Archives for April 2013

New HR Software Tries to Assess Productivity

No matter where they sit, employees at DeskTime have a grand view. Full-length windows at the company’s headquarters give a panoramic vista of downtown Riga, Latvia, about 5 miles away.

The ability to see at a distance is a metaphor for DeskTime, whose time-tracking software gives companies a window into employee productivity. DeskTime represents a new twist on conventional time-and-attendance software used for administrative and pay purposes.

DeskTime’s automated software collects and updates information in real time, such as the number of employees at work, how many are absent or outside the office—even who appears to be slacking off.

More important, it offers a measurement of productivity by sorting a company’s commonly used applications into three broad categories—productive, distracting and neutral—and monitors which employees access them and for how long. The resulting data are presented in graphs and charts in a dashboard format that is visible to managers and every employee.

DeskTime’s software collects fine-grained data, too, such as the time an employee clocks in or out, the percentage of time spent on productive tasks, and the period of time during the workday when the employee is most productive.

The system eliminates manual entry of time-and-attendance data. “You set it up once and don’t have to touch it ever again,” says the company’s CEO, Julia Gifford.

Software to track employee hours, provided by big vendors such as Kronos Inc. and Oracle Corp., has been around for years. Closely related are vendors of keystroke-monitoring software, which typically includes a surveillance feature to ensure employees don’t break company rules on Internet use.

Crowded Field

But DeskTime is part of a new breed of human resources vendors whose applications focus more on productivity than compliance. Among DeskTime’s rivals in this category are New York-based Harvest; TSheets of Eagle, Idaho; Seattle-based RescueTime; and Toggl, a startup based in Estonia, in Eastern Europe.

The potential to monitor employees minute by minute conjures up Big Brother, but DeskTime wasn’t designed for snooping, Gifford says.

“We encourage clients to leverage the information in a way that motivates employees to boost their performance and productivity. They need to be transparent and let employees know why the software is being used and the type of data it is collecting,” Gifford says.

Some customers have asked about more invasive features, such as screen captures and keystrokes, “but we’re just not comfortable with that.”

Companies have reason for concern over how employees use their time. Between 60 percent and 80 percent of workers spend time “cyberloafing” on the job, despite company policies that forbid it. So says a study to be published in May in Computers in Human Behavior, an academic journal.

The goldbricking results in lost productivity and exposes companies to potential legal risks, according to the report by associate business professors Joseph Ugrin at Kansas State University and John Pearson at Southern Illinois University.

The professors’ findings echo a survey of 3,200 workers last year by Salary.com. It reported that nearly two-thirds of employees acknowledge visiting nonwork-related websites each workday.

On the flip side, measuring productivity is an inexact science, especially in the case of knowledge workers. Rather than spending time in a productivity application, an employee might reflect on improved product features or a clever marketing campaign—work that won’t be captured merely by reading a graph.

The trick is to use these tools in ways that benefit employees, says Mary Ann Masarech, a lead consultant with BlessingWhite Inc. “Time-tracking tools can support engagement if they actually help people in their jobs,” such as enabling a project manager to track margins or assess if the time spent on the project is worth it.

“If the tool is only used as a policing device, then it can become a business practice that undermines engagement,” Masarech says.

There are situations in which employers are limited in their ability to monitor employees or prohibited from doing so altogether. Union contracts, for example, may restrict an employer’s monitoring while public-sector employees may have limited exemptions under the Fourth Amendment, according to Privacy Rights Clearinghouse, a consumer advocacy group based in California.

Growth at DeskTime

None of that really came into play when the idea behind DeskTime was first conceived, Gifford says. Before it was marketed as DeskTime, the software was used internally to track employees’ time and attendance at Draugiem Group, a business incubator and creator of a Latvian social network. Draugiem has launched more than 15 startups in Latvia, including DeskTime in 2011.

Draugiem Group has expanded rapidly to more than 100 employees, making it difficult for its makeshift human resources function to keep pace. “We realized at Draugiem that if we were having trouble keeping track of employees’ time, then other companies probably were having the same problem,” Gifford says.

