February 2015 – The Frustrated CFO

Our Fluid Morality, or What Makes “The Blacklist” So Seductive

Not the most watched TV show in America (somehow it’s impossible for any series to compete with everyone’s guilty pleasure aka the NCIS franchise), The Blacklist, nevertheless, draws respectable numbers of viewers: Between those who must watch every episode when it first airs (out of fear that they will be assaulted by the spoilers at the water coolers, no doubt) and those who are grateful for the opportunity to do things on their own schedule (i.e. DVRists and On-Demandists), about 16 million people watch every episode of the show within 3 days from its original airing (if you prefer accumulating new episodes and then watch them 6 at a time or you just binged on the entire first season on Netflix, you don’t count). The episode that aired after the Super Bowl had a record of 30 million viewers.

Impressive! Of course, the show’s creators keep hooking and reeling in the audience with secrets and vague hints about the main characters’ pasts, futures, connections and disconnects, the overall story arch, and the possible endgame. Plus, it’s an action thriller, so there are plenty of twists and turns, car chases, shootings, tortures, and “suspenseful” misadventures in every case. Except that we can get all that through so many other media outlets, don’t we?

There is no doubt in my mind that the main draw of the show is its chief protagonist – the former Navy officer (“he was groomed for admiral”), now one of the FBI Ten Most Wanted Fugitives, Raymond “Red” Reddington. We know it and so are the designers of all printed-media ads. And, some part of it may be attributed to James Spader‘s offbeat charm and subtlety, that almost shy smirk in the corners of his mouth, that hidden trauma deep inside his eyes (or to our memory of the charm and subtlety, the smirk, and the trauma as he finessed them as Graham Dalton). But the real truth is that, James Spader or not, we LOVE the hard-core criminal, the ruthless, the calculating, the self-righteous, the snobbish know-it-all, the flawed, the mysterious hero that is Red Reddington.

Look, we live in bizarre, degenerative times of perpetual futility and failure, with dubious future prospects and shifting moral standards. Everybody (and I mean, EVERYBODY) does illicit things, lies, steals, cheats, covets.

And I’m not even talking about big-time thieves (like corporate moguls) and liars (like politicians), arms and drug dealers, rapists and molesters, or even that CFO who stole $7 million from his employer.

I’m sure you, my reader, consider yourself a fairly decent person. So, I invite you to examine just one day in your life and I guarantee you will find something that, strictly speaking, is not moral.

Start small and “innocent”: half the time when you take a sick day off your aren’t sick at all, right? Of course. And what’s wrong with that? As far as you know, everyone does it. A man’s gotta do what a man’s gotta do… to survive: resumes, interviews, taxes, drugs, office supplies you bring home from your place of work, your expense account, that last drink you took before you got into the car, that little tryst with a hotty from marketing, 99% of the bullshit that comes out of your own and everyone else’s mouth, etc., etc. – just the basics of an average person’s somewhat moral existence.

All that matters is how slick and seamless you are when you do it and whether you can get away with it. As long as you don’t get caught, fired, kicked out of your house, or sued, you will continue doing what “everyone else does.”

When we see wrongdoings we don’t speak up because we are afraid of the consequences; and we don’t express our opinions because we don’t want to be ostracized; we hide our own sins and look away from those of others.

But most of us are not sociopaths: while on the surface this behavior goes unpunished, our buried in bullshit subconscious is nevertheless secretly troubled. As a result, we suffer from unexplainable fears, anxiety, and anger.

Yep, we are very-very angry; you may even say wrathful – pretty much at everyone and everything: our governments, generations of people who destroyed our planet and those fucks who still do, overpopulating nations and individual families, domestic animal abusers and wildlife killers, the dwindling quality and escalating prices, our bosses and subordinates, parents and children, spouses, boyfriends, girlfriends, exes, neighbors, customer services and customers, people who don’t think like us; every single motherfucker who takes advantage of us; everyone who we blame for who we are, including ourselves; our own cowardice and impotence.

We are livid watching the worst sinners reaping life’s rewards and those untalented idiots who, by some fluke of fate or flourishing nepotism, are recognized as cultural icons. Sometimes it overwhelms us to the point when we just want to grab people by their collars, lift them up, and smack them against the wall real hard.

