When is it not Capital? When it’s Human.

Every annual report talks about people being the company’s most important asset.. Except it isn’t.  A quick glance at the balance sheet reveals no line item for people.  The facilities are there.  The equipment is there. But nowhere do the people show up as an asset. 

Over the last few months I have been doing a bit of research into the historic effects of automation on the workforce.  Think elevator operators and bank tellers.  More on that at a later date. [spoiler alert: the robots are indeed coming for some of our jobs but that is a good thing] One thing that came from my research is that companies are incented to automate on multiple fronts.  It is on one of these fronts, accounting, that we may have a lever to incentivize upskilling.

A quick primer.  When companies buy a robot, or any piece of equipment, they pay for it but rather than have it simply take cash out of their account it does something else.  If they robot is estimated have a working life of 10 years the company places that “asset” on its balance sheet, reducing its value for every year of service.  This asset sits opposite the debt the company has, allowing it to borrow more. If I replace a human making $50K with a robot that costs $250K but is expected to last 10 years after the first year I have an asset worth $225K on my balance sheet (the cost spread over the lifespan less the first year).  If I spend $5K  to upskill the employee to perform at a higher level, equivalent to the robot, I have nothing but an expense that hits my bottom line.

Large publicly traded companies are evaluated quarterly by Wall Street.  The results reported often drive a short-term mindset but it also keeps key metrics front and center for these companies.  In addition to the asset to debt ratio, one of these measures is revenue per employee. This simple metric, top line revenue divided by the number of employees offers a clear way to see the benefit of automation. If a company can simply hold its revenue steady while reducing its headcount it looks better on paper than a company that might grow revenue modestly with the same, but upskilled, workforce.

So what if a company’s investment in  people could be truly treated as an asset.  Invest $1k in an employee and your average tenure for that role is 3 years. Why isn’t that a capital investment to be added to the balance sheet ($666). The switch is a case of accounting policy but what is more interesting to me is what the change in behaviors of companies might be.  If employee upskilling was treated as a true capital investment would L&D see more money, stricter reporting standards and a more respected seat at the table.?      

Fall in Love with the Problem

I was reading a recent article from the folks at Lean Startup and it hit a nerve as began writing up some new ideas for the Running Training Like a Startup (RTLAS) v2.0  The article revisits a long held tenet of product development, “fall in love with the problem, not the solution.” This is similar to, “if all you have is a hammer everything looks like a nail.”  In RTLAS v1.0 I describe the importance of deeply understanding both the challenge and the learner as part of the design process.

As someone with a foot both inside and outside the learning industry I often feel torn.  My outside foot telling me that the industry is misaligned and in desperate need of a full reboot.  My inside foot knows many of the talented learning professionals and empathizes with the challenges they face. In fact, in 2010 when I first began writing my Learning Hacks blog to explore the connections between startup techniques and L&D I wrote a post originally titled, “This Industry Needs an Enema.”

That said, judging by the literature, discussions, and personal experience the learning industry is deeply in love with solutions and only friendly with the problems being faced by businesses today. We know have many more tools in our toolbox than just a decade ago.  In fact keeping up with all the tools can be a full-time job. But just as “convert it all to elearning” was a hammer looking at a course catalog of nails, the industry needs to remember that great solutions come from loving the problem. Let’s at least be “friends with benefits” with it.

What are your thoughts?



Open Source

I just re-read Walter Isaacson’s “The Innovators”, a wonderful history of the people and events that made the digital age possible. In it he describes the creation of the software industry and the early formation of two camps. One thought that software should be free, describing the hobbyists that openly shared code between another. He even noted that that Wozniack’s early schematics for what would become the core of the Apple 1 computer were given away free by Woz at community meetings. The second camp, characterized best by Bill Gates, saw the protection of intellectual property as key to supporting future innovation.

