Customer Service

Customer-service-woman-on-headset-gives-OK-1024x770We all have our favorite customer service stories. For some of us, it might be lack of scruples of our local automobile repair shop, the horrible services of a restaurant, the cattle herding mentality of an airline, or completely inefficient and disorganized operation of the cell phone store. Regardless of the perpetrator, one bad experience tends to taint our view of that organization and in some cases, the industry as a whole.
Although almost every organization brags about its commitment to customers and their satisfaction, the results vary. NewVoiceMedia recently found that poor customer service results in an estimated $41 billion is loss to US companies. Other estimates place the losses due to poor customer service at approximately $83 billion. Moreover, most estimates of loses predict that they will rise as more consumer behavior arises from social media. Today, more than any other time in history, I can share my dissatisfaction with a product, service, or organization almost immediately. In a matter of seconds, I can post a review or comment that might be read by millions of other potential shoppers.

A recent story in the major media demonstrates the degree of connectivity. Recently, when a customer called to cancel cable service due the need to reduce their family budget, the customer service representative sent the customer to a retention specialist who sought to convince the customer to not reduce their service. When the “specialist” fails to arrive at the desired outcome, he or she changes the billing name of the customer to “A**hole Brown” from Ricardo Brown.

After the customer’s wife complains to a blogger, the story goes viral. A day after, the story is on numerous websites Mrs Brown has the number one story on and does interviews with Fox Business and CNN. All of sudden an inappropriate joke embarrasses the largest cable company in the US. Read more about the events at

What does that really mean?

• What we say and do really matters. Going back to NewVoiceMedia, their study estimates that 93 percent of customers will take action when receiving poor service.
•People have the tools and the motivation to punish those that refuse to provide the service expected. Up to 44 percent of consumers take their business elsewhere when unhappy with the service they receive and 89 percent have done just that in the last year. Almost as damaging, 34 percent have posted a negative review online.
•Customers have been told they are “king” for a long time and now they really are. Once having a negative interaction, 58 percent of customers refuse to buy from that company again and 50 percent would tell friends and colleagues not to use the business either.

What can we learn from these events?

We need to make sure that our staff work from the premise that every phone call, interaction, or concern is the most important thing on their plate. Customer service cannot be a sideline, but a mainline of our business. Even with internal services, the customer is key.

Millennials Revealed

Figure 1: Generations Comparison on Risk
Figure 1: Generations Comparison on Risk

As the workforce demographics change, millennials continue to grow in importance not only as team members, but as leaders. While considerable emphasis has been placed on recruiting and retaining millennials, most organizations still struggle to attract the best and brightest of this dynamic generation. A recent meeting with executives at a client summed up the situation well: “we just want to know what we need to do to make them interested in us.”

One of the struggles underlying our efforts pertains to the fact that millennials are the most studied and analyzed generation in history, yet we still tend toward overgeneralization when describing them. The media and other “snapshot” mediums paint a very one dimensional and simple picture of a non-material, socially conscious, electronically connected, and pampered group.

A recent study of 10,000 millennials by CEB found that the typical stereotypes may be off-base. They reported the following myths and realities based on their research:

• Myth No. 1: Millennials place high value on social media.
• Reality: Millennials use social media, but they do not trust it as much as other sources.
• Myth No. 2: Millennials are motivated by money.
• Reality: Money matters, but not as much as opportunity.
• Myth No. 3: Millennials would rather collaborate than compete.
• Reality: Millennials are the most competitive generation.
• Myth No. 4: Millennials rely on their peers to get work done.
• Reality: Millennials are less trusting of their peers and many prefer to “go it alone.”
• Myth No. 5: Millennials want to jump from organization to organization.
• Reality: Millennials want different experiences, not necessarily different organizations.

What do these results tell us? Basically, millennials recognize the value of opportunity, need new challenges and experiences, seek to standout, and want the freedom to design their own path. By nature, millennials encourage organizations to be more dynamic in their internal and external operations.

