Announcing ChefQuant – A Practical Guide to Data Analysis and Modeling for Restaurant Owners, Managers and Executive Chefs

Orlando, FL, October 05, 2016 --(PR.com)-- Sid Som, the author of popular info sites like HomeQuant, TownAnalyst and LocValu, is pleased to announce the availability of his newest e-book, ChefQuant, on Amazon.com. It’s a practical guide to data analysis and modeling for restaurant owners, managers and chefs.

This book will teach the readers the issues and techniques that are rarely found in textbooks and courses offered by professional institutions. It covers such hands-on chapters as location planning, demographic analysis, menu planning, pairing wines, sales analysis and rewards promotion, profitability analysis, seasonality to year-round business, alternative capital planning and real estate strategies, re-steadying business plans, etc. to help make more informed decisions. While this book is intended for restaurant owners and executive chefs, it could be very useful for anyone planning to start a non-dining retail business as well. People starting out as general financial and statistical analysts could make use of it as a primer, while business and economics professors can recommend it for the case studies.

While some restaurant review sites have gained tremendous popularity amongst consumers and media folks, they do not necessarily help the restaurant owners in making any meaningful operational or strategic decisions as those surveys do not constitute scientific polling, thus the underlying atomic data are generally unsuitable for any consequential statistical analysis or econometric modeling. Additionally, such surveys are usually few and far between for the smaller outfits and start-ups.

The primary objective of this book is to educate the owners and managers of independent restaurants as to how to apply a set of easy to use yet highly scientific methods to analyze and model the right type and amount of data. Given the highly diverse nature of restaurants and the general ease of data collection on their part, this book therefore focuses more on analyzing and modeling data and forecasting outcomes than on standard data collection methods, with the exception of specialized events like demographics, location and seasonality.

Data collection is generally a simpler process for restaurants than many other types of businesses. Each time the cash register rings, an atomic sales data is created. Of course, sales data alone does not provide a sound basis for technical analysis. They have to be properly complemented with the satisfaction data. A few straight forward survey questions immediately following the sales provide the feedback loop leading to enormously powerful and minable technical data. Then, by meaningfully connecting and mining the combined sales and satisfaction data, independent establishments may arm themselves with the knowledge that is utterly germane to informed and intelligent decisions.

Instead of writing the book in the form of a traditional text book, the author used a storyline to communicate with the readers, thus making it a fun experience as a whole, rather than forcing them into a black box and asking them to figure things out. To make the experience even more palatable, all mathematical equations and formulas have been steered clear of. While this is not a science fiction, this book additionally proves that science and fiction could be seamlessly married for maximum synergy.