Activating Employee Value

In this:

* Getting results with employees requires activation

* Understanding activated value

* Supporting performance and measuring activation

To create an above-average company, you have to do three things well:

1. acquire or attract employees capable of above-average performance (above-average relative to your competitors)
2. activate those employees you hire to a level of above-average performance
3. and keep more employees with above-average performance than those with average or low performance.

This post is about the second, activation

We know that acquiring uniquely talented people is vital to help any company create a high-performing workforce. We also know that retaining people — specifically, uniquely gifted people — is important. A topic that doesn’t get nearly enough attention is what happens to those employees day-to-day after they’re inside the company. Some call this culture or engagement; what I want to introduce you to is a simpler concept I call activation.

If each employee in the company were a component from which the company derived some value, activation would simply indicate whether the switch is on or off. Imagine, if you will, that every employee’s forehead sports an On-Off switch. (I know it sounds like something out of The Twilight Zone, but bear with me.)

In a simple real-life example of activation, you have hired a software engineer who is at work but cannot start working for two weeks because they are waiting for their computer to arrive. In those two weeks, the engineer is unable to deliver the value from work that you hired her to do, so if she had an On-Off switch, it would be in the Off position. You are paying her, and may even be recording this value in your other metrics, like HCROI or ELV, but you aren't receiving any actual value from that cost. This is the fundamental underlying problem with all quasi-financial HR metrics that attempt to relate employees to measures of business success. I have a solution for this, read on.

Of course, more things matter than having a computer, but if that’s the one thing that she was missing, the switch will move to the On position whenever the computer arrived. Not all activation problems are this simple to fix. In another example, imagine that after the engineer was hired, team members never wholly agreed about the best way to solve a problem, so the engineer ended up working for six months on code that would never be used. As a result of the conflicting perspectives among the broader team, you paid her during this period, but the company was unable to materialize value from her work. Again, in this scenario, the engineer is working, but her activation switch is in the Off position.

<Remember> When you’re paying employees but they aren’t activated, you aren’t deriving value; when they are activated, you are obtaining value. The challenge of correlating HR activities to business outcomes is that there's more to it than just knowing you have the “best” or “right” set HR programs; what you need to know are how many individual value switches are On or Off. Most, if not all, of the "best" or "right" practices have zero impact on individual results if they do not the current constraint standing in the way of that individual producing value. This then aggregates to teams, which aggregates to larger groups, which aggregates to the entire company.

When you think about a company from the standpoint of producing optimum results from employees’ efforts, you need a data-informed perspective on all three A’s (attraction, activation, and attrition) if you want to model out what is going on as a whole with employees at your company. Let’s see what happens when you have two of the three nailed down, but not all three:

* Attraction and activation (without retention): When your business can attract uniquely talented employees, but you're not retaining them (not retaining means they are leaving), you’re expending a lot of energy but merely going in circles.

* Activation and retention (without attraction): When you’re activating employees and retaining them, but you’re unable to attract uniquely talented employees, you face the danger of simply being beaten out by those of your competitors who have more talented employees working on whatever it is you want your product focus to be.

* Attraction and attrition (without activation): Finally, when you’re attracting uniquely talented employees and can retain them, but you don’t know how to activate them to a high level of performance, you aren’t getting the most out of the money you’re spending on those employees. You have the right people, and you are going to pay them regardless of the value they produce, but you are not obtaining optimum benefit from their potential.

For an illustration of the points, I make above, check out Figure 7-1.

Figure 7-1: The pitfalls posed if there are problems in attraction, activation, and attrition.

Now that you know in broad terms what activation is and where it fits into a people analytics HR strategy, I can break activation down into greater detail in the following section.

Introducing Activated Value

The influence of human resource management on organizational performance is a central research question capturing the interest of academics and practitioners for decades. My literature review turned up more than a hundred articles on the topic of the impact of human resource practices on firm performance that was published in peer-reviewed scientific journals between 1990 and 2018.

Researchers have repeatedly demonstrated that implementing a bundle of people management practices centered on creating strong employee involvement and morale can have a relevant and important influence on company performance.

