Easily Build Forecasting Systems: Avoid Costly AI & ERP Programs!
Just about everyone forecasts. If you will be hosting a Super Bowl party, you will need to predict the quantities of foods and beverages to buy. More critically, businesses need to predict their needs for raw materials, supplies, labor, storage space, demand for their products, etc. To better plan resource needs, 74% of the companies surveyed, by the American Marketing Association, were found to use formal forecasting systems, with Enterprise Resource Planning (ERP) and Artificial Intelligence (AI) models, accounting for 92% of successes.
Yet, in 2026, the average price, of such programs for small firms, was $10,000/user annually for a 5-year commitment. In mid-sized-businesses, initial implementation costs soared from $150,000 to $750,000, and at large entities to $15+ million annually. The result has been that over 25% of USA companies (and the individuals within them hoping to advance their careers) have simply settled for suboptimal solutions and/or gotten ripped off by unscrupulous software peddlers.
Thus, Dr. Clark decided to write this book, which teaches the nuts and bolts of such algoritms. As for Dr. Clark, he has multiple technical and business degrees from top-notch institutions, and has held senior staff and executive positions at blue-chip companies. He has also served as a Full Professor and aurhored dozens of academic articles in top journals. Besides many media appearances, he has been quoted in leading sources like FORTUNE magazine and has written more than a dozen books, with multiple best sellers, under the names Alan Bruce Clark PhD and Christian Bruce Clark PhD.
For more than four decades, he built (and taught numerous college students how to construct) AI and ERP forecasting systems, as evidenced by the stories (all his own) on the PremiereBusinessExperts.com site that he single-handedly built. The result is that after you read and work through the exercises in this book you should be able to not only eliminate the high purchase costs of forecasting programs but, more importantly, prepare, using simple spreadsheets, much more accurate forecasts than those of the expensive alternatives. This is especially the case when one realizes AI's 30% rule stating that "AI should handle 70% of a task, leaving the human focus on the remaining 30% that requires critical thinking, decision-making and oversight."
While there are many ways in which forecasting can be performed, they quintessentially rely on either judgmental (e.g., rules-of-thumb or "heuristic guestimates") or analytical (e.g., regression or time series) approaches. Further breaking these down leads to (1) Trend, (2) Time Series, (3) Causal, (4) Regression and (5) Judgmental analyses. However, multiple caveats (i.e., warnings) and problems exist with many of the approaches other than the one which will be the focus in this book.
The easily implemented judgmental methods, for instance, are often "highly political." For example, sales reps fearing they will lose their jobs, if they do not give high estimates will inflate their predicitons, while those believing their bonuses will be higher if they low ball their predictions will do exactly that.
As for many analytical approaches, they rely on variables that have, in essence, "already been forecast" or found by conducting a marketing study. Moroever, there are several different time series methods but there is just one, which is seemingly the most heavily relied upon by the leading Manufatturing, Marketing Research, Retailing, Service and Wholesaling companies. This is the one that will be the focus of this book.
Once you read this book and perform the spreadsheet exercises you will know how to prepare baseline forecasts, as well as handle seasonality, day of week effects, competitve influences, holidays, key customer demands, Leap Years, product and sales rep differences, promotional and post-promotional impacts, etc. You will even learn how to predict the sales of never before made products by combining the attributes of existing goods (or services) in unique ways, prepare "reasonability defaults" and develop confidence intervals (i.e, which show the upper and lower bound ranges for your forecasts), etc.
As a result of your buying this book and recommending it to others, you and they will be able to easily build sytems that outperform anything you can purchase and more importantly dranaticially improve bottom-line profits. While this book provides realistic examples for you to work through, it also shows you very simple methods of handling issues/concerns/problems that do not require you to have advanced statistical training. Nevertheless, the skills you develop will PROVE YOUR GENIUS ABILITIES WARRANTING THE HIGHER EARNINGS YOU SHOULD RECEIVE, due to your building robust systems, using only spreadsheets, which outperform the AI and ERP programs being sold at exceptionally high prices.
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Yet, in 2026, the average price, of such programs for small firms, was $10,000/user annually for a 5-year commitment. In mid-sized-businesses, initial implementation costs soared from $150,000 to $750,000, and at large entities to $15+ million annually. The result has been that over 25% of USA companies (and the individuals within them hoping to advance their careers) have simply settled for suboptimal solutions and/or gotten ripped off by unscrupulous software peddlers.
Thus, Dr. Clark decided to write this book, which teaches the nuts and bolts of such algoritms. As for Dr. Clark, he has multiple technical and business degrees from top-notch institutions, and has held senior staff and executive positions at blue-chip companies. He has also served as a Full Professor and aurhored dozens of academic articles in top journals. Besides many media appearances, he has been quoted in leading sources like FORTUNE magazine and has written more than a dozen books, with multiple best sellers, under the names Alan Bruce Clark PhD and Christian Bruce Clark PhD.
