The four horsemen of apocalyptic decision making are Volatility, Uncertainty, Complexity and Ambiguity or VUCA for short. Just as customers do when they don’t understand, we tend to procrastinate, postpone or avoid decisions on events we don’t understand. These horsemen thwart our decision making in this way causing lost opportunities and more problems.

Four Horsemen of Apocalyptic Decision Making

The Four Horsemen of Apocalyptic Decision Making

Nathan Bennett and G. James Lemoine in “What VUCA Really Means for You” (Harvard Business Review, January 2014 edition) provide basic definitions, examples and approaches for each in a brief table. Still, not understanding an event might diminish it in our minds but not in reality. Problems, like squirrels, don’t care about our mental boundaries.

Each horsemen strikes fear in our decision making. Since urgency and immediacy often drive us, we’ll waffle trying to keep up with volatility. Since we prefer certainty, we’ll discount or ignore uncertain factors. To simplify things, we’ll look for the silver-bullet rather than coordinate many solutions. To achieve understanding, we’ll create definition and quantification even if it means leaving out ambiguous intangibles. That is why these horsemen are also four of eight alerts that help us anticipate problems.

Rather than deal with the horsemen as Bennett’s and Lemoine’s table suggests, our fears will encourage us to see stability where volatility exists (prices won’t change anymore [see table’s examples]), to see certainty where uncertainty hides (competitor’s product launch won’t muddy the waters), to see simplicity in place of complexity (all customers basically need our product), and definition rather than ambiguity (we’ve done this before and succeeded so just follow the template).

Our emotional triggers for security (stability, certainty, simplicity and definition) are often so strong and the four horsemen so nebulous that rationalizing like this is easy. That is what makes them so apocalyptic and what we commonly call “being blindsided.”

 

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Placebo ManagementThree attorneys specializing in medical malpractice attested to me that better bedside manner lowers malpractice risk. One even claimed that he could predict doctors’ malpractice premiums based on how they entered his office and seated themselves. According to “Better Bedside Manners” (Time, September 5, 2007) by Laura Blue, “plenty of past studies have shown a link between lousy doctor communication and poor medical outcomes, such as inadequate care and malpractice suits.” For instance, one study claimed these results:

Positive physician communication behaviors increased patients’ perceptions of physician competence and decreased malpractice claim intentions toward both the physician and the hospital. A more severe outcome increased only patients’ intentions to sue the hospital.

Doctors’ people skills also improve medical outcomes. Thus, the effect minimizes negatives and maximizes positives. It has many business lessons extending beyond the medical field. These lessons have two overarching themes. People skills influence:

  1. Interpretations and assessments of objective skills and performances
  2. Outcomes dependent on those skills

In other words, we will perceive doctors’ with good people skills as having good technical skills too. Similarly, we will perceive such employees as possessing better technical skills. We will tend to see the friendly computer technician as being good technically, the friendly CFO as being so too and so on. This relates to phenomena where style trumps content and eloquence trumps honesty.

Reversing the effect though, people skills allow us to improve outcomes without tangibly improving others’ skills. By impacting beliefs and emotions, we can help people feel better about themselves just as patients can feel better about their medical treatment. Both yield better outcomes.

Collectively, these are placebo approaches and techniques. Placebos have an impact in medicine. No longer can we say they don’t. We can say the same in management and leadership.

 

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Leveraging group interactions to mold relationships and culture.

Leveraging group interactions to mold relationships and culture

Questions and comments in group interactions attack the relational challenges these interactions create. They can occur at any time during the interaction, even the beginning. Getting the first one is most important. It can open the dam. Receiving them though is another matter. Saying, “I encourage questions in this meeting” or “Feel free to ask questions,” doesn’t cut it. People want proof that we want their questions and comments.

First, we allow plenty of time for questions, even a ridiculous amount. Leaving only a few minutes isn’t proof we want questions. If there aren’t any, we end the interaction regardless of time remaining especially if we will have further interactions with the same group.

Second, we must discipline ourselves to wait when we ask, as much as thirty seconds if need be. Meanwhile, we don’t look at our notes or around the room. We look at the people. Their eyes are best. How can we be sincere about their questions if we’re not even looking for them?