And in this condition of perpetual moral sacrifices, bewilderment at the state of things, intense disappointment, and the pent-up anger, how can we not be drawn to a morally flawed character, who confirms that the world is fucked and we are not crazy, that we are justified in feeling the way we do?

Practically in every episode, he exposes every branch and every agency of every government as thoroughly corrupt and incapable. He confirms that money and the corporations behind them rule the world and us; that a handful of people possess virtually unlimited powers and can destroy fates of nations by raising their hands in some treacherous vote. And, given a chance, he will try to hurt those devils or at least to interfere with their evil plans.

He walks into the most dangerous situation with a surety of an invincible superhero. If it’s necessary, he coolly raises his hand with a gun in it and squeezes the trigger with an air of a vermin exterminator. He will lie, scheme, and take advantage of every opportunity to reach his goals. On top of that, he prefers animals to humans!

Even more impressive is his sober understanding of the faults and weaknesses of those to whom he is personally attached. Just because he cares about them, it doesn’t mean that he has any illusions about who they are.

We marvel at the way Reddington stands out against the background of powerless and defective schmucks, oh, so similar to us. Cause (did you notice?), whether they are on the side of the “law” or on the criminal side, there are no good, honest, decent people in the show’s vast cast of characters – everyone is ethically deficient and either confused about their selfish motivations or knowingly hide them. In contrast, Red’s immoral clarity is incredibly refreshing.

To tell you the truth, I don’t think that the show’s creators had consciously cooked this up as a marketing ploy. They are not different from us – just as ethically corrupt (maybe even more so) and anxious. They simply follow their instincts and realize their dreams of justice through their fictional creations. And by making these apparitions public they allow us to participate in the experience as well. Such has been the prerogative of writers for over 4000 years.

What I do have to give the creators and producers credit for is the targeting of wide slices of viewing demographics. First of all, they got the most relevant age groups covered: 20-somethings who like shows with hot FBI/CIA/Mossad chicks and ugly foreign dudes with big guns; 30-somethings still preoccupied with cool jobs, career advancements, and scarred-forever hearts; and middle-agers who fucked up their own lives and those kids’ futures to the irreversible point, yet still hope that they can “fix things.”

Then they got the important interests groups: people of both genders who are interested in guns and explosives and those who are into politics; women who put their jobs ahead of everything else and those who still dream the American dream. And they got nerds with cutting-edge tech stuff and conspiracy theories! Plus, they keep uncovering domestic and world-wide social boils, thus appealing to people with at least some ability for progressive thinking.

Bravo! They get them interested and then Red keeps them hooked. Let’s just hope that the show-runners have an actual sense of direction and that they will not let the seductively successful character drown in some muddy bullshit. Maybe James Spader’s new co-executive position that his reps negotiated for him after the first season’s success will prevent commonly destructive tendencies.

And look what happened: He just got the executive power and two episodes in the first half of the second season were directed by Andrew McCarthy. Nepotism, of course, but still, honoring old ties, supporting old friends – it ranks pretty high on our contemporary degraded morality scale. All we need now is a guest appearance by Jon Cryer (now available after 12 seasons of Two and a Half Men) and Molly Ringwald as agent Keen’s presumably dead mother. The Pretty Pinklist, anyone?

Joke of the Day: Get Your Animals Straight, Woman!

The Frustrated CFO's Preface:

Seriously, guys, this just happened, like, 20 minutes ago (I had to scramble to make the picture). Quoted verbatim from an email sent by the CEO of an internationally-mixed company:

"Dear all,

In honor of Chinese New Year, the Year of Goat/Sheep/Lamb, we will have a Chinese lunch together to celebrate on Friday."

The Frustrated CFO’sTalk on International Trade Turns into Gender Equality Q&A

If you took my absence from these pages during the past few months as an indication of my giving up on the blog, you were wrong. This activity is important to me. If nothing else, it lets me "talk" without being interrupted. It's just that the time slot in my overscheduled life, usually allotted to the writing of the blog posts, had to be temporarily relinquished to an extracurricular activity of preparing for a talk I was invited to give to a professional group called Women in International Trade.

