CHART OF THE DAY: ETFs, Active Managers, and Human Specialization

Today's Chart of the Day comes to us from the world of Finance and our pals at Bloomberg and shows just how once type of job, the "active", (and human) mutual fund manager is being disrupted by another kind of manager - a 'passive' one, modeled against the market more broadly, and dominated by algorithms and sophisticated computers.

Long story short - investors have been migrating their money away from the active, people-driven funds and strategies and towards the passive, ETF-type funds. Here's the chart from Bloomberg, then some comments below from your favorite active blog manager (me).

Some really interesting things to note from this chart. And recall, just like when we blog about basketball here, this blog about finance and investing isn't really just about finance and investing.

1. Highlighted on the chart is the worst of the financial crisis, September 2008. This appears to be the inflection point where investors bailed on active investment management in favor of passive investing. In other words, when times were tough, investors didn't seek 'expert' human management for their diminishing funds. In fact, they sought out the opposite.

2. As the chart above demonstrates, the current active management model for investments simply can't compete any longer with the cheaper passive/ETF model in either total asset gathering (trying to simply grow the way to prosperity), or in terms of returns. Whatever the current strategy is for the active managers, it is definitely not working and has not been for a decade.

3. So what can these highly-paid, expensive, and under threat active fund managers do to at least try and maintain some relevance and hold on to their country club memberships and beach houses? Bloomberg suggests one approach - hyper specialization.

From the piece:

What does the future of active management look like? We believe it should only seek a portion of an investor's assets. To do this, they will have to create highly idiosyncratic and concentrated portfolios. They will have to find the one thing they do well and do it in a concentrated, risk-seeking way, whether it be health-care, emerging markets, macro themes, algorithms, technology or trading. The manager will need to be known as the "go to" person in that space to emerge as the next star, allocating capital as efficiently as possible.

Again, the specific example/industry/job role doesn't matter here. What matters is the method and approach for people to remain valuable and competitive in a situation where machines and algorithms have plenty of advantages. The advice is not to try and out-compete the robots where you simply can't defeat them, but rather to seek out those areas, pockets, and opportunities where you can leverage uniquely human skills and experience to stay one step ahead of the machines.

Super interesing article and one that I think no matter what industry or job you are in, has something we can learn from as well.

Have a great day!

Learn a new word: 'Foldering'

From the world of 'the lengths people will go to in order to keep their employers, law enforcement, and/or the government from snooping on their digital communications' comes today's Learn a New Word - 'Foldering'.

Not familiar?

Neither was I until I saw the term pop up in one of the (many) legal scandals and issues swirling around in the Federal Government lately.

Here's the definition of 'Foldering' from our pals at Wikipedia:

Foldering is the practice of communicating via messages saved to the "drafts" folder of an email or other electronic messaging account that is accessible to multiple people.

Foldering is sometimes described as a digital equivalent to the dead drop.Like the dead drop, it has no usage outside of clandestine communications.

So you want/need to send someone an email, but want to (try) to make sure that no one but the intended recipient gets their eyes on its contents?

Well, since we know employers can see your sent emails and so can big tech like Google or Yahoo (once they get an order to turn over data from the Feds), you try this 'Foldering' tactic.

You set up an email address, create your intended email, but instead of sending the email to your recipient, you save the message as an unsent Draft. You then share the email account's login credentials with your recipient, (hopefully not in an email), and then they simply log in to the account, read the draft message, and then update the draft message (again without sending).

The two of you then go back and forth updating the message(s) in the Drafts folder instread of actually sending any email - thus the term 'Foldering'. Once the needed information is shared, someone deletes the draft - the idea being that by not ever sending the message it is less likely to be ever discovered by outsiders.

But the practice of Foldering while not that common, appears to be pretty well-known by Federal authorities who tend to interpret the act itself of indicating some kind of questionable or sketchy behavior. It isn't illegal per se, but it sends a red flag to information security and law enforcement types for sure.

I don't know if this really has too much of a workplace connection, unless your workplace is, well 'unusual', but it might be something you want to check on with your IT folks once in a while anyway. Maybe your kids too. Except your kids probably don't use email.

Learn something new every day. Like a new word. Like 'Foldering'.

Have a great day!

A chart, like a picture, says more than words do

Welcome back to the work week (and try not to skip out on too much of what you need to do this week to watch the World Cup). Actually, can we pass a law that makes the World Cup more convenient to my personal time zone? But enough about that.

Here's what I wanted to share today, an interesting, quick read from the Washington Post on how much more effective charts are when compared to straight text for making sure your audience clearly understands the underlying data surrounding a particular issue.

Researchers from Dartmouth College and the University of Exeter recently published some interesting findings, ones that you probably already would have guessed at, around the effectiveness of charts in combating false conclusions or ones that are not supported by the facts.

To prove this thesis, the researchers took a given issue, say whether or not participants believed that the Earth's temperatures were increasing, and then showed one group a chart containing the relevant climate data, a second group was given a text-only version of the climate data, and a third group was given no additional information at all.

Here's the chart (naturally), of what the researcher's found happened to the levels of incorrect or non-factual beliefs that were held by each group after seeing the chart, text, or just going with their gut.