A recent, 2014 survey by HCS captures the differences between millennials and other generations when considering workplace dynamism. Figure 1 summarizes the results in a sample of 80 organizations in a variety of industries. In all four categories, millennials possess more of an interest in the cumulative interest of those in other generations. The largest gap between groups appears in job sharing. The latest generation is not afraid to learn new things and to gain new experiences. Participating in high risk projects occupy a close second place in the survey results. Even the smallest difference (learning opportunities) speaks highly of millennials since the level of interest stands out as the highest of the four categories at 78 percent.

What does this tell us? We owe it to our employees and our organization to make sure we are going beyond the simple stereotypes and leveraging the values and attitudes of this key group of team members.

The Danger of Excuses

excusesExcuses make us human. They incorporate our imagination, higher level rationalization skills, desire for acceptance, and propensity for avoiding negative feelings or feedback. All of us have provided an excuse to cover our failure to meet expectations, when circumstances inhibited our best efforts, or the best of plans ends up derailed. In the simplest terms, an excuse is an attempt to lessen the blame attached to our words, actions, or behavior through seeking to defend or justify the resulting outcome. We all fear disapproval from ourselves and others. Excuses arise from our fear of failure, success, embarrassment, or responsibility.

How do excuses work? Excuses involve a rationalization process that works backwards from an outcome to justify the actions or events leading to the embarrassing or threatening outcome. In most cases, the excuse rationalization process begins as soon as we realize we might have to explain our actions to others. As the concern with accounting to others grow, the fear associated with the situation motivates us to identify an explanation that will assist our self-esteem and shift blame.

Most of use acknowledge that we use excuses when interacting with others, but overlook that we make excuses to ourselves just as often, if not more. Just as it is relatively easy to convince someone you did the best you could in an awkward situation, it is that much easier to convince yourself when the other side is not going argue. As a result, excuses directed internally possess more detrimental consequences since they can easily become the primary means to avoiding real change within ourselves. Think how easy it is to convince yourself you are too busy to take care of yourself or too overworked to do a good job. You are telling your closest follower exactly what he or she wants to hear. We have all met talented individuals who have inundated themselves with “could have, should have, and would have” explanations to the point that they are immobilized and unable to reach any of their potential. Consequently, the biggest danger lies in the fact that once we become comfortable with excuses, they send us down the pathway of:

• Less personal responsibility
• Stunted personal growth
• Overwhelming regrets
• Pessimism and lack of self-confidence
• Poor judgment
• Lack of action
• Limited expectations
• Reduced achievement

When dealing with others, excuses, not only undermine our credibility, but also become a crutch that eliminates the need for us to draw on innovation and extraordinary achievement. Put simply, once I have rationalized a challenge, there is no need to determine how I can overcome the situation and still succeed. I recently read a story of a small college that ended up with a perfect sports season. The coach, when interviewed by the national media was asked how he succeeded in beating bigger, faster, and better funded programs. His answer was that he did not accept excuses from his players. He gave an example of when a defensive player was having a hard time keeping with a bigger, faster, and more talented offensive player. The defensive player came over during a break out of breath and feeling beaten. He relayed to the coach how he is just not good enough to complete against the other kid. How did the coach answer? He said, “figure out how to beat him on your terms and think about what you can do.” The coach did not let him rationalize the outcome, but told him to use rationalization to change the outcome.

How do we tell ourselves the same thing? We start by asking ourselves:

• What excuses do I tend to make?
• Why am I making these excuses?
• How do these excuses prevent me from getting what I want?
• How can I beat the excuses?

Naughty and Nice

naughty_niceWe have all dealt with a “naughty” or problem employee. Most of us can close our eyes and remember at least one person we worked with that contributed little, yet stirred up controversy and consumed a disproportionate amount of time of the human resources and management staff. They tend to be disgruntled, suspicious, and apathetic employees that have chronic attendance, performance, and disciplinary issues. Put simply, they really just want to be anywhere, but at work.

Although the naughty come in a variety of types and combinations, two key characteristics provide the most simplistic categorization: internal and external facing. The internal facing problem employee sulks and internalizes his or her anger, unhappiness, and melancholy. The perceived injustices and wrongs committed against them constantly reoccur in their mind and interfere with most other thoughts. Although the person may lash out from time to time or even seek some attention, the norm is to hide and immerse themselves in their feelings. Many times, we refer to these employees as being “broken.”