Third, we can frame our request to show appreciation and ask for their help such as:

I’m done with my remarks. The remaining time is for addressing other points through your questions. I’d appreciate someone getting us started by asking or commenting about something that he found interesting.

 Here, we’ve embedded four themes:

  • Appreciation for questions
  • Questions help us
  • Being the one
  • More

People feel good when they help especially if we appreciate it. We give special appreciation to the first one who helps by being the initiator. We recognize that the first question is very important. Finally, we suggest that there is more, if they ask.

Seen from another perspective, we are allowing others to make this presentation, meeting or other group interaction theirs not ours.

 

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The Small Importance of Big Data

By Mike Lehr

Big Data Big PersonalityMany small things are critical to big data. Yet, as history shows, revolutionary uses will surprise us. Our imagination lags far behind technology’s possibilities. We often see technology as replacers for existing tools and methods. Cells phones would replace landlines and payphones. They are but have also become mobile accessories of the internet and our electronic partners.

Continuing the theme, big data will replace traditional research and problem-solving by providing better and quicker ways to do the same thing in the same way. This won’t tap though much of its potential. We will force big data to work within two of our problem-solving biases rather than cure them:

  1. The big solution over the small one
  2. The one solution over many solutions

These biases exist because they’re simpler, not necessarily better, for human problem solving. Combining them, our bias is for one big solution versus many small ones, meaning that we focus so much on locating the 20% increase or savings, that we’ll miss the twenty each producing 1%. “Little Things that Mean a Lot” (The Economist, July 19, 2014 edition) offers many examples of many small solutions adding up big.

Yet, even this oversimplifies because the many small solutions are integrated, either complementing or offsetting one another. “Which?” and “How?” will require us to avoid locking big data into another problem-solving bias, compartmentalizing, defining problems within our understanding rather than within the integrated reality they exist. This means learning to live with unknowns in solutions, another bias.

If big data must work within our problem-solving biases rather than around them, our expectations of it will likely go unfulfilled. This means of course damaged careers and enlightened competitors taking us by surprise. History already knows that’s in some of our futures.

 

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Personality Types That Share Ads

By Mike Lehr
Personification - Puttng On a Face

Next big marketing move: identifying and targeting by personality type

I had asked a LinkedIn guru whether he knew of a way to filter profiles based on personality types. He replied, “No.” A marketing professional might call this target marketing, but most targets are based on objective measurements such as gender, age, residence, job and income. Yet, even for those who fit these five, many different personalities exist. Different personalities respond differently to different marketing messages.

For example, in studying viral ads, Thales Teixeira (“The New Science of Viral Ads” [Harvard Business Review, March 2012 edition]) found “that whether or not an ad is shared depends as much on the personality types of viewers as on the ad itself.” Now, if we just change ad to product, we’ll have what will launch the real commercial importance of social media: assessing, identifying, filtering and reaching personality types within any market, target or otherwise, with a dynamically personalized message. A very intimate relationship between social media and big data will unavoidably result.

Diving deeper into this with Teixeira, he found two personality attributes most likely to share ads: extroversion and egocentricity. The attraction extroverts have for their external world makes sense here. Ad sharing is a form of interacting with that with which they find so attractive, the outside world.

Egocentricity is more complex. Teixeira initially thought sharing was helping others, something not normally associated with egocentricity. He eventually concluded:

. . . it’s because they are looking to increase their social status [see emotional recognition]. [Sending] an ad link isn’t to make others joyful; it’s to display their own taste, media savvy, and connectedness.

Essentially, social media activities help identify personalities. So, in this case, when the next great status item comes to market, we’ll not only know who’s likely to share the ad but also who’s likely to buy it.

 

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Book of Job, Favorite in Bible

By Mike Lehr
Book of Job illustrates the relationship between quality and quantity.

Book of Job illustrates relationship between quality and quantity.

The Book of Job is my favorite in the Bible because despite Job’s many sufferings God’s love is better. Translating into nonsectarian and business perspectives; even though quantity outnumbers quality, quality is better than quantity.

