! Driving transformation in large organisations is like trying to turn the QE2 — it’s slower than most people would like. And vendors need to recognise that and support their clients in innovating within their context and constraints. When I tweeted this, a friend of mine who works for a large insurer tweeted back and said “This is so relevant for me right now. Don’t show me shiny stuff, help me solve my problems!”

So if organisations can be honest with themselves about where they are now and where they want to be tomorrow (and potentially re-imagine what they do as Kjellberg said in the keynote), and vendors can support them with solutions that tackle genuine business issues and innovate at a realistic pace, maybe we can close that gap after all.

The full slides from David Wilson’s presentation can be downloaded here.

How Your Hiring Process Could Predict Unethical Behavior

How do you really get to know another person? More specifically, how do you know what type of employee that person will be? To help answer this question, many firms have incorporated personality tests into their applicant screening or employee training and development processes over the last several decades. According to a 2015 analysis by the Society for Human Resource Management, such assessments — of which there are thousands — combine to create an industry with annual sales of US$500 million.

But as Taya Cohen explains it, one of the critical problems with many personality tests is that they overlook moral character. Cohen, an associate professor of organizational behavior and theory and the Carnegie Bosch Junior Faculty Chair at Carnegie Mellon’s Tepper School of Business, argues that this should be a concern — because moral character is the aspect of personality that can best predict ethical behavior. Moral character encompasses several traits that influence people’s conduct and interpersonal interactions: Someone who is guilt-prone, for example, is more likely to demonstrate empathy, to be a team player, and to learn from his or her mistakes.

In the small window during which employers and job candidates become acquainted, a significant amount of information is exchanged. Some of it is visible and obvious, some of it is hidden from view; some of it is critical, some of it is noise. Cohen, who earned a Ph.D. in social psychology from the University of North Carolina at Chapel Hill, looks for ways to help companies sort through the data to reveal how people are likely to perform on the job. And that’s something the personality test your company is using today could be missing or, worse yet, getting wrong.

S+B: The concept of moral character is central to your research. Can you define moral character, and how it can shape job performance?
 Moral character is a broad dimension of personality that captures a person’s tendency to think, feel, and behave in ethical ways. It subsumes a number of more specific traits. For example, guilt proneness is an important moral character trait. People who have high levels of guilt proneness have a strong conscience — they feel guilty when they make mistakes or let others down. Moreover, they can anticipate this [feeling] and take proactive steps to avoid behaving badly in the first place. In my work, I have demonstrated that employees with high levels of guilt proneness have better job performance.

There are implications here for leaders, too. I like this quote by the psychologists Robert Hogan and Robert Kaiser: “Who we are determines how we lead.” Leaders who are more guilt-prone are seen by their subordinates as more effective. One of the reasons guilt proneness is such an important character trait, and the reason it is associated with more effective leadership, is its link to a sense of personal responsibility: “I wouldn’t want to let people down, and I’m personally responsible for doing the right thing, for helping my team, for not free riding on others’ contributions.”

S+B: Guilt proneness was the theme of an earlier body of your work. Can you talk more about that?
 In 2011, my colleagues and I developed the Guilt and Shame Proneness Scale. A person answers questions about different hypothetical scenarios in which they have done something wrong, indicating how likely it is that they would respond in the way described, from very unlikely (1) to very likely (7). The scale measures their tendency to anticipate that they would feel guilty or ashamed. If you imagine you did something wrong, to what extent would you feel bad about your behavior? This is guilt proneness. To what extent would you feel like a terrible person? This is shame proneness. The difference between feeling bad about your behavior and feeling that way about yourself more generally is important, because it can lead to different behaviors.

Leaders who are more guilt-prone are seen by their subordinates as more effective.

I discussed some of the behaviors associated with guilt earlier. Guilt tends to be a healthier response than shame, and it’s linked more closely to moral behavior. Shame is a much less healthy emotion. If you feel ashamed of yourself, it tends to lead to anger, avoidance, or even depression and anxiety in some cases. This is because these feelings are not focused on your behavior; they are focused on who you are as a person. Shame tends to lead to more self-centered responses, which lead to less moral behavior.

