HR News: Machine Learning Can Reduce Turnover

Every HR professional is trying to figure out how to stop turnover. At the same time, they are working on ways to predict which employees are preparing to leave the company and find a way to intervene before it actually happens. In other HR news, Qdoba is facing a $400,000 fine over child labor law allegations, August 23 is Black Women’s Equal Pay Day and some new figures out show how large the gap is and one author believes social learning is the next big corporate learning strategy.

HR News
Machine Learning Can Reduce Turnover
A new study from Harvard Business Review says using machine learning on certain types of data can predict who will leave a company before the exit occurs. The article’s authors, Brooks Holtom and David Allen, say that data, which includes the employee’s past job information and skills-related data, was used to make the prediction. This points to further proof that data-driven decision making can help employers retain those workers who best support the company and can reduce costs associated with turnover. Read more here.

Qdoba fined over $400,000 for child labor law violations
Qdoba restaurants in Massachusetts have been fined more than $400,000 after allegedly violating child labor laws more than 1,000 times. That’s according to Boston News. The state’s attorney general, Maura Healey, said minors employed at several of Qdoba locations worked beyond 10:30p on school nights. Additionally the attorney general said her office found “18 instances of a minor working over 48 hours in a week, and 25 times that Qdoba didn’t have the work permit required when hiring a minor. Each violation carried a $250 penalty.”

Black Women’s Pay Gap Continues to Exist
62% of people “acknowledge that white men make more money than Black women on average” according to a new study from SurveyMonkey and LeanIn.org. That same survey says 44% of people are aware a pay gap exists between black women and white women. These are just some of the newest figures released on August 23, 2019, also known as Black Women’s Equal Pay Day. According to Caroline Fairchild, managing news editor for LinkedIn, for “black women making roughly 61 cents for every dollar white, non-Hispanic men make, it would take about 19 months of work — January of one year until August of the next — for Black women to make up for the gap.” Read more here.

Why Social Learning is the Need of the Hour
Social Learning is the “need of the hour.” That’s according to Debadrita Sengupta. If you’re unfamiliar with social learning, It’s all about people learning by observing and imitating others. Why: because it boosts learning interaction and expression and fosters healthy competition among other things. Details here.

https://www.hrexchangenetwork.com/hr-talent-aquisition/news/hr-news-machine-learning-can-reduce-turnover

How to Use OKR Reviews to Determine Compensation

One of the most common questions we get asked as leadership team coaches is how Objectives and Key Results (OKRs) should be used to determine salary, compensation, or bonuses. A growing number of organizations are eliminating the annual performance review altogether, but a need still remains for an OKR process involving metrics and KPIs to exist in order to determine compensation and promotions. Or does it?

First, let’s distinguish the two kinds of OKRs we are speaking about here. The one popularized by Google is where OKRs represent stretch goals for an organization, a team or individual should hit 60-70% of the target, with the intention of rewarding courage, innovation, and ambition (vs mere execution). The other is configured for performance milestones to hit a target of 100% in completion.

We will be discussing the first option here as it is the OKR process we normally encounter and recommend for clients. It is also the methodology where a coupling of OKRs to compensation can quickly become counter-productive, if not done right. However, much of what we share will also apply as solid practices for any goal setting or OKR process.

It’s not just about completing the OKR for the sake of the review
You’ve likely already heard that OKRs should not be tightly coupled with employees evaluation and compensation. The biggest reason for this is that your team will stop “shooting for the moon”. More precisely, tightly coupling the OKR and review will lead to overstated accomplishments, stunted innovation, and sand-bagging of goals.

Coupling OKRs with pay leads to overstated accomplishments and stunted innovation.
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How come? Because OKR goals in this context work best when they stretch and push your people to become ambitious and self-driven. In other words, the OKR process work best when individuals and teams follow strong intrinsically motivating factors like autonomy, belonging, mastery, and taking on new challenges that inspire them.

Once compensation or promotion enters the picture, motivations shift towards far less effective extrinsic goals, which means the behavior can skew towards looking good or laying the fault on others for any failures. So status, money, or self-preservation are now running the show.

We’ve seen this again and again, going back to our days working in HR departments at large corporations when people play politics or try and game the system to meet targets and overall employee performance can actually drop.

Instead, we suggest the following practices for using OKRs in a review:

Make OKRs just one of the factors influencing compensation. When determining employee compensation, it is absolutely ok and perhaps even valuable to take into account the ambition of OKR goals and the success of results. However, it is also important to use OKRs as just one of the many data points available that influences these performance evaluations.

Looking for a software solution to help you manage OKRs and ongoing employee performance? Give 15Five a try!
Look at other work operations and overall behaviors. If you do decide to link OKRs with reviews – as many sales teams find useful, for example – make sure other operational goals and behaviors are a large part of the picture.

In instances where OKRs represent stretch goals, any individual or team is also going to have a lot of other important daily tasks and conversations that may or may not be directly reflected within the OKR process. Examples of these are progress in career growth and skills, contributions above and beyond job expectations, working collaboratively with others to drive total business revenue, and embracing the organizational culture and values.

For example, a manager may need to have 20 client interviews per quarter as part of their expected operational tasks, which is not covered by their OKR. But even if their supervisor measured this, an OKR review still wouldn’t reveal everything meaningful about the employee’s performance and growth. All these factors should matter a great deal in choosing how to reward an employee beyond their base income:

How are they doing these interviews? Do they go above and beyond in the expected quality of operations in them? Did they take on additional work? What is their attitude and level of professionalism? Do they consistently practice and model the company’s values?

Embrace collaboration over competition in OKR-related compensation. Consider offering the same bonus to a whole organization or team as a reward for meeting ambitious OKR goals. While individual rankings might have value in determining who to promote, giving bonuses to a whole team encourages greater collaboration, cooperation, and alignment in everyone in the team to drive results within your organization.

Compensation and the OKR Process
On the other hand, individualized compensation within a team for OKR goals can lead to internal competition within the team, with the ensuing politics, more rigid hierarchies, and unhealthy one-upmanship. Some organizations worry about social loafing factors if one or more individuals are not carrying their weight, and unfairly rewarding people by paying a whole group the same compensation for OKR results.

The roots of this potential issue are much better addressed through:

• Clearer agreements around work expectations for everyone on the team

• Mutual accountability processes where group members call out one another for not meeting their agreements or pulling their own weight in meeting a goal

• Peer-level feedback review sessions that can factor into determining promotions or salary raises for individuals

Here are some additional practices for streamlining your OKR process:

Have a gap between the two conversations. Development and financial reward should never be conflated, so be sure to separate your OKR review conversations from all employee evaluation and compensation conversations.

In Work Rules!, Laszlo Bock suggests making this separation at least one month apart to decouple the two processes in the minds of your employees. By taking away concerns around salary, ranking, or status in the OKR review process, you will free up your employees to become creative and step into a learner’s mindset. Contrast this with reactivity, manipulation, or defensiveness that may otherwise arise around meeting their goals.

Stay away from formulas. Fortunately, formulas for calculating compensation are not common these days, but we still hear about organizations attempting them. The belief that they can be effective goes back to the earliest days of the industrial era when productivity formulas became en vogue and have grown significantly more complex with time. The logic goes that if one can accurately measure employee productivity, then compensation should follow accordingly.

However, that’s not how it works. Formulas often fail to reward the highest performers, even if they include productivity metrics or OKRs. How come? Because attitude, professionalism, and the little daily contributions an employee makes have a large snowball effect that goes way beyond what any formula can capture or account for. Only a managerial and/or peer review process will reveal these important subjective factors.

Time intensive as they can be, there is no substitute for having these meaningful conversations to track and rate these crucial qualities. A common and successful approach that we have used, supported, and have seen work many times is manager-level calibration conversations about employees with the same standards applied transparently across the board. It is a much more fair and accurate process in evaluating the value of employee contributions.

Never use OKRs to determine base salary. This may sound obvious, but we continue to be surprised to hear people attempting this. Start with local market standards to actually determine base salary.

Accept that successful compensation processes are always subjective. This will no doubt irk some people, but it is perhaps the most important consideration. Even the most “objective” OKR metrics review process will not alleviate the inherent subjectivity of compensation, although the suggestions we have made here will ensure it far more fair and transparent. We have not seen any exceptions to this rule yet.

So can OKRs be part of a compensation and reward process? Certainly, and with all the guidelines and caveats shared above, they can actually help (rather than undermine) your employee motivation efforts.

When managers get together to discuss individual employee evaluation and compensation in a calibration session, be sure to have a checklist to call each other out on any implicit biases, errors, or blind-spots that compromise fairness or consistency in evaluations. We’ve seen these biases creep into many calibration scenarios unless they are specifically looked for.

Here are the most common examples of bias:

• Central Tendency – all employees are being rated about average (or above average if you live in the town of Lake Wobegon!).

• Leniency/Strictness bias – the appraiser tends to give all employees unusually high or unusually low ratings.

• Similar-to-Me bias – the appraiser inflates an employee evaluation because of a personal connection or identification with them, rather than objectively looking at their actual performance.

• Halo/Horns bias – An appraiser’s evaluation of an employee’s performance is biased/skewed because of the appraiser’s current judgment of the employee as being good (halo) or bad (horns), while ignoring new evidence to the contrary during the time period.

• Recency bias – an appraisal is based mostly on an employee’s most recent or memorable behavior, rather than on their behavior throughout the appraisal period.

• Contrast bias – an employee evaluation becomes skewed up or down from comparison with the employee that has just been evaluated before them.

We have personally seen many successful examples of goal setting and compensation processes that work really well together. Find and customize yours based on the OKR process in place, in addition to the needs, priorities, and culture of your organization and set your people up to performing as their best-selves at work. Please reach out to us if you have questions or would like more support with this process.

