Among the tools analyzed by the author in the textbook, I find graphic tools as the most substantial process improvement tools. There are varieties of graphic tools including bar charts, mapping, histogram, control chats, matrix analysis, scatter diagrams and statistical process control among other tools (Sobek & Jimmerson, 2004). Towards process improvement, these graphic tools are essential for giving the desired outputs hence effective for process improvement. Furthermore, choosing one of the graphic tools identified above would provide a significant approach for presenting different stages involved in a process.
Drive is among the tools discussed but the author in the textbook provided. I find it an effective tool necessary for creating a good problem-solving framework. The drive is an acronym that stands for define, review, identify, verify and execute (Sobek & Jimmerson, 2004). In order to solve a problem in any given environment, it must be defined and reviewed then its solution needs to be identified, verified and then executed. The terms provided in the acronym as substantial for creating a solution towards a given problem. To implement this tool, the user needs to define the scope of the problem and come up with effective strategies that will be executed to solve the identified problem. This will follow a review of the current situation and understanding of the environment then execute the solution.
Delegate your assignment to our experts and they will do the rest.
Building and using models
Among the effective business strategies that a firm can execute in order to both monitor/ control changes in the business process and predict future business performance include analyzing existing process data predicting future process performance (Kuhn, 2008) . Through analyzing the existing process data, a firm’s management is assured of successful growth since these strategies will help in the formulation of algorithms necessary for the growth of the firm. Predicting future process performance will help in the identification of different statistical correlations in the firm. In return, the firm managers will be able to predict the future of the firm by studying the correlations between the variables.
In order to monitor changes in the business process, a firm’s management should have the ability to control, manage and improve the process (Kuhn, 2008) . Therefore, the identified strategies will be responsible for the management and improvement of the process. Other strategies include measuring the impacts of process changes in order to identify the effectiveness of the currently executed strategies. Moreover, predicting future process performance can be significant in predicting future business performance. Lastly, monitoring changes in the business process can be effective through a deep understanding of the processes.
One-factor-at-a-time (OFAAT) and Design of Experiment (DOE)
Each of the identified approaches has numerous advantages and disadvantages as follows. One-factor-at-a-time (OFAAT) consists of intuition, trial and error, guesswork and the resulting experience. The resulting experience changes OFAAT while the other elements remain static. OFAAT approach requires fewer resources as the compared design of the experiment. The main disadvantage of OFAAT is lack of information to mislead the optimal circumstances of the process making the interaction between the causes immeasurable. Moreover, the approach is time consuming when testing one factor at a time. Lastly, the estimation of the factors is less effective since each trial is run through comparing the detected results with the prior outcomes (Marksberry & Parsley, 2011).
On the other hand, Design of experiment is necessary for determining factors that facilitate adjustments in the results and predict them in a coherent statistical system. In addition, this approach is significant in instances where traditional analysis, stimulations, and verifications are challenging to obtain. Unlike OFAAT, Design of the experiment changes multiple variables at a time. The main disadvantage of the DOE approach is that it strongly relies on statistics and mathematical systems hence making it more complicated. In addition, due to the lack of significance in variables, it is hard to distinguish optimum settings (Marksberry & Parsley, 2011).
On my point of view, Design of the experiment would be an effective approach to obtain a competitive business process. This approach is substantial since it recognizes the interface between factors used for a given experiment and it saves time through operating multiple variables at a time.
References
Kuhn, M. (2008). Building predictive models in R using the caret package. Journal of statistical software , 28 (5), 1-26.
Marksberry, P., & Parsley, D. C. (2011). Managing the IE (Industrial Engineering) Mindset: A quantitative investigation of Toyota's practical thinking shared among employees. Journal of Industrial Engineering and Management (JIEM) , 4 (4), 771-799.
Sobek II, D. K., & Jimmerson, C. (2004). A3 reports a tool for process improvement. In IIE Annual Conference. Proceedings (p. 1). Institute of Industrial and Systems Engineers (IISE).
