In capitalism, the purpose of a business is to maximise profit. 

A business may have other purposes (e.g being indefinitely sustainable, having a positive effect on human life, improving soil fertility) but secondary purposes do not exist without the primary purpose of profit maximisation.

Despite the simplicity of the single dollar metric defining profit, there are multitudes of variables that affect it. The state of the economy, access to consumers, legislation, geography, advertising, business longevity, debt, credit, competition, innovation, access to technology, supply chain, rent, and expenses such as paying employees – all these factors, and many others, impact a business's profit. 

Because almost all businesses use humans acting as decision makers, often profit maximisation is far from optimal. Businesses that may not have access to large-scale data analysis must make decisions based on limited data. These decisions are vulnerable to human error. This can and does compromise profit.

A common and much discussed form of human error arises in cost minimisation. Specifically in the cost of employee wages, simplistic cost-minimisation logic may be used: 

1. I want my profit maximised.
2. I need to minimise costs. 
3. I will pay employees minimum wage. 
4. This will avoid money being wasted by paying employees more than the necessary amount to get them to work. 

The appeal of this logic is its simplicity. But by focussing on money paid to employees, it ignores other directly relevant variables such as the financial benefits of employee retention, recruitment costs, training costs, and the cornicopia of brand and indirect revenue benefits of having loyal, long-term, passionate, happy staff who want to work and who will go above and beyond their resposibilities to ensure the business succeeds. 

The parable below illustrates the variable of employee wages in a comparison between two small business owners; one who focusses on wage cost minimisation, and another who welcomes the complex value generated by well paid employees. 

Thanks for learning!
Michael 

The content below this line has been published with permission from contributing author Richard Neate 

​Mike and Lisa are opening identical restaurants in Smalltown. They will have the only two restaurants in town.
 
Both have 30 tables. Both need 12 staff. Both serve similar food, of similar quality for the same prices.  The only difference is:

​Both restaurants are in the high street of Smalltown, and both are the same size. Therefore, their property costs are identical.  Ingredients and décor must match their place in the market, so their costs are identical, except for wages:

​On average, 40 groups of people go out for dinner in Smalltown.  Therefore, during their first few weeks they both average 20 covers each. BUT.....

​Both restaurants have been trading for 3 months now.  If we look at the scores, we see that Mike is winning at the moment – in monetary terms at least.  But Lisa is happier and works fewer hours.
 
But now the restaurants are starting to build their reputations.  Lisa’s staff are happier, they care more about the business, and this all means that they are better with the customers.

​On average, 40 groups of people still go out for dinner in Smalltown.  But now Lisa is getting better reviews and building more customer loyalty:

​On average, 40 groups of people still go out for dinner in Smalltown.  But now Lisa is getting better reviews even in National and international websites and has a big and loyal customer base because her staff do such a good job of looking after them:

The DORVA Scale of Emotional Response Scoring is a system for self-reported emotional response measurement that generates fast, reliable, and consistent quantitative data on your emotional responses to stimuli.

Let's start by taking a look at the scale itself. ​

• The DORVA scale is intended to be a simple, fast, and affordable means of producing self-reported data to measure the positivity or negativity of a human subject's emotional experience in reaction to external stimuli. It's terrific for self-examination, but also suitable for documenting the emotional experiences of study participants (including your study of yourself, if you like spreadsheets!). 
  
  
• While self-reported DORVA data has the benefit of being self-descriptive (i.e. a value of “repulsion” is as simple as recognising your own reflexive facial movements, unlike the results of repulsion as returned by brain scanning feedback imagery), DORVA isn't recommended as a substitute for other data production means like EEG feedback, fMRI scanning, and other emotion self-reporting models. ​Data should be obtained from all available sources. 

You'll notice the chart doesn't list the full spectrum of human emotions.

​That would be a big chart! Especially considering emotions can and routinely do occur in complex combinations; not just one at a time!

What the chart offers is a spectrum of emotional intensity to help record emotions based on their perceived severity in the moment in which they are experienced. For this reason, documenting emotions when they are felt is crucial: memory, even immediate-short-term memory, introduces too much of an error margin due to our propensity to compare how we felt about a topic to how we felt about another topic using pseudo-logic: "I was distraught when my puppy was killed yesterday, but I must have felt more distraught when my parent died years ago, so I will rank my emotions relative to each other." When in reality there is no reason that such grief for both events shouldn't have registered at a -5 (abominable) in emotional intensity for both events, for example. 