Conversely, the external type wants the world to know his or her plight and find justification for their feelings by having others “come on board” or accepting their point of view. These employees view their mission as influencing or evangelizing others to dislike certain coworkers, the leadership, or the organization as a whole as much as they do. We have all known people that want to make the world miserable if they are miserable. In the workplace, these individuals have a captive, and in some cases, sympathetic audience to cater to on a regular basis.

Regardless of the type of naughty employee, the cost and impact remains the same: reduced productivity, workplace instability, and morale. The other side of the cost pertains to the rising litigious nature of our society. As a result, avoiding litigation continues to be a constant concern of most organizations. So, what can we do?

Like many leadership challenges, we need to commit to the path we wish to follow. If we desire to have an environment where the impact of naughty employees is minimized, then we should practice the following:

• communicate your expectations for performance and attitude;
• engage employees and provide multiple methods for interaction;
• hire employees that possess the attitude, behaviors, and skills you desire;
• ensure that managers and coworkers are respectful and considerate of others;
• provide a comprehensive employee handbook that details you expectations;
• compensate employees reasonably vis-à-vis your relative market;
• address concerns promptly as they arise in order to demonstrate your commitment to a fair and positive work environment;
• create and enforce a clear attendance policy that addresses absenteeism;
• design and implement a strong performance management system that rewards our desired behaviors and outcomes;
• utilize progressive discipline to ensure that employees failing to meet expectations are warned, reported, and dismissed; and
• ensure that managers know the correct policies and procedures for dealing with problem employees.

These actions will not prevent the occurrence of naughty employees, but it should decrease the number and severity of bad behaviors. Finally, in some cases, it is simply better for the unhappy employee to leave. If the employee really does not want to be there, what is gained by keeping the person in their current job?

Who is Missing?

absent2As we near the holiday season, the temptation to have a “recovery day” or just an extra prep day for holiday festivities becomes greater. Based on a recent CareerBuilder survey, December is the most likely month for employees to be absent. Although one might assume that a few extra days of unscheduled leave matter little to the overall health and productivity of an organization, the reality provides a very different picture. When the average employee fails to come to work, the organization accrues direct and indirect costs.

The direct costs include:
• Wages paid to the absent employee;
• Replacement workers or overtime for present employees; and
• Administrative costs for managing absenteeism process.

The indirect costs include:
• Reduced productivity;
• Poor service or product quality;
• Reallocation of management time;
• Safety issues; and
• Reduced morale among those that have to do more.

Although various researchers and service providers estimate different total costs of absenteeism, all estimates prove substantial.

According to Kronos, the total cost of employee absenteeism averages 35 percent of base payroll when accounting for direct (pay) and indirect costs (replacement and lost productivity). When considering all costs, the percentage grows since administrative costs are not included in the 35 percent. For example, if an organization employees 100 people at $40,000 on average, the average cost of absenteeism is at least 35 percent of $4,000,000 or $1.4m per year.

Circadian’s report Absenteeism: The Bottom-Line Killer places the per employee cost lower with their conclusion that unscheduled absenteeism costs roughly $3,600 per year for each hourly worker and $2,650 each year for salaried employees.

Estimates place the cost of employee absenteeism at approximately $84 billion a year in lost productivity, according to Gallup.

Obviously, if someone suffers from illness, they should stay home more work. However, how often does absenteeism relates to another cause? Almost one in ten employees fail to come to work on the average day in the US.   According to a recent survey from CareerBuilder of 3,103 workers and 2,203 hiring managers and HR professionals, 28 percent of employees call in sick when they are well. Approximately 19 percent stay home to sleep and eleven percent stay in bed due to the weather.

