Demand Forecasting Quotes

Don’t let yourself forget how many doctors have died, furrowing their brows over how many deathbeds. How many astrologers, after pompous forecasts about others’ ends. How many philosophers, after endless disquisitions on death and immortality. How many warriors, after inflicting thousands of casualties themselves. How many tyrants, after abusing the power of life and death atrociously, as if they were themselves immortal. How many whole cities have met their end: Helike, Pompeii, Herculaneum, and countless others. And all the ones you know yourself, one after another. One who laid out another for burial, and was buried himself, and then the man who buried him - all in the same short space of time. In short, know this: Human lives are brief and trivial. Yesterday a blob of semen; tomorrow embalming fluid, ash. To pass through this brief life as nature demands. To give it up without complaint. Like an olive that ripens and falls. Praising its mother, thanking the tree it grew on.

As a result we are more and more directing the desires of men to something which does not exist - making the role of the eye in sexuality more and more important and at the same time making its demands more and more impossible. What follows you can easily forecast!

As a result we are more and more directing the desires of men to something which does not exist—making the rôle of the eye in sexuality more and more important and at the same time making its demands more and more impossible. What follows you can easily forecast! That

The ExxonMobil forecast numbers suggested that to make an impact on oil demand, the world’s governments would have to reach a unified conclusion that climate change presented an emergency on the scale of the Second World War—a threat so profound and disruptive as to require massive national investments and taxes designed to change the global energy mix.

We have documented in this book that: • Cost overruns of 50 per cent to 100 per cent in real terms are common in megaprojects; overruns above 100 per cent are not uncommon; • Demand forecasts that are wrong by 20 per cent to 70 per cent compared with actual developments are common; • The extent and magnitude of actual environmental impacts of projects are often very different from forecast impacts. Post-auditing is neglected;

Without action, forecasts and decisions about the future are not worth the paper they are written on. A decision that does not result in action is a poor one. The pace of business demands timely as well as informed decision making.

As a result we are more and more directing the desires of men to something which does not exist—making the rôle of the eye in sexuality more and more important and at the same time making its demands more and more impossible. What follows you can easily forecast!

Push” describes a method and means of organizing activities and actions. Push operates on a key assumption—that it is possible to forecast or anticipate demand. Based on this assumption, push works mightily to ensure that the right people and resources are delivered at the right place and the right time to serve the anticipated demand.

This book aims to learn from that mistake. One of its goals is to ask whether Minsky’s demand for a theory that generates the possibility of great depressions is reasonable and, if so, how economists should respond. I believe it is quite reasonable. Many mainstream economists react by arguing that crises are impossible to forecast: if they were not, they would either already have happened or been forestalled by rational agents. That is certainly a satisfying doctrine, since few mainstream economists foresaw the crisis, or even the possibility of one. For the dominant school of neoclassical economics, depressions are a result of some external (or, as economists say, ‘exogenous’) shock, not of forces generated within the system.

More often forecasts are made and then…nothing. Accuracy is seldom determined after the fact and is almost never done with sufficient regularity and rigor that conclusions can be drawn. The reason? Mostly it’s a demand-side problem: The consumers of forecasting—governments, business, and the public—don’t demand evidence of accuracy. So there is no measurement. Which means no revision. And without revision, there can be no improvement.

Complex operations, in which agencies assume complementary roles and operate in close proximity-often with similar missions but conflicting mandates-accentuate these tensions. The tensions are evident in the processes of analyzing complex environments, planning for complex interventions, and implementing complex operations. Many reports and analyses forecast that these complex operations are precisely those that will demand our attention most in the indefinite future. As essayist Barton and O'Connell note, our intelligence and understanding of the root cause of conflict, multiplicity of motivations and grievances, and disposition of actors is often inadequate. Moreover, the problems that complex operations are intended and implemented to address are convoluted, and often inscrutable. They exhibit many if not all the characteristics of "wicked problems," as enumerated by Rittel and Webber in 1973: they defy definitive formulations; any proposed solution or intervention causes the problem to mutate, so there is no second chance at a solution; every situation is unique; each wicked problem can be considered a symptom of another problem. As a result, policy objectives are often compound and ambiguous. The requirements of stability, for example, in Afghanistan today, may conflict with the requirements for democratic governance. Efforts to establish an equitable social contract may well exacerbate inter-communal tensions that can lead to violence. The rule of law, as we understand it, may displace indigenous conflict management and stabilization systems. The law of unintended consequences may indeed be the only law of the land. The complexity of the challenges we face in the current global environment would suggest the obvious benefit of joint analysis - bringing to bear on any given problem the analytic tools of military, diplomatic and development analysts. Instead, efforts to analyze jointly are most often an afterthought, initiated long after a problem has escalated to a level of urgency that negates much of the utility of deliberate planning.