Source : https://www.humanresourcestoday.com/compensation/?open-article-id=9079346&article-title=rewarding-ambition–determining-compensation-within-your-okr-process&blog-domain=15five.com&blog-title=15five

Learning to Work with Intelligent Machines

t’s 6:30 in the morning, and Kristen is wheeling her prostate patient into the OR. She’s a senior resident, a surgeon in training. Today she’s hoping to do some of the procedure’s delicate, nerve-sparing dissection herself. The attending physician is by her side, and their four hands are mostly in the patient, with Kristen leading the way under his watchful guidance. The work goes smoothly, the attending backs away, and Kristen closes the patient by 8:15, with a junior resident looking over her shoulder. She lets him do the final line of sutures. She feels great: The patient’s going to be fine, and she’s a better surgeon than she was at 6:30.

Fast-forward six months. It’s 6:30 AM again, and Kristen is wheeling another patient into the OR, but this time for robotic prostate surgery. The attending leads the setup of a thousand-pound robot, attaching each of its four arms to the patient. Then he and Kristen take their places at a control console 15 feet away. Their backs are to the patient, and Kristen just watches as the attending remotely manipulates the robot’s arms, delicately retracting and dissecting tissue. Using the robot, he can do the entire procedure himself, and he largely does. He knows Kristen needs practice, but he also knows she’d be slower and would make more mistakes. So she’ll be lucky if she operates more than 15 minutes during the four-hour surgery. And she knows that if she slips up, he’ll tap a touch screen and resume control, very publicly banishing her to watch from the sidelines.

Surgery may be extreme work, but until recently surgeons in training learned their profession the same way most of us learned how to do our jobs: We watched an expert, got involved in the easier work first, and then progressed to harder, often riskier tasks under close supervision until we became experts ourselves. This process goes by lots of names: apprenticeship, mentorship, on-the-job learning (OJL). In surgery it’s called See one, do one, teach one.

Critical as it is, companies tend to take on-the-job learning for granted; it’s almost never formally funded or managed, and little of the estimated $366 billion companies spent globally on formal training in 2018 directly addressed it. Yet decades of research show that although employer-provided training is important, the lion’s share of the skills needed to reliably perform a specific job can be learned only by doing it. Most organizations depend heavily on OJL: A 2011 Accenture survey, the most recent of its kind and scale, revealed that only one in five workers had learned any new job skills through formal training in the previous five years.

Today OJL is under threat. The headlong introduction of sophisticated analytics, AI, and robotics into many aspects of work is fundamentally disrupting this time-honored and effective approach. Tens of thousands of people will lose or gain jobs every year as those technologies automate work, and hundreds of millions will have to learn new skills and ways of working. Yet broad evidence demonstrates that companies’ deployment of intelligent machines often blocks this critical learning pathway: My colleagues and I have found that it moves trainees away from learning opportunities and experts away from the action, and overloads both with a mandate to master old and new methods simultaneously.

How, then, will employees learn to work alongside these machines? Early indications come from observing learners engaged in norm-challenging practices that are pursued out of the limelight and tolerated for the results they produce. I call this widespread and informal process shadow learning.

Obstacles to Learning
My discovery of shadow learning came from two years of watching surgeons and surgical residents at 18 top-rated teaching hospitals in the United States. I studied learning and training in two settings: traditional (“open”) surgery and robotic surgery. I gathered data on the challenges robotic surgery presented to senior surgeons, residents, nurses, and scrub technicians (who prep patients, help glove and gown surgeons, pass instruments, and so on), focusing particularly on the few residents who found new, rule-breaking ways to learn. Although this research concentrated on surgery, my broader purpose was to identify learning and training dynamics that would show up in many kinds of work with intelligent machines.

To this end, I connected with a small but growing group of field researchers who are studying how people work with smart machines in settings such as internet start-ups, policing organizations, investment banking, and online education. Their work reveals dynamics like those I observed in surgical training. Drawing on their disparate lines of research, I’ve identified four widespread obstacles to acquiring needed skills. Those obstacles drive shadow learning.

1. Trainees are being moved away from their “learning edge.”
Training people in any kind of work can incur costs and decrease quality, because novices move slowly and make mistakes. As organizations introduce intelligent machines, they often manage this by reducing trainees’ participation in the risky and complex portions of the work, as Kristen found. Thus trainees are being kept from situations in which they struggle near the boundaries of their capabilities and recover from mistakes with limited help—a requirement for learning new skills.

The same phenomenon can be seen in investment banking New York University’s Callen Anthony found that junior analysts in one firm were increasingly being separated from senior partners as those partners interpreted algorithm-assisted company valuations in M&As. The junior analysts were tasked with simply pulling raw reports from systems that scraped the web for financial data on companies of interest and passing them to the senior partners for analysis. The implicit rationale for this division of labor? First, reduce the risk that junior people would make mistakes in doing sophisticated work close to the customer; and second, maximize senior partners’ efficiency: The less time they needed to explain the work to junior staffers, the more they could focus on their higher-level analysis. This provided some short-term gains in efficiency, but it moved junior analysts away from challenging, complex work, making it harder for them to learn the entire valuation process and diminishing the firm’s future capability.

2. Experts are being distanced from the work.
Sometimes intelligent machines get between trainees and the job, and other times they’re deployed in a way that prevents experts from doing important hands-on work. In robotic surgery, surgeons don’t see the patient’s body or the robot for most of the procedure, so they can’t directly assess and manage critical parts of it. For example, in traditional surgery, the surgeon would be acutely aware of how devices and instruments impinged on the patient’s body and would adjust accordingly; but in robotic surgery, if a robot’s arm hits a patient’s head or a scrub is about to swap a robotic instrument, the surgeon won’t know unless someone tells her. This has two learning implications: Surgeons can’t practice the skills needed to make holistic sense of the work on their own, and they must build new skills related to making sense of the work through others.

Benjamin Shestakofsky, now at the University of Pennsylvania, described a similar phenomenon at a pre-IPO start-up that used machine learning to match local laborers with jobs and that provided a platform for laborers and those hiring them to negotiate terms. At first the algorithms weren’t making good matches, so managers in San Francisco hired people in the Philippines to manually create each match. And when laborers had difficulty with the platform—for instance, in using it to issue price quotes to those hiring, or to structure payments—the start-up managers outsourced the needed support to yet another distributed group of employees, in Las Vegas. Given their limited resources, the managers threw bodies at these problems to buy time while they sought the money and additional engineers needed to perfect the product. Delegation allowed the managers and engineers to focus on business development and writing code, but it deprived them of critical learning opportunities: It separated them from direct, regular input from customers—the laborers and the hiring contractors—about the problems they were experiencing and the features they wanted.

A company’s deployment of AI may move trainees away from learning opportunities.

3. Learners are expected to master both old and new methods.
Robotic surgery comprises a radically new set of techniques and technologies for accomplishing the same ends that traditional surgery seeks to achieve. Promising greater precision and ergonomics, it was simply added to the curriculum, and residents were expected to learn robotic as well as open approaches. But the curriculum didn’t include enough time to learn both thoroughly, which often led to a worst-case outcome: The residents mastered neither. I call this problem methodological overload.

Shreeharsh Kelkar, at UC Berkeley, found that something similar happened to many professors who were using a new technology platform called edX to develop massive open online courses (MOOCs). EdX provided them with a suite of course-design tools and instructional advice based on fine-grained algorithmic analysis of students’ interaction with the platform (clicks, posts, pauses in video replay, and so on). Those who wanted to develop and improve online courses had to learn a host of new skills—how to navigate the edX user interface, interpret analytics on learner behavior, compose and manage the course’s project team, and more—while keeping “old school” skills sharp for teaching their traditional classes. Dealing with this tension was difficult for everyone, especially because the approaches were in constant flux: New tools, metrics, and expectations arrived almost daily, and instructors had to quickly assess and master them. The only people who handled both old and new methods well were those who were already technically sophisticated and had significant organizational resources.

4. Standard learning methods are presumed to be effective.
Decades of research and tradition hold trainees in medicine to the See one, do one, teach one method, but as we’ve seen, it doesn’t adapt well to robotic surgery. Nonetheless, pressure to rely on approved learning methods is so strong that deviation is rare: Surgical-training research, standard routines, policy, and senior surgeons all continue to emphasize traditional approaches to learning, even though the method clearly needs updating for robotic surgery.

Sarah Brayne, at the University of Texas, found a similar mismatch between learning methods and needs among police chiefs and officers in Los Angeles as they tried to apply traditional policing approaches to beat assignments generated by an algorithm. Although the efficacy of such “predictive policing” is unclear, and its ethics are controversial, dozens of police forces are becoming deeply reliant on it. The LAPD’s PredPol system breaks the city up into 500-foot squares, or “boxes,” assigns a crime probability to each one, and directs officers to those boxes accordingly. Brayne found that it wasn’t always obvious to the officers—or to the police chiefs—when and how the former should follow their AI-driven assignments. In policing, the traditional and respected model for acquiring new techniques has been to combine a little formal instruction with lots of old-fashioned learning on the beat. Many chiefs therefore presumed that officers would mostly learn how to incorporate crime forecasts on the job. This dependence on traditional OJL contributed to confusion and resistance to the tool and its guidance. Chiefs didn’t want to tell officers what to do once “in the box,” because they wanted them to rely on their experiential knowledge and discretion. Nor did they want to irritate the officers by overtly reducing their autonomy and coming across as micromanagers. But by relying on the traditional OJL approach, they inadvertently sabotaged learning: Many officers never understood how to use PredPol or its potential benefits, so they wholly dismissed it—yet they were still held accountable for following its assignments. This wasted time, decreased trust, and led to miscommunication and faulty data entry—all of which undermined their policing.

Shadow Learning Responses
Faced with such barriers, shadow learners are bending or breaking the rules out of view to get the instruction and experience they need. We shouldn’t be surprised. Close to a hundred years ago, the sociologist Robert Merton showed that when legitimate means are no longer effective for achieving a valued goal, deviance results. Expertise—perhaps the ultimate occupational goal—is no exception: Given the barriers I’ve described, we should expect people to find deviant ways to learn key skills. Their approaches are often ingenious and effective, but they can take a personal and an organizational toll: Shadow learners may be punished (for example, by losing practice opportunities and status) or cause waste and even harm. Still, people repeatedly take those risks, because their learning methods work well where approved means fail. It’s almost always a bad idea to uncritically copy these deviant practices, but organizations do need to learn from them.

