Running Training Like A Business 2.0

On Enthusiasm

Book excerpt: Our industry’s path forward is not going to be an easy one and we will need a full tank of enthusiasm to fuel our organizations.

The following is excerpted from my open sourced ebook,

Running Training Like a Business: the startup way to delivering exponential value (working title, suggestions welcome)

I have been talking about the idea of this book for years. I was part of the team that launched Running Training Like a Business. An industry staple and game changing approach in the nineties. So why is it that after two decades, Learning and Development is still struggling to deliver unmistakable value? Technology, just emerging when Running Training Like a Business came out, is now at the core of the learning organization. The tools used by learning and development practitioners for everything from course creation to measurement have improved. Yet the same problems that stirred the need for the first book continue to challenge Learning and Development organizations around the globe. Recent research by Bersin by Deloitte indicates that, while employee development has never been as important, faith of the organization in the L&D function to deliver value has also never been so low.

In those two decades, the companies that L&D organizations serve have changed. Companies of all sizes, once comfortable in their place in the market, have been disrupted. Innovation, once a source of competitive advantage, is now a business requirement. With all of these changes to the business, how has L&D evolved? Some would say not very much. The use of outsourcing, controversial at the time of the first book, is fortunately now a widely accepted solution for many functions of L&D. Thanks to the migration to digital learning, measurement data, formerly difficult to collect beyond “smile sheets”, is now readily available. But, in many ways, L&D has not changed at all. As stated recently by Bersin, “business leaders and employees often cite little or no value coming from the learning organization. An ominous comment about Learning & Development, an organization that we would argue is more important today than ever.

Enthusiasm is defined as “intense and eager enjoyment, interest or approval”. My sense, having sat with many industry professionals at all levels and comparing that to the enthusiastic energy inherent in fast growing startups, is that our industry is sorely lacking enthusiasm. While we may experience excitement, a short duration form of enthusiasm, about new tools, technologies or toys, this is the emotional equivalent of a sugar high. As the last two decades have shown us, we are running a marathon, not a sprint, and sugar is not the fuel of success.

The lack of enthusiasm is not entirely unwarranted. The importance of employee engagement in an organization’s success is widely recognized. We have all seen the studies on what increases it; mission, leadership, development, among others. Yet, when you talk to learning pros, the focus is often on the lack of funding, limited executive support or latest tool or tactic being deployed. Even the cup of sugar is half empty. And when we hear from executives, we often find they have a low expectation of training. My belief is that is because they really do not know what is possible. If we, as an industry don’t have any enthusiasm, how can we expect executives to have any enthusiasm for learning?

Successful startups have enthusiasm in abundance. Founders actually take enthusiasm to the next level, passion. Passion is that intense, driving feeling or conviction and while at points this may be divorced from reason, it sets the highest possible standard for others to follow. Sit with a startup founder for two minutes and they cannot help but tell you what they are building. They will talk fast, as if they have had too many cups of coffee. Most importantly, they will leave you excited about their mission and looking for ways that you might help them. The passion for what they are doing is not only visible when they are talking to investors or potential customers. It comes through all the time. It is on display when they are talking with their teams, standing in line for lunch, sitting around with friends, riding the bus and even walking their dog through the park. If there are ears to listen, they feel compelled, like new parents, to share it. And this is not limited to just the founder.

Successful founders recruit people that share their passion and contribute their own enthusiasm to the mix. Enthusiasm is not solely enjoyment. It is also defined as “intense interest”. In this way, enthusiasm leads to curiosity and curiosity often leads to new, novel, more effective or more efficient solutions. Coding engineers at startups frequently spend long days at work only to go home and play around writing code for fun or to test ideas that they might be able to bring back to work. When was the last time you invited some friends over for some barbeque and some brainstorming on how redesign an assessment process or a learning program? Not because you had to, but because you wanted to.

Our industry’s path forward is not going to be an easy one and we will need a full tank of enthusiasm to fuel our organizations. We are enthusiastic about the future of learning and development and we think you should be too. We believe that unlocking the enthusiasm that our industry has for learning requires a new approach. An approach built on the timeless principle of delivering value holds huge opportunities for the professionals that practice it and the people and organizations they support.

Enthusiastically yours, j.

Data as Author Pt. 2

Be careful about your data narratives, someone might actually believe them.

Billy Valentine, data whisperer

Numbers are nice but it is the narrative, the story, the matters. As an outside advisor for learning leaders for over two decades I know that the data may raise questions it is the narrative that raises eyebrows. Data can always be found to prop up one’s gut or one’s desired POV. Words must be carefully chosen and implications properly couched.

I have written a few times about the annual State of the Industry numbers and the narrative spun by ATD and LinkedIn Research. Spoiler alert: not a fan and not a believer. But if you want to put your learning organization’s numbers in a positive light there is no doubt you can find a stat that looks nice sitting next to the leading companies.

Data doesn’t lie.

And we don’t have to either. But we do tell the truth in our own way. For example:

A company has 1000 employees with the level of manager or above. Last year L&D ran a pilot with 40 participant sin a new leadership program. This year they ran the course multiple times putting 120 future leaders through the program. The following data points are ALL accurate.