S+B: How has your thinking about how to assess people’s moral character evolved?
 People are able to talk about themselves when asked survey questions [as in the Guilt and Shame Proneness Scale], especially in settings where there’s no incentive to misrepresent oneself or others. But you can imagine that in organizations, especially when we think of a hiring context or other high-stakes contexts, people might be motivated to hide certain aspects of themselves. As a result, there’s a need to find more indirect ways to assess a person’s character.

That is where some new research I’m working on with a former doctoral student, Yeonjeong Kim, comes in. We are accumulating evidence showing that moral character can be accurately judged from open-ended behavioral interview questions. Our work in this area is informed by a theoretical framework Yeonjeong has developed called the hidden information, distribution, and evaluation model, or HIDE model for short.

At its highest level, this model separates perception into two rating sources: the self and the judge. In other words, there’s some information that I know about myself and am able to accurately describe, and there’s some information that other people might know about me that they’re able to accurately share. But then there’s also information that I — or other people — might be unaware of or be motivated to conceal. This model helps us think about how to piece together all of this visible and invisible information about a person, to get an accurate picture of who that person is.

S+B: Can you give us a couple of examples of these interview questions?
 Yeonjeong and I, along with Abigail Panter of the University of North Carolina, have come up with two questions that we think are particularly helpful for revealing a person’s character. These questions are modeled after questions that interviewers might already be using. Our contribution is to show that these questions can be used to accurately gauge respondents’ moral character.

One interview prompt is what we call the mistake question: “Please tell us about a time when you made a mistake at work. How did you feel when this occurred? What did you do? What, if anything, did you learn from this experience?” This series of questions is good at tapping into a person’s conscientiousness, which is one of the primary traits that integrity tests attempt to capture. People who are high in conscientiousness work hard toward their goals and they don’t want to let themselves and other people down. People low in conscientiousness often do sloppy work and can come off as lazy or irresponsible because they lack the industriousness that highly conscientious employees have. Accordingly, in organizations, conscientiousness tends to be a very positive trait that helps people avoid unethical behaviors and perform better at their job overall.

Another prompt is what we call the dilemma question: “Please describe an experience in which you were faced with a difficult dilemma at your job, a situation where you found it hard to decide what to do. What factors did you consider? What did you do? What, if anything, did you learn from this experience?”

This series of questions is good at revealing guilt proneness. As we’ve discussed, people with high levels of guilt proneness have a very strong sense of interpersonal responsibility and they are very empathic. They think about other people when they make decisions and are very cognizant of the impact their actions have on others — leading them to act in more moral ways. And the opposite is true: Those who think narrowly about themselves and their own self-interests, and who don’t consider the interests of others, tend to be more selfish, more Machiavellian. They tend to have lower levels of guilt proneness, and lower levels of moral character more generally.

S+B: What if people are disingenuous when participating in these assessments, telling the “judges” what they think will make them look good?
 Interview questions and surveys are not immune to faking. But interestingly, even when people try to fake their responses to look good, they often reveal subtle cues about their true character.

Even when people fake responses to interview questions to look good, they often reveal subtle cues about their true character.

For example, one interview question that we’ve tested in our work is a standard question about how a person’s current or former employer would describe him or her. And people usually say very positive things: “My employer would say I have the following good qualities.”

What’s been revealed by our research is that even though people say positive things in response to that question, people who are low in moral character often come across as boastful and self-centered. Whereas those with high moral character may also answer the question in a positive way, but come across as more considerate of others, more modest or humble. Information about a person’s moral character “leaks out” in response to certain types of behavioral interview questions. And the more a person tries to make himself or herself look good, the more information about character leaks out. We are still investigating the nature of the cues that are revealed in interviewees’ responses, exploring whether it is the content of what they say, or the manner in which they say it that is more revealing.

S+B: What are the implications of your research on the use of personality tests in corporate hiring practices?
 Organizations already use a lot of integrity testing and personality assessments. And I think we’re moving further in that direction as more data about employees becomes available. Of the many assessments out there, some are very good, and others less so. No assessment measure is perfect. And if no assessment is perfect, then there are bound to be mistakes: people who take some kind of personality assessment that says they’re not suited for a job, but in reality they are. Or maybe it looks like they’re not the most ethical person, even though they are, but for whatever reason, the test missed that.