For more than four decades, he built (and taught numerous college students how to construct) AI and ERP forecasting systems, as evidenced by the stories (all his own) on the PremiereBusinessExperts.com site that he single-handedly built. The result is that after you read and work through the exercises in this book you should be able to not only eliminate the high purchase costs of forecasting programs but, more importantly, prepare, using simple spreadsheets, much more accurate forecasts than those of the expensive alternatives. This is especially the case when one realizes AI's 30% rule stating that "AI should handle 70% of a task, leaving the human focus on the remaining 30% that requires critical thinking, decision-making and oversight."
While there are many ways in which forecasting can be performed, they quintessentially rely on either judgmental (e.g., rules-of-thumb or "heuristic guestimates") or analytical (e.g., regression or time series) approaches. Further breaking these down leads to (1) Trend, (2) Time Series, (3) Causal, (4) Regression and (5) Judgmental analyses. However, multiple caveats (i.e., warnings) and problems exist with many of the approaches other than the one which will be the focus in this book.
The easily implemented judgmental methods, for instance, are often "highly political." For example, sales reps fearing they will lose their jobs, if they do not give high estimates will inflate their predicitons, while those believing their bonuses will be higher if they low ball their predictions will do exactly that.
As for many analytical approaches, they rely on variables that have, in essence, "already been forecast" or found by conducting a marketing study. Moroever, there are several different time series methods but there is just one, which is seemingly the most heavily relied upon by the leading Manufatturing, Marketing Research, Retailing, Service and Wholesaling companies. This is the one that will be the focus of this book.
Once you read this book and perform the spreadsheet exercises you will know how to prepare baseline forecasts, as well as handle seasonality, day of week effects, competitve influences, holidays, key customer demands, Leap Years, product and sales rep differences, promotional and post-promotional impacts, etc. You will even learn how to predict the sales of never before made products by combining the attributes of existing goods (or services) in unique ways, prepare "reasonability defaults" and develop confidence intervals (i.e, which show the upper and lower bound ranges for your forecasts), etc.
As a result of your buying this book and recommending it to others, you and they will be able to easily build sytems that outperform anything you can purchase and more importantly dranaticially improve bottom-line profits. While this book provides realistic examples for you to work through, it also shows you very simple methods of handling issues/concerns/problems that do not require you to have advanced statistical training. Nevertheless, the skills you develop will PROVE YOUR GENIUS ABILITIES WARRANTING THE HIGHER EARNINGS YOU SHOULD RECEIVE, due to your building robust systems, using only spreadsheets, which outperform the AI and ERP programs being sold at exceptionally high prices.
Easily Build Forecasting Systems: Avoid Costly AI & ERP Programs!
Just about everyone forecasts. If you will be hosting a Super Bowl party, you will need to predict the quantities of foods and beverages to buy. More critically, businesses need to predict their needs for raw materials, supplies, labor, storage space, demand for their products, etc. To better plan resource needs, 74% of the companies surveyed, by the American Marketing Association, were found to use formal forecasting systems, with Enterprise Resource Planning (ERP) and Artificial Intelligence (AI) models, accounting for 92% of successes.
Yet, in 2026, the average price, of such programs for small firms, was $10,000/user annually for a 5-year commitment. In mid-sized-businesses, initial implementation costs soared from $150,000 to $750,000, and at large entities to $15+ million annually. The result has been that over 25% of USA companies (and the individuals within them hoping to advance their careers) have simply settled for suboptimal solutions and/or gotten ripped off by unscrupulous software peddlers.
Thus, Dr. Clark decided to write this book, which teaches the nuts and bolts of such algoritms. As for Dr. Clark, he has multiple technical and business degrees from top-notch institutions, and has held senior staff and executive positions at blue-chip companies. He has also served as a Full Professor and aurhored dozens of academic articles in top journals. Besides many media appearances, he has been quoted in leading sources like FORTUNE magazine and has written more than a dozen books, with multiple best sellers, under the names Alan Bruce Clark PhD and Christian Bruce Clark PhD.
For more than four decades, he built (and taught numerous college students how to construct) AI and ERP forecasting systems, as evidenced by the stories (all his own) on the PremiereBusinessExperts.com site that he single-handedly built. The result is that after you read and work through the exercises in this book you should be able to not only eliminate the high purchase costs of forecasting programs but, more importantly, prepare, using simple spreadsheets, much more accurate forecasts than those of the expensive alternatives. This is especially the case when one realizes AI's 30% rule stating that "AI should handle 70% of a task, leaving the human focus on the remaining 30% that requires critical thinking, decision-making and oversight."
While there are many ways in which forecasting can be performed, they quintessentially rely on either judgmental (e.g., rules-of-thumb or "heuristic guestimates") or analytical (e.g., regression or time series) approaches. Further breaking these down leads to (1) Trend, (2) Time Series, (3) Causal, (4) Regression and (5) Judgmental analyses. However, multiple caveats (i.e., warnings) and problems exist with many of the approaches other than the one which will be the focus in this book.
The easily implemented judgmental methods, for instance, are often "highly political." For example, sales reps fearing they will lose their jobs, if they do not give high estimates will inflate their predicitons, while those believing their bonuses will be higher if they low ball their predictions will do exactly that.