To date only 16% of the company’s leaders have received learning support.(makes the case for additional investment)
We trained 3X as many leaders this year than last. (demonstrates commitment to future leaders)
Our leadership program has directly impacted (participant + direct reports) almost 2000 employees (assumes 10-12 direct reports per manager)

So when you write your narrative be careful. The narrative can often say more about the author than it does about the data. Don’t overstate (tempting), know the limits of the data (it will have biases just like you), don’t over extend from data to assumption (without acknowledging it) and for heaven’s sake know the difference between causation and correlation.

The Way to a CEO’s Heart is Through Her Stock Options

L&D has been fighting for years decades to get the attention of the CEO. We have played the “it’s the right thing to do,” card. We have fought through convoluted ROI calculations. We are all adults here so let’s get honest. We know what will get the attention of our CEO. Money.

“Don’t hate the player. Hate the game”

This is not a condemnation of CEOs. In fact, I don’t blame them. Like economists who give up the myth of the “perfectly rational actors” in systems, acceptance of reality can make us much more effective. The idealist in me would certainly prefer to support a CEO who is a true believer in the power of learning. One motivated by the strategic advantage available to companies that invest wisely in their people. But lacking that, a bigger budget and the power to put the best (team, solutions, tools) to work is a close second.

“I got my mind on my money and my money on my mind”

-Snoop Dogg

So where does your CEO get her money? The typical CEO compensation package has a significant stock or options component. This pay usually dwarfs the cash portion. With our understanding of how incentives drive performance, we can not be surprised. We can, however, be clearer on how learning aligns with those incentives. Here is the logic as I see it.

What makes a CEOs stock or stock option plan worth more? A positive movement for the company stock in the market.

What makes her company stock go up in the market? Demand for the stock.

What makes demand go up? New money or reallocated money seeking what the company stock offers.

What creates new money or reallocations? Business performance, investor values, events or “shocks” and regulatory and structural changes.

The Value of Shared Values

L&D Leaders should understand all of these dynamics on the company. This post will focus on the investor value driver. Investors’ values change. So does the demand for specific stocks. Look at all the different flavors of funds available. No matter what your investment objectives or personal beliefs there is a fund for you. The more people that share your objectives or beliefs the more money flows into those stocks and funds.

ESG funds, which fall under the larger sustainability or stakeholder umbrella, values a variety of non-financial measures such as social impact, environmental footprint and a company’s human capital strategy.

Alex Bryan, Morningstar’s director of passive strategies research for North America, told CNBC, “There’s a great realization today that ESG issues are investment issues. They’re issues that can affect the bottom line, and that may not always be something that comes to bear immediately. But it’s something that I think more people are starting to understand is aligned with shareholder value maximization,”

As the demand for stocks that share these values increases so does the stock price. And the demand is rising fast. Combined inflows (new money and reallocated money) into both active and passive ESG-focused funds reached $71.1 billion during the second quarter alone.

The recent change at the SEC regarding the reporting of human capital practices are another indicator of this trend. Diversity & Inclusion receive the lion’s share of the media’s current attention but a rising tide lifts all boats. Research from Europe has already shown that the simple act of reporting human capital practices leads to increased investment by companies in these areas.

L&D shares the values of this new investment wave. Not only for self-serving reasons, but also because they have always been our values. Values we try and live out everyday in our roles as learning professionals. Now these same long-held values move our company’s stock price. Think that will get your CEO’s attention?

FOMO vs. NPS

Missing Out on L&D

I thought The following excerpt from my book (v3 coming in later this month) would be appropriate as we enter the budget season. Two decades ago when Ed Trolley and I started doing executive interviews in support of our training organization assessments we were sure to ask a rating question for learning and development. As time went on it became the net promoter score question. Over time, and many assessments, we continued to improve our data collection to provide a deeper understanding of the potential, and realized, value that the learning organization delivered. During this time we identified what we think was an even more powerful question.

Perceived Value Score (PVS) question:

“On a scale from “extremely impacted” [10] to “would not notice”[1], how would your business be affected if all of our L&D solutions went away?”

Startups are constantly seeking “product-market fit”. Simply defined by Marc Andreessen, founder of Netscape and leading startup investor, “Product-market fit means being in a good market with a product that can satisfy that market.” The fear of loss, captured by the PVS data, was identified as a strong indicator of startup success. Sean Ellis, founder of Growth Hackers, a community collecting actionable information on how to produce high growth for organizations, sets the bar for PMF at 40%. If forty-percent of your users aren’t rating your product/service top box then your product or organization doesn’t have it.

This gauge as to how essential learning and development is perceived by business leaders can be a compelling endorsement or call-to-action. The coronavirus shock has resulted in the provision of learning changing dramatically over the last six months. What was done face-to-face is now provided virtually or not at all. New skills such as managing at a distance were needed in short order. So now perhaps the question is less about business leaders’ability to imagine a world without L&D and more about today’s reality.

What is your learning organization’s PVS?

Data as Star/Data as Author pt.1

This is a two-part post with some ideas about the stories that data tells (author) and using data to tell a story (star).

