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 11 
 on: September 07, 2016, 07:58:42 am 
Started by Craig Wilkey - Last post by Craig Wilkey
Apophenia is the propensity to see patterns in random data. It was first coined in 1958 by Klaus Conrad – a German neurologist and psychiatrist who, perhaps a little ironically, was attempting to identify early indicators of psychosis.
An apophany (an instance of apophenia) can perhaps best be defined in contrast to an epiphany. An epiphany is a moment of sudden and striking realization that leads a person to a greater degree of clarity in the nature of reality – a discovery of a truism, often hidden in plain sight. An apophany is having the experience of an epiphany, but you’re just plain wrong.

We’ve all heard some version of the old adage that correlation does not imply causation.
It can be clearly demonstrated that in neighborhoods where there is an increase in ice cream consumption, there is a roughly equivalent spike in aggravated assault incidents. We’d be foolish to assume that eating ice cream makes people irrationally violent, but that doesn’t mean there is nothing valuable to learn from this. When we broaden the lens a bit, and include other variables, the connections become clearer.
In overpopulated urban environments, where there is a greater concentration of disenfranchised people – people who are statistically more likely to commit poverty crimes, and statistically less likely to have air-conditioned homes – heat waves usher in higher levels of frustration, lower levels of tolerance, and more people eating ice cream. You can also sharpen the focus by throwing in aggravation over public transit failures, brown-outs and black-outs, lower productivity, and countless other factors.
So, while enjoying tasty dairy products does not necessarily incite violence, the correlation between ice cream consumption and violence is not meaningless. Ice cream consumption analysis may indeed provide value as a leading indicator, or bellwether, of the potential for violent acts trending upward in a given community. If not a bellwether, it certainly is a valid correlation – as opposed to a simple coincidence.

The purpose of regression analysis is to identify those variables (referred to as independent variables) that help reveal valid correlations in the phenomena one is attempting to predict (the dependent variable).

Regression analysis is a tricky beast to harness. When the whole point is to find hidden correlations that may even defy intuitive understanding, it can be tempting to throw in the entire kitchen sink and see what comes out. The greatest perceived risk in that arises from patterns that may align, but are nevertheless invalid. These coincidences are referred to as ‘spurious relationships’.
If the patterns of some spurious relationship(s) happen to align with the patterns of other independent variables in a regression analysis model, the accuracy of the model will be impacted, and could be dramatically impacted.

It would be foolish to place any faith in all those quirky coincidences we always hear about with sports teams, for example. There is no reasonably conceivable way the first initial of the middle name of the first child born in some small town after the start of a sport’s season could predict the outcome of a team’s playoff standings – but I’d be genuinely surprised if there wasn’t some spurious relationship to be found there.
On the other hand, we do have a valid argument for replacing the dramatic orchestra strike that foreshadows violent crime in movies with the sound of an ice cream truck.

How do we strike the balance between the desire to uncover hidden variables that provide valuable insight into trends, and the fear of creating an apophenic, potentially psychotic, regression analysis model?

In my nearly two and a half decades of experience in IT, I have come to the conclusion that the field suffers from rampant apopheniphobia: The irrational fear of finding ostensibly meaningful patterns in random data. (Yes, I did just make that word up. © Craig Wilkey, 2016)
Almost invariably, we simply do not push far enough.

Should stock market analysis include things like weather patterns, celebrity news stories and grade school holidays?
Absolutely!
Classical stock market analysis techniques don’t work as well as they used to. Why? Frankly, we have a greater number of ignorant people playing the market. The proliferation of “Day Traders” has crippled the old market truisms, because so many people who are affecting the market dynamics don’t have any classical training. The things that affect the moods and daily lives of ‘normal people’ need to be considered, because ‘normal people’ are far more active in the markets than they used to be. If they don’t play by the rules, then some of those rules simply cease to apply.