At the same time, if we’re not using some kind of standardized instrument, what are we doing instead? And is that better or worse? If we don’t use some kind of standardized test, often we use our gut impression. I would argue that such impressions are often susceptible to all different sorts of biases. For example, we tend to like people who are similar to us, and we might assume if they’re similar to us, they must be good people. The less standardized the evaluation method, the more that stereotypes and biases will creep in.

Biases and subjectivity can certainly creep into our evaluations of interviewees, even when we do use standardized interview questions and evaluation rubrics. However, the potential for problems is mitigated when there is more structure in the interview process, such as when the same assessment method is used for all candidates, rather than idiosyncratic protocols for different candidates.

From the manager’s perspective, if you understand an employee — who they are, aspects of their personality, their character — then you can use information about their personality to optimize their performance by developing individualized plans of action or individualized ways of helping them be successful. For example, if you’re doing some kind of intervention in an organization, can you use these measures to check whether the intervention is having the desired effect? These are areas where we’re going to see a lot of developments in the near future as we continue down the path of big data and people analytics.

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AI in HR – how to understand what is happening

There is a considerable buzz these days about so-called ‘AI in HR’. Most vendors are claiming to have some sort of machine-learning within their products and some are making claims that, from the perspective of someone who has been doing this for the last 15 years, seem unlikely.

Understanding what these new technologies can (and can’t) do is vital if HR is able to evaluate purchasing them, or work with their internal teams in designing, developing and deploying their own approaches. Analytical literacy is rapidly becoming a core skill of HR.

Algorithms are free

Many of the technology vendors will market their products as having some amazing, unique algorithms. In almost all instances this is unlikely.

One of the remarkable trends that we’ve seen over the last years is that the big technology companies have acquired large teams of the best data scientists and have been publishing new algorithms in journals, often open-sourcing code at the same time.

Pretty much everyone is using these algorithms – and in many instances much earlier developed ones – as the basis of what they’re doing. They will almost certainly be combining them and changing settings but at the heart we should assume the same freely available building blocks.

What is needed is great training data

In contrast to algorithms being free, data is not and as such is what differentiates decent from great analytics efforts. This matches the message that we always tell clients – to improve early analytic results there is usually a need for better data, not better algorithms. It’s why we built Workometry – to make the collection of the great-quality data as easy as possible.

In 2014 I wrote an article describing the 5 types of HR Analytics vendors. In it I described a category which I called the ‘data aggregator’. This was a firm who, by collecting vast amount of cross-firm, individual-level data were able to build valuable analytics offerings.

In 2018 pretty much every SaaS HR offering is trying this model. In many instances the data doesn’t really have enough value (there is a lot of it, but it’s not really that rich – most survey providers could be put in this category). However some vendors will find true value in this approach.

This data becomes a barrier to entry for new firms wanting to enter the industry – it’s hard and costly to acquire. It’s a good reason why many of the most innovative HR analytics start-ups are in recruitment. In recruitment far more data exists outside the firm in public data sources.

General AI is a long way off

When vendors talk about AI in their product to the lay-person they often conjure-up images of technology that has near-human levels of reasoning. Most data scientists would tell you that this reality is a long way off.

One of the interesting aspects of machine learning techniques is that it can solve some tasks that we humans might find difficult (playing chess for example) yet it might struggle with tasks that even a 4 year old could achieve easily. I suspect that we’re close to developing an autonomous van which can take a parcel from the depot to your house but it might be harder for a robot to take the parcel from the van, up the stairs, enter the building and find the correct letter box.

What today’s current approaches can do is solve certain, well defined problems, usually with lots of available data with extraordinary levels of accuracy. Often, the narrower the problem and the greater the data size to learn from, the more accurate the prediction. These narrow problems are often described as ‘Specific AI’.

Benefiting from Specific AI

Take the example of text analytics. Even within text analysis there are different firms in the HR space doing wonderful things. TextKernel has developed very good approaches to understand CVs and Job Descriptions. We, through our Workometry technology, have probably the leading approach to understanding the answers to open questions (for example in employee suggestions or feedback). We even go so far as building specific models on the organization / question level (arguably our key differentiator is how quickly we can build these models). With such specific models we can out-perform skilled humans at this task in a fraction of the time / cost.

We can think of the implication on work of AI / robots therefore not as automation taking away whole jobs – as most jobs require a variety of tasks, but of AI automating specific tasks. These will be the ones with a lot of repetition or where large volumes of data need to be acquired and synthesised.