For years the financial services have been making stock-market forecasts without anyone taking this activity very seriously. Like everyone else in the field they are sometimes right and sometimes wrong. Wherever possible they hedge their opinions so as to avoid the risk of being proved completely wrong. (There is a well-developed art of Delphic phrasing that adjusts itself successfully to whatever the future brings.) In our view—perhaps a prejudiced one—this segment of their work has no real significance except for the light it throws on human nature in the securities markets. Nearly everyone interested in common stocks wants to be told by someone else what he thinks the market is going to do. The demand being there, it must be supplied. Their interpretations and forecasts of business conditions, of course, are much more authoritative and informing. These are an important part of the great body of economic intelligence which is spread continuously among buyers and sellers of securities and tends to create fairly rational prices for stocks and bonds under most circumstances. Undoubtedly the material published by the financial services adds to the store of information available and fortifies the investment judgment of their clients.

A few years ago my friend Jon Brooks supplied this great illustration of skewed interpretation at work. Here’s how investors react to events when they’re feeling good about life (which usually means the market has been rising): Strong data: economy strengthening—stocks rally Weak data: Fed likely to ease—stocks rally Data as expected: low volatility—stocks rally Banks make $4 billion: business conditions favorable—stocks rally Banks lose $4 billion: bad news out of the way—stocks rally Oil spikes: growing global economy contributing to demand—stocks rally Oil drops: more purchasing power for the consumer—stocks rally Dollar plunges: great for exporters—stocks rally Dollar strengthens: great for companies that buy from abroad—stocks rally Inflation spikes: will cause assets to appreciate—stocks rally Inflation drops: improves quality of earnings—stocks rally Of course, the same behavior also applies in the opposite direction. When psychology is negative and markets have been falling for a while, everything is capable of being interpreted negatively. Strong economic data is seen as likely to make the Fed withdraw stimulus by raising interest rates, and weak data is taken to mean companies will have trouble meeting earnings forecasts. In other words, it’s not the data or events; it’s the interpretation. And that fluctuates with swings in psychology.

if you can’t measure it, you can’t manage it.

Tough times brought on by the Gulf War were testing such assumptions, forcing us to consider our response. We needed to come up with new ideas, do more with less, make short-term gains through greater efficiency, and prepare for long-term gains. That meant cutting every dollar possible in overhead and procedures while maintaining or boosting spending in three vital competitive areas. Number one was product quality. World leadership demanded that we maintain world-class quality, and recession is generally a period when material and labor prices are lowest and room occupancies are down. So we renovated and refurbished at such normally busy properties as the Inn on the Park in London and The Pierre in New York at a time when revenue would be little affected and customers least inconvenienced. That meant we were spending when others were retrenching. We had followed that strategy in 1981-82, and the rebound from that recession had given us nine years of steady growth. I thought the odds were in our favor to score the same way again. The second area was marketing. It’s tempting during recession to cut back on consumer advertising. At the start of each of the last three recessions, the growth of spending on such advertising had slowed by an average of 27 percent. But consumer studies of those recessions had showed that companies that didn’t cut their ads had, in the recovery, captured the most market share. So we didn’t cut our ad budget. In fact, we raised it modestly to gain brand recognition, which continued advertising sustains. As studies show, it’s much easier to sustain momentum than restart it. Third, we eased the workload and reduced costs by simplifying reporting methods. We set up a new system that allowed each hotel to recalculate its forecast, with minimal input, to year’s end, then send it in electronically along with a brief monthly commentary.

Traders speculating on price moves must forecast not only current and future fundamentals but also how the trading world will react to those fundamentals. One must be able not only to study past supply-and-demand figures and how they affected price but also to know a little about crowd psychology. Predicting where prices will go is like trying to predict the direction of a hurricane. Even the experts can make only vague projections until the storm makes landfall.