A 2013 Gallup meta-analysis accumulated data representing well over 1.3 million employees from 263 research studies to study the relationship between employee engagement and business outcomes. Of the nine results studied — customer loyalty and engagement, profitability, productivity, turnover, safety incidents, shrinkage, absenteeism, patient safety incidents, and quality — all proved to be related to employee engagement. According to Gallup, the difference between falling in the top quartile and the bottom quartile of their engagement index could be a 22 percent difference in profitability, 21 percent in productivity, and 37 percent in absenteeism, to name just a few of the advantages.

The fact that what you do with people impacts company performance shouldn’t be a surprise or be that difficult to understand. What isn’t clear is how to get repeatable results in different contexts. Instead, what you find is an array of disconnected measurement ideas and a dizzying list of suggestions that total in the hundreds, if not thousands, of activities.

Examples from the Internet range from “ditch cubicles” to “provide ongoing coaching and training,” from “encourage volunteering” to “incentivize goals,” and from “start a newsletter” to “hold a brainstorming session.” I have nothing against any of these suggestions specifically. Still, it isn’t helpful to begin with a list of a thousand items that may or may not help gain more performance value out of employees for your company. It isn’t realistic to believe that you will ever get through the list, and you’re unlikely ever to find out how much value any of these contributed or destroyed.

Modern HR teams are looking to people analytics to guide their focus because they’re tired of the old idea of a human resources team that tirelessly implements the Activity of the Year or Quarter or Month or Week is chosen from a magic hat. The problem is that, without a guiding measurement framework, it’s challenging to find your way to the right things to do.

In the hope of providing just such a framework, I have come up with something I call activated value, a concept designed to focus attention where it will produce the most business value.

The origin and purpose of Activated Value

Activated value is a concept I developed after giving up employment at large companies like Google to start consulting for smaller companies that have less time and fewer people and resources yet are still trying to repeat the success of larger companies, like Google.

One of my first clients was a 500-person start-up that, at one point, had been a San Francisco start-up darling blessed with a venture capital valuation of over a billion dollars and loved by employees, customers, and investors alike. Much of the company’s initial growth was from its first product, which was a smash hit among its customers. However, this product was not enough to achieve profitability, and, before long, competitors copied its design. For years, employees tried to figure out who they wanted to be as a company as they tried to get other products launched. Unfortunately, their best efforts weren't so successful, because their second and third products didn’t “wow” customers as much as the first. By the time I started working with them, it was clear that the company was having financial problems but had a proud history of achievement and that employees were still confident they could turn this company around.

The imitation trap

The first thing I observed while working with the small, troubled company was that I could see much more clearly when smaller companies try to buy the affection and loyalty of employees by imitating the HR practices of larger companies, it can make them look good on the surface for a time, but if large scale success is not found quickly, these can undermine the company’s success in the long term.

For this company, imitating the expensive real-estate, open floor plan layout, bean bags, ping pong tables, micro kitchens, free lunches, and other liberal benefits and perks of neighbors like Google, Apple, and Facebook it made the startup look like a great place to work. Still, beneath the vibrant surface and upbeat demeanor, significant problems were hiding. Attempting to look like the much larger, better capitalized and profitable companies in compensation, benefits, perks, and expensive office space undermined the startup’s success by increasing the startup’s per-unit cost of production over that of the competitors that have much bigger war chests. At the same time, the company had to face competitors in other countries where workers that have lower expectations (and cost less) and a much smaller unit cost of production. This put the startup in an awkward position of not being particularly competitive on price. The ongoing higher cost of production undermined profitability, and this required executives to continually go back to investors to put in more money. Each time they went back to investors for more money, the employees’ share of the equity pie kept shrinking until the point that it became clear that the employee stock options may eventually be worth nothing. This undermined the reason the most talented employees took the risk on the start-up rather than work at an established company — they wanted their work to matter, and they wanted a piece of the company for their contribution. As the realization that the company might fail became apparent, and the stock options that were holding people in place had less value, critical employees began to leave, which in turn helped make the self-fulfilling prophecy for company failure more likely.

