What Happens When Technical Learning Goes Mobile?

Fast-paced organizational growth and competitive environments demand employees to be more productive and better informed to serve customers. To achieve these objectives, the population of mobile workforce is steadily growing in all organizational departments. According to a Gartner and BusinessWire forecast, this number will cross 1.3 billion by end of 2015 and will continue to rise.

Learning leaders can empower this mobile workforce by using digital learning tools with just-in-time access, delivering the knowledge employees need to complete the job at hand, quickly and effectively.

An increase in the number of powerful mobile computing devices plays a key role in empowering employees in the field. Apple’s iPhone and iPad, Google’s Android OS and Windows Mobile and other platforms in conjunction with technologies like augmented reality, proximity sensors, collaborative workflows and analytics make a compelling proposition for effective performance support tools.

With high expectations from the sales workforce to add to the organization’s top line, the demand for a mobile productivity tool is higher than ever before. Many organizations in the United States have started enabling the sales workforce with productivity tools, in turn providing returns for all departments.

Leveraging the authentication details, sales executives log in to the tool using mobile devices or a PC and access product specific details. In many organizations, details such as product features, value proposition, price points, possibility of discounts, tentative order closure details are dynamic in nature. The ability to update these details on a daily basis makes it a useful tool in the field.

Another aspect of the tool that gives its information context is its ability to tag information with location and time of day. With this feature, the mobile device understands the location of the sales executive and facilitates relevant information proactively.

Despite of all these information bytes, sales executives do have queries on products, hence a rapidly growing use of query resolution modules in productivity tools. This started with a simple form — users post a query to an expert or a peer community and receive resolution in asynchronous mode. To get employees speedier access to information, apps integrate instant messages so sales executives can seek clarity from an expert in synchronous mode. These instant messengers enable sales executives to share pictures or video files through instant messengers for faster resolution.

Sales executives with years of experience in the field often understand certain processes much better than others. Such wealth of tacit knowledge can be turned into explicit knowledge using productivity tools, where the experts make videos, store them on a central knowledge management repository and share with peers for replication.

Because sales executives are in the field most of the time, sharing updates on organizational events can be challenging. Productivity tools have started integrating organizational alerts as a feature where new product launches, messages, policy announcements, etc., are shared using a remote backend utility for alerts announcement. The remote backend utility of the performance support tools allows the administrator to push the information for sales executives on their mobile and PC apps.

The backend utility also facilitates analytics on data collected from end user access points. These analytics help the organization to understand the sales executive’s knowledge on products and map them with sales closures data.

Most of the time, these conclusions lead to training programs for sales executives on products or reassignment of field roles. They are also used to reward performance or winners on the field. All these actions help sales organization perform better and improve the top line of the organization.

Wellness Programs: Get Results or Go Away

If you haven’t been keeping tabs over the last few months, there has been some increasing friction between the EEOC and the corporate world over a seemingly harmless set of programs focusing on employee wellness. Note that this is primarily focused on health and wellness programs, not those targeting financial wellness.

While this has been frustrating for those affected, it does provide an impetus for companies that is long overdue. In the long run companies will focus more on wellness programs that actually bring results, not just on checking the obligatory box on a list of employee benefit offerings.

Wellness by the Numbers

According to the Kaiser Family Foundation Health survey:

  • 94% of firms with over 200 employees offer wellness programs
  • 11% of those organizations have penalties for employees that do not complete all required health management procedures
  • 9% of large companies penalize employees for not meeting specific biometric outcomes (BMI, cholesterol, etc.)

Wellness is here to stay, with the majority of companies believing that offering these types of options will help to lower insurance costs over time.

The Battle for Wellness

Orion Energy Systems was a typical organization with regard to its wellness program. It required health-related actions from its employees and used incentives/penalties to encourage the behaviors consistent with its wellness program goals. But it didn’t turn out so well.

Orion instituted a wellness program that required medical examinations…  When employee Wendy Schobert declined to participate in the program, Orion shifted responsibility for payment of the entire premium for her employee health benefits from Orion to Schobert.  Shortly thereafter, Orion fired Schobert.

For reference purposes, Orion meets the “large company” criteria in the Kaiser report cited above.  Here’s what happened next:

Orion Energy Systems violated federal law by requiring an employee to submit to medical exams and inquiries that were not job-related and consistent with business necessity as part of a so-called “wellness program,” which was not voluntary, and then by firing the employee when she objected to the program, the U.S. Equal Employment Opportunity Commission (EEOC) charged in a lawsuit it filed recently.

In case you’re wondering, Orion is not the only organization that falls into this category. Honeywell International also had an opportunity to face the ire of the EEOC for similar reasons.