When thinking of how to apply AI it’s important to therefore break a job down to tasks, ideally the smallest, most specific tasks possible and identify which are candidates for AI. At the same time we need to identify the value / cost of these tasks to identify which are worth developing solutions to automate.

When doing so we shouldn’t constrain ourselves to tasks that we’re currently doing. Many tasks are possible without AI, but prohibitively expensive. For many firms the sort of text coding Workometry does has been too expensive and time-consuming to perform. For many of our clients Workometry is 10x cheaper & 200x quicker than the alternative solutions and is of higher quality. What was difficult to justify therefore becomes attractive.

Benefits from AI

There are 2 key drivers of benefits from using so called ‘AI’ in HR:

  • To improve a business driver (eg productivity, customer experience) and by doing so enable the business to achieve better results
  • To reduce cost of of delivering HR.

In many instances the first is likely to provide opportunities to realise a greater return to the business, however it is also likely to require greater & more wide-spread buy in to results. Implementation costs and risks are likely to be higher with a greater number of uncertainties influencing the end deliverable.

With this type of analysis it’s highly unlikely that the data needed will be residing in one system or database. Given this we can expect fewer instances where a single system provider will have enough data-coverage to be able to build a complete model. The best work in this area will remain the preserve of data-science teams within a firm who can identify, process and join the necessary data sources into a reliable model.

Cost reduction for HR will ultimately be easier for predicted results to be achieved. In many instances there will be a smaller number of decision-makers (the HR leader) and it’s likely that cost reduction will be a core part of their objectives. Data for this type of analysis will be easily available and more likely to be of high quality / have less measurement error / to be more complete. It will also be more likely to reside in one system. In the medium term we can expect system providers to deliver such capability.

Some points getting the most out of AI for your HR team

  • A little knowledge will go a long way. Think about up-skilling your team so that they have a good understanding of where AI can be deployed in its current state and what the likely benefits are. Several providers (including us) can help here
  • Don’t expect system providers to provide complete solutions where they don’t have access to all the data. There will be a need for the foreseeable future to build good People Analytics capability
  • People Analytics technology won’t solve all your problems, but it might remove routine tasks from the People Analytics team, thereby enabling them to focus on higher-value tasks. Think of these solutions as complements to building capability, not a replacement
  • Challenge your technology vendors (especially if you’re a key client) to develop solutions that can identify cost improvements. With all the transaction data they should be identifying efficiencies. This will soon be a hygiene factor for systems providers
  • Often simple models can be built quickly. In a drive for accuracy you hit decreasing marginal returns pretty quickly. How much more valuable is this solution than what your team could build in 10 days?
  • General models, built on other firms data is unlikely to perform as well as specific models built on your data.

It’s Time for HR 3.0

Today we find ourselves in the middle of a turbo-charged version of Britain’s Industrial Revolution. Since the late 1970s in the U.S., GDP per worker has pretty much doubled, but average real wage is still exactly the same. All the signs are that this disruption is only just beginning. A recent report by the McKinsey Global Institute forecasts that by 2030 around 15 percent of today’s work activities may be automated and between 75 million and 375 million workers will need to shift occupational categories. My colleagues at MGI outline four priorities for policy makers and business leaders as they adapt to this disruption: Economic growth, skills upgrade, fluid labor market and transition support. The role of human resources is key in at least three of these priorities. But right now HR is nowhere near ready for such a massive change.

Don’t get me wrong — HR hasn’t been standing still. If we go back to the 1980s and before, HR could be described as a wholly administrative and industrial relations function — HR 1.0 so to speak. In the 1990s, an increasing awareness of the value of talent to organizations transformed the HR function into more of a business partner, with increasing professionalization of the field and greater use of analytics for reporting purposes — HR 2.0. But to navigate the increasingly complex world of talent, HR needs to grow more quickly into a strategic adviser. More companies will need CHROs, and they will need to have an equal voice alongside CEOs and CFOs in the most critical business decisions. In the coming decades of disruption, the management of talent will become the main differentiator of high performing organizations. This requires HR 3.0.