The most important thing I observed in working with a smaller company is that implementing all the little things the large companies do is not a prescription for success and may not even be possible at a smaller company. It could bankrupt them, and it was doing just that. Aside from the problem of the money to buy the coolest toys, the smaller company just doesn’t have enough people on the HR team to implement everything larger companies are doing even if they wanted to — there wasn’t enough time in the day for that small team. The smaller company has to figure out what of the many things the larger companies do matter most, or they had to find their way forward, or else they would be unable to beat larger, more profitable competitors that had a lot more money to spend on human resources. A smaller company can compete with a larger competitor, but not by playing by the rules of the larger competitor’s self-serving game.

<Remember> With no standardized, reliable way to measure whether is getting the deep things that matter (like goals, motivation, capability, and support) right, neither HR nor managers can be held accountable for actually achieving a great culture— so their attentions go to what is happening on the surface (bean bags, ping pong tables, and food). More specifically, managers’ attention goes to wherever they’re being held accountable, and HR's focus goes to activities that are pursued until complete, regardless of whether anyone has a way of knowing whether those activities matter. This missed opportunity to get the deep issues that matter right while focusing on the Fashion of Corporate Success undermines the company's real success over the long term by first increasing the costs over that of competitors and then increasing the company's need to continue acquiring people to replace those who are leaving. As the old saying goes, “what gets measured gets managed." If nothing profound and vital is measured, then nothing deep and important is managed.   

The need to streamline your efforts

All companies can benefit from measures of how effectively they are managing people found within the emerging practices of people analytics. The problem is that some large companies doing innovative work in the space of people analytics have hired 20 or more people to work on people analytics exclusively, yet, many smaller companies may not even have that many people working in all of human resources.

<TIP> In 2019 I surveyed over 100 companies who were investing in people analytics capability in human resources. The average people analytics teams is 5 people.

Given the necessity of people analytics to the effective management of people in a modern way of approaching human resources, small growing companies need people analytics as much (or more) than large companies. Still, they just don’t have the same resources to apply to people analytics, so they need it to approach it in a different way. A large-company approach to people analytics requires large upfront investments in systems as well as large teams full of people who can do advanced systems, behavioral science, and mathematics work — usually, people holding highly specialized training, including full PhDs. The large-company approach to people analytics simply wasn’t possible at the startup I was working with and wouldn’t be possible at any other small or medium-sized company either. The good news is that you don't have to have a large team if you follow the advice I provide a glimpse of in this post and expanded in more detail in the broader body of my writing, but summarized in one neat accessible package in People Analytics For Dummies.

<TechnicalStuff> My definition of a small company is any company with less than 250 employees, my definition of medium-sized company is 250 to 2500 employees, and my definition of large is above 2500. Others may have a different definition. The point remains, companies of different sizes have different challenges and have to address the problems of human resources in different ways.

When I started working with data in HR at Merck, we had 65,000 employees. At PetSmart, I believe we had 20,000. At Google, we had 7,000. Children's Health in Dallas was 5,000. As a consultant, I mainly worked with companies under 2,500 employees. The example I use in this article was under 500 employees.

Initially, I thought that I could meet the HR measurement needs of the smaller company by introducing a basic set of HR metrics and a comprehensive annual survey on employee culture. While through extraordinary effort, these methods were generating useful insights for the small company, the arrangements weren’t accessible to operators to take over from me — the everyday people who work in HR and manage people, as opposed to data scientists. It became clear that even the basics required too much work and expertise to safely handoff to a group of already overworked people. It just is not going to happen if someone isn't responsible, but one person can't do it all and especially not one that isn't well versed in all four S's: strategy, science, statistics, and systems. I could do many things myself because of my previous experiences, but not everything. Finally, it is difficult to find someone to hand the whole people analytics thing off to, and clearly, the small company couldn’t truly create a complete team just for people analytics. What an exciting dilemma! Are you looking for a job? When you finish this book, I may have a job for you!

Because I wouldn’t be able to effectively find a way to collect, report, and find insights for hundreds of metrics and survey questions, I set out with a goal to find a smaller number of people-measures that could be related to business results that connects employee value with business value and that can be administered anywhere by people without a Ph.D. in calculus or industrial-organizational psychology. So, I set out to design a key performance indicator (KPI) that I envisioned would be a composite measure (or index) of a few items that can be collected through a survey instrument. This measurement system wouldn’t require hundreds of questions, hundreds of HR metrics, or advanced data science to be highly useful. It would necessarily miss a lot of things, but it would measure the most critical elements.