For the open community, allowing innovations to be shared allowed for rapid adoption and accelerated advancement. Innovators didn’t need to recreate a solution that had already been found and could instead focus on building upon it. Also, by adopting an open approach an entire community became an extension to the development team. The opposing camp felt that without compensation innovation could not be supported. I see both sides and as a former interim-CEO for a music technology company, an industry where rights are front and center, feel strongly that the creator has the right to choose, and that choice must be respected.

As I came to complete the book Running Training Like a Startup I realized that I now had to make this choice. I could publish the book, thereby monetizing my efforts or I could give it away. When I work with startups I often refer back to a presentation on startup success that I saw during the first dotcom run that simply stated CFIMITYM. Cash flow is more important than your mother. Without cash flow, a startups life is on the clock. Many startups, even those so-called “unicorns” that are now going public, often chose another path. Monetization slows growth and adoption. “We can always monetize once we have a million users,” they say. And so, the freemium model, where there is a free tier of services available, was born. Once a user has seen the value of the product, they can upgrade to a paid tier later. When I was at Forum we called this “earning the right” in our sales training.

I believe strongly in the value that Running Training Like a Startup can contribute to the industry. I think that upskilling is the number one challenges facing the world. I believe that more minds, not a select few, will accelerate our industry’s ability to overcome this challenge. I also know that at the pace of business today reinventing the wheel will not cut it. For this reason, I have decided to open source the book. Feel free to download it, share it, discuss it, build on and improve its concepts with your own. I will be doing the same. This blog will continue to document my evolving thoughts on the concepts presented in v1 and I am committed to sharing my learnings with our community. All I ask is that you do the same.

Open source book here

Here Comes the Book

As I completed the v1 of Running Training Like a Startup I realized that during every review cycle I wanted to add in something new I had read about or experienced in my work with startups. In the lingo of early stage companies this is called “feature creep”. Reminding myself that this book (product) and its concepts (features) were in fact startups of their own I set a v1 release date and stopped. I feel strongly that the opportunity for learning organizations to deliver more value by adopting startup techniques. But the ideas I have captured offer no value to the industry sitting on my hard drive. More on the release in a few days. 

In order to offset my feature creep, I have identified 10 key threads that run through the book and will continue to update the here on this blog. For readers of the book this will offer a simple way to delve deeper into any particular or to see the evolution of that idea since the release of v1. As appropriate content will be integrated into future product releases. The ten threads covered in the book and incubated here are:

· Founders

· Founding Team

· Pitching and Communications

· Experiments

· Failure

· Product Management

· Speed

· Data

· Organizational Framework

· Tools and Resources

I look forward to the release and to watching how this approach can transparently grow the approaches to delivering unmistakable value.

Tough Conversations

I am immensely grateful to the early reviewers of my book.  They generously donated their time to give both the rough draft and various nascent concepts a look.  One piece of feedback that I thought was particularly interesting was that while they felt that the book would was both needed and valuable, learning organizations will face challenges putting it into action. Challenges not faced by startups.  Startups have the advantage of starting with a clean slate. An organization of two founders working closely has no defined roles. They are just gunning to get things done. Startups, at this stage, are flexible and fluid and rapidly adaptable. Everybody on the team knows that survival is all about meeting a deadline for shipping the product or reaching the next investor milestone. The goals are clear.  It’s all hands on deck there’s no time for the politics that get in the way at large organizations.

Scott Kirshner wrote an article for HBR recently in which he talked about the biggest barriers to innovation or disruption inside organizations and it should come as no surprise number one was politics.  What was a bit surprising was the percentage of executives citing this as barrier number one was twice the number of executives who said that budget got in the way. So while we may sing that constant refrain of,  “I don’t have enough money,” or, “it’s not in the budget.” The fact is that for those of us who are actively seeking to put new approaches into learning and to adopt principles, tools and techniques that are different from how things have been done, we will need to become better politicians.