The survey asks about the most ridiculous excuses for missing work. The 2014 list includes:

1. Employee just put a casserole in the oven.
2. Employee’s plastic surgery for enhancement purposes needed some “tweaking” to get it just right.
3. Employee was sitting in the bathroom and her feet and legs fell asleep. When she stood, up she fell and broke her ankle.
4. Employee had been at the casino all weekend and still had money left to play with on Monday morning.
5. Employee woke up in a good mood and didn’t want to ruin it.
6. Employee had a “lucky night” and didn’t know where he was.
7. Employee got stuck in the blood pressure machine at the grocery store and couldn’t get out.
8. Employee had a gall stone they wanted to heal holistically.
9. Employee caught their uniform on fire by putting it in the microwave to dry.
10. Employee accidentally got on a plane.

So, what can we do about those that opt out of coming to work?

• Identify the source of absences;
• Make sure you have a clear policy on absenteeism;
• Use a time and attendance system to keep appropriate records;
• Discuss absences with employees;
• Implement flexible work arrangements when appropriate; and
• Reward the behaviors you desire.

History and Value: Causation

evidenceCausation provides the foundation for action. If we know what event results in another, we can increase the chance of realizing the outcome that we desire. Put simply, causation demonstrates that one event is the result of another event or that a cause and effect relationship is present. When we use analytics for this purpose, the value of the data and its utilization become considerably more valuable. Through analytics, we can test:

• if event a causes event b
• when event a causes event b
• how much event a causes event b

In order to demonstrate causality, we have to meet certain requirements: empirical association, temporal ordering, and non-spuriousness. All three are required to substantiate a causal relationship. In addition, two other factors strength the validity of the conclusion of causality: identifying the causal mechanism and context for occurrence. As discussed in our last post, association occurs when two variables change together. Temporal ordering occurs when the independent variable (cause or factors that influence what we want to explain) changes before the dependent variable (effect of what we are trying to explain). In essence, the cause has to be present to impact the effect. A relationship is spurious when third or confounding variable actually changes the dependent variable. Think back to the shark and ice cream example from our last post. Spuriousness poses a real threat to our analysis since it leads us to identifying the wrong cause. The causal mechanism and context require us to describe the story while identifying other factors.

The most powerful tool for testing causality relates to the experimental design. Most of us probably remember doing experiments in school. The experimental design requires us to come up with a hypothesis or a testable statement of how two variables relate and use the following approach:

• Two comparison groups (experimental group and a control group)
• Variation in the independent variable before assessment of change in the dependent variable
• Random assignment to the two comparison groups

We determine if an association exists between the independent and dependent variables in an experiment when we alter the independent variable.Although an experiment might be ideal, it is rare we have the luxury of human experiments. There are a variety of statistical and mathematical tools that we can use to meet some, if not most of the criteria for causality.

Causal questions come in two primary varieties: effects of causes and causes of effects. For example, if you examine the effects of causes, you might ask if taking aspirin will help your headache. Similarly, if you are concerned with the cause of an effect, you might wonder if aspirin helped your headache when it is gone. Most research utilizes the effects of cause approach or poses a question to address a specific issue or concern.

Causality provides the basis for understanding, modeling, optimizing, and diagnosing the events important to our success. It grants us the ability to:

• Determine the factors that have the greatest impact on performance;
• Predict what will happen when certain conditions are met;
• Analyze why certain outcomes occur and others do not;
• Isolate that factors beyond our influence
• Alter future outcomes

Consequently, within human resources, the ability to determine causation provides the basis for maximizing our resources in our major processes: recruitment, development, performance, and retention. By analyzing how one event impacts another, we are able to isolate the best candidate, environment, and process.

History and Value: Association

numbersAlthough there is considerable value in producing measures, greater rewards result from connecting data with other data. When we compare to two variables or the same variable for two different points in time, greater perspective occurs. Put simply, when we understand which things go together, it simplifies the world around us. By joining things and comparing them, we can form explanations, create typologies, and refine or improve our actions.
The two parts of association that we need to be the most concerned about are comparison and dependence.