Data as Star

When I was running strategy for iZS, Zurich Scudder’s VC attempt during the first dot-com run, I read an HBR article (the physical, ridiculously priced magazine) talking about companies producing two things; a product and a data stream. Today’s environment has sensitized those of us who are paying attention to the fact that companies know a s*%$ ton about us. So with all this data flying around why are we still married to the old-school, direct data collection. Or limited by the lack thereof. We need to get smarter to solve for two problems:

What we are asking our measures to measure has changed but the measure has not.
Measures that don’t exist.

In order to use data as the star of our story, it must exist and it has to be believable (source, methodology, red-face test). Other than that, data in support of a pre-constructed narrative too often a creative endeavor. We use L&D spend benchmarks as a way of showing how our company is leading the pack in our industry. we use the same metric but compare it to the highest performers in the world (where the company is a bit more middle of the pack) when we submit our annual budget. While data authored narratives can also be fraught with biases, assumptions, and intent at least it starts with and is anchored by the data.

Two data scientists delivering a talk to a group of startups in Delaware remind the audience that data is like a bikini. Very intriguing but revealing nothing. Loved those guys.

I have a job, kinda.

I worked with a company that did a large volume of formation documents. These are the documents that need to be completed and filed with states and the Federal government when you start a company. They reached out to me to look for additional revenue streams, partnerships, or any other ideas that would help strengthen their already leading position.

Of the many ideas that my team and the internal team developed the one I loved was a data play. At the time, ADP has just begun releasing their employment data index. A set of publicly announced numbers that suggested the current state of employment. You may ask, “don’t we already have a number from the Bureau of Labor Statistics (BLS) for that?” We do. It sucks. If you go underneath the BLS numbers you realize the number’s number is up. Don’t take my word just google it. One of the many voices you will come across is Dr. Robert Shapiro’s from EconVue,

Dr. Shapira is no slouch having served as Under Secretary of Commerce for Economic Affairs for four years. Here is how he describes the reason why people at the outset of the pandemic were deemed not “available” for work and therefore excluded from the unemployment calculation.

“In fact, millions of Americans were not “available” for work in April because they were caring for children whose schools were closed—and millions of people didn’t look for new jobs because the avalanche of layoffs made a job search pointless. They fit a textbook definition of individuals whom the BLS excludes from the ranks of the labor force, and so do not count as unemployed.”

So tell me again why we don’t need a data point that simply counts the number of paychecks it issues for its clients every two weeks. Seems closer to the source. Still not perfect, but important.

So our data play for the formation king was just as simple as ADP’s. We already knew how many new businesses were being formed. We knew what percentage of the overall formations it represented (more than representative). Hell, we even knew what type of business was being formed (barbershop, restaurant, welding.) So why not create an entrepreneurial index that showed how active the startup spirit was and in which sectors they were seeking their fortunes. This information could be useful for commercial real estate, business banking, tax incentives, and more. Again, imperfect but important. They chose other options but this post is also me pitching the idea to them again (call me).

How will the rapidly growing gig economy make the current measures even less calibrated to reality? We have to look at new and better measures for important things that must be measured properly. If we are to use the unemployment data as a proxy for how well we are doing, as workers and as an economy, then it better be as close to right as possible.

The economy goes as pickup sales go

This proxy is real and has been around for a long time. DataTrek is a believer that, “pickup truck sales can be a helpful indicator since the trucks are used in a vast array of businesses, and are typically a discretionary purchase.” More here. To paraphrase Forum Corporation co-founder, Richard Whitely, quoting some ancient wisdom from someone…

“We cannot see the wind. We know it exists by watching the leaves.” – Unknown

“True dat.” – Me

So the pickup proxy may be a bit of a stretch but it has a history (relatively accurate directionally) and broad nodding acceptance. While these correlations may seem silly finding one that works can provide insight, and even advantage. Say for example you are the first to see the relationships between two data sets, Home Depot revenue and Housing Sales. Whenever housing sales go up revenue goes down implying that people are buying rather than building. Or revenues rises when home sales go down implying more fixing up less moving. Either way (or both) there is an insight into consumer behavior and as long as there is a time lag between dataset results there is time to exploit it.

So in the case of the health of the economy what other leaves could we be watching with our all-access pass to the data-sphere. So how about a healthy neighborhood index? It could consist of:

Credit card receipts for all the businesses in the ‘hood (local business revenue)
Utility late payments (resident disposable cash)
Major crime statistics (gun violence, home invasions, assaults)
Building permits issued (new development)
Employment by local businesses (growth, stability)
Aggregate savings growth
Property maintenance complaints filed
Utility events in the last time period (power outage, water quality, etc)
Solar installations (environmentally consciousness)

None of these ask residents how healthy is your neighborhood. NPS is a great proxy but redemption of referral codes is better. Leaves don’t lie. People can say that being green or putting money away for retirement is very important to them but counting solar panels, recycling bins and 401k balances are the truth.

L&D some days feels paralyzed by not having the direct answer to the question, “did the learning make a difference?” Too many levels removed. Too many variables in motion. So we say we don’t have the data. No data, no credit. It is a binary directional question. Precision is not required just a solid proxy that meets our requirements, especially the red-face one. Look for meaningful correlations. Not the “umbrella sales go up every time it rains,” kind.