Apopheniphobia is fueled by fears of falling prey to spurious relationships. Who wants to be known as the person who unleashed a dangerous psychotic algorithm into the world?
People think about the many statistical oddities they’ve come across, and it stunts their creative growth…
For example, did you know that there is a direct correlation between the per capita consumption of margarine and the divorce rate in Maine? Cheese consumption is far more dangerous than margarine consumption – it correlates with the number of people who die by becoming tangled in their bed sheets. (And you thought lactose intolerance was a bad reaction?) The number of people who drowned by falling into a pool also correlates with the number of films Nicholas Cage appeared in from 1999 through 2009.
(Source)

In IT, we have a tendency to drive toward ‘proving’ clear, unambiguous relationships that quantify efforts, justify means and, more often than not, clearly align to our own preconceived notions. We want to be able to show clear lines of progression and indisputably direct relationships – we tend to believe anything less will not be trusted by those who hold the purse strings.
Our hyper-rational modes of thinking have a tendency to overshadow our creative imaginations – which, almost inevitably, leads to hampered understanding.

Perhaps the greatest value of regression analysis is that it allows us to challenge our preconceived notions and learn something new. The greatest challenge with it is rarely throwing too much data at our models – it’s not having enough.
Yes, I know… We’re IT. We’re awash with data. We’re swimming in lakes of data and constantly inhaling the fumes of endless data exhaust. What we’re missing is the meaningful data extracted from unstructured information sources – in other words, the extraordinarily valuable information that’s locked away in language that has historically been inaccessible to machines – human language.
Estimates have been telling us for a decade or more that 80% of all information in a given organization is in the form unstructured, human-readable text. I think there is nowhere that rings more true or significant than in trying to understand customer experience. I’d also argue that the majority of the most important service information is within that 80%.

Customer Experience Personalization absolutely depends on translating that human-readable text to machine-actionable data.
When it comes to understanding and deriving value from actionable insights within our customer interactions, we must extract as much understanding from that unstructured text as possible and add it all to the other data in our regression models. Apopheniphbia be damned!

While it’s, admittedly, an oversimplification, it’s convenient to talk about two general approaches to extracting data from text.
Text Analytics/Mining breaks the textual input into digestible chunks of string variables and uses statistical modeling techniques to find patterns in those variables.
The ideal of Natural Language Processing is to develop a translation engine between human language and machine language. It uses some of the same statistical modeling approaches as Text Analytics, but goes much further by applying semantic and syntactic analysis to extract meaning, intention, sentiment and key concepts (among other things) covered in the text.

Our best opportunity to achieve our vision of industry-leading Customer Experience Personalization is to take advantage of Natural Language Processing. That barely scratches the surface of what’s possible. Natural Language Processing will enable us to step aggressively toward extracting real meaning from the vast amount of otherwise machine-invisible, extraordinarily valuable content we have. Using that extracted meaning, in conjunction with our structured data points, will allow us to build truly valuable regression analysis models to understand our customers like never before.
Keep pushing until the model breaks, then dial it back a scosche. That is the path to progress.

Apopheniphobia is the enemy of personalization and Customer Relationship Management.
This is why I’ve decided to launch the Apopheniphobia Awareness Campaign.
Please spread the word!
I need to come up with a design for the lapel pin… Maybe a ribbon with as many digits of pi I can squeeze on it – with all the prime digits bolded?
Maybe we can schedule a charity walk… Follow streets in alphabetical order, maybe?