Comparison provides perspective by exploring if a variable is the same, greater, less, or within an expected distance from another variable. Comparison typically involves scales or benchmarks. In school, most of us received grades between 0 and 100 on assignments. We could easily interpret our individual scores based on the range of available values and its relative placement. We all recognized the closer to 100, the better the score. Moreover, in most schools, grades tended to be distributed in a predictable pattern (remember all the talk about the “curve”). When dealing with HR analytics, the scale may be known, yet the probability of various levels of attainment may not be. That is where benchmarking comes into play. Benchmarking is the process of comparing one’s own metrics to the distribution as well as the best scores in your comparison group or industry.

A good example with comparison relates to assessing the meaning of the results from measurement or metrics. Let’s assume that our average time to hire is 60 days. How do we interpret our performance? Assuming all things are equal, if the average in our industry is 30 days, we have considerable room for improvement. Conversely, if the performance leaders in our industry average 65 days, we are performing well. As a result, the comparison provides as much value as the metric since it is the basis of interpretation. It is important to keep in mind that benchmarking provides more value than simple measurement, but does not address issues of efficiency of resources, relevance of situations, or other critical factors to success. It is typically a first step in the analytics journey.

The rise of scorecards demonstrates the evolution of comparison. Most organizations today not only track metrics over time and compare them, but also report them in an accessible format for business decision-making. In 2001, David Ulrich captures the essence of scorecards for human resources in his: The HR Scorecard: Linking People, Strategy, and Performance. Drawing on the scorecard revolution initiated by Kaplan and Norton, Ulrich and his coauthors introduced how a human resource scorecard is a mechanism for describing and measuring how people and people management systems create value in organizations, as well as communicating key organizational objectives to the workforce. The factors of comparison include:

• Workforce Success – Has the workforce accomplished the key strategic objectives for the business?
• Right HR Costs – Is our total investment in the workforce (not just the HR function) appropriate (not just minimized)?
• Right Types of HR Alignment – Are our HR practices aligned with the business strategy and differentiated across positions, where appropriate?
• Right HR Practices – Have we designed and implemented world class HR management policies and practices throughout the business?
• Right HR Professionals – Do our HR professionals have the skills they need to design and implement a world-class HR management system?

Although presenting measurement with as strong conceptual focus and based on the strategy map drawn from a visualization of casual relationships within an organization, it only refined out understanding of association, not causation.

Dependence pertains to any situation where multiple variables fail to meet the mathematical idea of probabilistic independence. Independence means that the occurrence of one event does not affect the probability of another event. In plain English, dependence occurs when there is a relationship between mean values. Most of the time, we would look for a linear relationship between two variables, but other types of relationships can be tested for, as well. Keep in mind that one event may not cause the other event, but varies together. In other words, association or correlation does not guarantee causality. Almost every introductory statistics course includes the example of the sharks and ice cream. Most vendors sale more ice cream at the beach during the summer and there are more shark attacks. The two would appear to associated, but it would be hard to blame the shark attacks on the ice cream, even if we assumed that sharks cannot withstand the flavor of a recently “ice creamed” human. There is a confounding variable in the mix; it is summer. Both increase due to the impact of summer and more people are available.

How might we use association? If we build employee profiles that join measurements together, we might find that employees that work with numbers also exhibit a lack of people skills. This would not surprise any of us once we have worked with different type of people. However, by further examining the associations, it might become apparent that those with a lack of people skills tend to prepare less for advancement, but seek it a rate similar to other, more prepared employees. Based on these related variables, we might alter our training programs for those employees.

Next post, we will move on to higher value tools related to causation.

History and Value of Analytics (Measurement)

Figure 1: Analytics Value Contribution
Figure 1: Analytics Value Contribution

Most of us have lived through more than a few fades in our personal as well as professional lives. There seems to be a new “hot” idea or method for leading, managing, or improving every year and they just keep coming. One might argue that new approaches have become a market unto themselves instead of real tool for productive change. Moreover, we live in a time when knowing and using the latest and greatest is a sign of prestige than effectiveness. Although HR analytics might appear to be a fade on the surface, it creates too much value for organizational and human capital management to be the “next big thing.”
This post and others that follow will explore the value of analytics by examining each of the evolutionary steps it has followed. Like most methods of analysis, the value of the actual knowledge gained increases as tool sophistication grows. Figure 1 captures the increasing sophistication and value of analytics as you view from left to right. Measures give us the basis for comparing to standards or benchmarks and provide the first level of value due to our ability to compare our experience to others. Multiple measures drawn from inputs, processes, outcomes grant us the ability to compare movement and relationships. The use of dashboards assists in this effort and provides an easily accessible visualization method as we increase our analytical sophistication. Measuring leads to associating. Once we know what goes together, we can better measure how the movement in one factor relates to the movement in another. These patterns assist with determining causation or factors that serve as prerequisites to change. From causation, we enhance our ability for prediction and take more control of our future.