I was looking to implement a system of measurement that can be boiled down into a single indexable key performance indicator (KPI) that could

* Be practical to implement

* Be easily grasped by front-line managers

* Correlate to employee performance and contribute to the understanding of employee performance

* Correlate to business performance and contribute to the understanding of the relative performance of different business units or the company when compared to competitors in an industry

* Simplify the production of the measure and clarify the possible range of options in the response

* Be used by managers and HR to track their performance regularly: quarter-by-quarter or (preferably) month-by-month

* Be used in conjunction with other people and business data to make better business decisions

After I worked through what was required, the single indexable measure I came up with that satisfied all requirements is what I call activated value.

<Remember> There are hundreds if not thousands of possible employee measures that could, in theory, be substituted as a central KPI. These will have varying qualities, uses, and lifespans. What I have set out to do is formulate a sound and simple starting point that meets the criteria above, which may be different than these other KPI's. You can and should scrutinize, challenge and improve the KPI I propose based on the criteria I have set above, your own criteria, and your own learning.

Measuring Activation

Anyone who has studied the research literature of human performance improvement knows that there is a large and frustratingly cloudy body of research that examines behavior influences of individual performance. Though it’s safe to say that many factors can drive or affect performance, what I sought to do was come up with a way of measuring just the bare-minimum conditions required for ideal performance to occur that anyone can agree with. Activated value is a way of simplifying the process by focusing on those factors that are essential contingencies of a "system of interrelated factors" that produce performance. More importantly, the concept of activated value would be especially easy to understand for managers and nontechnical people.

Determining the minimum conditions necessary for successful performance

Taken down to its essence, the theory of activation proposes four conditions must exist for an employee or a team to produce at or above performance expectations consistently. The employee or team must

* Be capable of performing the actions required

* Be aligned on what a good result looks like

* Be motivated to perform the actions

* Have all the tools and support that are necessary for the successful performance of those actions

Most people would agree that if any of these four conditions is missing, it’s difficult, if not impossible, for the employee or team to perform reliably.

To say that four conditions are absolute requirements to achieve performance isn’t to say that other aspects don’t matter at all. Many things can matter — the purpose of activation is to simplify your understanding of performance to the bare minimum. By bare minimum, I mean that if you removed one then the individual or team would be unable to perform at their finest, if at all. At the point at which you fully understand the presence or absence of these four conditions, the minimum, you can control these four in analysis to more reliably identify other factors that matter to performance.

<Technical Stuff> If you were to attempt to correlate the measurable concepts of Commitment, Engagement or NPS and any business outcome but had not mathematically controlled for the minimum conditions I describe as Activation, then you could get mixed results that would mask the real value of the other measures. This problem is so dire that it may result in an analysis that shows that Commitment, Engagement or NPS don't matter at all, when in fact they do matter but you can't see that because other conditions are absent or non-randomly distributed.

The following list summarizes each of the four conditions of activation:

* Capability (knowledge, skills, and abilities): In its most basic sense, a capable individual has the knowledge, skills, ability, and other characteristics necessary to perform the job. Capabilities are what people bring to the company — personal qualities such as technical knowledge, learning agility, social skills / emotional quotient (EQ), and grit, for example.

The company can increase capability in two ways: recruiting and training — keeping in mind that some characteristics aren’t possible to create through training and others are but would cost too much time and money.

The primary channel that the company has to increase capability is the optimal selection of people for jobs based on selection criteria related to job performance as determined by strategic planning and job analysis.

<Tip> Sometimes when all the other factors of activation have been handled well, some of the characteristics thought to be critical to performance aren’t essential in practice. Inversely, even an extraordinarily capable person put into a situation without appropriate supports will fail.

<Remember>It doesn’t matter whether people are aligned, motivated, and supported if they aren’t capable of performing the job with a high level of ability.

* Alignment: Employees who are aligned know what they’re expected to accomplish, and under what conditions, and how they’re performing in relation to those expectations.