I am sure you noted on the chart that the actual groups of people being tested in this experiment were folks who identified as Republican, but for what I took away from the Post piece and the research itself, that is only a footnote. What really matters here is that among folks holding a particular belief, one that seems to be counter-factual, (or even flat out false), you have a much better chance of getting them to embrace the facts (and change their opinions of those facts), by showing them a chart of the relevant data, not a text-only passage. Doing nothing at all, or just shouting at them, is definitely the most ineffective strategy.

In the experiment above, using the chart of global temperatures drove the percentage of people holding incorrect beliefs down to 10%, a huge improvement from the text-only or 'nothing' strategies. That's the takeaway from this, don't get caught up in the political topics themselves. T

his strategy can be used for just about anything in the workplace where there are incorrect beliefs, perceptions, or just a person or a group that has dug their heels into the ground over a particular issue and you can't find a way to make them budge.

That's your assignment for the week - find one opportunity to send your message and make your point in chart form - don't rely on a simple email or a chat message to convince anyone of anything.

Ok, I'm out - have a great week!

Balancing data and judgment in HR decision making

A few weeks ago I did an HR Happy Hour Show with Joshua Gans, co-author of the excellent book Prediction Machines. On the show, we talked about one of the central ideas in the book - the continuing importance of human judgment in decision making, even in an environment where advances in AI technology make predictions (essentially options) more available, numerous, and inexpensive.

I won't go back through all the reasoning behind this conclusion, I encourage you to listen to the podcast and/or read the book for that, but I did want to point out another excellent example of how this AI and prediction combined with human judgment idea plays out in human capital management planning and decisions. A recent piece in HBR titled Research: When Retail Workers Have Stable Schedules, Sales and Productivity Go Up shares some really interesting findings about a study that aimed to find out if giving retail workers more schedule certainty and clarity would impact business results, and if so, how?

Some back story on the idea behind the study first. As demand planning and workforce scheduling software has developed over the years, and become much more sophisticated, many retailers now have the information and ability to set and adjust worker schedules much more dynamically, and almost in real time, than they had in the past. Combining sales and store traffic estimates with workforce planning and scheduling tools that are able to match staffing levels to this demand - store managers are, for the most part, able to optimize staffing, (and therefore control labor costs), much more precisely.

But while optimizing the staffing levels in a retail store sounds like a sound business practice, and makes the owners of the store happy (typically via reduced labor costs), it also often make the staff unhappy. In a software and AI driven staffing model, workers can find their schedules uncertain, changing from week to week, and even find themselves losing expected shifts on very short notice, sometimes less than two hours.

The data and the AI might be 'right' when they recommend a set of staff schedules based on all the available information, but, as we will see in the research referenced in the HBR piece, the data and the AI usually fail to see and understand the impact this kind of scheduling has on the actual people that have to do the actual work.

You really should read the whole piece on HBR, but I want to share the money quote here - what the researchers found or recommended would be the best way for a retailer to incorporate these kinds of advanced AI tools to help set retail store worker schedules:

At the start of the study, we often heard HQ fault store managers for “emotional scheduling” — a script pushed by the purveyors of scheduling software. “In measuring customer experience and making decisions related to a labor model, retailers should rely solely on facts. Too often, changes are made because of an anecdotal or emotional response from the field,” notes a best practices guide from Kronos.

However, our experiment shows that a hybrid approach of combining algorithms with manager intuition can lead to better staffing decisions. While our experiment provided guidelines for managers, it still allowed the managers to make the final decision on how much of the interventions to implement. The increase in sales and productivity witnessed at the Gap shows that retailers stand to benefit when they allow discretion to store managers.

What were some of the benefits of giving managers at least some discretion over scheduling, even when the AI made different recommendations?

When managers could give more workers more 'certain' or predictable schedules, most of them benefited from ability to predict commute times, ability to schedule things like education, child care, other jobs, and enabled them to connect more deeply with customers and co-workers. In short, they were all happier, and this tended to lead to better work performance, better customer service, and in the case of the stores studied by HBR - increased revenues and profits.

In time, maybe the AI will learn to understand this, this nuanced, subtle, but important impact that work schedules have on workers, and how that impacts business results. But until then, it seems like it's best to let the AI make recommendations on the optimal staffing decisions, and let the managers make the final call, based on what they know about their staff, their customers, and well, human nature in general.

Have a great day!

CHART OF THE DAY: Job Openings Continue to Increase to New Record Highs

I know I've covered this territory a hundred times, it seems like every month lately, but I feel compelled once again to share the headline number from the monthly Bureau of Labor Statistics  JOLTS (Job Openings and Labor Turnover Survey) Report released earlier today.

Here's the headline (and an accompanying chart from our pals at the St. Louis FED) - Total Job Openings have climbed to 6.7 Million - reaching another new record high in the history of the data series.

The steady increase in record high job openings has been one of the truly amazing developments in the aftermath of the financial crisis and recession, which saw openings bottom out at about 2.2M in July 2009.

The questions are now twofold I think. One, just how high is the ceiling for US job openings to climb towards? I mean these records continue to be set even while trade wars are constantly in the news and many financial and labor markets observers have no idea what strange 'news' emanating from Washington might do to the market and the economy?

And two, when and by how much do we begin to see a much more pronounced increase in wage growth, as companies are finally forced to increase wages in order to try and fill these millions of openings? The sluggish nature of wage growth in the face of seemingly and endless supply of open jobs has been one of the must puzzling aspects of the labor market in the last several years. Something has to give soon, right?

It's a good time to be looking for work, I would say.

Have a great day!