Following are the shadow learning practices that I and others have observed:

Seeking struggle.
Recall that robotic surgical trainees often have little time on task. Shadow learners get around this by looking for opportunities to operate near the edge of their capability and with limited supervision. They know they must struggle to learn, and that many attending physicians are unlikely to let them. The subset of residents I studied who did become expert found ways to get the time on the robots they needed. One strategy was to seek collaboration with attendings who weren’t themselves seasoned experts. Residents in urology—the specialty having by far the most experience with robots—would rotate into departments whose attendings were less proficient in robotic surgery, allowing the residents to leverage the halo effect of their elite (if limited) training. The attendings were less able to detect quality deviations in their robotic surgical work and knew that the urology residents were being trained by true experts in the practice; thus they were more inclined to let the residents operate, and even to ask for their advice. But few would argue that this is an optimal learning approach.

When legitimate means can no longer achieve a goal, deviance results.

What about those junior analysts who were cut out of complex valuations? The junior and senior members of one group engaged in shadow learning by disregarding the company’s emerging standard practice and working together. Junior analysts continued to pull raw reports to produce the needed input, but they worked alongside senior partners on the analysis that followed.

In some ways this sounds like a risky business move. Indeed, it slowed down the process, and because it required the junior analysts to handle a wider range of valuation methods and calculations at a breakneck pace, it introduced mistakes that were difficult to catch. But the junior analysts developed a deeper knowledge of the multiple companies and other stakeholders involved in an M&A and of the relevant industry and learned how to manage the entire valuation process. Rather than function as a cog in a system they didn’t understand, they engaged in work that positioned them to take on more-senior roles. Another benefit was the discovery that, far from being interchangeable, the software packages they’d been using to create inputs for analysis sometimes produced valuations of a given company that were billions of dollars apart. Had the analysts remained siloed, that might never have come to light.

Tapping frontline know-how.
As discussed, robotic surgeons are isolated from the patient and so lack a holistic sense of the work, making it harder for residents to gain the skills they need. To understand the bigger picture, residents sometimes turn to scrub techs, who see the procedure in its totality: the patient’s entire body; the position and movement of the robot’s arms; the activities of the anesthesiologist, the nurse, and others around the patient; and all the instruments and supplies from start to finish. The best scrubs have paid careful attention during thousands of procedures. When residents shift from the console to the bedside, therefore, some bypass the attending and go straight to these “superscrubs” with technical questions, such as whether the intra-abdominal pressure is unusual, or when to clear the field of fluid or of smoke from cauterization. They do this despite norms and often unbeknownst to the attending.

And what about the start-up managers who were outsourcing jobs to workers in the Philippines and Las Vegas? They were expected to remain laser focused on raising capital and hiring engineers. But a few spent time with the frontline contract workers to learn how and why they made the matches they did. This led to insights that helped the company refine its processes for acquiring and cleaning data—an essential step in creating a stable platform. Similarly, some attentive managers spent time with the customer service reps in Las Vegas as they helped workers contend with the system. These “ride alongs” led the managers to divert some resources to improving the user interface, helping to sustain the start-up as it continued to acquire new users and recruit engineers who could build the robust machine learning systems it needed to succeed.

Redesigning roles.
The new work methods we create to deploy intelligent machines are driving a variety of shadow learning tactics that restructure work or alter how performance is measured and rewarded. A surgical resident may decide early on that she isn’t going to do robotic surgery as a senior physician and will therefore consciously minimize her robotic rotation. Some nurses I studied prefer the technical troubleshooting involved in robotic assignments, so they surreptitiously avoid open surgical work. Nurses who staff surgical procedures notice emerging preferences and skills and work around blanket staffing policies to accommodate them. People tacitly recognize and develop new roles that are better aligned with the work—whether or not the organization formally does so.

Consider how some police chiefs reframed expectations for beat cops who were having trouble integrating predictive analytics into their work. Brayne found that many officers assigned to patrol PredPol’s “boxes” appeared to be less productive on traditional measures such as number of arrests, citations, and FIs (field interview cards—records made by officers of their contacts with citizens, typically people who seem suspicious). FIs are particularly important in AI-assisted policing, because they provide crucial input data for predictive systems even when no arrests result. When cops went where the system directed them, they often made no arrests, wrote no tickets, and created no FIs.

Recognizing that these traditional measures discouraged beat cops from following PredPol’s recommendations, a few chiefs sidestepped standard practice and publicly and privately praised officers not for making arrests and delivering citations but for learning to work with the algorithmic assignments. As one captain said, “Good, fine, but we are telling you where the probability of a crime is at, so sit there, and if you come in with a zero [no crimes], that is a success.” These chiefs were taking a risk by encouraging what many saw as bad policing, but in doing so they were helping to move the law enforcement culture toward a future in which the police will increasingly collaborate with intelligent machines, whether or not PredPol remains in the tool kit.

Curating solutions.
Trainees in robotic surgery occasionally took time away from their formal responsibilities to create, annotate, and share play-by-play recordings of expert procedures. In addition to providing a resource for themselves and others, making the recordings helped them learn, because they had to classify phases of the work, techniques, types of failures, and responses to surprises.

Faculty members who were struggling to build online courses while maintaining their old-school skills used similar techniques to master the new technology. EdX provided tools, templates, and training materials to make things easier for instructors, but that wasn’t enough. Especially in the beginning, far-flung instructors in resource-strapped institutions took time to experiment with the platform, make notes and videos on their failures and successes, and share them informally with one another online. Establishing these connections was hard, especially when the instructors’ institutions were ambivalent about putting content and pedagogy online in the first place.

Shadow learning of a different type occurred among the original users of edX—well-funded, well-supported professors at topflight institutions who had provided early input during the development of the platform. To get the support and resources they needed from edX, they surreptitiously shared techniques for pitching desired changes in the platform, securing funding and staff support, and so on.

Learning from shadow learners.
Obviously shadow learning is not the ideal solution to the problems it addresses. No one should have to risk getting fired just to master a job. But these practices are hard-won, tested paths in a world where acquiring expertise is becoming more difficult and more important.

The four classes of behavior shadow learners exhibit—seeking struggle, tapping frontline know-how, redesigning roles, and curating solutions—suggest corresponding tactical responses. To take advantage of the lessons shadow learners offer, technologists, managers, experts, and workers themselves should:

ensure that learners get opportunities to struggle near the edge of their capacity in real (not simulated) work so that they can make and recover from mistakes
foster clear channels through which the best frontline workers can serve as instructors and coaches
restructure roles and incentives to help learners master new ways of working with intelligent machines
build searchable, annotated, crowdsourced “skill repositories” containing tools and expert guidance that learners can tap and contribute to as needed
The specific approach to these activities depends on organizational structure, culture, resources, technological options, existing skills, and, of course, the nature of the work itself. No single best practice will apply in all circumstances. But a large body of managerial literature explores each of these, and outside consulting is readily available.

More broadly, my research, and that of my colleagues, suggests three organizational strategies that may help leverage shadow learning’s lessons:

1. Keep studying it.
Shadow learning is evolving rapidly as intelligent technologies become more capable. New forms will emerge over time, offering new lessons. A cautious approach is critical. Shadow learners often realize that their practices are deviant and that they could be penalized for pursuing them. (Imagine if a surgical resident made it known that he sought out the least-skilled attendings to work with.) And middle managers often turn a blind eye to these practices because of the results they produce—as long as the shadow learning isn’t openly acknowledged. Thus learners and their managers may be less than forthcoming when an observer, particularly a senior manager, declares that he wants to study how employees are breaking the rules to build skills. A good solution is to bring in a neutral third party who can ensure strict anonymity while comparing practices across diverse cases. My informants came to know and trust me, and they were aware that I was observing work in numerous work groups and facilities, so they felt confident that their identities would be protected. That proved essential in getting them to open up.

2. Adapt the shadow learning practices you find to design organizations, work, and technology.
Organizations have often handled intelligent machines in ways that make it easier for a single expert to take more control of the work, reducing dependence on trainees’ help. Robotic surgical systems allow senior surgeons to operate with less assistance, so they do. Investment banking systems allow senior partners to exclude junior analysts from complex valuations, so they do. All stakeholders should insist on organizational, technological, and work designs that improve productivity and enhance on-the-job learning. In the LAPD, for example, this would mean moving beyond changing incentives for beat cops to efforts such as redesigning the PredPol user interface, creating new roles to bridge police officers and software engineers, and establishing a cop-curated repository for annotated best practice use cases.

3. Make intelligent machines part of the solution.
AI can be built to coach learners as they struggle, coach experts on their mentorship, and connect those two groups in smart ways. For example, when Juho Kim was a doctoral student at MIT, he built ToolScape and LectureScape, which allow for crowdsourced annotation of instructional videos and provide clarification and opportunities for practice where many prior users have paused to look for them. He called this learnersourcing. On the hardware side, augmented reality systems are beginning to bring expert instruction and annotation right into the flow of work. Existing applications use tablets or smart glasses to overlay instructions on work in real time. More-sophisticated intelligent systems are expected soon. Such systems might, for example, superimpose a recording of the best welder in the factory on an apprentice welder’s visual field to show how the job is done, record the apprentice’s attempt to match it, and connect the apprentice to the welder as needed. The growing community of engineers in these domains have mostly been focused on formal training, and the deeper crisis is in on-the-job learning. We need to redirect our efforts there.

CONCLUSION
For thousands of years, advances in technology have driven the redesign of work processes, and apprentices have learned necessary new skills from mentors. But as we’ve seen, intelligent machines now motivate us to peel apprentices away from masters, and masters from the work itself, all in the name of productivity. Organizations often unwittingly choose productivity over considered human involvement, and learning on the job is getting harder as a result. Shadow learners are nevertheless finding risky, rule-breaking ways to learn. Organizations that hope to compete in a world filling with increasingly intelligent machines should pay close attention to these “deviants.” Their actions provide insight into how the best work will be done in the future, when experts, apprentices, and intelligent machines work, and learn, together.