Data recorded using the DORVA model doesn't cater to memory-alterations made in this way. 

The name of the model, DORVA, is just an acronym for the 5 scores on the negative side of the scale. When self-evaluating, remembering the name can make recollection of the measurement chart a little easier when experiencing intense negative emotions. 

The emotions listed in the chart and their defining characteristics are a usage guide only. Grief, for example, could be felt at an intensity score of -4 (Vile) without any desire to punish or cause suffering. Sincere joy could be felt at an intensity score of 3 (Joyful) without any sensation of warmth. Individuals feel emotions differently, have different physiological predispositions to causative hormones like dopamine and cortisol, and are capable of complex emotion combinations. When recording DORVA data, getting each datum exactly "right" according to the description in the chart not as valuable as logging your data as close to the time it's experienced as possible with your honest evaluation of your emotion.

This is not a perfect tool for measuring emotions. But generating any data set of emotional experience, even with an unknown error margin, is going to provide more valuable insight than undocumented observational, memory-based reflection of emotional experiences. That's the whole point of the DORVA scale! To give you a readily accessible quantitative look without any more sophisticated equipment than notebook or spreadsheet.

Next, let's talk about how you can use it. 

Draw a chart with these columns entitled: Date, Time, Location, Event description, and DORVA response. 
​
If you have a smartphone with Google Spreadsheets on it, you can use that. Otherwise a notebook you carry often would be suitable. Here's a template.

Record your data however you wish. Some recommended methods for producing data are below. 

Baseline data: Every day when you wake up (and/or before going to bed) record a DORVA entry. This will show your emotional baseline when you start the day. It can be useful to compare this to how you end the day! (See Using your data below)

Event data: Every time you feel a strong emotion, and successfully remember to record it, and make the choice to record it... make a DORVA entry. This is a powerful way to see the range of your emotional intensity. It can also indicate a possible positive or negative bias. ​

Each month or frequency of your choice, review your data representing key parts of your emotional experience. Below are some recommended considerations for analysing your data to produce useful and actionable insights. 

Produce an average on what your general baseline emotional state is. How do I feel about this? Do I want to improve it?

​Review baseline data
Recording your baseline is a key way to see how your emotions have changed over time. If you make an entry every day for years, you may notice a difference or no change at all. But even over a period of a few weeks you can spot differences. What has changed in your life that could explain these? What other changes could you make that could get you waking up happy every day? 

If you record your waking and bedtime emotional state most days, you will be able to compare these trends. Is either or both changing, or are they static over time? Are they the same emotional state?

​Do you generally end the day on a more positive or negative emotional point than you began it? Why might this be the case? Is there a standout recurring difference on a particular day of the week, or between work days and days off? 

What days have you had the happiest wake-up and bedtime? What days were the worst? What can you do differently to wake up and go to sleep feeling consistently contented and happy? 

Review event data

Do you have records of major emotional events multiple times a day? Do you have them only some days or seldom? Are they in some places or anywhere? 

Do you consider yourself an optimist, a pessimist, neither, or both? Which would you rather be?

Does the data show you have more strong negative emotional reactions than positive ones throughout a typical day? 

Think about changes you might like to make to your outlook, if any. How will you achieve those? 

Do you consider yourself a particularly emotional person? Does the frequency or intensity of emotionally significant events meet your expectations or surprise you? In what ways? 

What significant positive events happen regularly in your life. Who are they with? Where do they happen? How might you create more of this positivity?

Do any significant negative events happen regularly in your life? What can I do to change the cause? Do you also want to change your emotional response to that cause? How will you do that?

As you can see from this exercise, these questions are very inward focussed. They are excellent questions to reflect on your life and choices at any time. The advantage of involving DORVA in the mix is that you no longer need to rely on a vague amalgamated feeling built up over time, or specific memories (reconstructions) of individual events and how you think you felt at the time. You can rely on the data which is a reflection of the actual intensity that you honestly felt at that time, and make a more informed evaluation of your emotional experience that will better inform any changes to your life that you want to make. 