Longer sales calls could be an indication of better customer engagement skills. Lower T&E expenses could indicate stronger adoption of Zoom. Increased sticky note purchases could be the basis for a corporate innovation index by including cross-department meetings (pulled from the attendee lists in our work calendars) and Ted.com views from the work internet (IT has this just like they have your entire browser history.)

If you want or need data to be the star of your show, it is out there. Sometimes you just need to not look directly at it. Some people say that selling is not convincing but rather helping a customer do the right thing. Data can do both. It can convince and help. How it is used is up to those of us who use it.

“Use your powers for good, you will.” – Yoda?

Part 2 – What’s My Backstory? [coming soon]

Catching Lightning on the Back-of-an-Envelope

“How far away is it?” Depending on the reason for the question, the precision of the answer has a different value. “No more than a mile” may be specific enough for you to make the decision between walking and grabbing an Uber. Every tenth of a mile may make a huge difference if you are wondering if you have enough gas to get to the next service station. Different uses for the results of a query help to define the valuable level of precision. I love the hacks, shortcuts, and rules-of-thumb that relieve me from spending energy on precision that is not valued.

One Mississippi… Two Mississippi…

I will let the National Weather Service explain one of the most well-known guesstimates. It is also one where the level of precision in the answer matches the question being sought to be answered.

“Since you see lightning immediately and it takes the sound of thunder about 5 seconds to travel a mile, you can calculate the distance between you and the lightning. If you count the number of seconds between the flash of lightning and the sound of thunder, and then divide by 5, you’ll get the distance in miles to the lightning: 5 seconds = 1 mile, 15 seconds = 3 miles, 0 seconds = very close.”

So it is not a terribly precise measure. It actually only takes a little over 4.8 seconds for sound to travel a mile, Based on that difference alone a perfect count would still be off by half a football field for every “mile” counted. And that is not even including the many variations of “Mississippi” in spoken timekeeping. But who cares? No one cares!

The questions that this guesstimate seeks to provide input to are equally imprecise. In answering, “how far away is the storm?” fifty yards is hardly relevant. The actions taken to prepare for a storm that is 3 miles away are identical to those for one that is only two and one-half miles away. “Is the storm moving towards us?” the other question frequently informed by this data, is equally imprecise. It is simply a directional measure. Did I count fewer Mississippis this time versus the time before? Having more precision adds little value to answering the question.

The ROI Misalignment

I am thinking about this alignment as I read yet another article promising to deliver a straight forward method for capturing ROI. I appreciate the noble quest but wonder if it is really needed. What are the questions seeking input? What precision is valuable to these questions?

Binary, one-time questions are what come to mind first. “Is this a worthwhile investment?” This is a simple yes or no question which does not value a highly specific percentage to be calculated. Confidence that I am going to at least get my money’s worth may be the hurdle to be cleared. The difference between 125% and 140% is negligible for confidence building.

There is a slide that used to be part of the standard startup pitch deck that made me cringe. The slide’s objective was to reduce the perceived risk associated with competition, prove the size of the market, and get potential investors excited about the startup’s potential. We called it the 1% slide. Often it was little more than a large pie chart showing the billion-dollar market size with a small 1% slice. The slide’s commentary always included some variation of, “and if we are only able to capture 1% of the market we are still a $400 million business.” Translated, “even if we suck, you win.”

So what if, rather than saying a certain learning initiative has a certain return perhaps all we need to do is show that the return clears some hurdle. The equivalent of the 1% slide. A blog on what is called the kaizen method sums it up this way.

“It might not seem like much, but those 1% improvements start compounding on each other.”

What L&D needs is a simple back-of-the-envelope calculation that allows it to confidently say to our business sponsors, “even if the initiative only moves the [profit/revenue] needle 1% we still show a positive return on your investment.” In my next blog I will lay out my back-of-the-envelope (BOTE) calculation. Spoiler alert: even if we suck the business wins. I look forward to your feedback and suggestions.

Bruce Lee on L&D Data

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“I am but a finger pointing to the moon. Don’t look at me; look at the moon.”

Love me some Bruce Lee.

I began this weekend’s mental wanderings with a thought that maybe, just maybe, when it comes to discussions on data the issue may be a “finger/moon” issue. For those not schooled in the ways of Enter the Dragon allow me to bring you up to speed. In the movie, Sensei Lee is instructing his pupil on kicking. He is actually exhorting his student for “more emotional content.” Maybe there are future Bruce Lee blog posts coming. Maybe ATD should re-issue this movie with associated CPEs. When he sits down to hammer home the lessons of the day with his student he explains to the student that,

“the finger is useful because of what it points us toward, not as an object of study for its own sake.”

Thanks to FakeBuddhaQuotes.com for the perfect summary. Upon reflection, I am now very convinced we have a finger/moon situation going on. And here is why we should care. The peaceful Essence of Buddhism Blog gives readers the big three reasons not to just look at the finger.

You’ll miss the moon
You think the finger is the moon
You don’t know what is naturally bright (has enlightenment) vs what is naturally dark (lacks enlightenment)

We will leave #3 to others to ponder. But #1 and #2 need some more time in the dohyō.