Oh, no-no-no! I'm not talking about OWIT (the Organization of Women in International Trade), the big non-profit with global reach headquartered in Washington, DC. This group is much smaller - sponsored by a reputable New Jersey CPA firm, it is pretty much localized to the international-commerce entities and banks (like PNC) with offices and operations in that particular state. It's not like they don't welcome sisters-in-trade from everywhere, it's just how their network happened to develop: commercial clients of the said CPA firm, trade finance clients of the said bank, the local government bureau that deals with exports – all of them work and live in New Jersey.

And the reality is, there are a lot of big and small international businesses located in New Jersey. That's where you can have large office buildings that cost a fraction of what they would in Manhattan; there is plenty of open space for manufacturing and storage; there are Hudson ports that can berth oceanic freighters, etc., etc.

Truth be told, I would never know about these particular Women in International Trade if it weren't for one of the group's member who is also one of my former trade finance bankers and a friend. She is the one who mentioned me to the sponsoring CPA firm's Chief Growth Strategist - a force behind a lot of women initiatives in the Garden State.

They've been inviting me to participate in various women's and co-ed business events for some time. But I have to admit that when you live and work in Manhattan, the hassle of getting to an 8 o'clock breakfast meeting in New Jersey's Essex County makes such invitation very unattractive. I mean you need to drive or get a limo. You'll do it for business, of course, but for a semi-social gathering… that's a bit too much.

Of course, your attitude totally changes when the same professional group invites you to appear for them as a speaker. Vanity is a terrible sin – it demands constant massaging of one's ego. That's why some of us write books that bring meager royalty, give lectures without fees, etc. Plus, unlike the vast majority of people, I actually enjoy sharing my knowledge. And not for narcissistic, show-off reasons – I get a kick out of recognizing to myself, "I taught her that." So, naturally, I agreed.

After the initial invitation, I kicked a list of possible topics at the talk's organizer and we settled on two that we both agreed would be the most interesting to international-trade professionals: the position of trade finance in the value chain and KPIs specific to international commerce. I was advised of the reglament: 1.5 hours talk and 30 min Q&A.

"Well," I thought, "If you are going to talk shop with a group of working women for 90 minutes at 8 o'clock in the morning on a Wednesday, you'd better make it engaging and gratifying," and went to work. The rule of thumb is that 90 minutes of talking translates into about 15,000 words. And that's actually is not very short.

Of course, if you are the one who proposed the topic in the first place, you most likely know the subject at hand through and through; you have already developed original ideas and time-proven recommendations; your thoughts and opinions are well formulated. And that's great, but if you are not a professional lecturer who does this sort of things all the time, you still need to outline what you want to say; you have to construct your delivery in a coherent and logical way; you must prepare an exciting Power Point presentation that would prevent your audience from getting drowsy, and use cultural references to make your points memorable. Yeah! If you want to impress people, it's a lot of work. As I said, vanity – it costs you.

The third week of January came, and there I was, in New Jersey, shaking hands with the organizers and the attendees – by all appearances a group of successful and confident women, whose statuses make it okay to be out of the office in the morning hours for the sake of this event.

I proceeded with my presentation and it went well: they paid attention, they were interested, they nodded, they offered sensible and appropriate comments, they loved my visual tricks, and they sincerely laughed at my jokes. The time ran out. "Do you have any questions?" I asked. I was convinced that I've had a pretty good idea about the points of the talk that could've prompted further inquiries.

Imagine my surprise when the first comment/question I've received was, "You are obviously a strong woman. In your professional capacity, how do you handle male resistance to your authority or any other sorts of gender difficulties?" (Notice how the question was formulated: The woman had no doubt that I've encountered such obstacles ans she wanted to know how I dealt with them.)

Slightly taken aback by the sharp shift of gears I skipped a bit, but really – just a bit. I don't need to prepare for a gender equality discussion; I was born ready for it. So, I briefly described my experience: the unfair treatment; the skewed perception; the idiotic remarks; the preferences given to nitwits because "they have to support their families" (many of us have to do the same); which battles I pick; what I say and how I say it; when I bite my tongue and walk away; how I lie in wait and then find a way to teach them a lesson, etc., etc.

Oh my God! It was as if that question and my answer triggered a flood. Apparently these women found my interpretation of the international-trade topics quite clear. What they were confused about was why in 2015 we are still treated like second-class citizens.