A version of this article appeared in the September–October 2019 issue of Harvard Business Review.
Matt Beane is an assistant professor of technology management at the University of California, Santa Barbara, and a research affiliate with MIT’s Initiative on the Digital Economy.

Source: https://hbr.org/2019/09/learning-to-work-with-intelligent-machines

Keys to effective succession planning: Talent management special report

Are changes in your market forcing a change in strategy that will demand new talent?

Have one or more of your long-time stars started thinking about moving to a competitor or retiring?

Or are you just trying to make sure the wheels keep turning for a few weeks or months if one of your top people gets sick or dies unexpectedly?

Succession planning is a talent management must-do for organizations of all sizes, whether a global corporation, a small non-profit, a mid-sized college or a family business with a dozen employees.

Long-term success depends on creating a plan for how you’ll keep your team moving forward when you lose a key player or encounter a skills gap that must be filled quickly.

It brings focus to the process of identifying top performers, employees with strong potential and the people that you need to push hard or push out.

For employees, the succession planning process translates into stretch opportunities that can help them learn new skills, advance their careers, increase their value to the team and boost earning power. All of those positives can translate into an increased commitment to your organization.

What are you planning for?
It’s important to differentiate succession planning from other strategic staffing plans, says William J. Rothwell in a Dale Carnegie white paper entitled The Nuts and Bolts of Succession Planning.

What it’s not is replacement planning, Rothwell says. That’s the process of identifying individuals within an organization, and often in the same division or department, who would be best-equipped to serve as backups for current employees.

While replacement planning is an important part of an organization’s overall operating strategy, succession planning takes a much broader viewpoint – it encompasses the total operation, rather than individual positions, departments or divisions.

As Robert E. Lewis and Robert J. Heckman put it in their oft-cited paper, Talent management: A critical review:

Consider the following question, If you were to begin the process of constructing a building how would you go about it? Would you assemble a group of the best professionals in each necessary craft (plumbing, electrical systems, carpentry, etc.) and let them define your building? Or, would you start with an analysis of the relationship between “construction practices” and some outcome you hope to achieve (building longevity or cost of operation)? Probably not. You probably would first meet with an architect to begin drawing a blueprint after considering a series of key questions such as, what do you hope to accomplish with this building? Will those goals appeal to the intended customers (tenants or shoppers)? What alternatives for orienting the building on its site best accomplish its purpose?

It is always important to be clear about the end-goal of any strategic planning effort and succession planning is no different.

The first thing to do is figure out your plan’s target and scope. To be effective, the succession planning process should be:

Formal. While a succession planning process needs to match an organization’s overall culture, whether buttoned down and hierarchical or more casual and egalitarian, everyone involved needs to understand that this is a well-defined process with support from top leadership and mission-critical outcomes at stake.

Comprehensive. It’s tempting to think of succession planning as applying only to senior leadership roles, but an effective plan will look at critical positions and people at every level of the organization.

Strategically Linked. Every aspect of your succession plan needs to support the organization’s overall strategy. That is the guiding star that will help to define the kinds of people and types of training you need to put in place as you build a talent pipeline to the future.

Linking Succession Planning to Your Strategic Plan
A paint-by-numbers succession planning effort is doomed to give you an uninspired and amateurish result. Only by matching your succession planning to your organization’s guiding strategy can you confidently identify the positions, skills and employees needed to succeed.

Whatever your organization’s size and your target, a succession plan should focus on four specific outcomes:

Identify mission-critical positions and any current or impending talent gaps – based on the strategic opportunities you identify and how you create competitive advantage. Which jobs and skills are must-haves? Do those positions already exist or do we need to create them?
Identify employees at every level who have the potential to assume greater responsibility advancing your organization’s strategic goals and how they fit together – what combination of A, B and C performers do we need and how do we attract and keep them?
Encourage meaningful investment in a training and development program for high-potential employees – be ready to defend allocating resources to a given talent pool(s) or to talent in
general rather than technology, marketing or other investments.
What is the process for revisiting and revising your succession plan as conditions change?
With those factors in mind, how do you go about building and refining a succession plan? Here’s some help.

Building a team
You’ve committed to building a succession plan, now its time to think about who you need on the team who will do the work. You need to decide who will design the plan and also determine who will be responsible for implementing and evolving your plan when it’s in place.

You’ll want to include people with different skills and from a variety of functions when assembling the succession planning team.

Of course, in smaller organizations, team members are going to wear multiple hats.

Some of the needed skills include:

Organization and process-orientation. While the succession planning effort itself needs to focus on goals, you’ll want someone on the team who will keep things moving along during the plan development phase.

That person needs to have enough authority to give other members assignments and to get answers from various departments.

Organizational knowledge. The team needs to include someone with a solid handle on most of the organization’s existing job descriptions and insight into any new positions that might be needed to accomplish the goals you’ve set.

And at least one member of the team should have connections throughout the organization and know who they can approach to build support for the succession planning effort.

Effective communication. Like many other strategic initiatives, the information gathering phase of succession planning can create nervousness and give rise to rumors about job changes (often true) or massive job losses (often false).

Keeping the rest of your organization working productively while this is going on requires skillful communication to share enough information to keep a lid on any panic-button pushers.

If handled well, giving employees insight into the process can help reassure them that company leaders are preparing the organization for the long haul.

Identifying strengths and weaknesses
So, you’ve committed to building a succession plan and picked your team. What’s their next step?

It’s time to brainstorm. What are all the internal and external factors that your plan needs to account for? Here are some questions to consider:

Organizations face increasingly rapid changes in macroeconomic, industry and social trends — which ones can you anticipate and prepare for?
Competition can come from anywhere in the world. How will you keep an eye on — and respond to — new challenges?
Does your team have all the skills you’ll need? Can training fill the gaps or will you need to hire?
Boomers are retiring and the generational mix of your workforce will look very different soon. What do demographic changes mean for your organization?
The research is clear: companies with a diverse workforce outperform the competition. How will you leverage succession planning to increase diversity in your line organization and leadership team?
Do you need to change your org structure and talent management processes to match these challenges?
Build or Buy? Finding the right people
The first phase of this part of the process is to identify key/critical positions, ideally at every level of the organization. A position is determined to be key or critical under the following criteria:

Organizational structure — The position is a key contributor in achieving the organization’s mission
Key task — The position performs a critical task that would stop or hinder vital functions from being performed if it were left vacant
Specialized competencies — The position requires a specialized or unique skill set that is difficult to replace
Geography — The position is the only one of its kind in a particular location or it would be difficult for a similar position in another location to carry out its functions remotely,
Potential high turnover job classes — Positions in danger of “knowledge drain” due to impending retirements or high market demand for the skill set, and
Future needs — based on the SWOT analysis that launched the succession management project, positions that need to be created and defined.
Skillset analysis
Once critical positions and areas at risk of high turnover are identified, it’s time to look at the specific competencies required to do those jobs effectively.

The questions you need to ask during the skill set analysis are closely related to the strategic questions your team addressed in the first part of this process:

What are the external and internal factors affecting this specific position?
How will the position be used in the future?
What competencies or skillsets will be required?
What is the current bench strength?
How will you provide stretch opportunities to high-potential employees?
What is the path from where they are to where you need them to be? and
What are the gaps (competencies or skillsets not possessed by current employees)?
At the end of this analysis you will have the answer to the most important succession planning question: “Can we develop our existing pool of internal candidates quickly enough or must we ramp up our search for strong outside candidates?”

The good news is you now have a clear idea of what you have and what you are still looking for and can move on to the next steps in the process, which we look at in other reports in our HR Morning talent management series:

designing the right training programs for each talent pool based on strategic importance, available resources and growth path
refining your recruiting plan to maximize your chances to get the most from your recruiting efforts, to use your time and energy wisely and effectively, and to pursue only the most likely paths to recruiting success and
retaining key personnel.

Source :https://www.hrmorning.com/articles/succession-planning-talent-management/