The moon is beautiful. Don’t miss it!

How do you know how fast you are going in your car?

How does your car know? Sensor on hub? Sensor on axle? GPS movement? Transferred on a tension wire? Onboard calculation?

Without knowing about “the moon” you can’t validate/invalidate a reading. You can’t know the impact changing out the axle for a thicker one or getting the big rimless tires on the odometer, speedometer and other measures. And by understanding the moon you are able to draw the connections and queries that lead to actionable insight.

This is where most data conversations get awkward. Most people don’t know the source data and so the conversation starts to sound like an interrogation. But it is just genuine curiosity. There is a lot of recent talk about the importance of curiosity. Feel free to get curious and go find some of these great articles. Scorecards are great but if you don’t trust where the numbers are coming from or don’t understand the calculations used you can’t understand why an initiative may or may not move the needle. The definitions of key data points are often undefined and it is only through this curiosity that the questions that need answers can get needed attention?

Let’s look at a simple question like, “How many FTE did your company have last year?” Answering this question is not as straightforward as it may seem. For example, how does your FTE answer treat elements such as working days per year? (220? Less due to vacation policy?) Hours per day? (8? 6.5?) Answers to these questions open a range of >23%. in a 10,000 person company that is 2,300 jobs that can make a big impact on any metric. Now the big moonbeam here is that FTE is part of the calculation of a ton of numbers. Wherever you see the lovely phrase “per employee” there FTE is, somewhere in the Excel spreadsheet…giving you the finger.

The key to avoiding #1 is simple. Get curious. Ask questions. You will be rewarded. And if you are wondering what the answer to the speedometer question is. Click here. Warning, the answer is really cool and while it feels a little bit overcomplicated (showing off?) it is still awesome.

“Don’t look at me; look at the moon.”

Ok so let me start this round out by assuming the following:

You are not/no longer suffering from #1
You are “nice”
Your boss is only watching the finger (all she has time for? understanding of?)

Taking #1 off the table saves us a bunch of time. Many New Orleans restaurants/bars have a sign somewhere in their establishment that simply says, “Be nice or leave.” I agree. If you want to game the numbers go ahead. Most good thieves have a deep understanding of the numbers so a slight hat tip to them. But since embezzlement and theft are not nice, they are out.

The last one…I will simply say this. I get it. If the finger is my $scorecard$ then yes I will look at the finger. Ignoring this dynamic is not going to help. We are all grown-ups and can talk about this stuff right? I wish business execs all wore their scorecards like handkerchiefs. I could instantly find business alignment and have an idea of the economics on the business leader’s side. A high impact learning event delivered in an area that moves a business sponsor’s personal scorecard is more valuable as the one for a non-scorecard business unit. Eye of the beholder and all, it just is.

And then there is 70/20/10

Please reconsider the value of this metric today. Blindly measuring Blend (delivered, available) is not valuable. Like Malcolm Gladwell’s 100,000 hours, we love clear finish lines. However, this part of the finger is my nomination for the most gamed stat in the L&D organization. What likely started as a slide to justify the costs of a digital library conversion became an industry gold-standard for a hot minute is pretty amazing. Someone should do a map of the acceptance of the 70/20/10 concept (google search?) along with Skillsoft stock price. We all get lazy and when everyone is yelling 70/20/10 you know where your safe place is. Sometimes we need to remember that there is a moon out there.

As for re-imagining the stat, with the moon on my mind, here are my thoughts. It should still be blend but from a learner’s perspective. So typical employee persona (please tell me you have these for your org) is seeing learning from all these channels at this %. The right mix is the one that drive results, just be prepared to defend your mix. By starting from the learner, not the media, we can now follow a valuable path of questioning:

How is this mix impacting employee experience?
How can mix be improved through scheduling?
How does this media mix compare with non-business related learner behaviors?
Every channel (online, in flow, etc) should have a channel objectives quant and qual. How are we doing against those channel objectives?

Sensei Lee would say to stay curious about the moon and remember to ask why of the finger. Crazy uncle Elon would ask if we are prepared for Mars. I would say that all we need to do is to get the boss curious about the moon.

Goofus Data

Goofus image

When I was a kid, one of the only exciting things about going to the dentist was the chance to catch up on my Highlights magazine reading. The childrens’ magazine is famous for a monthly feature titled “Goofus and Gallant” which showed the behaviors of good children versus those of not-so-good kids.

I was reminded of these cartoons as I sat, frustrated once again, listening to the media and politicians discuss Covid data. If you wanted to put together some real life Goofus examples for dealing with data you don’t have to look any further than the local or network news. From “garbage in, garbage out” to mistaking the data as the end and not an input to a deeper insight, Goofus seems to be hard at work daily.

Don’t have unclear/inconsistent reporting standards.

What is the definition of a Covid death? When do numbers get reported (even on Sunday?)

Don’t focus on the wrong data.

Infection count is only useful or important in the context of audience size or tests conducted.

Don’t look at daily data if the system operates on a different time scale.

We know there is a lag between action and impact with Covid. Would a rolling 14 day average be more useful for planning and trend analysis?

Don’t lose the message in averages.