The quality and conduct of management. A company’s executives should say what they will do, then do what they said. Read the past annual reports to see what forecasts the managers made and if they fulfilled them or fell short. Managers should forthrightly admit their failures and take responsibility for them, rather than blaming all-purpose scapegoats like “the economy,” “uncertainty,” or “weak demand.” Check whether the tone and substance of the chairman’s letter stay constant, or fluctuate with the latest fads on Wall Street. (Pay special attention to boom years like 1999: Did the executives of a cement or underwear company suddenly declare that they were “on the leading edge of the transformative software revolution

A century ago, as physicians were slowly professionalizing and medicine was on the cusp of becoming scientific, a Boston doctor named Ernest Amory Codman had an idea similar in spirit to forecaster scorekeeping. He called it the End Result System. Hospitals should record what ailments incoming patients had, how they were treated, and—most important—the end result of each case. These records should be compiled and statistics released so consumers could choose hospitals on the basis of good evidence. Hospitals would respond to consumer pressure by hiring and promoting doctors on the same basis. Medicine would improve, to the benefit of all. “Codman’s plan disregarded a physician’s clinical reputation or social standing as well as bedside manner or technical skills,” noted the historian Ira Rutkow. “All that counted were the clinical consequences of a doctor’s effort.”8 Today, hospitals do much of what Codman demanded, and more, and physicians would find it flabbergasting if anyone suggested they stop. But the medical establishment saw it differently when Codman first proposed the idea.

the senior inventory managers typically lock themselves in a room and find a Band-Aid tool that satisfies the immediate request. Inevitably, the Band-Aid comes loose and those people uninvolved and underutilized in the decision-making process were then overworked trying to force the plan to work. But this time it was different. The entire inventory management team had just signed up for the 30-Day Challenge and selected the Debate Maker discipline for their work. This time, when the urgent request came from senior management, the group prepared for a thorough debate to find a sustainable solution. They brought in senior planners and the IT group (who usually had to scramble after the fact), who could give practical input to the feasibility of any suggested solution. They framed the issues and set ground rules for debate, including no barriers to the thinking. The team challenged their assumptions and in the end developed a means of in-season forecasting that served the new demands. The solution they arrived at started as a wild idea, but with input from IT, it became a plausible reality.

The Bayesian Invisible Hand … free-market capitalism and Bayes’ theorem come out of something of the same intellectual tradition. Adam Smith and Thomas Bayes were contemporaries, and both were educated in Scotland and were heavily influenced by the philosopher David Hume. Smith’s 'Invisible hand' might be thought of as a Bayesian process, in which prices are gradually updated in response to changes in supply and demand, eventually reaching some equilibrium. Or, Bayesian reasoning might be thought of as an 'invisible hand' wherein we gradually update and improve our beliefs as we debate our ideas, sometimes placing bets on them when we can’t agree. Both are consensus-seeking processes that take advantage of the wisdom of crowds. It might follow, then, that markets are an especially good way to make predictions. That’s really what the stock market is: a series of predictions about the future earnings and dividends of a company. My view is that this notion is 'mostly' right 'most' of the time. I advocate the use of betting markets for forecasting economic variables like GDP, for instance. One might expect these markets to improve predictions for the simple reason that they force us to put our money where our mouth is, and create an incentive for our forecasts to be accurate. Another viewpoint, the efficient-market hypothesis, makes this point much more forcefully: it holds that it is 'impossible' under certain conditions to outpredict markets. This view, which was the orthodoxy in economics departments for several decades, has become unpopular given the recent bubbles and busts in the market, some of which seemed predictable after the fact. But, the theory is more robust than you might think. And yet, a central premise of this book is that we must accept the fallibility of our judgment if we want to come to more accurate predictions. To the extent that markets are reflections of our collective judgment, they are fallible too. In fact, a market that makes perfect predictions is a logical impossibility.

We want products in stock and immediately available to customers, and we want minimal total inventory in order to keep associated holding costs, and thus prices, low. To achieve both, there is a right amount of inventory. We use historical purchase data to forecast customer demand for a product and expected variability in that demand. We use data on the historical performance of vendors to estimate replenishment times. We can determine where to stock the product within our fulfillment network based on inbound and outbound transportation costs, storage costs, and anticipated customer locations.

They are placing demands on American corporations to provide prayer time for Islamic employees on the job. Dell Computers has already caved in to the pressure put forth by the Council on American-Islamic Relations (CAIR) regarding this issue and now allows its Muslim employees prayer time on the job. Our radio and TV talk show hosts are watching their tongues when criticizing even the radical Islamic element of the religion lest they be fired or sued, just as Michael Graham was fired from ABC radio for linking Islam to terrorism. The Islamic community throughout the world is outreproducing Christians and Jews almost seven to one. It will be a matter of a few generations before they can get voting power to challenge state laws and change the Constitution of the United States. Islam is already the fastest-growing religion in Europe. Driven by immigration and high birthrates, the number of Muslims on the continent has tripled in the last thirty years. Most demographers forecast a similar or even higher rate of growth in the coming decades. It is important to note that the world’s fastest-growing Muslim populations are found in Europe and the United States, where they are the second- or third-largest religious communities. This is the beginning of America’s and the West’s war with radical Islam.

The Fortune Teller vs The Forecaster Another reason you shouldn't be putting exact figures and time-frames on these larger goals, is again due to limitations of the human brain.