In our lives and business, quantity is easy to measure, easy to see. Quality isn’t because it’s highly subjective and variable depending upon circumstances. Returning to Job, even though God’s love is outnumbered by all the sufferings, it is still better.

As illustration, imagine if only good happened. We would come to take it for granted. As proof, consider all the miracles we take for granted. In fact, we do so to such a degree that many of us don’t believe in miracles.

At some point, even waking and getting out of bed is a miracle. If we keep asking, “How?” and “Why?” eventually we arrive at, “We don’t know.” Moreover, we’re not even talking about complex things such as love or empathy. Twenty years ago, we thought we had a handle on empathy, but the more we study it, the more it becomes a multi-headed monster of questions. Even our brains are miracles. Everyday a miracles stares at us from the mirror.  Yes, we often take both for granted.

Many bad things happen so we appreciate the good. Movies play this out endlessly as bad guys always outnumber good ones, but the good guys are always better. In business, the average always outnumber the best but the best are always better, whether it’s customers, employees, competitors, products or services.

Job reminds us that quality is better than quantity no matter how much quantity outnumbers quality. More importantly though, Job reminds us that quality is there even if we can’t see and touch it. The key is not letting numbers distract us.

 

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Dice (Twelve & Two)  [0691]

Who forecasts the future better, the confident or the prudent?

Who’s better at forecasting, the confident or prudent? So far, the prudent seem to be winning confidently. More decisively, those most confident tend to be most wrong.

We have endured the wrong forecasts of pundits and experts without them experiencing any costs for their errors. Yet, Philip Tetlock ( University of Pennsylvania) highlighted this in 2005, when he released his 20-year study of 284 experts (professors, journalists, civil servants, etc.). According to “Intelligent Intelligence” (The Economist, July 19, 2014 edition) “their performance was abysmal.”

These results automatically created questions about intelligence agencies, causing David Mandel, of Defence Research and Development Canada, and Alan Barnes, a former intelligence analyst to publish, Accuracy of Forecasts in Strategic Intelligence. In this examination of intelligence analysts’ forecasts, they found significantly better forecasters than Tetlock did with pundits and experts.

When they dug deeper into analysts’ personalities, they found caution – even about their own abilities – pronounced especially among those classified as “superforecasters.” If they erred, it was on the side of uncertainty, meaning they were more likely to say, “I don’t know.”

More significantly, experienced analysts forecasted better than junior ones, meaning good forecasting is learnable as long as three protocols exist:

  1. Accountability for forecasts
  2. Skepticism by analysts’ managers
  3. Absence of self-serving biases

As James Surowiecki writes in “Punditonomics” (The New Yorker, April 7, 2014 edition), pundits and experts don’t forecast within these protocols. Their confidence is rewarded and errors unpunished. People can suffer from erroneous intelligence forecasts.

Businesses aren’t immune. Confidence and glowing forecasts easily seduce us. Style often trumps content and competence. Skepticism is difficult when hearing what we want to hear, and more so when seeing it as dissent or pessimism. That doesn’t even address interpreting prudence as underconfidence.

All of which I’m prudently confident will change . . . some day.

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When tapping group interactions to mold relationships and culture, the relational challenges center on groups naturally constraining individual expression. We frequently experience this in large meetings when no one says anything unless prompted.

Group Interaction - Relational Challenge

The relational challenge in group interactions is to get everyone to come out of their boxes (their shells) so we can mold relationships and business cultures.

Consequently, as visualized in the left schematic of the figure, every person is in his own box, his own safe space which allows withdrawal and protection by not saying or doing anything to draw attention. He isolates himself from us and the team. It’s similar to withdrawing physically when people enter his personal space. Thus, removing these boxes, as visually expressed in the right schematic, is the relational challenge.