Pull out a few early states, or remove the elephant that is New York and watch how the chart of the country’s battle changes.

Don’t use the wrong units.

Percentages can be a marketers friend (100% growth of a small number sounds better than the actual number) but sometimes it is also the best way to understand the data. Percentage (%) of beds in use versus number (#) of hospitalizations is more readily understandable when ICU beds are a key capacity constraint.

Those are just some of my daily irritants. And don’t get me started on false positive % or how an exponential function works (just watch this old shampoo commercial.) https://youtu.be/mcskckuosxQ

Do you work with data? What would you add?

Project Dragonfly

Last fall a client asked me to write a quick brief on the book Range. With permission from the client, I am sharing it here. You can read it below and download it here Dragonfly Concept Design

Enjoy. – j.

named for an insect whose eye contains thousands of “eyes”, giving it a wide range of perspectives from which its brain constructs its reality and actions.

Project Genesis

Sparked by the release of David Epstein’s book Range, the question that launched the quest was crafted as follows:

“Is there a way to predict employee high performance, and therefore company high performance, by examining the degree to which their path to performance (P2P) is in alignment with the principles outlined in Range?”

Contributing questions include:

What performance does business need from its employees?
What is the traditional/current/accepted P2P for employees?
What are the principles that define the Range P2P?
How can we objectively measure the alignment of a company’s current P2P?
What are the barriers to organizations adopting a “Range-driven” approach to talent management?

What performance does business need from its employees?

Today’s business environment has been termed and widely accepted as VUCA (volatile, uncertain, complex, ambiguous.) This environment has placed a premium on organizations that are:

Agile – able to quickly deploy and redeploy human capital to emerging needs and opportunities.
Experimental – have a culture and resources able to conceive, test and iterate of new hypotheses.
Innovative – ability to generate and execute new ideas in order to capture business opportunities.
Data powered – human capital is augmented by data for management (ie. performance tracking, succession planning) and the delivery of the above capabilities.

Today’s business environment is as being what Robin Hogarth calls a “wicked domain.” Wicked domains are defined as having problems that are not readily computable and have feedback loops that are long and may not provide accurate feedback. The answers to wicked problems are unknown at the outset and need to be created. Examples of wicked domains include improvisational jazz, and cancer research.

Net: Today’s business environment requires a P2P that makes human capital “wicked smart” (Boston joke)

What is the traditional/current/accepted P2P for employees?

Today’s development paths generally follow two paths depending n the employee. Designated high potential employees are often provided a wide ranging development path early on in their careers. Business units rotations, projects and even mentorship expose this employee to all aspects of the company as a means of preparing them for future leadership positions. This cohort is typically extremely small relative to the employee base.

The second path serves the typical employee. On this path employes, who have been hired for a specific domain experience are funneled into deeper knowledge of that domain. Sales people receive sales and product training, an operations employee may receive task management and process training wile operators might attend equipment and safety courses. These trainings, limited to a single domain are associated with the assumption of a kind domain and problems.

Kind problems are domain-constrained with tight and accurate feedback loops. Unlike the wicked variety, answers to kind problems are known and simply need to be found. Kind doesn’t mean easy, a sport can be kind because you quickly know if you executed the correct stroke. Examples of kind domains include classical music, hernia surgery and chess. Kind domains are are often the best targets for automation.

Range principles, where existing, are often found in the initial hiring process. In 1991 David Guest introduced the concept of t-shaped skills. The vertical bar of the T refers to expert knowledge and experience in a particular area, while the top of the T refers to an ability to collaborate with experts in other disciplines and a willingness to use the knowledge gained from this collaboration. This concept was further popularised by Tim Brown, CEO of design firm IDEO. While the concept was seen to have value and gained momentum with HR the concept of developing t-shaped employees never took hold. The priority for most recruiting and promotions involves an emphasis on the vertical domain of the individual.

T-shaped employees provide companies with increased talent agility and mobility. Having an agile workforce can spell the difference between being an industry leader or falling behind. PwC reports that when businesses have development programs that increase agility, 86 percent respond rapidly to changes in the business environment. Without these kinds of programs, only about half do. A Forbes article from earlier this year stated that talent mobility enables organizations to rapidly adapt to changing environments, with the ability to deploy and move key skills across projects, across the business and across borders when needed. Mobility provides avenues for staff to progress and evolve within an organization, and can lead to 30% better processes and 23% more productivity.

Epstein captures it this way. “Facing uncertain environments and wicked problems, breadth of experience is invaluable. Facing kind problems, narrow specialization can be remarkably efficient. The problem is that we often expect the hyperspecialist, because of their expertise in a narrow area, to magically be able to extend their skills to wicked problems. The results can be disastrous.”

Net: Today’s P2P does not fit business to a “T” (I am on a roll)

What are the principles that define the Range P2P?