DeskTime developers later added functions to enable companies to do more than capture data on time and attendance, Gifford says. The company, headquartered in Riga with U.S. operations in Santa Monica, California, says its software has been licensed to about 90 companies globally, encompassing 12,000 users.

Among the customers is Fueled, a New York-based company that builds interactive mobile Web applications. It uses DeskTime’s reporting feature to generate a daily productivity report that gets emailed to employees.

The purpose is to get employees to compete to be the most productive, says Rameet Chawla Fueled’s founder and CEO. “It lets the entire team see who is working most productively. It’s more of a higher level thing to increase our overall production.”

About the Author:

Garry Kranz is a Workforce contributing editor. Reprinted from Workforce

Filed Under: Articles Tagged With: , , ,

How Do People Learn Best?

Top MBA programs don’t load their students down with books of rules and abstract theories that may or may not have any bearing on the real world. Instead, their central tool is the case study method: real-life examples with all the complicated push and pull of the actual business world. Case study learning puts the next generation of leaders in the driver’s seat with skin in the game as they work to answer the foundational question in business education: how would you make this decision?

Case study learning is the best tool in business education. The only place people learn better is the real world itself. But out in the real world, few leaders make use of the incredible opportunities that real-life cases of day-to-day business offer their team members to learn and develop. That’s because, in most organizations, a handful of leaders make the vast majority of decisions. After all, isn’t that a leader’s job?

But when leaders make all the decisions, those decisions aren’t always the best. Leaders aren’t closest to most situations. They don’t always understand all of the factors and personalities at play. They aren’t the most affected by the consequences. When leaders make all the decisions, the organization loses a great deal of the perspective and creativity of the people who understand the situation best.

Perhaps even more important, when leaders make all the decisions, the organization misses out on the opportunity to develop team members through on-the-job, skin-in-the-game, case study learning.

During my tenure as co-founder and CEO of AES, a Fortune 200 global power company, and then as co-founder of Imagine Schools, one of the largest nonprofit charter school networks in the U.S., we pioneered pushing decision-making down deep into the organization. The approach served as a massive learning and development initiative. We didn’t just pass off decisions to people and then leave them unsupported. We implemented all the best elements of the case study method into our day-to-day business. As a result, we developed leaders and experts at all levels of our organization.

Our crucial tool for learning and development is the decision-maker process. It’s based on a set of basic assumptions about our people: that they’re unique, creative thinkers who like a challenge, want to contribute and are able to learn. But it’s got one more assumption: they’re also fallible. That’s true of everyone in the organization, both leaders and team members. Just because you’re on top doesn’t mean you can’t make mistakes. And in the decision-maker model, leaders still lead. Here’s what it looks like:

• The leader chooses someone to make a key decision.
• The decision-maker seeks advice — including from the leader — to gather information.
• The final decision is made not by the leader, but by the chosen decision-maker.

The real learning and development begins during the advice process, which requires the decision-maker to seek out people who have had experience with similar issues. It also requires that the decision-maker consult people in different positions, because people see different things from different perspectives.

The decision-maker asks a leader, a peer, someone who works in a position below him or her in the hierarchy — and if circumstances warrant, experts from outside the company. In the process, the decision-maker becomes an expert on the issue, and not only does the individual develop personal skills, but a deep bench of experts and leaders are created.

Dixie Benny, senior organizational development consultant at Providence Health & Services, said “on-the-job learning, with experienced leaders teaching leaders, is the single most effective approach to increase leadership capability. We dramatically boost productivity and employee engagement by supportively enabling decision-making at the lowest possible level in the organization. The result is a flexible, nimble organization poised to respond quickly to rapidly changing business conditions.”

The decision-maker approach creates a culture of learning that turns the organization into a more powerful engine of education than the top business programs in the world. It uses the same tools those programs do, but with a crucial advantage no business school can provide: the all-important context of real consequences in real life.

