Business Analytics Quotes

Organizational structure and management style are those two factors that we always forget to analyze when the performance of our businesses goes down.

You are dealing with emotional customers and not analytical bots.

Maintaining a healthy balance of analytics, strategy and creativity is very important as they’re all equally important.

A discontent employee means not getting the results 100% and the loss of a company advocate as well.

When it comes to riding a trend for business growth, there are three important steps that we should always remember: data analysis, trend identification, and fast and effective decision making.

Tweet others the way you want to be tweeted.

When we pair modern tech like Blockchain technology, cryptography and data analytics with the ancient practice of bartering, a lot of business opportunities emerge.

Good decision-making is based on access to the correct information at the right time.

Keep learning more and more about your customers, your competitors, your brand, your target market, and business opportunities.

Let market research be a permanent, ongoing part of your business strategy.

When we master customer behavior and are able to offer them exactly what they want, we can achieve the biggest business opportunities.

Making the right decision at the right time is what sets a successful entrepreneur apart from the others.

In current times, we have access to so much data. Having said that, data analysis can uncover so many hidden patterns about customer behavior and how they interact with various products.

The kind of data and the data-analytical perspective privy to banks is quite unique to banks.

That is why a good reader does not cheer an apt sentence or pause to applaud even an inspired paragraph. Analytic thought is too busy for that, and too detached.

Ratios matter in Data Science. Dreams should be big and worries small.

If you can’t explain it simply, you don’t understand it well enough. — Albert Einstein

The critic's proper business is explanation and evaluation, which means he must make use of his analytic powers to translate the concrete to the abstract.

As business leaders we need to understand that lack of data is not the issue. Most businesses have more than enough data to use constructively; we just don't know how to use it. The reality is that most businesses are already data rich, but insight poor.

Your job isn’t to build a product; it’s to de-risk a business model.

Someday soon, say predictive analytics experts, it will be possible for companies to know our tastes and predict our habits better than we know ourselves.

data mining is an exploratory undertaking closer to research and development than it is to engineering.

Data Analytics is critical to wise investing, but so is good old fashioned understanding of business and markets.

almost every scholar who has grappled with the question of what reading does to one’s habits of mind has concluded that the process encourages rationality; that the sequential, propositional character of the written word fosters what Walter Ong calls the “analytic management of knowledge.

Forward-thinking organizations seek hybrid professionals who are highly proficient writers, analytical, creative, and tech savvy, with strong competencies in business management, information technology (IT), and human behavior.

To engage the written word means to follow a line of thought, which requires considerable powers of classifying, inference-making and reasoning. It means to uncover lies, confusions, and overgeneralizations, to detect abuses of logic and common sense. It also means to weigh ideas, to compare and contrast assertions, to connect one generalization to another. To accomplish this, one must achieve a certain distance from the words themselves, which is, in fact, encouraged by the isolated and impersonal text. That is why a good reader does not cheer an apt sentence or pause to applaud even an inspired paragraph. Analytic thought is too busy for that, and too detached.

It is useful for companies to look at AI through the lens of business capabilities rather than technologies. Broadly speaking, AI can support three important business needs: automating business processes, gaining insight through data analysis, and engaging with customers and employees.

All good decisions are Data dependent. To make good decisions, you need good data. And you need that good data to be organized according to it's applicable use value. So every business should be mining data and organizing data to enable business leaders to make good decisions on behalf of the business.

As Paul Saffo, a forecaster of large-scale change at Discern Analytics, observes wisely, 'Change is never linear. Our expectations are linear, but new technologies come in S curves, so we routinely overestimate short-term change and underestimate long-term change.' Never mistake a clear view for a short distance, he adds.

Quick Review of Core Behavior Patterns Reds are quick and more than happy to take command if needed. They make things happen. However, when they get going, they become control freaks and can be hopeless to deal with. And they repeatedly trample on people’s toes. Yellows can be amusing, creative, and elevate the mood regardless of who they’re with. However, when they are given unlimited space, they will consume all the oxygen in the room, they won’t allow anyone into a conversation, and their stories will reflect reality less and less. The friendly Greens are easy to hang out with because they are so pleasant and genuinely care for others. Unfortunately, they can be too wishy-washy and unclear. Anyone who never takes a stand eventually becomes difficult to handle. You don’t know where they really stand, and indecision kills the energy in other people. The analytical Blues are calm, levelheaded, and think before they speak. Their ability to keep a cool head is undoubtedly an enviable quality for all who aren’t capable of doing that. However, Blues’ critical thinking can easily turn to suspicion and questioning those around them. Everything can become suspect and sinister.