First it is important to acknowledge, as Epstein does multiple times in the book, that while Range-enabled generalists are critical to business success the value of specialists is not diminished. A multitude of examples are provided showing how generalists draw on the deep expertise of specialists in order to achieve the results delivered. Distilling the book’s insights and translating them to corporate talent management creates three levels of guidance. The first contains the characteristics of a Rangey(?) path-to-performance (rP2P). The second, is guidance on keys to rangey teams. The final level is focused on the organizations itself.

rP2P

The goal of the rP2P is to build polymaths. Polymaths differ from T-shaped employees in that the emphasis is on the horizontal dimension. A polymath’s breadth is greater than T-shaped human capital while their vertical depth may be less than traditional T-shapes. The polymath’s superpower comes from a range of transferable thinking skills (conceptual, computational, lateral, and ambidextrous for example) that allow for innovative problem solving across multiple domains. It also includes more tangible skills such as communication, collaboration and anticipatory competencies that drive higher value solutions. The final element of a range-y employee is attitudinal with value-adding polymaths displaying active open mindedness and scientific curiosity.

The first two principles associated with a Range-aligned P2P focus on the structure and focus of the developmental path. The rP2P contains:

A sampling period – This is characterized by what experts often call “unstructured play.” This feature of the developmental path allows for individuals to experiment in domains other than their own. In the corporate environment this may be a rotational program or project-based. The unstructured element forces participants to improvise first before learning existing rules. This is analogous to the way in which humans learn language. We learn the sounds first before we learn the rules of grammar. This element should be designed to provide the participant with experiences that allow them to better understand alternative domains giving them knowledge of resources that may be valuable when facing later challenges as well as exposure and personal knowledge of their interest and proclivity for other areas.
Mechanisms for improving “match quality” – The rP2P should include opportunities for individuals and organizations to re-deploy individuals to domains better suited to their skills, interests, and proclivities. Short-term assignments, internal internships and project participation can be used to serve this purpose. Up or out development paths serve neither the individual or organization.

The final two principles associated with a Range-aligned P2P focus on the content and presentation of that content on the developmental path. The rP2P contains:

Flexible content – Flexible content is content that is both sticky (retained over the long-term) and broadly applicable. Retention of rP2P content is driven by two key factors. The first is the use of testing. rP2P test questions are connection making in nature versus procedural. Testing should focus on cross domain application, pattern recognition, categorization and decision making. Procedural questions such as “what are the four steps in handling a customer objection?” are minimized in far of questions such as, “what other uses for the customer objection handling process are there?” Stickiness is also enhanced by the use of spacing. Delaying the testing process forces the knowledge to be placed into long-term memory. End of class assessments are less indicative of future performance than follow up assessments given at a later date.
Difficult learning experiences – Learning should include what Nate Kornell calls “desirable difficulties.” These productive difficulties include creating a generational effect, where participants produce their own answers exclusive of guidance. Learners benefit greatly from this self-reliant process even if the answer generated is incorrect. Instructors should also be creating environments in which learners struggle. This may include problems beyond learners’ capabilities, mixing multiple areas of new knowledge together to prohibit “block” learning (aka memorization) and assessments in which few learners achieve a passing score. While this often results in lower instructor/session ratings from participants it has been shown to have significant long-term benefits in retention and performance.

Rangey Groups

While the book focuses primarily on the individual, Epstein highlights two characteristics of high performing groups.

Diverse – High performing groups included a wide variety of participants. This includes range in:
- Geography/World view
- Demographic
- Experience in domain from novice to expert
- Domain, but still polymaths not a collection of specialists
Porous boundaries – Groups that performed well were also not walled off from the rest of the organization. Groups frequently showed improved value when they were able to reach out to specialists across the organization and even outside the organization.

Rangey Organizations

Example such as 3M are cited in the book as examples of an organization that supports its range-y individuals and teams. From creating an internal award for innovation to the ways it allows individuals to follow their passions (increased match quality) 3M regularly produces significant innovations across a wide range of domains. Epstein touches on a few organizational keys.

Culture – 3M’s internal award and its talent management approach are operational examples of a culture that sees the value of supporting its rangey employees. By celebrating, facilitating and empowering range, 3M has created a culture that makes it values more than just an annual statement cliche.
Long-term focus – Because range often does not show immediate results the organizations that embrace it must have a longer view. Think of the innovations that emerged from Amazon and the newly approved LTSE (long-term stock exchange) that clearly states that “Companies that operate with a long-term mindset tend to outperform their peers over time. But going public can pressure even the most visionary founder into a short-term mindset.”
Risk tolerant – Creating new solutions that work often means finding many more that don’t. Acceptance, even encouragement of failure, and the adoption of an experimental scientific mindset are cornerstones of organizations that deliver higher performance over the long-term.

Net: The principles of Range have implications for a number of areas in talent management including; candidate selection, onboarding, development, succession planning and leadership. In order to drive success in today’s wicked environment organizations, and talent management functions that support them, must become an integrated farm (egg-to-soup) for free-range talent. (the roll continues)

How can we objectively measure the alignment of a company’s current P2P?

Standard measures for HR practices are in limited supply and often not publicly available. The table below captures some initial thoughts regarding potential metrics/proxies for the various elements of range. Primary research in collaboration with one or more of the partner listed at the end of this section and/or analyst-like interviews focused on HR leaders may also prove useful in the development and testing of a quantitative range “score”.