As for many analytical approaches, they rely on variables that have, in essence, "already been forecast" or found by conducting a marketing study. Moroever, there are several different time series methods but there is just one, which is seemingly the most heavily relied upon by the leading Manufatturing, Marketing Research, Retailing, Service and Wholesaling companies. This is the one that will be the focus of this book.
Once you read this book and perform the spreadsheet exercises you will know how to prepare baseline forecasts, as well as handle seasonality, day of week effects, competitve influences, holidays, key customer demands, Leap Years, product and sales rep differences, promotional and post-promotional impacts, etc. You will even learn how to predict the sales of never before made products by combining the attributes of existing goods (or services) in unique ways, prepare "reasonability defaults" and develop confidence intervals (i.e, which show the upper and lower bound ranges for your forecasts), etc.
As a result of your buying this book and recommending it to others, you and they will be able to easily build sytems that outperform anything you can purchase and more importantly dranaticially improve bottom-line profits. While this book provides realistic examples for you to work through, it also shows you very simple methods of handling issues/concerns/problems that do not require you to have advanced statistical training. Nevertheless, the skills you develop will PROVE YOUR GENIUS ABILITIES WARRANTING THE HIGHER EARNINGS YOU SHOULD RECEIVE, due to your building robust systems, using only spreadsheets, which outperform the AI and ERP programs being sold at exceptionally high prices.
Yet, in 2026, the average price, of such programs for small firms, was $10,000/user annually for a 5-year commitment. In mid-sized-businesses, initial implementation costs soared from $150,000 to $750,000, and at large entities to $15+ million annually. The result has been that over 25% of USA companies (and the individuals within them hoping to advance their careers) have simply settled for suboptimal solutions and/or gotten ripped off by unscrupulous software peddlers.
Thus, Dr. Clark decided to write this book, which teaches the nuts and bolts of such algoritms. As for Dr. Clark, he has multiple technical and business degrees from top-notch institutions, and has held senior staff and executive positions at blue-chip companies. He has also served as a Full Professor and aurhored dozens of academic articles in top journals. Besides many media appearances, he has been quoted in leading sources like FORTUNE magazine and has written more than a dozen books, with multiple best sellers, under the names Alan Bruce Clark PhD and Christian Bruce Clark PhD.
For more than four decades, he built (and taught numerous college students how to construct) AI and ERP forecasting systems, as evidenced by the stories (all his own) on the PremiereBusinessExperts.com site that he single-handedly built. The result is that after you read and work through the exercises in this book you should be able to not only eliminate the high purchase costs of forecasting programs but, more importantly, prepare, using simple spreadsheets, much more accurate forecasts than those of the expensive alternatives. This is especially the case when one realizes AI's 30% rule stating that "AI should handle 70% of a task, leaving the human focus on the remaining 30% that requires critical thinking, decision-making and oversight."
While there are many ways in which forecasting can be performed, they quintessentially rely on either judgmental (e.g., rules-of-thumb or "heuristic guestimates") or analytical (e.g., regression or time series) approaches. Further breaking these down leads to (1) Trend, (2) Time Series, (3) Causal, (4) Regression and (5) Judgmental analyses. However, multiple caveats (i.e., warnings) and problems exist with many of the approaches other than the one which will be the focus in this book.
The easily implemented judgmental methods, for instance, are often "highly political." For example, sales reps fearing they will lose their jobs, if they do not give high estimates will inflate their predicitons, while those believing their bonuses will be higher if they low ball their predictions will do exactly that.
As for many analytical approaches, they rely on variables that have, in essence, "already been forecast" or found by conducting a marketing study. Moroever, there are several different time series methods but there is just one, which is seemingly the most heavily relied upon by the leading Manufatturing, Marketing Research, Retailing, Service and Wholesaling companies. This is the one that will be the focus of this book.
Once you read this book and perform the spreadsheet exercises you will know how to prepare baseline forecasts, as well as handle seasonality, day of week effects, competitve influences, holidays, key customer demands, Leap Years, product and sales rep differences, promotional and post-promotional impacts, etc. You will even learn how to predict the sales of never before made products by combining the attributes of existing goods (or services) in unique ways, prepare "reasonability defaults" and develop confidence intervals (i.e, which show the upper and lower bound ranges for your forecasts), etc.
As a result of your buying this book and recommending it to others, you and they will be able to easily build sytems that outperform anything you can purchase and more importantly dranaticially improve bottom-line profits. While this book provides realistic examples for you to work through, it also shows you very simple methods of handling issues/concerns/problems that do not require you to have advanced statistical training. Nevertheless, the skills you develop will PROVE YOUR GENIUS ABILITIES WARRANTING THE HIGHER EARNINGS YOU SHOULD RECEIVE, due to your building robust systems, using only spreadsheets, which outperform the AI and ERP programs being sold at exceptionally high prices.
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Easily Build Forecasting Systems: Avoid Costly AI & ERP Programs!
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Easily Build Forecasting Systems: Avoid Costly AI & ERP Programs!
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Product Details
| ISBN-13: | 9781967287086 |
|---|---|
| Publisher: | Leading Insights |
| Publication date: | 12/12/2025 |
| Pages: | 70 |
| Product dimensions: | 7.00(w) x 10.00(h) x 0.15(d) |
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