The nature of business is that of uncertainty. In many instances businesses must forecast or project many unknown factors affecting their underlying business operations. The impact of globalization has created an even more uncertain period in which business must now operate in. Aspects that pertain to one geographic region, due primarily to globalization, now create systemic effects in other regions. As such, management, through the use of data must be able to properly ascertain or predict these occurrences to better insulate their businesses. As seen by the recent financial crisis in 2008, quantitative techniques are vitally important in helping to prevent unwarranted bankruptcy or financial lose. In particular, quantitative quality management techniques can help diminish or abate many of the negative influences embedded within the business environment. Techniques such as linear programming, control charts, and fishbone diagrams all help management make better informed decisions (Dmitris, 2001). These decisions, when combined with other factors, can help businesses navigate an otherwise competitive marketplace. In fact, through the use of quantitative quality management techniques, society benefits through increase company efficiencies and fewer errors.
The IT organization in which I work is prime example of how quantitative quality management techniques provide a foundation by which management can make better informed decisions. Service is very vital component within the IT organization in which I work. Our organization is predicated on providing strong customer service to each client. It is through this service component that allows our company to command premium pricing for our products and services. With the quality of service, the value proposition of the organization would not be as compelling. As such, management will need a mechanism by which they can management and subsequently enhance the service component of the business. Quantitative quality management provides a prime mechanism by which to do so (Deming,, 1975). A good quality management approach should provide warning signs early in the project and not only towards the end, when the options available are limited. When conducted properly QQM can provide for intervention early within the process. For this, it is essential to predict values of some parameters at different stages in the project such that controlling these parameters in project execution will ensure that the final product has the desired quality. This concept applies to service quality and in subsequent paragraphs, invoicing. If these predictions can be made, then the actual data during the execution of the process can be used to judge whether the process has been effectively applied. These standards are critical in regards to QQM. Predictive analytics are data management is integral aspects within the QQM process. Within the IT organization use of control charts provides instrumental data in regards to service quality. Control charts are very useful in regards to time series data. For example, management may want to view response times for customer complaints or issues (Shewhart, 1939). Management may also want to see the time between an actual claim filed and the time in which the claim is resolved for the customer. Likewise, management may want to determine the length of time customers remain on hold before an actual representative speaks with them. Control charts can provide useful information in regard to the variations of wait or service times. For example, if analysis of the control chart indicates that the process is currently under control, then management will not need to make alterations or corrections to the process. However, if analysis indicates that the process is out of control, then management can make informed decisions in regards to staffing, or system improvements. If the chart indicates that the monitored process is not in control, analysis of the chart can help determine the sources of variation, as this will result in degraded process performance. In addition, data from the process can be used to predict the future performance of the process. This will be useful to management, as the IT business is generally cyclical. Many purchases and subsequent issues arise near the latter part of the year as consumers take advantage of discounting. In addition, corporate budjects are usually approve for the subsequent year, which allows for increased purchases. Realzing this information, management, through the use of control charts, can predict performance in regards to service quality. They then can react through the use of increased staffing, increased technology use or other mechanisms (Tague, 2004).
Another example of management use of QQM is demonstrated through the actual production of software within the organization. There are two key aspects to quantitative quality management. These two aspects are the actual setting of a quantitative quality goal, and then managing the software development process quantitatively so that the quality goal is met. Management often has a short-term view within the IT organization. However, managing the process quantitatively requires that intermediate goals are set for different stages in the project. These short, intermediate, and long-term goals will often ensure that the quality goal is met. These intermediate goals can then be used for quantitatively monitoring the execution of the project. A fishbone diagram can help in ascertaining the problem areas of production that might occur . The company uses the fishbone diagram to better aid management in pinpointing the exact cause of a defect in production (Mandel, 1969).
To produce high quality software, the final software should have as few defects as possible. As such a fishbone diagram helps management to locate the defects and correct them in a timely fashion. The task of quality management is to plan suitable quality control activities, and properly execute and control these activities such that most of the defects are detected before the software is delivered. This can be a daunting task as thousands of product is produced each day. Through the fishbone diagram management can better prepare and locate defects irrespective of their origins. To further improve the control and provide warnings early, the macro-level controls are complemented with activity-level control using statistical processes. For activities like reviews and unit testing, which are often based on past data, control charts have been built for key characteristics like defect density within the organization. As each review or unit testing is completed, the results are compared against the control limits. Corrective and preventive action is then taken if the data is out of limits. The fishbone diagram is then used to help detect the actual point of defect. Once this occurs, management is then able to take corrective action.
Finally, the last use of the QQM process within the IT organization comes from linear programming. Linear programming is used commonly within the technology sector. Large companies such as IBM and Google use linear programming for predictive analytics. The company I work for uses it to make better informed decisions internally. Linear programing is used primarily to help generate the largest amounts of profit with the smallest amount of costs. The company also uses linear programming to help minimize the overall costs associate with the production of its products and services (Alexander, 1998). Management in turn uses the information garnered from the results to make better informed decisions regarding the underlying business operations of the firm. For example, does the facility producing software need to be expanded? Does the company invoicing process cost to much to produce per person working? These are all questions in which the organization answers on a monthly basis. Through this process, the company allocates hours towards certain activities. During peek season for instance, linear programming can help ascertain the correct amount of staffing needs to produce to the greatest amount of sales volume. Management can then use this information to make hiring of layoff recommendations. Through the use of linear programming, the organization can decide if it wants to produce more product to meet demand, or will doing so hamper profit margins. In some instances, it is better to curtail production of a product even though it is in demand. Linear programming helps managers of the organization ascertain the appropriate time to increase production or when to curtail production. In combination with the control chart, and managing for defects (Bernd, 2006).
How well do you think the organization manages an uncertain future?
The IT organization in which I work does an outstanding job of managing for the future. IT in particular is prone to the natural vicissitudes of the market in which it operates. Technology changes at such a rapid rate that the IT firm must constantly look towards the future. If not, the company's products, goods, and services could quickly become obsolete. As such, the company must monitor future trends which are often uncertain. The company has many processes and mechanisms in place to better ascertain an uncertain future. Many of these aspects pertain to the QQM process mentioned earlier. The future is always uncertain. The company does a great job of looking externally of what is on the horizon, while also taking subsequent action internally. For example, the company has taken advantage of the coming trends of cloud computing.…