 12 
 on: March 22, 2016, 04:04:34 am 
Started by Craig Wilkey - Last post by Richardhofs
我反駁道袋鼠精,足協要會打架的,會罵人的樂威壯心得,你們去不行。國足要說他們奪了世界杯只有兩種情況一在意淫威而剛藥局,二就是只有一個隊參加比賽由于睡覺的人太多樂威壯10mg口含錠,校長不知道懲罰誰,只好帶著小兵離開這個班老師拿的工資少,還要受你們氣。歷史課上梁老師感嘆道。
大一點的孩子必要時可以用閃光燈拍金槍不倒,但也最好以反射補光或在閃燈前加柔光片兒童照片記錄著成長的經歷日本性素,應該是多維多向的。這里的“角度”有兩方面的含義迷昏藥,一是拍攝的視角,拍攝時至少應有三個角度,與兒童平視角度拍、站高些俯拍、蹲下甚至躺下來仰著拍,盡量多些拍攝垂直角度上的變化,還要變化拍攝的距離及鏡頭的焦距,除了全身或大半身像,也要有特寫和遠景,除了用中長焦鏡頭,也可用廣角鏡頭。就好象一部電影多些場景的變化,才更“生活”另一方面是兒童表情的角度也應豐富西力士效果,大多數家長拍攝的兒童照片一律是“笑”容催情王,未免單調和生硬,兒童的表情是豐富的,記錄他的成長,就要記錄他的喜怒哀樂樂威壯價錢,這才是人生。
廣州城竟下起大雪,滿城皆白,起義失敗。 區舒云眼看秦少白倒下持久藥物,一夜苦尋阿四。南門下,阿四大難不死被送到阿純所在的教會醫院。
孫卓熟悉阿精的助手工作,但典當物的歸放韓諾都親自處理。韓諾每回經過放置孫卓愛情的典當柜樂威壯價錢,便忍不住想起阿精。孫卓希望韓諾別再當她是孩子,要求韓諾能將心事與她分享秘魯MACA天然偉哥,韓諾寵愛地輕擁著孫卓。
美國女星穆恩 布勞德古德


 13 
 on: March 08, 2016, 01:26:04 pm 
Started by Craig Wilkey - Last post by Craig Wilkey
When you mention Knowledge Management to most people, they think of the knowledge base.

To be sure, building, cultivating and maintaining a comprehensive knowledge base is a critical part of Knowledge Management, but it’s just one piece of much, much larger picture.

Let’s set aside, for the moment, that the knowledge base is only a small fraction of our inventory of available information and knowledge. Still, curating knowledge is but one of the three primary roles of Knowledge Management…

Knowledge Curation focuses on:
  • Gathering existing knowledge & information
  • Capturing knowledge from process execution
  • Fostering a knowledge-sharing culture
  • Building tools and processes to maintain knowledge resources

You can have the most comprehensive knowledge base in the world, but without an equally comprehensive Knowledge Delivery strategy, that’s all it is – a great, big, steaming pile of knowledge.

Knowledge Delivery, the second primary role of Knowledge Management, is chiefly concerned with getting that valuable insight to everyone who needs it – and ensuring it’s presented in a consumable, useful format.

Where most organizations start with Knowledge Delivery is search optimization. Unfortunately, that’s also where many end.

Effective Knowledge Delivery is equal parts search optimization, technology, process engineering, analytics, organizational change management, user interface design, and psychology. The other half is consumer profiling.

Knowledge Delivery requires a thorough understanding of not only what people need to know, but why, how and when they apply that knowledge.

The best way to understand knowledge consumers is through understanding their motivations, the desired outcomes of the multitude of tasks they perform, and the ways they use their tools to accomplish those tasks. The better we know our consumers, the better we can seamlessly integrate knowledge directly into their existing processes and tools.

Rather than forcing consumers to search for knowledge, we should place it right there at their fingertips when it’s needed.

Service Delivery Optimization is the final, and most often overlooked, role of Knowledge Management.

Various systems, scattered across the enterprise, store staggering amounts of valuable data and information about our solutions, historical customer engagements, accounts and resources.

Imagine we have a customer with an aging infrastructure that has been growing increasingly prone to failure, and their contract is nearing expiration. Their internal operations team consistently returns surveys with reasonably high Transactional-CSAT scores, but when their Business Service Owner reaches out to our Account Management team, it’s often with concerns over failure response times, and these emails tend to arrive several weeks after the failures have occurred. These complaints started shortly after a leadership shake-up in the customer’s organization. They’re in the middle of a full infrastructure assessment, and expect to make some critical decisions on a data center tech refresh within the next six months. We have an influential internal champion there who is very well-versed in their legacy environment, but lacks deep understanding of our latest product lines.