Reprinted from Chief Learning Officer

Filed Under: Articles Tagged With: , , , , , ,

When It’s Not a Knowledge Problem

For me, the most interesting instructional design challenges are the ones where it’s not a knowledge problem. If simply giving people information resolves the challenge, problem, or opportunity, then that’s pretty straightforward, and we have a lot of tools to use for that.

I’m most interested in the situations where the person knows the right thing to do, but doesn’t do it for some reason. Is there anything instructional designers can do to help with that? For example, most people know that texting while driving is bad, but they still do it. Why is that, and what can we do about it?

One of the interesting theories is the idea that people can know something intellectually, without believing it viscerally, and that can impact their behavior.

Can visceral experiences change behavior?

A really interesting study that the Virtual Human Interaction Lab at Stanford conducted recently used virtual reality to look at the influence of a visceral experience on behavior. While I think it would be extremely problematic to generalize practical application from this single study, it’s worth taking a closer look at the findings in this case.

Cutting down virtual trees

The study looked at the result of learning about the negative impact on deforestation of using non-recycled paper goods. They gave both groups in the study substantive information on the use of non-recycled paper products and deforestation problems. They learned how much toilet paper a single tree could produce, and how many trees needed to be cut down to provide toilet paper for a single person.

In one group, participants were asked to read a vivid account of the physical act of cutting down a tree, and to mentally imagine they were doing it (the “mental simulation” condition).

In the other group (the “immersive virtual environment”condition), participants put on a head-mounted virtual-reality device, and went into a virtual-reality environment where they had the experience of cutting down a tree in virtual forest. They held a virtual chainsaw that had haptic feedback, so they physically felt the resistance of the wood when the chainsaw bit into the tree, and they experienced the sights and sounds of the virtual forest.

So both groups received information about the importance of not using too much non-recycled paper and about the impact on deforestation. They basically had identical information but they had different visceral experiences.

How’d the two groups do?

Both groups filled out surveys that measured their sense of self-efficacy—how much they felt that their actions can improve the quality of the environment (e.g., “My individual actions would improve the quality of the environment if I were to buy and use recycled paper products”). Both groups showed a significant increase in their self-efficacy measures after the experiment compared to the survey they took before the experiment began.

Basically, both groups self-reported significant change in their attitudes.

Here’s where it gets interesting

In addition to filling out the survey, they asked participants to fill out some demographic data. While they were doing that, the researcher would “accidentally” knock over a glass of water. They then handed a pre-counted stack of paper napkins to the participant and asked for help mopping up the water.

Then they counted the used napkins.

Participants who had been in the immersive virtual environment used approximately 20 percent fewer napkins to clean up the water spill than did participants in the mental simulation condition, despite having reporting similar attitudes in both conditions.

Having a visceral experience mattered

As I mentioned at the beginning of this research review, it would be difficult to generate guidelines for application from this single study, but it does suggest that visceral, physical experiences can have an impact on behavior.

While we should be cautious about overgeneralizing, I think there are some keys ideas we can consider:

  • Attitude is not necessarily a predictor of behavior. When you are looking for a behavior change, you need to evaluate based on what the participants do, rather than what they say.
  • Active, visceral experiences may influence behavior change. If you are trying to change a particularly challenging or important behavior, you can consider first-person active experiences as a tool in your instructional design toolbox, even without access to a virtual-reality environment.

 

The Study

Information on the study:  Ahn, Sun Joo and Jeremy Bailenson. “Embodied Experiences in Immersive Virtual Environments: Effects on Pro-Environmental Self-Efficacy and Behavior” (2011). Virtual Human Interaction Lab, Stanford University. Viewed 4/3/2013 at http://vhil.stanford.edu/pubs/2011/VHIL-technical-report.pdf

Reprinted from Learning Solutions Magazine

Filed Under: Articles Tagged With:

Data, Data Everywhere: But Not a Drop to Understand

“Why can’t we get useful data from our health plan?” benefit managers often bemoan. A common and persistent problem for practitioners is the scarcity of useful data, though pros often have reams of reports from their plan. However, finding real answers to the most pressing health data questions lies in the words you use.