Like large areas of analytic philosophy today, scholasticism, too, preferred to busy itself with the fetishization of fine distinctions on an apparently secure investigative foundation, rather than engaging in the adventure of providing a relevant contribution to the understanding of its own age, with its shifting foundational structures.

Now is the moment to define our terms. In this book, Fast and Slow do more than just describe a rate of change. They are shorthand for ways of being, or philosophies of life. Fast is busy, controlling, aggressive, hurried, analytical, stressed, superficial, impatient, active, quantity-over-quality. Slow is the opposite: calm, careful, receptive, still, intuitive, unhurried, patient, reflective, quality-over-quantity. It is about making real and meaningful connections - with people, culture, work, food, everything.

While CEO of P&G, John Pepper was once asked in an interview which skill or characteristic was most important to look for when hiring new employees. Was it leadership? Analytical ability? Problem solving? Collaboration? Strategic thinking? Or something else? His answer was integrity. He explained, “All the rest, we can teach them after they get here.

All revolutions are impossible till they happen, then they become inevitable.

Most people use statistics the way a drunkard uses a lamp post, more for support than illumination.

opinion-based decision making, statistical malfeasance, and counterfeit analysis are pandemic. We are swimming in make-believe analytics.

We have met the enemy and he is us.” We need to change the ways we do our job.

All models are wrong, but some are useful.” In other words, models intentionally simplify our complex world.

You can't manage what you don't measure.

An intelligent organization is not about the “cleverness” of one analytics team but the insightful nature of the entire business.

All data has its beauty, but not everyone sees it.

You need to know which aspects of your business are too risky and then work to improve the metric that represents that risk.

The human job losses we’ve seen were primarily due to attrition of workers who were not replaced or through automation of outsourced work.

Unfortunately, creating an objective function that matches the true goal of the data mining is usually impossible, so data scientists often choose based on faith[22] and experience.

Anyone who knows anything about data knows that it is critical to have authentic data – data that holistically represents the truth of something, as opposed to fragments or biased portions.

Often, the answer to a problem or dilemma is not immediately obvious, and we simply don’t know what to do next. As we mentioned earlier, a problem cannot be solved at the same level of thinking in which it was created; we need a shift in our level of understanding. This logic reminds us that if we do not know the answer to a specific problem, recycling the same information over and over usually will not produce a solution. It will, however, keep our minds busy and speeded up. It will create stress. We’ve all had the experience of being stuck in “thought quicksand,” where our mental struggling sucks us deeper into our analytical thinking. This is an example of the misuse of the analytical thought process.

Create mode is when you’re imaginative, creative, and open to new ideas. Edit mode is when you are logical, regulated, and analytical. Most of us constantly switch back and forth between the two within a given piece of work, like when we write an email. You write a small part, read it, make edits, and then write some more. The major issue is that your editor brain gets in the way of your creator brain. It stops the flow, which can remove the potential of amazing thoughts that you didn’t even know exist in your head from ever coming out. You need these thoughts to surface during this experiment, but your editor brain can get in the way because it’s too focused on making everything right or perfect. Thinking puts your editor brain into the driver’s seat.

The construction industry is the world’s second largest (after agriculture), worth $8 trillion a year. But it’s remarkably inefficient. The typical commercial construction project runs 80% over budget and 20 months behind schedule, according to McKinsey.

In spite of its undeniable power, so many leaders struggle to embrace organizational health (which I’ll be defining shortly) because they quietly believe they are too sophisticated, too busy, or too analytical to bother with it. In other words, they think it’s beneath them.

Digital analytics is the analysis of qualitative and quantitative data from your business and the competition to drive a continual improvement of the online experience that your customers and potential customers have which translates to your desired outcomes (both online and offline).