Every person who directly (and indirectly) services this customer should be keenly aware of the situation. It’s Knowledge Management’s job to foster that situational awareness.

Such a level of account health and wellness awareness requires performance data, historical serviceability information, market analysis, competitive landscaping, insight from numerous people in different departments, and on and on…

Knowledge Management strives to find new ways of connecting, combining and processing all those data, information and knowledge sources (along with other external sources) to actually create new knowledge – knowledge that enables us to:
  • Deliver highly personalized service
  • Optimize our workforce and processes
  • Uncover revenue opportunities
o   …and make the most of those opportunities

Knowledge Management both welds our processes together, and greases the gears.

My career has spanned across many different disciplines within the scope of IT Service Management over the past two decades. I built that career upon the foundation of one simple premise: If your people are not following your processes, don’t blame the people.

Nowhere is this perspective more clear than in Knowledge Management.

Knowledge Management should be as transparent as it is ubiquitous.

In fact, I’d go a step further and say the ultimate goal of Knowledge Management as a practice is to eliminate Knowledge Management as a process.

 14 
 on: February 26, 2016, 06:15:37 am 
Started by Craig Wilkey - Last post by Donalsldrowl
BIG DICK))
Copy link
 
http://ddd.marketpill.com

 15 
 on: October 08, 2015, 09:30:32 am 
Started by Craig Wilkey - Last post by Craig Wilkey
     For the better part of two decades, I have bristled against using Transactional Customer Satisfaction scores (CSAT) to measure the performance of Customer Service Case Managers (Incident Managers, Incident Analysts, call them what you will – I mean the people who wrangle the support resources to resolve customers’ incidents and solve their problems). Until recently, I couldn’t put my finger on exactly why, but I had quite a strong reaction against it.

     I could go on for hours (and have) about the inherent drawbacks and inaccuracies of measuring CSAT…
     Who responds to surveys but the very happy and the very unhappy?
     Even if you do get abnormally high response rates – like 1% or greater – pretty much everyone else is doing so from obligation, is generally indifferent and just wants to get on with their day.
     Even if you do apply analysis to separate the wheat from the chaff, you’re still inconveniencing and annoying your customer with surveys.
     Even if you do stumble upon the ideal concoction of alchemy, sorcery and truly extraordinary luck, the best you can hope for when applying hard numbers to performance of soft skills, is to generate a one dimensional, pallid representation of a complex, richly-flavored human experience…

     I am a process engineer at heart… Not just in my career, but across every aspect of my life – and I have been for pretty much my entire life. Measuring a person’s performance on something as subjective and woefully flawed as CSAT deeply offends my sensibilities.
     This is the argument I’ve been making against CSAT measurements throughout my career, but there was something more than that – something much deeper. What I’ve finally come to realize is that, regardless with what level of fidelity you may capture CSAT, the concept itself is fundamentally flawed and actually results in driving customer satisfaction in the wrong direction.
     Measurement drives behavior drives performance... What does measuring Transactional CSAT drive?

Moments of Truth

     Throughout any customer interaction, we encounter a number of opportunities to influence the outcome of the interaction. These “Moments of Truth” are the points in time that make or break any service experience, therefore any service organization. Moments of Truth in a service organization lie, overwhelmingly, within the hands of Customer Service Professionals – and, more often than not, they occur when the customer is already in a difficult, vulnerable position. For better or worse, Case Managers are the face of the organization in the customer’s eyes. The reputation of the entire organization rests squarely upon their shoulders.

     Using CSAT surveys and the like to gauge the quality of a service engagement (and holding those scores over the heads of Customer Service Professionals) starts with a perspective that has proven, time and again over decades, to ultimately lead to failure.
     All transaction-based service interaction metrics – CSAT not being the least of which – belie the entire premise of what a Customer Service Professional is. It reinforces the notion of the Service Desk as an entry-level position, filled with transient employees (or a dead-end job) and undermines any effort to transform the Service Desk as a potential career destination.