Imagine a benefit manager faced with this question from his/her CEO: How much did we spend last year on depression?

Each part of the question is a data point.  The phrase “how much did we spend” could mean how much the plan actually paid in benefits (after copays or benefits from other plans), or how much the plan benefit or allowed amount was. It could include or exclude how much employees paid in copays and deductibles.

“Last year” could mean calendar year, plan year, or fiscal year. It could mean the most recent 12 months. Further, it’s uncertain whether the CEO wants only the dollars that left the plan during the “year” (incurred and paid claims) or the dollars that were spent to cover all the services that occurred during the “year,” regardless of when the claim was actually paid.

“On depression” could mean medical bills that have “depression” as the principal (first) reason for the care. Or, it could mean medical bills that have depression as a diagnosis anywhere on the claim. Further, it could include or exclude prescription drugs that are typically used for depression.

Comparatively, here is the same question translated into a data request: What was the net plan payment for medical claims with a principal diagnosis code of 311 (depressive disorder), where the claim date of service occurred during the 12-month period ending June 30, 2012, and the claim was paid during the 15-month period ending Sept. 30, 2012?

If you wanted the figures for depression-related medications, you would ask: What was the net-plan payment for pharmacy claims for drugs with ATC code N06A* where the claim date of service occurred during the 12-month period ending June 30, 2012 and the claims was paid during the 15-month period ending Sept. 30, 2012?

Somewhere in those stacks of reports, the data to answer the CEO’s question is hiding — but it’s cloaked in numbers, codes and jargon.  As a result, plan administrators throw up their hands, and say, “We’ve given them all the data!” And benefit managers say, “We have no data!”

Health data is not intuitive. You can’t look at diagnosis codes and instantly know what they mean — it’s a specialized skill to make lists of numbers and codes useful for decision-making.  Without this skill, benefit managers will stay in the drought even while they are deluged by data.

About the Author:

Linda K. Riddell is a principal at Health Economy, LLC.  Reprinted from Employee Benefit News

Filed Under: Articles Tagged With: , , ,

Inside the Learning Brain

Sophisticated brain-imaging tools allow researchers to study the brain and revolutionize the understanding of how we learn. As a result, today we know more about learning than ever before, which provides great opportunities for training and development professionals to harness new insights and apply this new knowledge to advance the field.

The emerging field of neuroeducation

This year, I celebrate 25 years in the field of training and development. Over the years, it always has intrigued me that during the same learning experience people learn differently, and learning outcomes for individuals can differ significantly. I have become increasingly more interested in creating training initiatives that embrace and enhance these differences in learning to gain more competitive advantage for individuals and for the organization.

In training and development until now, our field of study has had its roots in pedagogy, didactics, and instructional design focused on individual education and learning. The field of developmental psychology provides us with additional important insights on the integration of the mind and behaviors.

Cognitive neuroscience is the study of mental brain processes and its underlying neural systems. This includes thinking and behavior and is underpinned by the learning brain. Therefore, cognitive neuroscience looks at how the brain learns, stores, and uses the information it acquires. It is through learning that the brain enables us to adapt to our ever-changing environment.

The area of overlap between different disciplines, including cognitive neuroscience and education, has been identified as a transdisciplinary field of study called educational neuroscience or neuroeducation. According to The Royal Society February 2011 report, The Brain Waves Module 2: Neuroscience: Implications for Education and Lifelong Learning, this field investigates basic biological processes involved in becoming literate and numerate, and explores learning to learn, cognitive control, flexibility, and motivation, as well as social and emotional experiences.

Our brain and learning

Learning is a physical process in which new knowledge is represented by new brain cell connections. The strength and formation of these connections are facilitated by chemicals in the brain called growth factors.