The company can increase alignment by way of goal setting, performance appraisal, and regular executive, manager, and employee communication.

<Remember> It doesn’t matter whether people are capable, motivated, and supported if individuals, teams, managers, and leaders don’t understand and agree on expectations.

* Motivation (preferences, commitment, engagement): Motivation is the general desire or willingness of someone to do something.

Motivation reflects the interaction of personal preferences with the job, working environment, company culture, leadership, managers, peers, rewards, and incentives, which result in motivation or demotivation to perform the tasks at hand.

When the company adequately addresses the other factors, motivation often takes care of itself. Regardless, the company can take many actions to create an environment conducive to high levels of motivation. The most important is to find and select people who are excited about the company’s mission and products. The second most important way the company can maintain high levels of motivation is to listen to employees when they specify the tools and support they need to perform at their best.

<Tip>Attempts to "pump up" motivation without managing the other factors don't produce the desired outcome.

<Remember> It doesn’t matter whether people are aligned, capable, and supported if they aren’t motivated to perform the job.

 * Support: This category covers not only the particular technical tools used to perform work but also any other support that’s necessary, such as access to documentation, access to manager and teammates to help solve problems, resources designed to produce skills and knowledge in the individual, technical support, and camaraderie.

<Tip> In assessing support, it’s also important to evaluate negative consequences built into the work environment and work processes, such as the failure by other departments to fulfill orders or conflicting or competing objectives between teams or peers that punish or fail to reward individuals for doing the right thing for the company. Investing in common supports, such as training, can be unproductive if done without ensuring that influences are aligned.

<Remember> It doesn’t matter whether people are aligned, capable, and motivated if they aren’t provided with the supports they need to perform the job.

Now that you know what activation is, it's time to step it up a level. When you think about a company from the standpoint of producing results through people, you need a data-informed perspective on capability, alignment, motivation, and support of people if you genuinely perform individual and group diagnostics that provide useful information about what is preventing performance or use any data to make predictions.

For an illustration of the CAMS Activation Framework described above, check out Figure 7-2.

Figure 7-2: The problems presented if any of Capability, Alignment, Motivation, or Support is missing.

Now that you know in broad terms what activation is and where it fits into a people analytics HR strategy, I can break activation down into greater detail in the following section.

The calculation nitty-gritty

You can infer all four model variables — capability (C), alignment (A), motivation (M), and support (S) — with a short, 8-item survey using a 0–10 agreement scale. First, here are the survey items:

Survey items are listed here and further described in the table below:

CAMS Survey Statement Items

There is a clear objective around which myself and the people I work with rally.

I have a clear understanding of the difference between an average contribution and a great contribution to my role.

My primary workgroup has all the capabilities it needs right now to achieve top performance as a team.

I have the capabilities I need right now to achieve top performance in my current role right now.

The people I work with are willing to help even if it means doing something outside of their usual activities.

I am motivated to do more than minimum expectations.

I have the cooperation and support from others at <company> I need to be successful.

I have the resources and tools I need to be successful.

<TechnicalStuff> Notice that for the items in each category are intentionally similar, but one is asked from the perspective of the team, and one is asked from the perspective of the individual. Asking about the same concept in more than one way creates a better performing index. Each survey item is framed in a particular way, which is subject to a specific bias. Asking the question in more than one way is intended to provide balance to minimize the impact of various types of bias. The overall index will be more reliable than the response to a single item or subset of items.

INDEX STRUCTURE AND SUB-CATEGORY TABLE

CAMS Survey Response Scale

For the response scale, let’s use an agreement scale from 0 to 10.

<Tip> Pay careful attention when dealing with a 0–10 agreement scale; 11 responses are possible on such a scale (0,1,2,3,4,5,6,7,8,9,10).

<Tip> On the actual survey, you would just list the statements in the survey tool, along with the suggested 0-10 agreement scale. While the categorical classification of each item should not be shown on the survey, for background, see the subcategories or dimensions noted in the first two columns of the table below. You maintain the categories in the background so that you can calculate and report by any of the four major categories on the survey in addition to calculating an overall index as a whole using all seven items. Others do not need to be distracted or burdened by the details of how you categorize each item, and in particular, these distractions should not be on the survey itself.