Matching talent to value

We’re really testing for, where is the hard-core
work and strategic decision making and leadership
happening? In the cybersecurity example, one of
the things that we look for frequently and have
discussions about is, how much value is at risk?
And how much do we want to assign in terms of
protecting risk? That’s where cybersecurity roles
come in rather frequently.
Mike Barriere: One thing I would emphasize is the
front end of this. When you think of value drivers,
let’s say you think of some that might be around
organic growth, let’s say revenue growth as an
example. You start to look across the organization.
Let’s say you want to grow a billion dollars on the
top line. You look at your commercial groups, sales,
and marketing. You look at product or operations,
depending on your business, and then you look at
those enabling functions.
You could literally take a billion dollars of top-line
revenue growth and say, OK, 30 percent of that has
to come from sales and marketing. They have to go
out and create the demand. But obviously, that’s
not all of it. We have to deliver the product. Maybe
there’s an R&D contribution, or maybe there’s a
real operations component. These are the creator
roles, because they’re so important to generate
the demand for, in this case, the top-line revenue
growth, as well as the delivery.
So maybe 30 percent is in sales and marketing,
another 30 percent in operations. Now you still
have 40 percent of that value, which could come
from these enabling functions like technology or
HR to provide the talent to the sales teams or the
operations teams. You start to build this mapping—
and we have a great way to model this—of the
value driver. What functions are contributing what
percentage of that value? Then that’s where you
get into the valuation of the role.
Let’s say you take 30 percent of a billion [dollars] into sales and marketing, there’s a value there, and
you say, OK, well, there’s seven roles in marketing
that are absolutely essential to grow top-line
revenue. They’re those key account managers
that we’ve been using as an example. You then
distribute that value across those roles. There
are some heuristics that we work with, some
percentages, whether you’re a creator or enabler
type of role. But the beauty of putting this into a
model is that then you can do sensitivity analysis.
So maybe it’s 60 percent on the front end and only
20 percent on the product side, or vice versa. You
can quickly see the impact on the kind of roles that
pop up.
Simon London: So we’ve had a robust conversation
as a management team about what our value
agenda is. We’ve hammered out some areas of
ambiguity. We’ve done the hard work of then
identifying the roles that are really going to matter
over the next few years. What happens next?
Mike Barriere: The fun stuff. First is, if these are
the roles, what does success look like? I come
from HR, so I can pick on myself. Usually, HR
doesn’t have up-to-date, nimble, and dynamic role
descriptions that capture what a role needs to
do today.
This is part of the issue, Simon, where a lot of our
HR processes are dated and not designed for this
period of exponential change and disruption. The
first thing, when you say this is a critical role, we all
agree it’s one of the top 50, is to define, and Carla
mentioned it, a role card.
A role card consists of the mission for the job, and
then in language of jobs to be done, what are the
five to seven things that are most important that
this role has to accomplish to be successful? You
also know the value that the role should capture.
It should be written in a language that’s clear,
concise, and tied to those value drivers that we
talked about.
Some roles might hit two or three or even four
value drivers, and you want to be clear that this
is exactly what needs to be done in the role to
capture that. That’s half the role card. The other
half is, how are you going to assess somebody
against those requirements?
Matching talent to value 5
Role descriptions were designed to stand the test
of time. A lot of them are old, static, they’ve been
around. Compensation teams use them to price
jobs relative to market. Search firms use them.
We’re talking about something different. We need a
much more nimble, concise way to think about jobs
and design jobs, so you don’t get this phenomenon
of double-, triple-hatting somebody, or having
them do 60 percent non–value-add work.
We want to be really crisp, and that’s why we
even changed the language to role card, not a job
description, because you want to be clear about,
this is what this role needs to do over, like, a threeyear time horizon, and this is the value that you can
measure success in the role against.
Simon London: It’s a hybrid between a role
description and your annual objectives, somewhere
in the middle there. It’s a different critter.
Carla Arellano: Yes, very much so. When we’ve
developed these baseball cards or role cards for
leaders, one of the first things that happens is
the reaction that, oh, we have the person in this
role doing 50 other things that are not on that list,
usually followed by, how would we expect them to
actually deliver this, when we have them doing all
these other things. And are they best placed for
everything else?
The other thing, where Mike was going with this
notion of the knowledge, skills, attributes, and
experiences, is that most organizations have
moved people into roles based on the fact that they
were successful in this other role, or somebody
likes them and knows them, and they’ve worked
well together for a very long time.
But the focus should instead be on, do we want
somebody who can build a team of very diverse
profiles to go do something different or hard?
Or do we want somebody who can be a strategic
negotiator with customers? Those are very
different requirements for a role. Getting specific
on those and how you might measure it can be
hard. But the rewards are very high.
Mike Barriere: Now we’re going into the third
step, which is the matching. We defined the value
agenda, the drivers, we know where the critical
roles are in the organization, we write the role cards,
and now it’s time to assess and match the talent.
A lot of times you’ll find that you don’t have your
best talent in a good percentage of the critical
roles and your best talent is somewhere else and
not even on the radar for these kind of roles. That’s
why the matching is really important.
Simon London: What’s the percentage of
mismatch? When you do this for the first time,
do you find that organizations are 70 percent
mismatched? Or in most organizations is it more
like 10 percent of the roles cause some serious
head-scratching and conversations once these
cards are laid out?
Mike Barriere: What comes to mind is a recent
experience where we found 45 percent of the roles
were a great match. The incumbent was the best
fit. Twenty percent to 30 percent typically have
gaps, but they’re addressable. They do have some
gaps, but they are the best talent you have, and if
you have clarity about how to help them address
their gaps—which we can get to in a minute, the
techniques for that—typically, it could be in the
ballpark of 20 to 30 percent that are mismatched.
It doesn’t mean you fire them. It means that there’s
probably a better role for them, or you’ve got to
look either internally or maybe go external.
These are not the roles you want to give somebody
a stretch assignment for. These are your critical
roles that are going to deliver value, so you really
want to put your best players in these roles.
Carla Arellano: I think the other thing alongside
that, Simon, that I’ve seen frequently is looking at
the team around a role or looking at the team of
roles. Because you might find that there’s a gap
of an incumbent to a role. You might also find that
across a team, there’s a core missing experience
or capability set that you need to complement in
some way.
6 Matching talent to value
I have an organization that’s been going through
a restructuring for quite a while. None of the
individuals in critical roles had actual restructuring
experience, which was a little bit of a flag. It wasn’t
that every single one of those roles needed to have
it, but it was important that at least one or two of
them did to get there. There’s that individual view,
and then there’s a little bit of a team view as well.
Simon London: This goes back to my slight
skepticism about how easy it is to assign value to
roles, because I think we’re acknowledging that so
much of what goes on in an organization is a matter
of team production. There are teams delivering
value, not individuals.
If you say you need to reinforce a role by
bringing in somebody else as a wingman—it’s
a gendered phrase—but a wingman effectively
who compensates for one element. Aren’t you
immediately beginning to undermine this idea that
it’s that role and that role alone that’s delivering
the value?
Mike Barriere: No, I have a very strong view on that.
A critical role leader needs to absolutely leverage
the team—and it might not even be their own team.
There could be an important collaboration across
function or function to a business unit or across a
business unit.
Now we’re getting into, how do you optimize value
capture for that critical role leader? They’re on
the hook. You need somebody responsible. If you
just try to tackle it from the team dynamic, you’re
going to miss something. We like to think that
there’s a critical role leader that’s on the hook, but
part of their success is going to be driven by how
well they build the team around them and how well
they can build cross-functionally or collaborate
horizontally in the organization. It doesn’t put teams
aside and say it’s only the role that’s important.
To be successful in the role, team competency is
absolutely essential.
Simon London: Ultimately somebody has to be
on the hook, though. I think that’s the message.
Somebody has to own the delivery of that value.
Mike Barriere: Exactly, because that happens a
lot. You take a team approach or you do something
broad strokes without really having that person
who you look at and say, that’s their role, the
value is tied to them in that role. But the way they
succeed involves not only the team, it involves
the workforce. And does the workforce have the
capabilities? What about the culture, how they
run the place. Do they take out organizational
bureaucracy, so they can move with speed and
agility? A lot of the organizational things light up
here, but this is the front end to prioritize the role.
Then how do you make a leader successful in that
role vis-à-vis the top team and the organization and
the capabilities and the culture to run the place?
Simon London: Do you get pushback from
organizations at that cultural level? That doing this
in this way just feels kind of countercultural?
Carla Arellano: Definitely. Maybe more than
pushback, there tends to be a very deep-seated
philosophical question for organizations. One,
about what’s the difference between critical and
important, and how do we make sure that we’re not
creating a stratification of our workforce and making
some people feel more important than others?
A lot of organizations—this is going to sound a little
bit harsh—confuse fairness with, everybody has
to get everything the same no matter what. They
end up struggling to feel comfortable doing the
approach, and then figuring out what they would do
differently for that group of critical roles than they
might do for other roles in the organization.
There’s also this sense of what’s the urgency?
And where Mike was going about the culture
and the agility that you create in an organization,
to make sure that those critical roles are able
to be successful and deliver on the value. That
likely will require a shift from the way things are
normally done to drive forward a different sense
of urgency than you might have had in terms of
certain things.
Mike Barriere: I have two principles related to
this, Carla. It’s that development matters for
Matching talent to value 7
everybody. Every employee in an organization
should have the opportunity to reach his or her full
potential, and you want to provide that, especially
as leaders.
While that’s important, it’s also important to
think about the future of the company. Therefore,
who are those talents that you absolutely want
to get into the most critical roles? You need to
do both, but many times, we only do the broader
set. Because there’s a culture that it’s one team,
rather than there being a specific set of certain
people. That’s why we really put the emphasis on
the roles that matter, and then not only looking for
the 50 people, but what’s the succession pipeline
behind them?
There could be a couple hundred people that you’re
also developing to be ready to take those roles in
the future.
Simon London: It’s true, every organization treats
people differently. It’s just that we’re used to doing
it based on hierarchy. The difference here is, we’re
focusing on value first and role first, and that can
feel a little unusual. But it’s not like everybody in
an organization gets the same treatment today
anyway. Hierarchy takes care of that.
Mike Barriere: I’d add that it is hierarchy, but it’s
also the definition of top talent, or when you use
the nine box to try to find out who are our highest
potentials. Companies segment already, but they
segment the talent, not the roles. Then you need
more of a fact base of who has the potential? And
potential for what?
We’re saying it’s potential to be successful in
critical roles. To leverage the fact that most
companies are already segmenting talent, we’re
saying, segment the roles first, and then match
the talent and get that right, and then broaden
it. Broaden development and leadership and
opportunity and tackle it that way.
Simon London: If you think about what a CHRO
needs and what a good HR function needs in a
company that’s going to do all this well, what are
the gaps that we often see?
Mike Barriere: The first part is guts. The CHRO
has to have the moxie to push up against the
CEO and the CFO, the exec team, and call out if
the value agenda is not clear. If it’s ambiguous
or fluffy or ownership is not quite there, this is
the moment that a CHRO can really say, “Hey, if
we want to leverage our human assets, we need
much more clarity about drivers and where in
the organization is the most critical, because we
want to deploy our talent just like you would think
about deploying the financial capital.” The role
of the CHRO, particularly with the G3, is to
increase awareness and to lead. We need to take
our value agenda and our value drivers into
the organization.
From there, the CHRO does need a good sense
of the business and the industry and what are the
trends. To Carla’s point, the CHRO is an officer first,
and you happen to have an HR talent tool kit, but
the role is about understanding the business, the
business dynamics, the ways that the company can
achieve value in the future.
Carla Arellano: Mike, one of the things that you
said really jumps out at me. CHROs are probably
most comfortable, but I think if you get into some of
their teams, there tends to be less comfort. And it’s
this concept of really knowing the business and the
industry and how it makes money.
What I tend to find is, it might be that an HR leader
understands it but might feel uncomfortable
engaging a business leader on where value is going
to come from, and why they think they’re going
to achieve a certain margin, or what is the plan to
capture that digital growth?
There’s something about what you said earlier
on, having the moxie but also enabling that in
your team and giving them the comfort level
that they have just as much right, as well as
the demand on them to really understand what
needs to happen and by whom, so that they can
engage productively.
8 Matching talent to value
Simon London: So, I think we’re out of time for
today. Carla and Mike, thank you so much for
doing this.
Carla Arellano: Thank you, Simon, it was a pleasure

Source: https://www.mckinsey.com/business-functions/organization/our-insights/matching-talent-to-value

Performance management in agile organizations

Performance management is tough enough in traditional organizations;
in agile organizations, three changes are essential to success.