The Outlook on Wellness

The EEOC has just released its Notice of Proposed Rulemaking (NPRM) with regard to this complex issue. This breakdown by the Jackson Lewis law firm is a great look at some of the key areas of the proposal, but one piece in particular stuck out for me (emphasis mine):

“The NPRM requires that if an employee health program seeks information about employee health or medical examinations, the program must be reasonably likely to promote health or prevent disease. Employees may not be required to participate in a wellness program, and they may not be denied health coverage or disciplined if they refuse to participate.”

Believe it or not, after all of the time, legal battles, and other resources expended on the world of wellness, it comes down to whether or not the program is actually going to promote health or prevent disease. We actually have to measure these initiatives and not just put blind faith in their ability to make our employees and organizations healthier. If that sounds a bit harsh, I’d advise you to check out this discussion on the results of wellness (or a lack thereof). On the other hand, companies like Johnson & Johnson have been more successful.

There are other aspects, such as voluntary participation and limits on incentives, but I think it’s just one more push in the direction of measuring everything and only pursuing those that are going to deliver results. Not everything that is measurable matters, but everything that matters should be measurable.

About the Author:

Ben Eubanks is an associate HCM Analyst at the Brandon Hall Group, a preeminent research and analyst firm covering Learning & Development, Talent Management, Leadership Development, Talent Acquisition, and Human Resources.

Workforce Analytics: Disney’s Real-Life Fairy Tale

It was a numbers game at the HR Tech conference this year in Las Vegas.

I do mean numbers like lucky 7s, hard 8s and terrible 12s (more on my introduction to craps in a later post). But also a numbers game in terms of the growing exploration and adoption of workforce analytics.

A highlight at the industry trade show Oct. 8 was

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a Clear Talent Picture at Disney Animation Studios.”

Presenters Ann Le Cam, vice president of human resources and production management at Walt Disney Animation Studios, and Al Adamsen, president of consulting firm The Talent Strategy Institute, spoke about the way Disney has become data-conscious in the way it manages its creative workforce.

It’s a true-life fairy tale of sorts. The studio, with a rich history of producing the likes of “Snow White” among other treasured classics, hit hard times in the 2000s. Disney animators and managers struggled to make the shift from two-dimensional animated films to 3-D pictures. Films including “Treasure Planet” flopped. Management tended not to be grounded in hard facts.

“We were very emotional” in decision-making, Le Cam said.

Things changed when Disney bought computer-animated studio Pixar in 2006. Pixar executive Ed Catmull is a computer scientist and expected a more rigorous approach to operations, Le Cam said. That sparked an effort to focus more on metrics.

To aid the project, Le Cam brought in Adamsen, who had been an HR analytics practice leader at software firm Kenexa, which is now part of IBM.

Disney’s analytics push began in part with basic definitions. It created a “data dictionary” spelling out how different metrics would be calculated. Terms like “capacity planning” and “workforce planning” had different meanings to different people. “A data dictionary is square one,” Adamsen said.

And rather than focus too much on technology tools, Le Cam and her team emphasized working with colleagues to get agreement on the goals of the effort and how it would be carried out.

Film production has an inherent element of volatility. Le Cam noted that studio head John Lasseter or other members of Disney’s “brain trust” can come in part way through production and declare that a movie isn’t good enough. Films sent back to the drawing board in this way can trigger talent shake-ups, such as the need to hire more people pronto.

Still, Disney is working to be more systematic with its planning. It now creates a chart demonstrating the expected talent needs for multiple films over time. Another step is surveying those involved with a movie about the likelihood that it will be done on time. If answers are consistent, that’s a predictor of success. If they vary widely, trouble is probably brewing.

Adamsen said efforts like Disney’s should focus on business goals like better performance, a better work experience for employees and reduced risk rather than simply being able to produce numbers. The term “workforce analytics” isn’t going to mean much to executives, he said.

Indeed, the language around analytics proved to be important to Disney. The term “data-driven decisions” didn’t sit well with everyone. There was concern the “human” was getting lost in human resources. So Le Cam and her team altered the phrasing to “data-informed” decision-making.

Disney has a ways to go with respect to workforce analytics, Le Cam said. Nevertheless, her work to date has a happy ending apropos of a Disney movie classic. Attention to metrics, data and planning around talent has shifted the culture of Disney animated films and contributed to recent successes such as “Tangled” and “Wreck-It Ralph,” she said: “We transformed the studio.”

Reprinted from Workforce.com

5 Ways High-Performance Organizations Use HR Analytics

Mining masses of data for performance-improving insights is at  once the biggest challenge and greatest opportunity presented by big data.  While this is true for every function in the enterprise, the wake-up call for  HR should have been answered well before now. In fact, i4cp’s most recent  research on the analytical practices and capabilities of HR organizations  suggests that most are woefully unprepared to do little more with a rapidly  rising ocean of data than drown in it.