 Note that all of the statements used are positive, so the 0-10 scale response can be interpreted consistently, such that a 0 would be the worst response, and a 10 would be the best response for all items. This allows a simple calculation of the index.

The index calculations proposed in this post assume 8 positively worded items on a 0-10 agreement scale. If for various reasons, you want to use a different agreement scale, for example, 1 to 5 or 1 to 7, or add or remove an item, you may do so. However, you would have to consider this in the index calculation and other uses of this data described below. If you change the construction of the survey, then you will have to adjust the index and your interpretation of the index accordingly.

Calculating the CAMS Index

Sum the total counts (0–10) from the individual response to the eight items. This should produce a score ranging from 0 to 80 per individual, known as the CAMS index.

Calculate the “Net Activated”

Net activated is a metric that is a count of the number of people who have responded positively enough to the eight questions to be considered sufficiently Activated for purposes of reporting and other calculations.

To calculate net activated systematically assign a categorical description for all individual survey respondents using the following rules:

* Activated = CAMS index equal to or greater than 70

* At-Risk = CAMS index less than 60

Count the number of individual survey respondents that are Activated and At-Risk.

Calculate the Net Activated Percent

Net Activated Percent is a metric that calculates the percentage of a segment that is activated.

Now use the following formula to calculate the Net Activated Percent.

Net Activated Percent = (# activated in segment – # at-risk in segment) / (total headcount of segment)

Additional reporting

While it is nice to see the average CAMS Index and the Net Activated Percent for the company, it will be much more useful to calculate these by segment so you can see what is going on in different parts of the company and compare segments of the company to each other.

Follow these steps:

1.  Calculate the average CAMS index per segment.

<Tip> A segment can be any number of different layers or dimensions of the company. For example, you can segment by division, by department, by the director, by the manager, by job family, by the job, by job level, by location, by performance, by key jobs or key talent, by gender and so on. For more on segmentation, see Segmenting for Perspective, Finding Useful Insight in Differences, and Making Sense of HR Metrics.

2. Cross-tab the average CAMS index by segment. For more on cross-tabs, see the section 'Getting Started With Cross-Tabs' in Segmenting for Perspective

3. After you have completed more than one survey, you can trend each segment over time. This will show you if each segment is getting better or getting worse over time.

4. You should cross-tab each of the four subcategories (Capability, Alignment, Motivation & Support) as well as each of the seven individual items to provide more specific feedback about what is going well or going poorly, specifically about where the greatest opportunity to improve the CAMS index is. Is there is a problem in capability, alignment, motivation, support, or some combination?

5. Follow steps 1-4 above for Net Activated Percent too.

Survey administration

This 8-item inventory is short enough that it can be distributed monthly or quarterly as a regular management ritual and essential operational tool that can be associated with other outcomes without degrading response rate or presenting difficulty when it comes to producing and distributing reports.

This survey should be conducted confidentially by a third-party agent so that individual responses can be joined with other data and reported by segment while protecting the integrity of the process and the safety of individual responses.

Though we protect the individual responses for the integrity of the process and the accuracy of the data, you can and should have follow-up group or one-on-one meetings where people who feel safe doing so have the opportunity to talk about the four factors (capability, alignment, motivation, and support) and contribute inputs for solutions. These meetings should be facilitated to be voluntary, positive, constructive, and safe for everyone involved.

Survey analysis

With the same 8-item inventory, you can

* Identify which of the four factors, if any, can be categorized as a weakness for the company as a whole or for a particular segment.

* Provide executives a perspective across the entire business to enable them to see strengths, weaknesses, risks, and opportunities among divisions and teams so that they can work with managers to solve problems and hold managers accountable.

* Measure the performance of managers at facilitating activation among the organizations they manage and provide individual advice based on the profile of the groups they manage.

* Identify whether the specific issues blocking activation vary among groups or if the issue is relatively consistent across many groups.

* Correlate activation to other surveys, performance or business outcomes data. You may have other survey items, performance, or business outcomes data that you want correlate.

Use your third-party survey partner or another partner for data management to maintain the safety and confidentiality of individuals and protect the professional integrity of the process.