The evidence is clear: a small number of priority
practices make the difference between an
effective and fair performance-management
approach and one that falls short. Organizations
that link employee goals to business priorities,
invest in managers’ capabilities, and differentiate
rewards for the extremes of performance are
84 percent more likely to have performancemanagement approaches that their employees
perceive and recognize as being fair. Furthermore,
these practices are mutually reinforcing:
implementing one practice well can have a positive
effect on the performance of others, which leads
to positive impact on employee and organizational
performance, which, in turn, drives organizations to
outperform peers.
But how do these priority practices work in the
context of agile organizations, which feature
networks of empowered teams and rely on a
dynamic people model? Colleagues rightfully ask a
number of related questions:
— Why do I need individual goals when the locus of
organizational performance is my squad, chapter,
and tribe?
— Who will coach and evaluate me when I have no
boss? How can my evaluator understand my
performance when he or she doesn’t see my
work day to day?
— How can we maintain a team spirit while still
fairly differentiating the highest- and lowestperforming colleagues?
The good news is that there are answers to these
questions—and, going further, agility can be a
springboard to improve performance-management
practices that traditional organizations struggle with
What defines an agile organization
“Traditional” organizations, designed
primarily for stability, involve a static,
siloed, structural hierarchy. Goals and
decision rights flow downward, with the
most powerful governance bodies at the
top. These organizations operate through
linear planning and control to capture
value for shareholders. Although such a
structure can be strong, it is often rigid
and slow moving.
In contrast, agile organizations
are designed for both stability and
dynamism. They are made up of a
network of teams within a peoplecentered culture that features rapid
learning and fast decision cycles
enabled by technology and guided by a
powerful common purpose to cocreate
value for all stakeholders. Such agile
operating models allow for quick and
efficient reconfigurations of strategy,
structure, processes, people, and
technology toward value-creating
and -protecting opportunities. Agile
organizations thus add velocity and
adaptability to stability, creating a
critical source of competitive advantage
in volatile, uncertain, complex, and
ambiguous (VUCA) conditions.
Five trademarks distinguish these
organizations:
— a North Star embodied across
the organization
— a network of empowered teams
— rapid decision and learning cycles
— a dynamic people model that
ignites passion
— next-generation-enabling
technology

2 Performance management in agile organizations
(Exhibit 1). Nearly all organizations, for example, feel
the need for more frequent feedback. Working in
agile sprints of a few weeks each creates a cadence
into which collective and individual feedback
naturally fits. Similarly, a culture of more autonomy
and risk taking opens opportunities for employees
to stretch, take on more responsibility, and find out
quickly how they can improve.
Agile organizations will, however, need to adapt each
of three core performance-management practices
to make the recommendations actionable in the
agile operating model (Exhibit 2).
Linking goals to business priorities
Transparently linking employees’ goals to business
priorities and maintaining a strong element of
flexibility are core practices of agile ways of working.
They are also significant practices if employees are
to have a sense of meaning and purpose in their
work. But agile organizations may worry about
how the emphasis on individual goals marries with
the autonomous teams that characterize agility.
There are three approaches that can help agile
organizations to adapt and ensure that goals remain
meaningful and linked to business priorities.
Introduce team objectives in addition to (or
instead of) individual targets
Empowered and autonomous teams are central to
agility. It therefore makes little sense to manage
performance solely—or even primarily—on an
individual level. Successful agile organizations
focus on team performance when setting goals and
evaluating performance, often allowing teams to
define their own goals to drive ownership. At one
bank, for example, performance objectives are a
combination of team goals, individual contributions
to the team, mastery of competencies required

The five trademarks of agile organizations have profound relevance for
performance management.
Trademark Changes aecting traditional performance management
Leadership sets broad direction and priorities, against which teams dene their own
objectives, iterating at pace
Flat organizational structure with limited hierarchy and no middle
management
Empowered and autonomous teams, with end-to-end accountability and
clear purpose
Risk taking, failing, and learning fast are encouraged
Continuous people development aimed at improving the level of performance
Culture that empowers the agile way of working
Craftsmanship (ie, development of expertise) as a cornerstone
Performance management isn’t materially di…erent just because of enabling tech
North Star embodied across
the organization
Network of
empowered teams
Rapid decision and
learning cycles
Dynamic people model that
ignites passion
Next-generation
enabling technology
Performance management in agile organizations 3
at the level of individual jobs, and alignment of
professional behavior to the bank’s values. The
weighting of these components varies by role, with
specialists, in particular, more inclined toward team
performance to encourage collaboration. Another
financial institution experimented with replacing
individual objectives in contact centers with team
objectives. Within a few months, it saw productivity
gains of more than 10 percent, compared with
control-group centers, in addition to a noticeable
increase in teamwork and cohesion.
Set objectives as a team, discuss results
frequently, and pivot as required
Teams in agile organizations work autonomously
and at pace, with a clear focus on output. They
follow broadly set directions and strategic priorities
rather than detailed, top-down instructions (Exhibit
3). Agile organizations typically rely on a tightly run
process—often a quarterly business review (QBR)—
to ensure alignment among the autonomous teams.
This is where objectives and key results (OKRs),
popularized at Intel in the 1970s and now used in
many organizations, from the Bill & Melinda Gates
Foundation to Google, come in. Every quarter, a
clear cascade from strategic priorities to objectives
at the team level is created, while performance
versus key results is made transparent and
discussed. To allow for changing priorities coming
out of the QBR, team and individual objectives
need to be dynamic, rather than fixed in a once-ayear exercise. Setting objectives collectively can
have other benefits, too, particularly with regard
to engagement and ambition. Unsurprisingly,
commitment to goals that you have set for yourself is
typically stronger than to those set for you by others.
At a B2B sales organization, shifting to bottom-up
goal setting (versus top-down setting by executives)
resulted in 20 percent higher overall targets.
Create transparency of targets and performance

Adapting three core performance-management practices will be crucial.
Performance-management practice What agile organizations may want to do
Introduce team objectives in addition to (or instead of) individual targets
Set objectives as a team, discuss results frequently, pivot as required
Create transparency of targets and performance
Clarify the roles that leaders play in development and evaluation
Focus on continuous feedback and ongoing development conversations
Frequently collect input from multiple sources when evaluating performance
Dierentiate individual contribution to team performance based on desired values,
mind-sets, and behaviors
Increase the emphasis on intrinsic motivation and nonmonetary rewards
Linking goals to
business priorities
Investing in managers’
coaching skills
Dierentiating
consequences
4 Performance management in agile organizations
creates a risk that devolution and empowerment
might drift into chaos. One way to avoid this is to
introduce extreme transparency of objectives and
performance. At Google, all OKRs, starting with
the CEO’s, are visible to all other employees. At
LinkedIn, the CEO’s executive team reviews OKRs
weekly. This kind of transparency also has several
benefits: surfacing interdependencies among teams
and units, creating urgency and “mindshare,” and
reinforcing the nonhierarchical culture and mind-set
that characterize truly agile organizations.
Investing in the coaching skills
of managers
Our prior research shows that managers—
typically, line managers—are important stewards
of effective performance management. Investing
in their coaching skills to help them become
better arbiters of day-to-day fairness is often
the most powerful intervention in performancemanagement transformations. The agile
organization, however, challenges the traditional
model of the line manager. Who, then, acts
as the day-to-day arbiter of fairness? And
whose capability needs to be built? Agile