We now know from neuroscience that the availability of these growth factors can be enhanced. For example, specific exercise routines, optimal sleep structure, and silencing the mind can all enhance the availability of these growth factors. Nature and nurture affect the learning brain. People have different genetic predispositions, but experience continuously shapes our brain structure and modifies behavior.

During the past decade numerous peer-reviewed publications have connected the fields of neuroscience with education and learning. Several studies report structural and functional changes in the brain related to training. A working understanding of how the brain learns and performs is an invaluable new skill. It is essential for the future success of individual employees and their organizations.

What follows are evidence-based results that have an impact on how companies should design and deploy training initiatives.

Increasing knowledge of people is key to innovation

We intuitively understand the knowledge worker’s need to acquire new knowledge that optimizes the value of his unique contribution to the business. What is less obvious, but of great importance, is that creative and innovative thinking processes in our brains are built on the foundation of knowledge.

Our brains continuously draw on this knowledge base to create simple solutions to complex problems. Knowledge provides the building blocks for innovation, which is the number one priority for many enterprises.

For this reason alone, employees wanting to be more innovative (and, thereby, increasing the value of their contribution to the business) should explore every opportunity to add to their knowledge base. And since we live in a fast-paced world with ever increasing sensory overload, we need well-designed and structured learning opportunities to make best use of the limited time available to us to build new knowledge.

Active engagement is necessary for learning

Changes in neural connections, which are fundamental for learning to take place in the brain, do not seem to occur when learning experiences are not active. Many research studies suggest that active engagement is a prerequisite for changes in the brain.

Not surprisingly, just listening to a presentation or lecture will not lead to learning. Powerful training initiatives that stimulate active engagement include facilitation, simulation, games, and role play.

All learning has an emotional base

Neuroscientists believe that emotions are fundamental to learning. One of the earlier advocates of this was Plato, who mentioned more than 2,000 years ago that “All learning has an emotional base.”

Motivation in the brain is driven by emotion. Individuals are motivated to engage in situations with an emotionally positive valence and avoid those with an emotionally negative valence. Research findings indicate that different aspects of memory are activated in different emotional contexts, and that demonstrates there are links between emotion and cognition.

Training professionals can design learning sessions that tap into the emotions. For example, ask learners to share work experiences that have been difficult for them.

Focused attention is fundamental to acquiring new knowledge

We now have learned from neuroscience that sustained focus is largely an unconscious process but essential for learning and creative thinking. Actively silencing the mind through a process of focused attention (focusing on the major senses while breathing deeply) or open monitoring (actively allowing incoming stimuli without reacting or responding to it) for 20 minutes per day will go a long way toward enhancing the ability for focused and sustained attention.

Therefore, it is a powerful imperative to include time for meditation and breathing in the design of classroom programs.

Deployment of short learning sessions will increase knowledge retention

The brain remembers the first part and the last part of a training initiative best. This is called the primacy-recency effect.

The middle period of learning should be filled with the least important information, and shorter learning sessions will reduce the middle “down” period. This is why training sessions ideally should be no more than 20 minutes, with planned “brain breaks” separating sessions.

Use learning techniques that enhance memory formation

Learning techniques that have shown to enhance memory formation include elaborating, verbalizing, writing and drawing, and sharing learned information during and at the end of a learning session. Interweaving different subject matter categories during a training event enhances the learning process.

Simply, this means that three different subjects can be learned by studying them simultaneously, moving from one subject to the next in an open-ended interweaving fashion. That is because the brain learns and packages new knowledge even while we are not aware of it; it’s a continuous and vastly unconscious process. The brain continues to learn and consolidate new knowledge unconsciously, even as we consciously start to focus on new material.

Use it or lose it

The adult brain changes following the acquisition of new skills. However, the changes in the brain reverse when people do not have the opportunity to use the skills they have developed.

Unfortunately, many training initiatives are less effective because people can’t apply their learning in the workplace after completion of training. This is one of the benefits of digital learning. It provides on-demand learning and knowledge that can be reviewed at any time and any place.