Combining Lifetime Value and Activation with Net Activated Value (NAV)

In Estimating Employee Lifetime Value, I introduce employee lifetime value (ELV) as the people analytics version of customer analytics customer lifetime value (CLV).

<Remember> CLV is the total profit estimated over the entire future relationship with a customer. CLV was designed to put the cost of customer acquisition and retention into the proper context of the long-term profitability of each customer — on average, by segment, and in some cases by the individual. CLV allows companies to compare the likely return on investment of spending for acquiring or retaining a customer with the total predicted value of the relationship.

ELV a method of putting employee-related issues on a financial basis for relative prioritization that is similar to CLV.

Remember the critical difference between customer lifetime value (CLV) and employee lifetime value (ELV): Whenever a customer spends money, that value is immediately captured; when you spend money on an employee, the value of that spending may or may not be captured by the company, depending on what the employee does. It’s entirely possible for employees to show up and collect their paychecks but exert no effort to create value for the company — or they can make an effort and still miss the mark. Because ELV is contingent and, therefore, less predictable, you have to look at ELV a little differently from CLV.

Activated percent (NA%) is a metric described earlier in this post that represents the percentage of employees that are activated. Net activated value (NAV) combines the concepts of Activated percent with ELV into one measure. NAV helps you navigate the winding path of employee lifetime value on the employee journey. In this section, I show how you can build on this measure to obtain more insight.

You can obtain a clear focus on where to spend your time and money if you compare the estimated value represented in that segment if 100 percent of the employees in that segment are activated versus the estimated value of that segment at the current net active percent (NA%). If you multiply the ELV of the segment times the current net active percent (NA%), you have a new measure called net activated value (NAV). This new measure, NAV, represents roughly the value of the efforts of the people in the segment that are activated. NAV discounts the expected value of the segment, taking into consideration that because not all employees are activated, the part of the organization can't possibly deliver full value.

Here’s the formula for calculating Net Activated Value (NAV):

Segment NAV = (Segment Activated Percent) x (Segment ELV)

As shown in Table 7-1, you can compare the dollar value of the opportunity between groups to figure out where to focus your attention to have the largest business impact.

Table 7-1: Net Activated Value

In the example shown in Table 7-1, going to work on increasing NAV in Segment 2 is the best investment of your time and resources, based on the information you have that combines Net Active Percent with employee lifetime value.

<Tip> NAV (like ELV) is not intended to be used as a rigorous financial accounting exercise. Rather, these are tools to put concepts like employee attraction, activation and attrition into a relative dollar context, recognizing that not all jobs or people have the same value and the value that is produced may be different than the value expected as a result of some missing contingency as represented by CAMS. The conversion of headcount to ELV helps to get the magnitude of values you are dealing with correct, and then Net Activated value shows how efforts to improve value from different segments (based on the information you have at the time) compare on a relative basis for prioritization. Do not confuse this with asserting that the fix is worth $X million dollars from a finance standpoint. I think it is safe to say that if a group of employees is being paid and they can't perform optimally as they have told us by survey, then some value is lost. NAV just helps you prioritize your focus among the various options and use the same consistent measure to track changes over time.

Using Activation for Business Impact

You can use the activation measurement framework in many ways to improve the bottom line. I list the most effective ways here first and then delve a little deeper into each approach over the course of this section. First off, you can

* Gain business buy-in on the people analytics research plan

* Analyze organization problems and design solutions

* Support managers

* Support organization change

The following sections spell out the details.

Gaining business buy-in on the people analytics research plan

Often when I work with companies, I have to quickly gain consensus among the various influencers and decision-makers (from different departments or functions within the organization) about the specific business goals and job outputs (accomplishments) we are trying to understand and improve with people analytics.

People often see “part of the elephant” when it comes to concepts that they believe influence attainment of business unit performance goals — that's to say they see the parts that interest them or are familiar with, but not the other parts. Some people may be focused on compensation issues; others look at company climate and culture; others emphasize employee selection, and still, others may be focused on learning and development. Though it can be frustrating to mediate between so many different points of view, this diversity of perspective is helpful for people analytics.

