Jonah In The Goal

After a run in with an old physics teacher, Alex Rogo discovers new meaning to the management terms throughput, inventory and operational expense during his quest to turn his plant around. Jonah, his teacher, defines throughput as “the rate at which the system generates money through sale” (Goldratt and Cox). His definition of throughput catches Rogo off guard as it is different from the version he learned. Operations and Supply Chain Management, defines throughput as the “output rate that the process is expected to produce over a period of time”. Jonah explains the reason for this difference is that if the plant is manufacturing products but not selling them they shouldn’t count it as throughput. This I find useful as it adds more meaning
While throughput could signify high efficiency of the production line, it does not mean the company is profiting. By using the term as it as defined in The Goal, throughput would be showing the rate in which the production line is producing sales and therefore more clearly defines potential successes. Jonah then defines inventory as, “all the money that the system has invested in purchasing things which it intends to sell” (Goldratt and Cox). This is different from the traditional sense of inventory, as it is normally defined as the total materials, work in process products and finished goods within a business they intend to sell. The reason Jonah’s definition is useful is it not only considers the product but also the machinery and other investments. For example, in the book this definition changes Rogo’s outlook on investments such as the robots since they could potentially be sold off in the future. Lastly, Jonah defines operational expense as, “all the money the system spends in order to turn inventory into throughput.” (Goldratt and Cox). This definition of operational expense is the most similar to the traditional definition of the
He describes dependent events as, “a series of events, that must take place before another can begin…the subsequent event depends upon the ones prior to it” (Goldratt and Cox). This sounds simple, but depending on the situation, the series of events could have a large variation of subsequent reactions. For example, my cousin works as a professional dog walker. She schedules several client’s dogs to take on walks throughout each day and on a weekly basis. Each client’s dog walk depends on the walk beforehand since the next walk cannot be performed until the last walk is finished. But while walking a dog many uncontrollable variables arise, such as the dog going to the bathroom or the pace of the walk. This is when the phenomena of statistical fluctuations come into play since the different variables lead to fluctuations in day to day operations that need to be taken into consideration when planning walks. Rogo describes the combination of statistical fluctuations and dependent events as when “the big deal occurs” (Goldratt and Cox). The different variables like pace and number of bathroom breaks play a major role in the time each walk takes. Before she schedules each dog’s walk, she must accurately estimate the time of each walk so to not make overlapping walks in her schedule. However, if she overestimates the time of each walk, she would be lowering her