The current analytics revolution started with establishing the value of measurement through data collection. Once measurement gained the recognition as a necessary element of effective human resource management practice, descriptive methods came more into use. HR functions initiated more surveys, collected data on core processes, and sought to develop metrics to measure outcomes. In 1984, Jac Fitz-enz published How to Measure Human Resources Management and changed the way we looked at human resource outcomes and transitioned data from “nice to have” to “need to know” in most large organizational human resource functions. His work profoundly influenced our understanding of not just the importance of human capital, but also how it could be measured like other operational areas and the value the function provides. In his second edition in 1995, Fitz-enz identified the most critical measures for assessing effectiveness as:

Revenue per Employee
Expense per Employee
Compensation as a Percentage of Revenue
Compensation as a Percentage of Expense
Benefit Cost as a Percentage of Revenue
Benefit Cost as a Percentage of Expense
Benefit Cost as a Percentage of Compensation
Retiree Benefit Cost per Retiree
Retiree Benefit Cost as a Percentage of Expense
Hires as a Percentage of Total Employees
Cost of Hire
Time to Fill Jobs
Time to Start Jobs
HR Department Expense as a Percentage of Company Expense
HR Headcount Ratio—HR Employees: Company Employees
HR Department Expense per Company Employee
Supervisory Compensation Percentage
Workers’ Compensation Cost as a Percentage of Expense
Workers’ Compensation Cost per Employee
Workers’ Compensation Cost per Claim
Absence Rate
Involuntary Separation
Voluntary Separation
Voluntary Separation by Length of Service
Ratio of Offers Made to Acceptances

SHRM provides a nice webpage with many of these metrics as well as the method of calculation (

The real value of measurement is summarized well by Jac Fitz-enz from A New Vision for Human Resources: “To move to the center of the organization, HR must be able to talk in quantitative, objective terms. Organizations are managed by data. Unquestionably, at times, managers make decisions based on emotions as fact. Nevertheless, day-to-day operations are discussed, planned and evaluated in hard data terms.”

HR Analytics: 101

webanalyticsRecently, a few readers have sent questions regarding HR analytics. Like any paradigm shift, the level of understanding, commitment, as well as utilization of these new techniques and tools varies by leader, team, and organization. For those of us that have already “bought into” the idea of using data to model human behavior, the move to analytics makes perfect sense since it offers the next level of explanatory and predictive precision. For those of us that opted to “wait and see,” the time to act appears to be upon us. As markets become more competitive as well as complex, business intelligence not only provides for competitive differentiation, but also significantly increases the success rate of growth strategies. The convergence of affordable technical resources, more accessibility to proven approaches of analysis, and greater understanding of behavior now allow organizations to employ predictive as well as prescriptive tools.

What does this mean for those of us not using analytics already? We are about to join the party. Just as measurement expanded into almost every occupation and industry over the last few decades, analytics continues to expand in a similar fashion. While in most cases, it started as a project or small program in one area of most organizations, it now possesses its own standing. Most innovative organizations have analytics teams or even functions. The next step will be the expansion of analytics into most functions and areas as a regular tool. An interesting article on the continued diffusion and the associated challenges for change management appeared in earlier this month ( Given the importance and growing utilization of analytics, we will spend a few posts discussing what is going on with HR analytics and how they might be useful to you.