And you can completely trust the data source, because it is an honest reflection of your emotional journey and forms part of the record of your life. Now that's something to feel good about. :)

Thanks for learning! 
Michael 

We say things like this too:

"Bottom feeder." “That’s low.” “Downtrodden.” “You have to learn to crawl before you walk.” and even the term “To put someone down.” “To fall from grace.” “To be taken down a peg.” “To be laid low.” “Scraping the bottom of the barrel.” “To be “tread on” or “stepped over”. And of course depictions abound of Hell as subterranean, “down there”, below our feet, ever presently waiting for us to fail and fall. “It’s all downhill from here,” indicates a “descent” into an inferior circumstance, even despite the considerable biophysical realities of moving downhill consuming less energy than moving uphill.

There are many situations where elevation is not good – or downright dangerous. The fear of heights is one common example. The actual danger of heights is another. Yet humans can also have a rush of adrenaline and dopamine in response to such danger – a physical acrocentric response!

1. A bill is written and a case is made defining the expected benefits to society of the proposed law change, including specific metrics for measuring efficacy. Current data defining the problem the bill intends to fix is also provided. This is put before the law approvers to implement or reject.
2. The bill is passed and becomes law for a provisional period determined by the approvers.
3. The law change is communicated to the populace.
4. Data is accumulated using the stated metrics for the provisional period.
5. At the end of the provisional period the law is evaluated by the approvers. Did it measurably improve society in the manner expected, or did it make it worse?
6. The law is moved from provisional to permanent status, or is removed.
7. The result and the data on which it is based are communicated to the populace.

This post is to thank Concept Frontier readers for coming to my website and learning what I have to offer. Here are 30 new ideas for you to do whatever you want with.

Humans have a lot of defects. The Blame Reflex, and our innate "Us vs Them” pathology are two big ones. 

Our defects lead us to behaviours that aren't in civilisation's best interest, or even our own best interest. No single human's behaviour has been, or ever will be perfect. Every one of us behaves badly sometimes, as you might have noticed. 

Yet civilisation is improving. How is this possible?

Here's one explanation.

If you applied these 2 attributes – 'Good for the individual human', and 'Good for civilisation' – to all human behaviours in a big list, you'd wind up with four types of behaviour: 

1. Bad for everybody (B)
2. Good for the individual, bad for civilisation (GI)
3. Good for civilisation, bad for the individual (GC)
4. Good for everybody (G)

Bad for everybody (B) and Good for everybody (G) are easy. We all agree behaviours that are good for everyone should be maximised, and behaviours that are bad for everyone should be eliminated. That’s a consensus, and a fundamental factor in civilisation’s improvement. But it’s not the only factor. ​

Today Harvard Business Review (publishers of all manner of goodies at hbr.org) emailed me some sales material with the hardest-hitting subject line in the history of sales email subject lines. It was a thing of strangely cohesive abstract beauty, like Frankenstein's monster would be had he been sewn together from various and sundry chunks of Disney Princesses rather than local cadavers.

Here is Harvard Business Review's incredible email subject line:

That subject line is a rich vein of psychological sales gold. I counted 10 distinct psychological principles utilised in it. Maybe you can spot even more. Here are mine:

1. Get (a verb that triggers the "what's in it for me" mentality from the outset)
   
2. 7 (research shows people click numbered lists, as BuzzFeed will tell you)
   
3. Free (English language's most effective buzz word)
   
4. Gifts (another way of saying and reinforcing free, uses the power of repetition to sell)
   
5. When (not if or should, but when to indicate certitude)
   
6. You (personal pronoun, this is conversational language)
   
7. Subscribe (your call to action power verb)
   
8. and Save (second most effective buzz word)
   
9. Up to 80% (a statistic, triggering a sense of measured credibility)
   
10. (Bonus psychological principle: Jaden Smith Style First Letter Capitalisation Catches The Eye Like A News Headline!)
    

This is email list marketing at it's most thoroughly researched and deviously influential. I am richer for the experience.

If you'd like to learn more about how human psychological principles are veritably milked for their applications in clickbait, here's a clever one from Wired.com:

You’ll Be Outraged at How Easy It Was to Get You to Click on This Headline

Thanks for learning!
Michael