When you work with a large group, you can draw the 4-factor activation model on a whiteboard (you know — the capability-alignment-motivation-support/tools concept), begin jotting down each person’s interests or concerns in the appropriate columns, and drive the discussion toward an understanding of how it all fits together as a whole to influence behavior and its performance products. When you explain that these same four factors of influence will be used to define your approach for analysis, it should soon become clear how many parties will need to work together to ensure a successful analysis and eventual solution to any underlying problems. (As you might expect, not just one stakeholder or team can be expected to tackle the task)

<Remember> By using the activation model to explain how all four factors fit together, looking for examples of misalignment (expectations and incentives in conflict), and expanding all participant's views to include the four elements, you will be able to gain increased alignment on objectives and how to proceed.

Analyzing problems and designing solutions

Phase 1 of most analysis should be the 4-factor activation survey outlined earlier in this post. The findings from this survey can be used in the design of data measurements collected from systems, additional surveys (as needed), interviews, and other sources.

Also, the four factors provide a useful way of organizing information to guide the discussion. When a stakeholder has a specific “best practice” solution in mind, I have found that one of the most powerful applications of the model is to use it to explain that investments in one factor will not pay off if it’s not the problem or if other needed factors are missing or in conflict. You can use a discussion like this one to manage the risk that the stakeholder may implement a solution without making other equally important changes — and then expressing frustration at not seeing the expected results. Introducing the 4-factor model early on in the engagement can sometimes provide a transition from a tactical focus to a focus on business impact.

When you make a recommendation for a solution — even a simple one — you can use the 4-factor framework to assess relevant information in each of the factors and to suggest a comprehensive solution that includes all four. The model can be used to create checklists to ensure that the items to be considered when preparing to roll out an intervention are not missed.

Supporting managers

Front-line managers like the simplicity and functional language of the activation model. It takes about five minutes to introduce minimally. In a few hours, it’s possible to provide a systematic introduction to how managers can use these factors for assessing the main factors that affect the performance of the groups and individuals they manage.

Performance-appraisal discussions between managers and employees can benefit from the 4-factor activation model as well. Once managers agree with their people on goals or targets, they can use the four elements of activation to collaborate with employees to find the pieces’ missing supports that might help make a difference.

Supporting organizational change

An important function of a model is to establish a common language. A common language can be a huge advantage, especially when you have to obtain a consensus among many stakeholders. The 4-factor model proposes a fundamental language for how to support performance, moving the company beyond a fixation on the result to a focus on the conditions that are required to gain a better result.

Taking stock of what resources are available and where you are in them

Part 1 of People Analytics For Dummies introduces the big idea of people analytics and shows the role it plays in understanding and improving the impact of human resources on company performance. Start with these: Introduction to People Analytics for Dummies, Introducing People Analytics, Making the Business Case for People Analytics.

In Segmenting for Perspective, I specify that you can break your workforce down into many different types of parts and that each segment may offer a different perspective. In Finding Useful Insight in Differences, I explain that the way you segment the workforce and where you should put your dollars to achieve the biggest return on investment on people will not be the same as in any other company. In Estimating Employee Lifetime Value, I describe how to put all segments into a comparable financial basis — in dollars — for a long-term perspective using employee lifetime value (ELV).

Part 2 of People Analytics For Dummies establishes a flexible, lean measurement framework for people analytics built around the Triple-A Framework. Attraction, Activation (this post), and Attrition. In this post, I tell you how to adjust ELV for activation, a concept that reflects the minimum conditions for value to be produced and then measured by NAV. With NAV, you can evaluate where to spend time and money on people to gain the highest return on investment.

Part 3 of People Analytics For Dummies gives you a grounding in the fundamental measurement and analysis tools for making the most of The Triple-A Model and the Employee Journey.

This is an excerpt from the book People Analytics for Dummies, published by Wiley, written by me.

Don't judge a book by its cover. More on People Analytics For Dummies here

I have moved the growing list of pre-publication writing samples here: Index of People Analytics for Dummies sample chapters on PeopleAnalyst.com

You will find many differences between these samples and the physical copy in the book - notably my posts lack the excellent editing, finish, and binding applied by the print publisher. If you find these samples interesting, you think the book sounds useful; please buy a copy, or two, or twenty-four.

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