The CHRO of the future will need to preside over a function that is fundamentally better prepared in three ways. Firstly, HR 3.0 will be much more analytically sophisticated; people analytics and data driven decision-making will be at its core. Secondly, the HR 3.0 function will be more agile and more efficient, with fewer silos, swim lanes and specializations and a greater ability to deploy HR professionals flexibly across the human capital spectrum. Finally, to enable a more data-driven and agile operating environment, we will need the HR 3.0 professional, with skill sets more oriented around business acumen and problem-solving skills and less dominated by focused customer service and process management capabilities, both of which are themselves targets for future automation.

Practicing People Analytics

People analytics in particular has had a head start on the other elements of HR 3.0. The need for more sophisticated analytics around human capital first entered the business consciousness around 2010. Much excitement has been generated around the topic in recent years, often by data and technology that stand to benefit from a growing interest in this space. In the course of a decade or so, it’s fair to say that HR analytics has come out of the dark ages. Recent research by Bersin by Deloitte shows that over two thirds of organizations now believe they can generate solid reporting and have a consistent approach to the use of people data. While that’s certainly progress, it’s not very rapid progress. A recent study by the Corporate Research Forum concluded that more than half of organizations were very limited or worse in their ability to use talent data to predict and improve business outcomes.

For HR 3.0 to take hold, it is critical that people analytics can get to a point in organizations where it can help link talent to value. This will require much more than recordkeeping systems and dashboards. It will require a strong understanding of how talent dynamics can affect outcomes like recruiting, mobility and retention. It will require creative use of internal and external data. It will require a variety of domain expertise, such as statistics, organizational psychology and epidemiology. It will require integrated data across the employee life cycle and strong engineering of that data.

RELATED: 4 HR Analytics Trends to Follow in 2018

The Bersin report also concluded that more organizations now have a people analytics team than do not — an important watershed moment for the field. In reality, however, the majority of these teams have not moved past very basic reporting around simple measures like headcount, attrition and employee engagement. Examples of more advanced people analytics teams do exist and serve as good examples of how to enhance the impact of people analytics in organizations. At McKinsey, we have made substantial progress in understanding individual skills and better matching them to roles, as well as understanding how talent factors such as diversity, connectivity and engagement can influence attrition, retention and other outcomes. At Google, the people analytics team has built a sophisticated understanding of high-performing teams, concluding that the team environment is more important that the individual constituents of the team. At Microsoft, creative use of email and calendar data has revealed the daily behaviors of effective managers.

There are others, too, and these more developed people analytics groups have a few things in common. They were birthed in an environment where a data-driven approach is part of the prevailing culture. They are resourced well and are well positioned in the organization to drive impact. They include a broad mix of skills including data scientists, organizational psychologists and “translators,” who act as data-savvy “account managers” for critical projects and use cases. It would be wise for CHROs to look to these organizations for inspiration as they try to embed analytics in their functions.

The New HR Function

Efficiency and agility will be critical to HR functions operating in a more unpredictable and complex talent market. Traditionally, leaders have considered it a more or less binary choice to have either a stable, predictable, efficient and lean function or a more well-resourced, dynamic and nimble function. There is no longer a choice to be made here; there is an increasing expectation to deliver on both.

HR leaders, like those in many other functions, need to embrace automation and process efficiency to create a lean backbone of critical administrative and process management functions, while cultivating a dynamic, nimble team that can apply itself to varied talent-related problems across the organization. The HR 3.0 function will more or less be comprised of 50 percent fixed staff — back-office shared services enabled by advanced automation, senior account managers, subject matter experts — and 50 percent “pooled” HR professionals who have the skills and business acumen to be deployed broadly.

A new breed of HR professional is required in substantial numbers to make all this happen. The successful HR 3.0 professional will be data-driven, business savvy, comfortable with unpredictability and ambiguity, and capable of thinking and communicating strategically. Pay scales will need to adjust to attract this caliber of HR professional, MBA programs will need to invest more time in human capital subject matter, and more teachers, professors and practitioners will need to contribute to building this new class of professional.

HR 3.0 is an exciting and challenging prospect, but one which is critical for the future of work. It’s a big step to take for a function which until not long ago was mostly administrative and back-office oriented, but it is also the final step in bringing talent strategy to the top table in companies and organizations. The first to move to HR 3.0 will enjoy substantial advantages in the rapidly changing talent marketplace we find ourselves in.

Keith McNulty is head of people analytics and measurement at McKinsey & Co. in London. To comment, email editor@talenteconomy.io.