The second most cited barrier innovation and understanding in the article was risk aversion.  A thought on this is that this objection may mean something else. It may mean that the population of the company is weary from “flavor of the day”. Many companies follow business fashion.  A business concept, widely accepted and supported this year, may fall out of favor next year.  Due to this, a company culture can be taught that they actually don’t need to do anything other than simply ignoring a new approach, knowing that this too shall pass. Defining this as risk aversion may simply be an easy way out. 

In Running Training Like a Startup I introduce a number of new and novel approaches adopted from the best practices of early-stage startups.  These tools are gonna feel unfamiliar to many business leaders . For implementation to succeed tomorrow’s learning leaders will need to have conversations, that while potentially uncomfortable, will lead to a stronger relationship between these learning pros and their business sponsors.

Some L&D Math and Some Questions

Disclaimer: I am a lover of data.

I had some time play with some of the data in ATD’s State of the Industry Report and it raised some questions for me. In order to better understand the ATD data, I looked at the “implied” results that are not included in the report. Because ATD includes data such as percentage of revenue and percentage of profit I can simply reverse the calculation to see what the trends are for both revenue and profit per employee. Since these are the ultimate measures of the success of learning, the trends in these should be trending positive or at least correlated to the investment in learning being made by organizations.


The first thing that stood out was the delta between the implied revenue per employee (RPE), a common public market metric, and the profit per employee in the ATD report and the S&P 500 average. According to Yardeni, an economic advisory, the 2016 Average RPE for S&P 500 ranged from $321,000 and $1.7 million depending on industry with a profit margin of approximately 10%. The revenue discrepancy for Consolidated cohort is understandable given the smaller size for many of the reporting companies for the ATD data. The comparison to the BEST cohort is closer but still under the S&P averages.

The comparison to profit per employee was similarly off.


I then looked for a correlation between learning and an impact on revenue and/or profit in two ways. First, I looked to see how the numbers compared year over year. I then looked for a correlation between learning and an impact on revenue and/or profit in two ways.

First, I looked to see how the numbers compared year over year. This view showed that the increased percentage of investment in learning, touted as a positive reflection on businesses opinion of learning in the ATD report might be misplaced. The ATD report states “Confirming organizations’ commitment to learning, this indicator [% of profit] grew from 8.3 percent in 2015 to 8.4 percent in 2016; the ratio has climbed steadily for four years in a row.”


While ATD seems to draw a positive connection, in fact this may simply be a case of reported profit and revenue dropping, things that businesses care about. There appears to be no correlation. The resulting chart shows years where learning hours rose and the implied profit or revenue dropped. If there is a return to be captured from learning, the ATD numbers don’t seem to reflect it. I did a similar look lagging the revenue and profit a year, to let the impact of the learning spend sink in. Still nothing that showed a correlation much less a causation.

As I stated in the post on benchmarks, be careful.

Benchmarks and the Danger of Data


We are always excited to read the annual installment of ATD’s State of the Industry.  Cited year round by our clients, and the industry as a whole, this compendium of data is seen as an important touchstone for many L&D professionals. But, while these numbers are used by so many to justify a sought after initiatives or validate current activities, benchmarks can be misleading.

The other note about benchmarks and data is that cherry picking a single data point or even source can be misleading.  While it can be comforting, it comes with a caution.  While some will point to the positivity of increased spend, others will cite the data from Bersin by Deloitte, Corporate Executive Board and others, that shows the lack of confidence in L&D, the amount of waste caused by scrap learning or the negative net promoter score for L&D.

Achieving benchmarks is not the goal for today’s learning organizations.  While directional, every company is its own group of one. Your company’s business strategy, market conditions and human capital are unlikely to be identical to any other. If you are spending lower or higher than benchmarks, and delivering no value, you are overspending. The reverse also holds true.  The true metric for learning professionals to watch is their contribution to the success of the businesses that L&D serves not spending levels.

Some additional thoughts for math lovers here.