20th Century 21st Century Scale and Scope Speed and Fluidity Predictability Agility Rigid Organization Boundaries Fluid Organization Boundaries Command and Control Creative Empowerment Reactive and Risk Averse Intrapreneur Strategic Intent Profit and Purpose Competitive Advantage Comparative Advantage Data and Analytics Synthesizing Big Data

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I was thinking about Leon and our affinity for busyness, when I happened upon a book called In Praise of Slowness, written by Carl Honoré. In that book he describes a New Yorker cartoon that illustrates our dilemma. Two little girls are standing at a school-bus stop, each clutching a personal planner. One says to the other, “Okay, I’ll move ballet back an hour, reschedule gymnastics, and cancel piano. You shift your violin lessons to Thursday and skip soccer practice. That gives us from 3:15 to 3:45 on Wednesday the sixteenth to play.” This, I suppose, is how the madness starts. Pay close attention to the words Honoré uses to describe this fast-life/slow-life dichotomy. “Fast is busy, controlling, aggressive, hurried, analytical, stressed, superficial, impatient, active, quantity-over-quality. Slow is the opposite: calm, careful, receptive, intuitive, unhurried, patient, reflective, quality-over-quantity…. It is seeking to live at what musicians call the tempo giusto—the right speed.”* Which of those lifestyles would you prefer?

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Simon Leigh Pure Reputation, The Role of AI in Online Reputation Management (ORM) Artificial Intelligence (AI) plays a transformative role in Online Reputation Management by automating monitoring, analysis, and response to online content. AI-powered tools scan social media, review platforms, forums, and news sites in real time to detect mentions of a brand or individual. Through sentiment analysis, AI evaluates whether the mentions are positive, negative, or neutral, helping businesses gauge public perception instantly. AI also enables predictive analytics, identifying emerging reputation risks before they escalate. Chatbots and automated response systems use natural language processing (NLP) to manage customer interactions quickly and consistently. Additionally, AI supports content generation and SEO optimization, ensuring positive brand stories and authoritative profiles rank higher in search results. Overall, AI enhances ORM by making it faster, data-driven, and proactive, allowing organizations to protect and strengthen their digital reputation efficiently.

Charles Munger, right-hand adviser to Warren Buffett, the richest man on the planet, is known for his unparalleled clear thinking and near-failure-proof track record. How did he refine his thinking to help build a $3 trillion business in Berkshire Hathaway? The answer is “mental models,” or analytical rules-of-thumb4 pulled from disciplines outside of investing, ranging from physics to evolutionary biology. Eighty to 90 models have helped Charles Munger develop, in Warren Buffett’s words, “the best 30-second mind in the world. He goes from A to Z in one move. He sees the essence of everything before you even finish the sentence.

Minds are great when it comes to inventing new devices, constructing business plans, or organizing daily schedules. But, by themselves, minds are far less useful in learning to be present, learning to love, or discovering how best to carry the complexities of a personal history. Verbal knowledge is not the only kind of knowledge there is. We must learn to use our analytical and evaluative skills when doing so promotes workability and to use other forms of knowledge when they best serve our interests. In effect, the ultimate goal of ACT is to teach clients to make such distinctions in the service of promoting a more workable life.

That you have to ask Krishnamurti, not me. That is not my business. He loves it, that’s how he has grown. For centuries, for many, many lives, he has been moving towards a tunnel vision. And the tunnel vision has its own beauties, because whatsoever you see, you see very clearly because your eyes are focused. Hence the clarity of Krishnamurti. Nobody has ever been so clear, so crystal clear. Nobody has ever been so logical, so rational; nobody has ever been so analytical. His profundity in going into things and their details is simply unbelievable. But that is part of his tunnel vision. You cannot have everything, remember. If you want clarity you will need tunnel vision; you will have to become more and more focused on less and less.

My “10 Smart Market Diagnosis and Profiling Questions” What keeps them awake at night, indigestion boiling up their esophagus, eyes open, staring at the ceiling? What are they afraid of? What are they angry about? Who are they angry at? What are their top three daily frustrations? What trends are occurring and will occur in their businesses or lives? What do they secretly, ardently desire most? Is there a built-in bias to the way they make decisions? (Example: engineers = exceptionally analytical) Do they have their own language? Who else is selling something similar to their product, and how? Who else has tried selling them something similar, and how has that effort failed? So, Step 1 in our system is to analyze thoroughly, understand, and connect with the customer.

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The need for managers with data-analytic skills The consulting firm McKinsey and Company estimates that “there will be a shortage of talent necessary for organizations to take advantage of big data. By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.” (Manyika, 2011). Why 10 times as many managers and analysts than those with deep analytical skills? Surely data scientists aren’t so difficult to manage that they need 10 managers! The reason is that a business can get leverage from a data science team for making better decisions in multiple areas of the business. However, as McKinsey is pointing out, the managers in those areas need to understand the fundamentals of data science to effectively get that leverage.