Typically, we express feelings of constraint as peer pressure and conformity. Attendees though have many ways to rationalize them such as:

  • This isn’t the time or place to ask my question.
  • My comment really isn’t pertinent.
  • I should have worn something more professional (or more casual).
  • The presenter doesn’t really want to hear what I have to say.
  • I’m wearing the same thing that person is.
  • This topic really isn’t that important to me (or doesn’t apply to me).
  • I didn’t want to attend; my boss told me to be here.
  • They’ll probably think my comment stupid, and I’ll look foolish.

These feelings intensify with such factors as:

  • Large group
  • Extensive formality
  • Serious occasion
  • Multiple hierarchical levels present
  • Many unfamiliar people
  • Diverse personalities, departments, teams or culture

Whether a straight presentation or an interactive format, we can remove these boxes in such basic ways as:

Removing these boxes will foster the integration necessary to mold relationships and business cultures.

 

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Big Data Big PersonalityImagine applying for a job. In addition, to all the necessary disclosures for background checks, references, credit reports, drug tests and personality assessments, there is a new one: accessing our consumer history, social media activity and internet browsing records. While perhaps not the actual data, future employers could gain rights permitting its input through personality assessment applications contracted through third parties.

This differs from current personality assessments because almost all are currently self-reporting, having us respond based on who we think we are. Big data though can give greater insight into who we are by analyzing what we actually do. Consumer psychology and online dating have already exposed contradictions with self-reporting methodologies.

Already, in “Your Doctor Knows You’re Killing Yourself” (BloombergBuisnessweek, June 26, 2014) by Shannon Pettypiece and Jordan Robertson, reports of medical centers accessing consumer data, “public records, store loyalty transactions, and credit card purchases.” By putting this “data into predictive models that give [health] risk scores,” doctors can better advise patients based on what they’re doing not what they say they’re doing.

Private Traits and Attributes are Predictable from Digital Records of Human Behavior (pdf), by Michal Kosinski, David Stillwell and Thore Graepel, shows what people’s Facebook Likes disclose. Commercially, providers are already tapping Twitter streams. Since our personalities often influence our health and job performance, medical professionals could further improve if they had better insight into our personalities.

Politicians already use this information to analyze candidates and issues we like (see “Data Unravels Voters’ Political DNA” [CBS Evening News, October 24, 2006]). Since personality correlates strongly to politics, we’re already well on our way of tapping big data’s full personality assessment capabilities. Furthermore, as 60 Minutes (March 9, 2014) reported in “The Data Brokers: Selling Your Personal Information,” data brokers avail this information in a relatively unregulated market. This means that the only problem with the above scenario might be that employers won’t need our permission.

 

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External - Internal Feelings

Soft skills are harder to see, define and quantify than hard skills are.

The body has 206 bones. The number of skeleton muscles is in the 639-850 range depending on definition, not including though the heart muscle, smooth muscles or ones for each hair follicle. Defining muscles is a far harder task than defining bones is.

In business we apply hard and soft skills. Hard are specific, teachable, definable and measurable. Soft make those much more difficult. Hard skills apply to companies’ structures: organization, processes, operations, rules and procedures – their bones. Soft skills apply to their people – their muscles.

Without bones, our muscles would collapse as soft tissue blobs inert on the ground. Without muscles, bones would fall like sticks. Without structure, companies would be chaotic groups of people. Without people, they would be just bytes of procedures, policies and rules.

Repairing and healing broken bones is critical, requiring rest and perhaps a couple months. Rehabilitating surrounding muscles, even before a surgery, is important too, but is much harder, requiring much more work and time. As a juror, both lawyers explained the much harder task of defining and diagnosing soft tissue injuries versus structural ones. Even legally, soft is harder, and hard is easier.

Comparatively, companies’ people are much harder to define and quantify than their structural aspects are, making soft skills harder to apply and hard ones easier. After all, we naturally drift to easily visible, definable and quantifiable problems, those usually requiring hard skills. Similarly, lying still while a doctor repairs bone is much easier than rehabilitating muscles is. If undone though, muscles will be weaker.

Thus, reorganizing and restructuring companies without applying necessary soft skills before and after is akin to neglecting rehab. As doctors say though, it’s most critical for a successful recovery. Working soft tissues and applying soft skills are much harder work though . . . and easier to neglect.

 

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