Multitasking slows down learning

Multitasking has become a way of living and working for many people. Unfortunately, our brains are not wired for multitasking because most of us can only apply our full conscious attention to one stimulus at a time. (A small proportion of the population, called “super-taskers,” can pay attention to two stimuli at one time.)

Our working memory—this is the part of the brain that allows us to focus our attention on a task such as reading—continues to interact with our long-term memory where we retrieve and store specific information. If we try to conduct two tasks at the same time, we must switch between the different tasks and an overload results between our working memory and long-term memory, which causes us to lose time.

Multitasking is not effective and costs an estimate of $650 billion because employees spend one-third of their time interrupting existing tasks to continue later with the same tasks. Therefore, it is important during training programs to limit multitasking such as simultaneously reading or writing email during a class.

Enhancing brain performance capacity supports learning

Etienne van der Walt, an experienced neurologist and expert in cognitive neuroscience, has developed diagnostics to assess the extent to which an individual complies with current neuroscientific applications that are proved to enhance brain performance capacity. According to him, human brain performance is continuously affected by identifiable brain performance drivers.

Guided by current evidence from the best neuroscience research available, van der Walt has identified 12 drivers that can be individually and collectively enhanced for optimum brain performance. These include the foundational drivers of exercise, sleep, nutrition, and rhythms; emotional drivers such as belonging and identity; higher order drivers that include the executive planning functions of the prefrontal cortex; and sensory drivers.

By using a program called BrainCoach, an individual’s compliance levels and current level and mix of each brain performance driver can be measured. According to van der Walt, all these individual brain performance drivers can be enhanced and fine-tuned to improve the performance capacity of brain performance. In other words, we can develop skills that may allow us to manage these drivers for optimum brain performance.

Challenges and opportunities

There is plenty of research that provides clear and accurate summaries of progress in the cognitive neuroscience of learning. However, there are at the same time questionable media reports and claims about brain-based learning that, according to some scientists, often oversimplify, misrepresent, and allow for “neuromyths” to flourish. Training professionals should only use research that provides sufficient evidence and that can be put into practice.

Cognitive neuroscience is a promising field of study and has exciting potential discoveries ahead. Medical professionals often are trained in molecular biology and organic chemistry, knowledge that indirectly affects the future practice of physicians.

Similarly, training professionals should have a fundamental knowledge about the brain and apply cognitive neuroscience evidence to their practice of developing people. In the 21st century, companies will put much more emphasis on individual and organizational learning to innovate and compete successfully in a global knowledge economy.

The Application of Brain-Based Learning at Deloitte*

Deloitte’s learning and leadership curriculums are dynamic and go through ongoing stages of refreshment and redesign to make sure they are aligned with business needs. The learning design principles increasingly use evidence brain-based learning practices. For example:

  • Classroom programs are designed to support a high level of engagement and intentionally touch on emotions. Learners are expected to participate actively by collaborating, elaborating, verbalizing, drawing, and sharing what has been learned. Lecture-driven experiences are kept to a minimum.
  • Learning sessions are reduced to smaller bytes and chunks and provide a high level of personalization.
  • Learners are strongly encouraged to use valuable offsite classroom time to reflect on their development and are discouraged to look at emails and texts during classroom time. This ensures that people stay focused on learning.
  • A large inventory of digital learning provides learners with an opportunity to acquire knowledge and develop skills as needed. As a result they can apply and practice new skills directly on the job, making the learning stick.
  • Health and well-being are supported by providing fitness, yoga, and meditation classes at Deloitte University in Dallas. Participants can take advantage of healthy food choices to stimulate body and brain.

Note: *Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited and its network of member firms, each of which is a legally separate and independent entity.

About the Author:

Nick van Dam is an internationally recognized consultant, author, speaker, and thought leader. He is a director and chief learning officer in global talent for Deloitte Touche Tohmatsu Limited. He also is founder and chairman of the e-Learning for Kids Foundation, which provides children with free digital education globally.

Reprinted from T&D Magazine

Filed Under: Articles Tagged With: , , , ,

Pin It on Pinterest