While many HR organizations are proficient  at collecting and measuring activities, few have the ambition or ability to  measure outcomes or identify the factors that most affect results.

i4cp’s new report, HR Analytics: Why We’re Not There Yet, pinpoints  the reasons for these shortcomings and highlights differences in the strategies  and practices of high-performing organizations (HPOs) and low-performing  organizations (LPOs) in addressing five key factors driving effective usage of  HR analytics – ambition, skills, data accuracy, HR leadership’s role and level  of sophistication.

1) HPOs use HR data to plan and perform better;  LPOs seem content to merely report it.

HPOs take a more calculated approach, using data for strategic, long-term  planning over twice as much as LPOs (96% compared to 47%). Far more HPOs (91% compared  to 59%) rigorously assess the ROI of initiatives and programs. Not only is the use of data to make business decisions the marker of an astute organization, it  underscores that HPOs are focused on far more than simply reporting.

HPOs actively seek information that improves the effectiveness of their planning and the performance of their programs and processes. Low-performing companies do little more than meet minimum requirements necessary for business.

2) Turning data into information is the most pressing analytics challenge — and HPOs are better equipped to meet it.

A common challenge cited by HR practitioners is the difficulty in  determining what the data that is gathered actually means. This was the top  data collection obstacle cited by all survey respondents. As Sue Suver, Head of  Global HR at U.S. Steel pointed out, “Data is great if you have it. But without  people who know what to do with it, you’re still stuck.”

Sifting through an  expanse of big data to pinpoint trends or uncover stories is a difficult and  time-consuming task. It requires analytical and interpretive skills, which more than half of respondents from low-performing companies said they seriously lack compared to little more than a third of those from HPOs. Their experience  suggests that companies that can transform data into information, and  information into profitable action, will reap a competitive advantage.

3) HPOs take full advantage of processes,  automation and standards to ensure data accuracy, while LPOs rely mostly on manual checking.

Twice as many HPOs reported using company-wide standard definitions as a method for guaranteeing data accuracy. Both HPOs and LPOs check data reliability, but HPOs use automated processes (68% compared to 38%) to a  greater extent, which not only reduces errors, it frees up employee time for more  pressing tasks.

The most difficult task of all is setting data standards in the  first place. Data councils, which convene stakeholders to set policy around activities such as data collection, standards,  and security, are pivotal because they enable enterprise solutions and ensure organization-wide  consistency.

4) HPOs’ HR leaders are highly engaged in using analytics to drive performance; LPOs are content to supply data to the  executive team.

More than twice as many HPOs have HR leaders receiving workforce data than LPOs  (81% compared to 33%), which suggests a more robust, analytics-savvy HR  department in more successful companies. i4cp’s study indicates that HPOs are moving more aggressively toward the  performance advisor role identified in i4cp’s 2012 report, The Future of  HR: The Transition to Performance Advisor. HPOs are also using  people-related data and metrics to proactively inform and engage both the  senior leadership and line managers on how to better manage talent and improve  business performance.

Dominique Ben Dhaou, SVP of HR at SGS, a global leader in providing verification, testing and certification services, underscores  the importance of having a basis for action regarding data: “If you benchmark  or read a report and do nothing with it, it’s useless. But if you transform the data you have access to into solutions for business issues, it has value. When  business people say HR doesn’t understand the business, it isn’t that – it’s that  we don’t do anything with the information we have.”

5) Predictive analytics are underused for  human capital measures – even by HPOs. 

Both HPOs and LPOs are still finding their way in developing the skills and technical capability to perform and use predictive analytics. Few are now using  analytics to answer questions such as how many employees are needed, who is likely to leave, which skills will be in short supply, how changes in workforce  cost and productivity affect the bottom line, and which HR practices directly  increase company performance.

Predictive analytics can reduce uncertainty and provide an evidence-based grounding to the decisions of both HR and the  business. Using predictive analytics to understand the true drivers of customer  service representative productivity, i4cp member-company Sprint was able to improve its customer satisfaction by  record levels.

The bottom line: HPOs  are ahead in the race to connect HR initiatives to business outcomes through  data. The gap between HPOs and LPOs in mining insights from big data to show how HR initiatives  and practices generate hard financial returns is the single-most important  difference between the two groups.

The ability to close this gap – to find and  use data that can show the impact of HR programs – is one sure way that LPOs can become HPOs. By showing the actual financial impact of a program or a practice, the  relative merit of each can be seen, and strategies and budgets can be adjusted  accordingly. This evaluation of ROI is the key advantage of meaningful HR  metrics.

Reprinted from The Institute for Corporate Productivity

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