Although some organizations today may survive and prosper because they have intu- itive geniuses managing them, most are not so fortunate. Most organizations can benefit from strategic management, which is based upon integrating intuition and analysis in decision making. Choosing an intuitive or analytic approach to decision making is not an either–or proposition. Managers at all levels in an organization inject their intuition and judgment into strategic-management analyses. Analytical thinking and intuitive thinking complement each other. Operating from the I’ve-already-made-up-my-mind-don’t-bother-me-with-the-facts mode is not management by intuition; it is management by ignorance. Drucker says, “I believe in intuition only if you discipline it. ‘Hunch’ artists, who make a diagnosis but don’t check it out with the facts, are the ones in medicine who kill people, and in management kill businesses.

But increasing the amount of equity finance in an economy is easier said than done: it is a project that would take decades rather than years. Some of the barriers are institutional: outside of the very small world of venture capital (of which more later) and the even smaller and newer field of equity crowdfunding, most businesses do not raise equity, and most financial institutions do not provide it. There are established agencies that can rate the creditworthiness of even quite small businesses, and algorithms to allow banks to quickly and cheaply decide whether to lend to them. Nothing similar exists for equity investment, and the equivalent analytical task (working out a company's likely future value, rather than its likelihood of servicing a fixed debt) is more complex. And cultural factors stand in the ways too: despite a very elegant financial economics theorem that shows that business owners should be indifferent between equity and debt finance, for many small business owners there seems a cognitive and cultural bias against giving away equity.

There was little effort to conceal this method of doing business. It was common knowledge, from senior managers and heads of research and development to the people responsible for formulation and the clinical people. Essentially, Ranbaxy’s manufacturing standards boiled down to whatever the company could get away with. As Thakur knew from his years of training, a well-made drug is not one that passes its final test. Its quality must be assessed at each step of production and lies in all the data that accompanies it. Each of those test results, recorded along the way, helps to create an essential roadmap of quality. But because Ranbaxy was fixated on results, regulations and requirements were viewed with indifference. Good manufacturing practices were stop signs and inconvenient detours. So Ranbaxy was driving any way it chose to arrive at favorable results, then moving around road signs, rearranging traffic lights, and adjusting mileage after the fact. As the company’s head of analytical research would later tell an auditor: “It is not in Indian culture to record the data while we conduct our experiments.

A good metric is a ratio or a rate. Accountants and financial analysts have several ratios they look at to understand, at a glance, the fundamental health of a company. You need some, too. There are several reasons ratios tend to be the best metrics: • Ratios are easier to act on. Think about driving a car. Distance traveled is informational. But speed—distance per hour—is something you can act on, because it tells you about your current state, and whether you need to go faster or slower to get to your destination on time. • Ratios are inherently comparative. If you compare a daily metric to the same metric over a month, you’ll see whether you’re looking at a sudden spike or a long-term trend. In a car, speed is one metric, but speed right now over average speed this hour shows you a lot about whether you’re accelerating or slowing down. • Ratios are also good for comparing factors that are somehow opposed, or for which there’s an inherent tension. In a car, this might be distance covered divided by traffic tickets. The faster you drive, the more distance you cover—but the more tickets you get. This ratio might suggest whether or not you should be breaking the speed limit.