At this point (the time was, obviously, running out), everyone talked fast. Many things were mentioned: "honeys" and "sweeties," unequal raises, unreasonable promotions, difficulty of holding back the tears, female professional "ceilings," the insulting male disbelief at a good-looking woman who is also smart. Amazingly, there were not a single person who didn't have something to add. Nobody said, "I have no idea what you all are talking about." You know why? Because there were no men in the room.

One woman in her 30s who was just recently appointed to a Marketing Director position (her warpath has just began), asked me whether I was born "this tough." Actually, I've thought about it before. What I told her was that we (i.e. the women who want to succeed) are not born tough. What we are born with is the ambition, the desire to be rewarded in accordance with our merits, the need to be treated as human beings regardless of our gender. But, while we claw our ways towards whatever peaks we want to achieve, we have to acquire toughness. We have to harden or they will eat us alive.

It is possible that I will never see most of the members of this group again, but when we were saying our goodbyes we felt like sisters. I taught these women a thing or two about trade finance and performance analytics, and, in return, I've learned a lesson of my own: There are no happy and satisfied women in international trade (and, I dare to extrapolate, in other business activities as well), because their ambitions and efforts are constantly curtailed on account of their gender, which is silly, irrelevant, anti-merit, and (call me an idealist) anti-American.

IBM Predictive Analytics, or Are We There Yet, Watson?

I have no clue what a Venn diagram for conjuction of this blog's readers and tennis fans would look like – probably unnoticeable to human eye, but whether you care about professional tennis or not, bear with me and I'll explain its relevance to the subject at hand.

Those who watched Australian Open during the last two weeks of January on ESPN2 (or any grand slam in the past few years) incidentally exposed themselves to various elements of IBM's "Let's Build a Smarter Planet" promotional campaign. IBM has been sponsoring ATP and WTA tours for years. They don't limit themselves to the ads that run during commercial breaks, but it's a good starting point for our topic.

The current versions of these TV spots are a lot of fun – very slick, very futuristic, very high-tech, very white-surface, and they feature Dominic Cooper (whom I first saw on stage [I cannot help myself, can I?] back in 2006 as Stuart Dakin in Alan Bennett's The History Boys)! Handsome, in the contemporary sense of the word, and serious, but tongue-in-cheek, British actor promotes IBM's cloud, smart day in the office, and… PREDICTIVE ANALYTICS.

Aha! Very interesting: Did IBM branch out into Astrology Charts and Crystal Balls? The advertisement's copywriters are appropriately non-specific and vague so not to bore an averagely challenged viewer, but let's look a bit closer at the core issue here.

Predictive Analytics belong to the realm of other popular concepts, such as business intelligence and performance assessment – none of them new ideas, by the way. Data warehousing may sound like a novelty, but collecting and organizing records in a particular order for easier access existed for centuries. The concept of information as a key to business success is millennia old. In ancient times tribal chiefs were estimating how many spearheads their craftsmen needed to make in order to win a battle.

Yet, in the past 10-15 years, the obsession with gauges, graphs, and all other forms of Key Performance Indicators (KPIs) have become pervasive to the point of silliness, especially in business, financial, and data-management spheres. Everyone and their mothers are absolutely convinced that they MUST have KPIs or they will be running a danger of failing, while analysts and software developers just know that they MUST provide KPI capabilities or their services will be deemed obsolete.

Truth be told, the escalation of urgency is totally understandable. The pace and
vulnerability of the business environment and entire human existence have increased exponentially. Today, more than ever, we need to have timely and valid data that has a power of springing us into immediate corrective actions.

Of course, as it always happens, the form obscures substance and common sense. In most cases, the procurers of reports with colorful dials, bars, and pyramids end up just staring at pretty pictures, nothing more.

Now, the Predictive Analytics are a very special brand of information manipulation because they claim that on the other side of chewing up and digesting tons of historical data they can poop out specific recommendations for WHAT NEEDS TO BE DONE IN ORDER TO SUCCEED, i.e. an action plan for a prosperous future.

And I have to say, when it comes to chomping massive inputs of data, while allowing flexible and customized outputs, various IBM Business Intelligence Suites, including Cognos, are probably the best performance analytics software out there in the land of information management - terribly expensive, of course, but awfully powerful in terms of the facts-and-figures consumption (imagine Coneheads at breakfast).