Businessexpansion
goals are
assigned to
one tribe
Project is
assigned to
chapters and
squads
Project is
assigned to one
squad
Product owners
translate the
project into
OKRs1
Chapter leads or
product owners
meet with individuals to
set goals
Executive board
sets goal
to expand
business
into China;
communicates
strategic
direction to
chapter and tribe
leads.
“We will be in
China next year”
Tribe leads
provide
feedback and
further shape
organization
goal.
“We will achieve
xx sales in
China by end of
year; Jason will
lead this”
Tribe and chapter leads
translate project into
tribe, chapter, and
individual OKRs.
“We will have our oce
opened and our rst
customer in China by
end of quarter; Mary will
take care of
opening oce and John
of business
development”
Product owners
provide
feedback and
further shape
tribe and
chapter goals.
Mary:
“We will
open our
rst oce by end
of quarter”
Tangible OKRs
are set.
“We will hire x
people in y
functions, have
regulatory
requirements xyz
fullled, have an
oce space rented,
and all IT
infrastructure
bought and set up
by end of quarter”
Assess individuals on impact against
business goals and desired
behavioral attributes.
For „ow-to-work and
mono-skilled teams, chapter leads
meet with all part-time members to
set goals.
For the cross-functional squad for
opening the o‡ce, product owner
meets with individual squad members
(eg, sales, government relations,
supply chain, HR, IT) to set goals.
Performance management in agile organizations 5
organizations can address these questions
through three approaches.
Clarify the roles that leaders play in development
and evaluation
In a prior publication, we described three different
types of managers in agile organizations. In the
context of performance management, each
performs different roles. Chapter leaders evaluate,
promote, coach, and develop their people. Tribe
leaders set directions linked to business priorities,
match the right people to opportunities or squads,
coach their teams on how to enable collaboration
across organizational boundaries, and empower
people. Squad leaders strive to maintain a cohesive
team by inspiring, coaching, and providing feedback
to everyone. The common theme across these
leaders is active coaching for ongoing development
and arbitration of day-to-day fairness.
Focus on continuous feedback and ongoing
development conversations
As in any organization, individuals in agile
organizations develop through receiving feedback
and being exposed to development opportunities.
In successful agile organizations, feedback is
the heartbeat in a culture of taking risks,
failing fast, and pursuing continuous personal
development at all levels. These organizations
encourage employees to ask for and give feedback
constantly. Making this happen is often hard.
Managers and nonmanagers alike may need to
overcome mind-set and capability barriers to
giving and receiving feedback more frequently—
not just up and down the hierarchy, but also to
peers. A European financial institution, for example,
invested in dedicated capability building for teams
on how to have courageous conversations in a
peer-like way.
Frequently collect input from multiple sources
when evaluating performance
Agile organizations need disciplined rituals for
continuously gathering feedback and evaluating
performance (Exhibit 4). The line manager has
traditionally been the conduit for all information
about the employee. But without the line manager,
who acts for the employee? This requires a single
person to gather feedback on an individual from
several sources, synthesizing it, and working
with other peers to make sure that evidence and
decisions are calibrated. At a telco, for example,
a chapter lead1
evaluates the development of
an individual within the chapter, gathering and
synthesizing input from the product owners, team
members, and agile coaches that the individual has
worked with. The chapter lead then presents the
individual’s case to a people-review board made
up of chapter leads. The board makes a collective
performance decision and provides advice to the
individual on how to develop further, which is then
relayed by the chapter lead. Technology can help
here. A leading e-commerce player developed an
app for its employees that facilitates feedback and
allows employees to share feedback with others
after every interaction, the aim being for each
employee to collect more than 200 feedback points
during the year.
Differentiating consequences
Employees are more likely to view their
performance-management approach as fair if
outcomes are differentiated, particularly at the two
extremes of performance. In some ways, this can be
harder in agile organizations, at which collaborative
and highly interdependent teams mean that it is
difficult to trace results to individual efforts. Two
practices can help maintain differentiation and the
accompanying sense of fairness, without detracting
from the team spirit.
Differentiate individual contribution to team
performance based on desired values, mind-sets,
and behaviors
Successful agile organizations embody agile
methodologies and ways of working that are
tangible and visible in day-to-day work. Less
tangible, but a critical stable practice of agile
organizations, is culture—the strong, shared
1 Chapters are groups of employees with similar functional competencies who share knowledge and further develop expertise. The chapter lead
typically coordinates performance evaluations of the chapter’s members.
6 Performance management in agile organizations
values, mind-sets, and behaviors that underpin
and enable those methodologies and ways of
working. Successful agile organizations evaluate
and manage performance of individuals not just
against hard targets but also by the extent to
which the individual has shown and “lived” the
desired values, mind-sets, and behaviors. Potential
rewards or consequences should be well aligned
with these goals. In the case of a telco, for example,
rewards for sales teams are based on achievement
against individual and team targets in addition
to how well and how often employees offer
coaching and mentoring to their team members.
These contributions should be well codified and
recognized because they both motivate individuals
and create “pull” for the next opportunity.
Conversely, organizations should make clear
choices with employees who don’t actively live and
show the desired values, mind-sets, and behaviors,
as in the case of a fintech company at which
individuals not aligned with its core cultural values
and defined associated behaviors are simply let go.
Increase the emphasis on intrinsic motivation
and nonmonetary rewards
Work at most successful agile organizations is
characterized by a sense of fulfillment and fun: it
is common to hear employees describe how their
daily activity “does not feel like work.” Netflix offers
flexible benefits, such as unlimited vacation days.
Employees stay because they are passionate about
their work and the unique culture. While individuals

Mary compiles exposure list from
people she had signicant
interactions with during cycle in
review; her list includes some
description of the type of
interactions, and her chapter
lead approves the list
Mary holds regular one-on-one
interactions with her chapter
lead to discuss achievement of
OKRs.1
“…it is taking longer than
expected to hire people as the
HR lead had to leave due to a
family emergency…”
Mary’s chapter lead
sources feedback
from her exposure
list, ensuring leaders,
peers, and subordinates provide input
“Can you tell
me about your
experience working
with Mary? What
impact did she have
on the team?”
Chapter lead
summarizes Mary’s
performance and
recommends a rating
“…in summary, Mary
opened the oce with a
1-month delay. However,
she retained the same
contractors and our next
oce will be open ahead
of time.”
Mary’s chapter
lead presents her
case in calibration
meeting and
updates her memo
accordingly
“Is this enough to
justify a top
performer?”
Mary receives
executive feedback
when her chapter lead
presents calibrated
results to her
“Congratulations,
you achieved your
goals in the cycle!
Let’s go into the
details …”
Performance management in agile organizations 7
expect to be paid fairly for their contributions,
offering flexible benefits gives agile organizations
an opportunity to place greater emphasis on
intrinsic motivation and frequent nonmonetary
rewards—including special assignments,
opportunities to present externally or attend special
events, high recognition in the workplace (awards
and celebrations), and time for pro bono work. For
example, a North America–based fintech company
offers unique leadership-exposure opportunities
and mentorship programs to reward performance
and increase retention.
Organizations embarking on agile transformations
cannot afford to ignore performance management.
Even teams undergoing pilots need to be ringfenced from traditional approaches to ensure that
agile practices and mind-sets have the freedom
to take hold and are appropriately recognized and
rewarded. Done well, performance management
that is customized to the agile goals and context
of an organization will enable full capture and
sustainability of the benefits promised by agility.

Source :https://www.mckinsey.com/business-functions/organization/our-insights/performance-management-in-agile-organizations

Blockchain Realities in Recruitment

Every HR professional tasked with finding the best talent for their companies is looking for tools to aid them in the charge. Some are turning to AI. Others are employing a change in their benefits strategy that makes the company more attractive to job candidates. Of course, those are just some of the more popular ones.

Then there are those options that are more “pie in the sky” concepts, at least that’s what they seem to be at the moment. Among them: blockchain.

More than likely the word blockchain conjures up thoughts of cryptocurrencies such as BitCoin. While that would be an appropriate thought, blockchain technology represents more to the HR professional than a way to track monetary changes online. It represents a new tool in their recruiting arsenal.

Blockchain in Recruitment
For recruiters, reading and looking through resumes is a long and arduous task. It involves a fair amount of verifying education, certifications, work experience, and applicant skills. Imagine now if those same resumes were in a blockchain.

Once information is entered in to a blockchain, it cannot be edited. Users can only add information, and even then it must be approved by those with access to the chain.

When put in context of recruitment, the path is clear. Once a person creates a blockchain resume, it cannot be altered. This gives recruiters a chance to verify a candidate’s credentials in a secure way. It also reduces the chances those credentials can be altered or faked. Put simply, it impairs the ability of a person to exaggerate or flat out lie on their resumes.

 

It also allows for real candidate history to be recorded.

“It would force people to rethink not giving notice, starting a job, but then they leave after a few days, all kinds of crazy things we see candidates do but it never ‘hits’ their permanent record,” Tim Sackett said. He’s the President of HRU Technical Resources, a leading IT and Engineering Staffing firm headquartered in Lansing, Michigan. “What if your blockchain profile would show the times you accepted an interview, then no call/no showed it!? Oh boy! I would sign up for that!”

At least two companies are looking at using blockchain in the recruiting space. Recruit Technologies and Ascribe are developing a prototype blockchain resume authentication service for job hunters. It would allow for digital verification of certificates and resumes.

Blockchain Reality Sets In
According to McKinsey & Company, “The potential for blockchain to become a new open-standard protocol for trusted records, identity, and transactions cannot be simply dismissed.”

But there are some concerns. Verifying a person’s education is one thing. Looking at employment history and the details involved there is something completely different.

LinkedIn John Jersin suggests thinking about the average resume for a moment. If the potential employer wanted to see were the last five places a candidate worked, the resume would be quite short. But most recruiters want to see the candidate’s story. What did they do while they were employed in a particular job? What successes did they have? There is so much to convey. While that information can be shared in a blockchain, it is very hard to change.

Additionally, how many employers want employees sharing information about a position that may be considered “proprietary” if you will? It could conceivably lead to the company’s top talent being poached by competitors. And even if that information is made public, how would it be verified? It would be difficult to prove whether or not the information being provided is accurate or truthful.

There are also legality concerns.

Today’s blockchain technology does not “play well” with the General Data Protection Regulation (GDPR) in the European Union. GDPR sets forth rules that state a person must be able to change or delete any personal information at anytime. That goes against blockchain’s most fundamental benefit. It is practically impossible to change or delete information once it has been entered into a blockchain.

 

That’s not the only legal blow to the technology. Just like GDPR, the United States has its own rules outlined in the Fair Credit Report Act. It specifically details the rights a person has when being considered for employment. Again, if a person is unable to alter the information in the chain, they could be very easily misrepresented and that could broach legality concerns.

In summation
Don’t expect blockchain to a big player in the recruiting field anytime soon. The technology is still limited by a lack of regulation. It also lacks sufficient standardization. Until that happens, it’s going to be very difficult to apply the technology to recruitment. Again, it just needs some refinement.

With all of that said, blockchain does have its uses from an HR perspective.

HR deals heavily in personnel and financial data. As such, this makes HR departments a prime target for hackers and other cyber criminals. Because of blockchain’s attributes, it severely cripples cyber criminals’ abilities to hack and cause mayhem with this type of personal data.

So, don’t count on blockchain now, but don’t count it out in the future.

Source : https://www.hrexchangenetwork.com/hr-talent-aquisition/articles/blockchain-realities-in-recruitment

How HR Handles Complaints Against Managers

Another employee has come to Human Resources complaining about poor management in their team. This individual is the third employee to register a complaint against the same manager in less than one month.

I know you investigated the first and second-time allegations. For discussion purposes, I will make a couple of assumptions:

A trained/qualified HR investigator followed your documented investigation procedure checklist. (Note: Do you have a written investigation procedure HR follows? If not, you need one.)
Your investigator spoke to all involved parties (employees, “witnesses,” and the manager). These conversations were documented for the file and reviewed by at least one other HR manager.
The investigator or HR leader spoke to the alleged “poor “manager’s manager. This leader reported that they had never had cause to expect that their employee (the manager in question) was anything less than professional.
In both cases reported earlier, no findings of fault were identified.
HR Complaint Investigation
Well, now you have another allegation. Do you suspect that you have disgruntled employees rather than poor management? Maybe this is no one’s fault; perhaps you see a very serious communication issue, potentially a challenge to authority or a case of clashing personalities. Here’s the key: action needs to be taken. The organization will suffer (decreased productivity, a decline in employee morale, perhaps even undesirable attrition) unless demonstrable steps are taken to substantively address the now stream of complaints.