Let us begin, then, with the mad-house; from this evil and fantastic inn let us set forth on our intellectual journey. Now, if we are to glance at the philosophy of sanity, the first thing to do in the matter is to blot out one big and common mistake. There is a notion adrift everywhere that imagination, especially mystical imagination, is dangerous to man’s mental balance. Poets are commonly spoken of as psychologically unreliable; and generally there is a vague association between wreathing laurels in your hair and sticking straws in it. Facts and history utterly contradict this view. Most of the very great poets have been not only sane, but extremely business-like; and if Shakespeare ever really held horses, it was because he was much the safest man to hold them. Imagination does not breed insanity. Exactly what does breed insanity is reason. Poets do not go mad; but chess-players do. Mathematicians go mad, and cashiers; but creative artists very seldom. I am not, as will be seen, in any sense attacking logic: I only say that this danger does lie in logic, not in imagination. Artistic paternity is as wholesome as physical paternity. Moreover, it is worthy of remark that when a poet really was morbid it was commonly because he had some weak spot of rationality on his brain. Poe, for instance, really was morbid; not because he was poetical, but because he was specially analytical. Even chess was too poetical for him; he disliked chess because it was full of knights and castles, like a poem. He avowedly preferred the black discs of draughts, because they were more like the mere black dots on a diagram. Perhaps the strongest case of all is this: that only one great English poet went mad, Cowper. And he was definitely driven mad by logic, by the ugly and alien logic of predestination. Poetry was not the disease, but the medicine; poetry partly kept him in health. He could sometimes forget the red and thirsty hell to which his hideous necessitarianism dragged him among the wide waters and the white flat lilies of the Ouse. He was damned by John Calvin; he was almost saved by John Gilpin. Everywhere we see that men do not go mad by dreaming. Critics are much madder than poets. Homer is complete and calm enough; it is his critics who tear him into extravagant tatters. Shakespeare is quite himself; it is only some of his critics who have discovered that he was somebody else. And though St. John the Evangelist saw many strange monsters in his vision, he saw no creature so wild as one of his own commentators. The general fact is simple. Poetry is sane because it floats easily in an infinite sea; reason seeks to cross the infinite sea, and so make it finite. The result is mental exhaustion, like the physical exhaustion of Mr. Holbein. To accept everything is an exercise, to understand everything a strain. The poet only desires exaltation and expansion, a world to stretch himself in. The poet only asks to get his head into the heavens. It is the logician who seeks to get the heavens into his head. And it is his head that splits.

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ever. Amen. Thank God for self-help books. No wonder the business is booming. It reminds me of junior high school, where everybody was afraid of the really cool kids because they knew the latest, most potent putdowns, and were not afraid to use them. Dah! But there must be another reason that one of the best-selling books in the history of the world is Men Are From Mars, Women Are From Venus by John Gray. Could it be that our culture is oh so eager for a quick fix? What a relief it must be for some people to think “Oh, that’s why we fight like cats and dogs, it is because he’s from Mars and I am from Venus. I thought it was just because we’re messed up in the head.” Can you imagine Calvin Consumer’s excitement and relief to get the video on “The Secret to her Sexual Satisfaction” with Dr. GraySpot, a picture chart, a big pointer, and an X marking the spot. Could that “G” be for “giggle” rather than Dr. “Graffenberg?” Perhaps we are always looking for the secret, the gold mine, the G-spot because we are afraid of the real G-word: Growth—and the energy it requires of us. I am worried that just becoming more educated or well-read is chopping at the leaves of ignorance but is not cutting at the roots. Take my own example: I used to be a lowly busboy at 12 East Restaurant in Florida. One Christmas Eve the manager fired me for eating on the job. As I slunk away I muttered under my breath, “Scrooge!” Years later, after obtaining a Masters Degree in Psychology and getting a California license to practice psychotherapy, I was fired by the clinical director of a psychiatric institute for being unorthodox. This time I knew just what to say. This time I was much more assertive and articulate. As I left I told the director “You obviously have a narcissistic pseudo-neurotic paranoia of anything that does not fit your myopic Procrustean paradigm.” Thank God for higher education. No wonder colleges are packed. What if there was a language designed not to put down or control each other, but nurture and release each other to grow? What if you could develop a consciousness of expressing your feelings and needs fully and completely without having any intention of blaming, attacking, intimidating, begging, punishing, coercing or disrespecting the other person? What if there was a language that kept us focused in the present, and prevented us from speaking like moralistic mini-gods? There is: The name of one such language is Nonviolent Communication. Marshall Rosenberg’s Nonviolent Communication provides a wealth of simple principles and effective techniques to maintain a laser focus on the human heart and innocent child within the other person, even when they have lost contact with that part of themselves. You know how it is when you are hurt or scared: suddenly you become cold and critical, or aloof and analytical. Would it not be wonderful if someone could see through the mask, and warmly meet your need for understanding or reassurance? What I am presenting are some tools for staying locked onto the other person’s humanness, even when they have become an alien monster. Remember that episode of Star Trek where Captain Kirk was turned into a Klingon, and Bones was freaking out? (I felt sorry for Bones because I’ve had friends turn into Cling-ons too.) But then Spock, in his cool, Vulcan way, performed a mind meld to determine that James T. Kirk was trapped inside the alien form. And finally Scotty was able to put some dilithium crystals into his phaser and destroy the alien cloaking device, freeing the captain from his Klingon form. Oh, how I wish that, in my youth or childhood,