And as noted, IBM wants to take you a step further on the road to the future of business intelligence. In 2009 the computing giant bought SPSS, which stands for Statistical Package for the Social Science, a software product that was created in 1970 to deal specifically with the analysis of what I personally call “data with a psychological twist.” In other word, it digests information that doesn’t necessarily have dollar signs or volume units attached to it. It was widely used in sociology, marketing, health care, education, and government.

In its current developmental stage SPSS has become an integral part of IBM's predictive analytics solutions, which presumably can be applied in any field. According to IBM’s own description, the SPSS’s mission is “to help organizations to predict what will happen next, so that they can make smarter decisions to improve business outcomes."

Are they succeeding in this futuristic endeavor? It’s hard to tell, because there is not enough readily available feedback: everyone’s KPIs are proprietary. Even public companies will not disclose how IBM’s predictive analytics compare to the actual results. Fortunately, there is one application of IBM’s analytical intelligence that is very public. Here's where tennis comes back into the picture, offering us an opportunity to look at the system’s predictive aptitude.

Nowadays, IBM's sponsorship of the Grand Slams also includes the powering of the websites of individual tournaments, including the Wimbledon, Australian, French, and US Opens. And so, if you go on one of these sites’ home page you will see right there, in the top-right corner: Smarter Analytics by IBM.

Well, right now it says “Completed Matches” above it because we are still almost 7 months away from the US Open 2015, but if you were to track a live match during a tournament, you can observe the IBM’s predictive functionality in real time:

This here is one of the most important predictive KPIs provided by Smarter Analytics – it is designed to show most important milestones one must achieve to reach one’s goals, and supposedly it is applicable to any data set.

In tennis application they call them Keys to the Match. Right there on the screen, in just two sentences IBM delivers the gist of the chart, explaining both the terminology and the methodology: “Keys to the Match system identifies key performance indicators – what players need to do to succeed in a match. Each player’s performance is measured against their keys and updated in real time.”

This one in particular was for the 2014 Championship match between our very own champion extraordinaire Serena Williams and Caroline Wozniacki. The system isolated three performance keys for Serena: 1^st serve points, medium rallies, and the returns of the opponent’s 1^st serve.

According to the system’s algorithm these parameters are the most impactful in terms of the winning statistics. The calculated "musts" are in blue and according to the statistical analysis of the historical data, Serena won 74% of sets when she won more than 61% of points on her own serve; 87% of sets when she won more than 49% of medium rallies, and 81% of sets when she won more than 38% of points returning her opponents 1^st serve.

The red sectors show where Serena was in this match. She exceeded all requirements: reaching 62% in the first parameter (very close), 54% in the second (also pretty relevant), and 68% in the third. It is no surprise that she won the Championship match, but that wild discrepancy between the prediction and the actual in the third indicator (38% vs. 68%) makes me question its relevance.

We will come back to my doubts about the validity of the entire model in a moment. Now, let’s see how we would apply the same approach to a business. Here is a chart that identifies AZ Company’s Keys to a Successful Month: what needs to be done to achieve sufficient profitability and positive cash flow.

AZ Company's Keys (640x495) These are very familiar to all business runners and highly vital parameters. Product mix is a crucial profitability factor. The same goes for the portion of the gross profit eaten up by the overhead. And, of course, the speed with which we manage to turn our inventories into receivables and receivables into cash determines whether we can generate more cash than we disburse during a particular period, in other words, produce a positive cash flow.

The green bars represent the levels of the parameters at the moment this snapshot was taken. Orange ones are the objectives that simply must be achieved, and pinks are desirable targets that supposedly guarantee a financially successful performance.

According to the model’s algorithm the share of the highly profitable product X in the
trading mix should be at least 39%, because 69% of the months when such mark
was achieved were profitable. Obviously the overhead has far more definitive impact on the bottom line – the model confirms it by calculating a higher probability of success (79%) at its relatively lower levels. There is even closer interrelationship between receivables and inventory turnovers on one side and the positive cash flow on the other – respectively 80 and 85 percent.

Many business owners and executive managers, when they see a chart like that, get very excited by the prospective of having a system that can “see the future” – they think they’ve got the ultimate solution in their hands. The widespread assumption is that Technology is smarter than a human, calculates everything faster and with higher accuracy. And this application presumably eliminates the need to process information yourself – analyze, ponder, be anxious, listen to your gut feelings, or rely on anybody’s expertise. Just follow the model’s suggestions and everything will be fine.