     The most crucial skills required to be a successful Customer Service Professional all revolve around building relationships. A quality Customer Service Professional is an advocate for the customer. They have to be able to understand the situation the customer is facing, but anyone with adequate language skills and minimal training can do that well enough. Far more critical than that is exceptional interpersonal acumen.
     If I were to profile my ideal Customer Service Professional, it would look something like this:
•   Personable
•   Places a high degree of importance on honesty and integrity
•   Highly focused and detail-oriented
•   Empathetic
•   Intelligent
•   Exceptional communication skills
•   Secondary education in Psychology
      o    Yes, really!
•   Calm under pressure
•   Confident and assertive, without being arrogant

     The ideal Customer Service Professional should be seen as just that – a professional!
     Far too often, and for far too long, organizations have focused on remediating service failures as quickly and cheaply as possible. They stock their service desks with overworked and underpaid entry-level personnel (or far worse, outsource it to cheap clearing houses).

     Let that sink in for a moment…
     The people hired to be the face of your organization to your customers, at the most critical moments that define your relationship with them, have roughly the same professional profile as the person working at your local coffee shop.

     Don’t align them to your own service and product lines – align them to your customers. They should know the customers intimately. They should understand their business models and customers. They should understand what’s important to them.
     When a customer calls, they should reach someone they have a relationship with… someone they trust… someone that will serve as their advocate, and will work to wrangle the resources and skills required to satisfy their needs.

     The ideal career path up and out of a Service Desk should not be into a technical role – it should be through whatever Customer Success/Trusted Advisor/Customer Experience Management structure your organization has in place.

     We shouldn’t measure CSAT to try and tell us how our Case Managers are doing – we should hire Customer Service Professionals with the appropriate skills and experience to tell us how our customers are doing.

 16 
 on: October 07, 2015, 10:13:47 am 
Started by Craig Wilkey - Last post by Craig Wilkey
(This is definitely more general philosophy than Service Management, but I think it fits better here than in my General Ramblings blog section.)

Pessimist: This glass is half empty.

Optimist: It's half full!

Engineer: The glass is operating at 50% capacity. My research shows the optimal operating capacity is 92.3%. We should transfer the water to an appropriately-sized glass, and keep the larger glass readily available for unexpected peaks in demand.

Middle Manager: With this increased efficiency, we can fire the engineer!

Paranoid: Did someone poison this water?

Conspiracy Theorist: The government did.

Schizophrenic: With alien DNA!

Pragmatist: You're all missing the point! What's the best use of this water?

Communist: Let the people decide!

Democrat: Well... 51% of the people, anyway.

Republican: The people don't know what's best for them. That's why they elected us to decide FOR them!

Socialist: The state should find the best method of distributing the water among the people in the most equitable fashion.

Liberal: Good idea! Give each person one drop of water, starting with those in the most need. When we run out, we'll figure something else out.

Cynic: You're only saying that because it makes you feel better about yourself.

Aristocrat: Wait! What?? If you give it to the rich, who benevolently support the poor, you'll help MANY more people than if you give it to the poor – who don't matter anyway!

Conservative: You can redistribute this water when you pry it from my cold, dead hands! I earned this glass of water and will defend it, and the other 50,000 gallons in my basement, with deadly force, if I have to!

Libertarian: Screw all of you. I'm going to get my own water.

Anarchist: We should all be responsible for getting our own water. People's inherent compassion, integrity and good sense will result in the most equitable cooperative conglomerates.

Marketing Executive: This stylish, functional glass will continue to quench your thirst for the rest of your life.

Lawyer: (*Endless supply of water not included.)

Sales Executive: Don't worry. I'll make sure you always get the lowest water rates.

Corporate Executive: Lifetime glasses leaves us with diminishing demand. We need to make these glasses more fragile.

Fashionista: That glass is so last week, ANYWAY...

Hippie: Water should be free for all!

Capitalist: OK. But you have to pay license fees to use the glass.

CEO: Brilliant! Fire the imbecile who came up with the fragile glasses and hire that guy!

The Thirsty People: Put the imbecile in Congress!

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