As a first step, how do you define analytics? Like many innovations, the strength of the proliferation of the term matches its ambiguity and lack of definitional consistency. Put simply, analytics encompass a set of tools, practices, and technologies utilized to analyze data on customers, employees, or other groups in order to enhance strategic decision-making for improved performance. With the increased availability and accessibility of data, analytics arose as a method of extracting meaningful insight and actionable intelligence in a real-time fashion from this new resource. As a result, the utilization of analytics not only changes the tools we use and the insight that we have, it has changed the way we think about our internal operations and the external environment.

Based on our understanding of analytics, what is the definition of HR analytics? HR analytics encompass a set of tools, practices, and technologies utilized to analyze data on employees or workers in order to enhance strategic decision-making for improved human capital performance. HR analytics focuses us on the human capital element of the organization as well as related processes, behaviors, and outcomes within the organization as a whole. The most valuable contributions of HR analytics allow us to understand how people produce tangible results as well as the factors that lead to positive change in the future. As a result, HR analytics combine the following key elements:

• Methodology for posing human capital-related questions and seeking valid answers;
• Approach for linking data for various sources inside and outside of the organization (metrics, surveys, outcome data);
• Set of statistical techniques for identifying relationships, causation, and potential actions; and
• Standards for quantifying the return on investment in human capital.

Our next post will delve more into the value of analytics and how we arrived at our current state.

Technology and HR:Obserations from HR Tech 2014

HRTechToday, technology shapes every aspect of how we live and work. It affects how we communicate, manage travel, obtain information, interact socially, and coordinate our activities. The digital revolution has reached a point of not only influencing us, but also assisting in defining who we are. The Daily Mail recently reported that the average person looks at their smart phone 110 times a day and up to every six seconds in the evening. Clearly, technology is transforming from being a tool to assist us with life to taking on a more preeminent role in our lives.

Last week, I attended the 2014 HR Tech Conference and had a chance to look and try out a fair number of new tools for automating human resources. Like most big shows in Las Vegas, it contained a full serving of glitz, glamor, and gadgets. You know HR technology has “come into its own” when some of the vendor booths are bigger than my first house and the whole event almost sold out three strip hotels.

As I interacted with various HR professionals, several key observations kept coming up:

HR still covets a “seat at the table”

More than a few presenters mentioned that even with all of the effort and success at adding value in their organizations, HR continues to struggle with “re-branding” or redefining itself as more than a record-keeping and compliance component of the organization. During one session, a presenter asked how many feel that they are a strategic partner in their organization and about 25 percent raised their hand. After more than a decade and a dramatic professionalization of the field, the “people business” still lacks the prestige of other areas in most organizations, namely finance. Among those suffering less from the stigma of the past, a common theme across those successful few related to providing actionable data on a regular basis that decreased costs and improved financial performance. Put simply, organizations that valued HR more received contributions beyond the “typical” HR offerings that affected the financial success of the organization. In other words, it was not enough to provide something new beyond past HR offerings, but the something new had to contribute a clearly quantifiable gain.

Predictive analytics remains more concept than reality for most

Analytics and big data hold a position of preeminence in our field, but most organizations still lack the resources and capability to realize all of the value of this paradigm shift. Most of us have been tracking and analyzing HR metrics for years and have realized efficiency and effectiveness gains in a variety of process areas. However, few have transitioned to identifying more causal relationships or actionable and predictive outcomes. Although monitoring provides a strong basis for developing a plan for action, causality illustrates the most optimal methods of change. With the cost and user complexity of new tools decreasing, more organizations will be able to incorporate higher-level analytics into their business strategy in the near future.

Modeling of human behavior continues to advance

Modeling human behavior and linking the core elements to the associated outcomes stands out as one of the next frontiers of the dig data revolution. While tools for predicting an applicant’s potential success through their skill and personality alignment was innovative a few years ago, new tools allow HR professionals to assess and act on numerous indicators of alignment, performance, and interaction. Furthermore, greater availability of data, increasingly sophisticated algorithms, and affordable analysis tools will only enhance our ability to predict future behavior and outcomes. An interesting example from a presenter pertained to new models that can predict with incredible accuracy how learners will score on a test, thus negating the need for testing when assessing competence. We are only at the beginning of not only better understanding how we work, but also how to maximize who we can be.

I think we can all agree: it is a very exciting time to be in the “people business.”