If you sense sarcasm between the lines it’s because I am very resentful to such a blind reverence of computing technology. And coming from me it’s a very serious statement, because I love progressive computerization. But I cannot tolerate the lack of common sense.

Look, the selected parameters themselves are great – no question about it, but do we need a fancy program to tell us that the business is going to be okay if we push sales of a high-margin product to nearly 40% of the volume and turn most of our beginning-of-the-month AR into cash? I don’t think so. The years of our own expertise will kick in and reassure us – we don’t really need the statistical confirmation of the possibly successful outcome.

But I have even more troubling concerns about this “keys to success” model. Let me show you that the examples we just reviewed are fraught with at least two serious problems.

The first one is the size of the statistical sample. In quantitative research, you need a sufficiently large sample in order to be able to pinpoint trends with an acceptable level of realism. Did you notice that Serena’s KPIs were related
to sets rather than matches? That's understandable. The Smarter Analytics uses just 8 years of grand slam performance. In the period from 2007 through 2014 Serena Williams played 157 matches in the four major tournaments of the year.

Women play “win-2-out-of -3-sets” matches. Sometimes it’s 2 sets, sometimes it’s 3, and sometimes your opponent retires before you get to finish the first set. Serena has a high percentage of straight-set wins, so we can safely estimate her average at 2.25 sets per match. This means that the predictions produced by IBM are based on a pool of
data collected over 353 sets. It’s not US census, of course, but it's an okay sample size.

Now, in business, to approximate the tennis-model’s reliability of conclusions we would need to look at least at 30 years of a company's monthly performance data. And that's a lot to hope for: 25 years ago the majority of small to mid-size companies were not even computerized and the paper journals and ledgers are either rotting in some storage unit or gone!

But the bigger problem is the quality of the historical data, its relevance to the very specific, very present moment in time. We operate in remarkably dynamic environments. Business conditions change every moment. One day everything is going great and another day everything falls apart. Labor costs grow exponentially in every corner of the world. Foreign exchange policies force one currency to soar and another currency to drop below everyone’s expectations. Cyclicality shifts all the time: what was true for February of 2005 may not be applicable at all for this month. And there are multitudes of industry-specific stressors.

For decades Kodak was competing with BASF, TDK, etc. for the worldwide market share of film distribution. Who knew that the biggest challenge would come from the photo and video equipment that didn’t need any film at all?

20 years ago American agricultural sector exported nearly 3 million tons of frozen meat and poultry to Eastern Europe. Then came 1999 and protectionist governments in the region declared US produce unsanitary. Prices tanked and multiple industries contracted.

15 years ago fashion industry had six major seasons. Today it operates in micro-cycles with styles changing every two weeks. This dramatically altered the landscape of apparel importation.

Well, business insiders live and breath this knowledge, but does the prediction model take into account all these factors? It simply cannot – any mathematical algorithm can only account for a limited number of time-proven constraints. How can we presume then that what might have been true historically will apply to our current conditions?

Even Serena’s keys to success, as far as I am concerned, are not too trustworthy, even though they are based on the game that have been played by the same rules year after year, on exactly the same courts, tended in exactly the same way. But was it the same winning Serena Williams in September 2014 as she was in 2007, when she fell away in quarterfinals? Or was she even the same in January of 2014, at Australian Open? Can you spot the difference that made a significant improvement to her swing?

Can IMB’s "social" software comprehend that? I don't think so!

There is no way I'm putting away the years of expertise and my business instincts to start relying 100% on some computerized predictions in my strategic and tactical decision-making. It may be a good contributing tool (again if you can afford it), but a computer is nothing more than a sidekick to the human brain; even if it's the IBM’s star artificial-intelligence child Watson. Hence, the appropriate name it's given. Yes, it can answer questions posed in natural language and wins Jeopardy! thanks to the 4 terabytes of information stored inside its metal guts. Yet it's not able to intuit the right response to a simple clue “This hat is elementary, my dear contestant!” My mind, on the other hand, serves up the answer instantaneously.

An expert with a common sense should be able to formulate her conclusions and make fast decisions herself, without any magical software, as long as she is steadily provided with timely and relevant information – whatever it is: business, sports, or arts. It's as I always say: give me sensible data and I will tell you what needs to be done.

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