If you want to learn more about the zodiac by examining all of the many branches of astrology, don’t skip this article. Astrology has grown in popularity since ancient times. When people interpreted the position of the stars concerning agricultural necessities and told stories around the fireplace inspired by the cosmos. It has developed in many different directions over time to meet the varying needs of humanity. As an immensely strong tool for self-discovery and all types of forecasting. Branches of astrology have served as anything from a king’s electoral tool to a beacon of hope for people in need. Its dark ages and degeneration turned out to have a positive impact on it as well. As it is today stronger than it has ever been, with a wide range of products and ways to meet every demand that arises.

A forecast from SpaceWorks in 2019 further predicted 2,000–2,800 nano or microsatellites will launch in over the next five years between the military, commercial, and civil sectors. This segment of satellites already increased in launch and production by 25 percent from 2017 to 2018; in 2018, 253 of the planned 262 nanosatellites actually launched, reflecting “Greater launch consistency and better execution on the part of small satellite operators.”5 Factors like the Internet of Things (IoT), demand for communications data, and increased need for Earth observation are all helping to drive this market.

The researcher who led that work went on to study thousands of businesses. She found that the most effective leaders and organizations had range; they were, in effect, paradoxical. They could be demanding and nurturing, orderly and entrepreneurial, even hierarchical and individualistic all at once. A level of ambiguity, it seemed, was not harmful. In decision making, it can broaden an organization’s toolbox in a way that is uniquely valuable. Philip Tetlock and Barbara Mellers showed that thinkers who tolerate ambiguity make the best forecasts; one of Tetlock’s former graduate students, University of Texas professor Shefali Patil, spearheaded a project with them to show that cultures can build in a form of ambiguity that forces decision makers to use more than one tool, and to become more flexible and learn more readily.

The First Autonomous Teams Autonomous teams are built for speed. When they are aligned toward a common destination, they can go a long way in a short time. But when they are poorly aligned, the team can veer far off course just as quickly. So they need to be pointed in the right direction and have the tools to quickly course-correct when warranted. That’s why, before any proposed two-pizza team was approved, they had to meet with Jeff and their S-Team manager—often more than once—to discuss the team’s composition, charter, and fitness function. For instance, the Inventory Planning team would convene with Jeff, Jeff Wilke, and me to ensure that they were meeting the following criteria: The team had a well-defined purpose. For example, the team intends to answer the question, “How much inventory should Amazon buy of a given product and when should we buy it?” The boundaries of ownership were well understood. For example, the team asks the Forecasting team what the demand will be for a particular product at a given time, and then uses their answer as an input to make a buying decision. The metrics used to measure progress were agreed upon. For example, In-stock Product Pages Displayed divided by Total Product Pages Displayed, weighted at 60 percent; and Inventory Holding Cost, weighted at 40 percent.

By all means, demand certainty for the next picnic; but avoid government social-security forecasts for the year 2040.

Test the market with samples first, if you can, to know what is really going to sell. • If possible, don’t build inventory in large quantities and eat up cash unless the business has the orders in its hands. • Try to find strategic partners that have quick turnarounds for building inventory. • Unless you have real-time data on customer demand and have an extremely tight connection to your suppliers, you’ll never get inventory forecasting exactly right. • Err on the side of less rather than more inventory as a rule of thumb. • If you have to make a trade-off between paying more per unit in COGS to reduce the cycle time to build inventory, choose the higher COGS and reduced production time. You’ll be placing smaller orders with greater frequency, turning inventory faster and cash faster. Read this point again—it’s not very complicated (place smaller orders, more frequently), but it’s really, really important for managing your inventory.

Strategy usually begins with an assessment of your industry. Your choice of strategic style should begin there as well. Although many industry factors will play into the strategy you actually formulate, you can narrow down your options by considering just two critical factors: predictability (How far into the future and how accurately can you confidently forecast demand, corporate performance, competitive dynamics, and market expectations?) and malleability (To what extent can you or your competitors influence those factors?).

demanded. Starting in the 1950s, however, as computers became more powerful, scientists found they could use Bayesian approaches to forecast events that were previously thought unpredictable, such as the likelihood of a war, or the odds that a drug will be broadly effective even if it has only been tested on a handful of people. Even today, though, calculating a Bayesian probability curve can, in some cases, tie up a computer for hours.

Every team should be required to use the same reconciled demand, pricing, and master data (as well as any other relevant information sources). A supply chain cannot allow two teams to use different historical figures to populate forecasts.24

15.2.1 Short history of machine-learning models Harder, Better, Faster, Stronger —Daft Punk