Start by conducting another fresh investigation. If possible, have a different HR investigator assigned to seek statements, check timetables, and observe (fresh eyes). HR is not called upon to “find something” rather, they should be the source of solutions for problems when identified. HR is also not “on my side” or “their side.” HR’s function is to review, analyze, and synthesize the evidence, the symptoms, the personalities involved. What if all your efforts to get to the facts results in a “he said, they said” case? Be vigilant to consider the following possible root cause: Is this a case where the manager isn’t trained or ready to manage?

I keep a now dated Gallup Business Journal article in my top desk drawer. It’s title: “Only One in 10 People Possess the Talent to Manage (April 13, 2015)”. My head spun when I read this article the first time and still experienced the same response when reading it for the 20th time. One key finding resonated so loudly:” Companies fail to choose the candidate (for management, emphasis mine) with the right talent for the job 82% of the time.” After your head stops spinning, think of the consequences an 80%+mismatch in role responsibilities means for an organization. Managers, especially front line and mid-managers, play an essential role. They are often key to change initiatives, vital to production fulfillment, key contributors to quality programs, formidable brand ambassadors, and they are indisputably the heart of employee engagement and satisfaction. Underestimate front-line managers impact and value at your peril.

 

The burden for resolution rests with the organization selecting these individuals to serve in such a critical role. And then we learn most companies choose incorrectly. Now, what do we do? A large, rapidly growing technology organization was expanding its manufacturing footprint and needed team leads as the floor teams grew by leaps and bounds. HR sought candidates with technical expertise; many of the new team leads were recent college graduates. They were bright, knowledgeable, from world-class universities and enthusiastic new hires. The problem was that they were hired to lead teams without any requisite management training. HR and company management alike assumed that they would grow into their roles. Unfortunately, learning the role of manager, embracing a new company culture, grappling with new engineering processes all while settling into their own “space” prolonged the path to becoming a good leader of teams. Undesirable attrition began to spike. This data-driven company looked at employee engagement surveys and found a glaring issue: front line managers were not serving their teams or the company well.

Responding to the data, HR and executive leadership created clearly defined roles and expectations of managers, very carefully aligned to company values, mission, and culture. They designed and conducted five-day residential training programs where students were admonished to choose the role of manager, along with its responsibilities. For those who opted out of the management track, individual contributor roles were found. The key here and the very foundation of the success of the program was that the company articulated management expectations, trained on them and were explicit on the responsibilities of people managers. This organization was highly successful in turning around employees’ perception of managers concomitantly with these new managers embracing their roles.

So, when you repeatedly hear complaints about managers, remember Gallup’s research findings on the five talent dimensions attributed to successful managers:

ability to motivate teams and individuals to continually improving performance;
appropriately assert themselves in the face of challenge and adversity;
stand accountable for team performance and success;
build relationships;
decisively make decisions in a balanced and data-driven manner.
Dive into complaint investigations with an unbiased perspective, yet remain vigilant to see whether management needs your assistance on becoming better managers. This issue doesn’t align with an overnight “fix” nor an inexpensive one. It does, however, offer the potential for real change, real growth, and better management. Start today; there is much to be lost and so much more to be gained.

Wishing you learn something new each and every day!

Source  : https://www.hrexchangenetwork.com/hr-talent-management/columns/how-hr-handles-complaints-against-managers

Key Factors to Manage Employee Merit, Bonus & Incentive Plans Effectively

There are many ways to incentive performance in an organization. Typically grouped together under the umbrella term “pay for performance plans,” employers may choose among merit programs, bonus options, and individual or team incentive plans. In order to manage employee merit, bonus, and incentive plans effectively, however, it’s important to first understand the key differences among these types of pay. Below is a brief description of each.

Bonus Plans: Bonus plans can be based on any number of metrics, which may incorporate factors such as how long the employee has been with the organization, their role and responsibilities, and their job level. For instance, a manager might receive a bonus for keeping costs down in their department. In addition to individual bonuses, team bonuses can be given to reward and incentivize accomplishments across a group of employees. Sales bonuses are also used frequently to reward sales staff for meeting specific goals within a given period of time.
Merit Pay Plans: Merit pay plans aim to motivate employees to perform their best. This form of pay consists of a raise in the salary and is typically based solely on the employee’s performance, independent of other factors such as a promotion or time spent at the company.
Incentive Plans: Like pay-for-performance plans, “incentive plan” tends to be used as an umbrella term to describe any plan used to motivate an individual or group of employees. With that said, there are specific types of incentive plans, including 401(k) incentive plans in which the company contributes to the employee’s retirement plan up to a certain amount.
Which is Right for Your Company?

Determining which type of pay for performance plan is right for your organization will require you to consider a number of key factors. If high levels of motivation are required, for instance, merit pay can be useful. Yet, over time, this option can become very costly, as the value of the merit-based raises carries forward cumulatively. If long-term costs are a concern, short-term motivators, such as bonus and incentive plans, may be a more fitting option.

Source: https://hrsoft.com/blog/key-factors-to-manage-employee-merit-bonus-incentive-plans-effectively/

 

Quick Tips to Measure Training ROI

The end goal of every enterprise is to earn profits. Revenue is what drives a business. With this vision in mind, business leaders make decisions about investments and expenses. All investments are carefully planned in a way that it will generate ROI in the future. So, when an organization sets aside a certain budget to invest in employee training, they expect a return on training investment too. Employers expect their employees to be well trained so that they can effectively contribute to the growth of the organization.

As most of the training programs these days are being delivered on mobile devices, enterprises have a better chance of getting accurate information about the actual returns on training investment. This has been made possible with the help of back-end tools which collect employee engagement data, analyze it and displays it in a comprehensive format. Apart from numerical data, there are certain other factors which help in determining the training ROI. All this data combined, helps the employer plan their budget and make informed business decisions.

Let us have a look at how you can measure return on training investment:
1. Data Analytics
Businesses work on numbers and statistics. There has to be a visible record of all the transactions and activities undertaken in the organization. So, for employee training, merely creating and delivering courses isn’t enough. There has to be a report to validate the effectiveness of the training program, where analytics can help. A lot of training delivery platforms have an analytics feature which lets you view the performance of the employees. With a clear visual representation of the engagement levels, assessment scores, and overall performance, enterprises can make informed decisions about the further course of action. Based on the findings of the report, one can redesign or modify certain elements of the training module. So, a detailed analytics report can help you measure the ROI in terms of training effectiveness.

Related: Employee Training Metrics: 7 Ways HR Experts Use Them

2. Client Satisfaction
A happy client is always good for your business. But, apart from increasing revenues, this criterion can also be leveraged to measure the training ROI as well. When employees are well trained in providing good quality service or developing a robust product or application, it shows the effectiveness of the training program. What they learn is what they implement. So, if the employee is doing everything right, eventually addressing all the client needs and delivering a quality product/service, it can be considered as a validation of a training program done well. So, client satisfaction can also be considered as a factor for measuring the return on training investment.

Related: How to Empower Frontline Employees with Mobile Training

3. Assessment Scores
Assessments are used to evaluate the employee’s knowledge of the course module. How does this help in assessing the return on training investment?

When employees score well in their tests, it reflects that they have understood the concepts and are ready for the job. The sooner the employees pass the assessments or the higher the scores they get, the better the training program is considered to be. After investing in a mobile training program, employers wish to see its effectiveness and engagement value. And hence, assessment scores are considered quite useful in measuring training ROI.

Related: [Infographic] Accelerate Employee Engagement With Mobile-Based Corporate Training Program

4. Knowledge Retention
This one’s linked to the earlier point. Knowledge retention determines the effectiveness of the training program and can be ascertained through assessments. All your efforts are futile if the employee is unable to remember the information learned. So, to ensure that employees retain as much information as possible, you must create an engaging training module, which includes interactivities and other features. This will help employees in retaining and recalling the information when required. From an ROI perspective, the sooner and longer the employee is able to remember the training information, the sooner they are able to deliver results and ensure higher productivity.

Related: 7 Most Effective Ways to Make Corporate Training Engaging

5. Employee Turnover Rates
High turnover is an indication of dissatisfied employees. Either they are not receiving suitable training and development opportunities, or they are unhappy with the work environment. Employees mostly leave an organization due to a lack of growth opportunities.

An added advantage of creating mobile training programs is that you can create multiple courses in different domains and make it available to your employees. It could be related to the work at hand, or skill development courses. Once the employees are done with their recommended course modules, they can browse for additional courses and enhance their skills or learn new skills. This provides them with an opportunity to enhance their knowledge and capabilities, which will lead to growth opportunities in the organization, and thus reducing the number of employee turnovers and increasing return on training investments.

Related: 8 Best Employee Engagement Strategies

6. No More Spending on Physical Training Materials
No more training booklets and manuals, or training room resources. People carry mobile phones and tablets in person every moment. So, delivering training on these devices removes the need for you to provide physical training resources, maintaining a training room and all the associated costs. All those resources that were earlier used to print manuals, recruit trainers, etc., can now be redirected for other uses. Now all you need is an employee training platform or software to create and deliver training modules. This practice has given rise to the BYOD trend. As the company is not required to pay for the mobile devices used for accessing training, it results in cost savings, thus increasing your ROI.

Conclusion:
Today, although companies are willing to spend on training and development programs, the calculations have to be supported with estimates of the potential benefits of investing in learning programs and technologies. In order to justify one’s investment, there has to be positive results as an evidence. Delivering mobile-first training content helps in analyzing the effectiveness of the training program with the help of measurable data. All the strategies mentioned above can be utilized to calculate the ROI of the training. To increase the training ROI, enterprises must first invest in a well-designed training plan, which will help them achieve improved productivity, cost reductions and increase in customer satisfaction.

Source : https://www.humanresourcestoday.com/?source=kitaboo—employee-training&open-article-id=10565905&article-title=quick-tips-to-measure-training-roi&blog-domain=kitaboo.com&blog-title=kitaboo—employee-training