	Dimension	Metric/Area of Inquiry
rP2P	Sampling	Onboarding process Use of project assignments Cross domain rotations
	Match Quality	Internal lateral transfers versus upward promotions Use of project assignments Cross domain rotations Former employees now working in another domain Employee satisfaction Employee retention Employee engagement Employee development plans
	Flexible Content	Learning experience (LXP) design LXP satisfaction scores Cross functional applicability of LXP (multi-audience) Layoffs
	Difficult Learning XP	Learning experience (LXP) design LXP assessment timing LXP pre/post assessments Instructor ratings Post-LXP performance reviews
rGroup	Diversity	Employee census Recruitment procedures Job requirements (narrow/broad)
	Porous Boundaries	Resource sharing policies Use of outside experts/consultants
rOrg	Culture	Employee survey Leadership characteristics
	Long-term Focus	Strategic plan R&D spend

What are the barriers to organizations adopting a “Range-driven” approach to talent management?

While the value of rangey practices are widely documented, adoption of the proven practices face a number of challenges. Some of these challenges are documented below. This list is not meant to be all-inclusive as it excludes any number of organizational structure, compensation and process barriers.

Slow thinking requires a longer payback period – As is the case in spacing of testing where immediate results may be poor while results produced further out exceed the current P2P so it is with much of the range principles. Organizations and other stakeholders (HR, Management) may find it difficult to “stay the course” without near-term ROI.
Spacing assessments is less rewarding to learners – Individuals often do not receive the immediate gratification of progress and success when participating in a rP2P. Without buy-in from individuals to the range approach and the safety of knowing that their immediate performance will not be seen as a negative by the broader organization individuals may not actively engage in the path.
The result of increased match quality (job switching) can make individuals feel like they are falling behind – Job switching, often the result of seeking improved match quality may leave individuals feeling behind their peers. The concept of sunk cost, time and energy committed to a pre-switch domain, may make individuals and organizations reluctant to follow through with match optimization.
Misaligned metrics (learner satisfaction, post-assessment scoring) reward non-rangey principles – Current P2P metrics are short-term oriented and in many cases run contrary to effective implementation of range principles. Changes to how rP2P facilitators (recruitment, development, management) are necessary in order to properly measure range-y progress.
Lack of obvious linkage to near-term business results – Rangey performance often delivers value in unexpected areas/was. Measurement and management of impact on wicked problems must be different than on kind ones. New product development (connected/wicked) should have a set of metrics distinct from new store openings (procedural/kind).
Short-term perception of poor performance – Public company cadence (quarterly) may inhibit the longer term investment in a rP2P.

Net: Lots of fences between the herd of sheep and the range. “Just let me know if you wanna go to that home out on the range. They got a lot of nice girls.” – ZZ Top

Final Thoughts

After reviewing the publicly available research used for the compilation of this document I believe the following to be true:

“Wicked” is an accurate description for an ever increasing portion of the business environments and the “kind” portion will increasing face the pressures of automation and commoditization.
The companies that win in a wicked world win exhibit a significantly higher degree of “range”.
Adoption of range positive dimensions require significant change for both the individual seeking to increase their personal range and companies seeking to provide a range-enabling organization.
The current structure for talent development and management is designed for the creation of specialists and ill-prepared for a shift to polymath focused human capital.
With additional work there exists an opportunity to capture or create qualitative and quantitative metrics for assessing range on both the individual and organization levels.

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The Tail Will Wag the Dog

David Vance recently did a webinar regarding the pending legislation requiring the reporting of human capital metrics for public companies. I cannot state strongly enough the potential implications of this move. A move which I feel equally strongly is being largely ignored by my L&D colleagues. I do not have a crystal ball but simply applying the dynamics of other publicly reported numbers may help to clarify.

Publicly Reported Numbers Get C-Suite Attention

L&D has long asked for it but is it ready for it’s close up? While L&D’s current data reporting may make the industry feel good but will it stand up to the scrutiny given to financial data reporting. As a CLO can you sit with your CFO and defend the numbers, the methodology of collection and the actions taken as a result of them. Financial numbers (margins, expense, key ratios) are never good enough and always include the plan for improvement.

Transparency

Having the numbers out there without context is going to create some interesting dynamics. The L&D metrics for a company are highly contextual. This is something that I have long argued as a mitigating force to the use of benchmarks. Most companies are a cohort of one. The growth goals, competitive environment, geographic challenges and legacy paradigms are just a few a few of the things that can make a company’s metrics right for them and them alone. Without this context L&D may face pressure from new external and ill-informed senior internal sources.

Teaching the Test

If the metrics are what becomes the face of L&D the natural response is to game them. This is no different than sales organizations that pull sales forward to make a quarter look better or an operations department that delays a purchase to manage costs. When what gets delivered is in pursuit of two masters (performance and metrics) and one is highly visible, which one do you think wins.

Short-term Thinking

There are many who decry the behavior of public companies driven by a quarter-by-quarter mentality. We know that performance development occurs over time. How will our approaches to leadership, diversity, and upskilling change when they are held to the 90 day window of reporting. This is not to mention the fact that if the metrics are wrong. We all know that vanity metrics are a constant, although comforting, threat to true performance development.

What do you think will happen when L&D goes from opt-in self-reported numbers to a friendly industry organization to a federal requirement? Is your organization ready?