Abstract
The paper reviews the published literature related to six-sigma implementation for information technology. The methodology involved is the review study of eight papers related to implementation of six-sigma from renowned database searches such as Google Scholars and ProQuest. The review includes results from various IT environments such as help desk, internet, software, website, and enterprise information system. The paper found that six-sigma methodology is implemented successfully in the target areas.
Introduction
Six-sigma is a management approach that focuses on quality improvement of diverse aspects such as profit, efficiency, and speed within the working environment of an enterprise.
Beginning in the manufacturing industry, the approach gradually made its way into other industries as enterprises realized the importance of enhancing efficiency. At present, the methodology is widely implemented in both manufacturing and service industries for their IT systems.
Information technology and six-sigma implementation
The value of IT in six-sigma methodology derives from its concepts and tools. In fact, researchers point out that a successful six-sigma methodology in IT environment involves many concepts, tools, and principles (Hsieh, Lin & Manduca, 2007). Effective integration of these elements leads to the results expected from six-sigma project such as customer satisfaction and waste reduction.
In essence, this means that six-sigma methodology involves the clear understanding of the various processes an enterprise depends on for success and finding solutions to the problems therein. A six-sigma initiative is therefore a systematic methodology whose functions filter through all operative stages and environments of an enterprise.
Perhaps the framework that works best is DMAIC (defines, measure, analyze, improve and control). Evidently, the roadmap embraces the themes of organizations strategic visions that eventually lead to success. The framework meets the six-sigma goals of connecting operative functions and Information System management to customer needs (Hsieh, Lin & Manduca, 2007).
The six phases assist the management to avoid overlooking the factors that affect the quality of target aspects. When the improvement goals are the central focus, six-sigma initiatives can be applied in IT environment successfully.
Six-sigma availability management of information technology
As the importance of information systems and data security became prevalent, IT gained significance in the service industry. Hence, availability management with six-sigma was vital especially for security agencies like the Office of the Chief Technology Officer (OCTO).
Apart from data security, Bigio, Edgeman and Ferleman (2004) highlighted other deficiencies within the information systems of OCTO that could have resulted into inconveniences and loss of integrity. Six-sigma methodology becomes the ultimate solution for improving system performance particularly availability management of information technology.
However, the DMAIC roadmap for OCTO’s six-sigma methodology requires a focus on specific elements of the IT systems such as frequency and duration deficiencies. The define phase emphasizes on the assessment of the system parameters that are concerned with availability management as well as developing solutions to the issues concerned. The business focus necessary for this initiative left the agency with no other choice, but to consider its representatives as the ‘customers’ (Bigio, Edgeman & Ferleman, 2004).
The DMAIC measure phase involved two standard surveys on the maturity practices within the Availability Management context. The effort ensures that any shortcoming that arises from the weaknesses of the previous system is addressed fully. The DMAIC analyze phase settled on the results from the two surveys which were harmonized with the responses from OCTO experts. Such an endeavor reveals variations in various areas of availability management.
As for the areas that needed continuous improvement, OCTO should focus on customer satisfaction. Therefore, as Bigio, Edgeman and Ferleman (2004) recommended, benchmarking was to be an important tool for measuring, improving, and redefining internal processes in OCTO because the environment allowed.
Six-sigma for internet application development
The implementation of six-sigma methodology for internet development revolves around its rapid changes that fail to match with customer expectations and budgets. Today, the internet demands quality management more than any other time in history. Competition within the industry is on the increase. In addition, internet environment and customers are widening. As a result, the effectiveness of the six-sigma approach is crucial to organizations operating in this vulnerable online environment.
According to Harrington & McNellis (2001), the implementation of six-sigma for internet application development is quite demanding. It may require thorough investigation and identification of the problematic areas. Yet, the most prevalent areas are product issue, customer dissatisfaction, cycle time, and excessive turnover rate.
Since the workers use the six-sigma model in developing other initiatives, there is a dire need to bring into line its cycles with project management life cycle. In this way, the business strategy aligns with important business requirements such as finances and customer satisfaction.
The DMAIC define stage is aligned with project selection and initiation while the DMAIC measure stage maps to process review and planning. DMAIC analyze phase maps to execution while DMAIC improve and control stages map to monitoring and closeout respectively.
It can be argued that internet services would require a series of stages that would lead to satisfactory completion. Hence, the rapid changes affecting the internet environment compel organizations to implement six-sigma initiatives that are reflected in other project management tools in order to achieve acceptable service quality.
Six-sigma for IT call center
The fact that IT service is a competitive field compels companies to review their competitive positions continuously; perhaps through initiatives that ensure quality improvement. Hence, the use of data and benchmarking tools are paramount. Six-sigma implementation supports this requirement. No wonder the company in this case opted to focus its project activities on this approach. As the benchmark data revealed the weak points, the DMAIC focus was on increasing customer satisfaction (Hallowell, n.d).
The DMAIC define phase entailed three responsibilities – project charter, customer requirements, and high-level process map (Hallowell, n.d). These outlined to the project team the benchmark findings as well as setting the goals for the endeavor. The DMAIC measure phase entails the definition of performance variables and collection of current information from the call centers with the aim of comparing project parameters with those of the industry.
The DMAIC analyze phase settles on establishing the actions that would respond to the deficiencies created by the variation between the current measure parameters of the call centers and benchmark results. The improve phase was to direct the project team towards implementing the most effective action plans as postulated by the critical six-sigma parameters for improvement. Team consolidation, review of the improved services, and development of the control plans takes on during the DMAIC control phase.
Six-sigma in software quality
Software development is not understood fully in terms of good quality and customer satisfaction. In fact, there are divided views on the application of six-sigma doctrine within the software context. Hong and Goh (2003) highlighted several aspects of resistance to the adoption of six-sigma doctrine including the distinctive nature of software development.
While the distinctive nature may be a theoretical challenge to the application of six-sigma doctrine, the fact remains that the software process is aimed at meeting some customer expectations. Lack of a defined process does not ward off legal responsibility, and a strong competitive position needs to be maintained by meeting those expectations. Hong and Goh (2003) explained how this could be achieved by implementing six-sigma approach.
Software projects are characterized by lifecycles that require continuous improvement. Likewise, the lifecycles should be characterized by projects like six-sigma that ensure the achievement of this goal. For the case under study, the DMAIC define phase is aimed at ensuring a clear understanding of customer specifications. The DMAIC measure phase determines the variations between the current performance and the expected output.
During the DMAIC improve phase, deficiencies are prioritized and action plans identified. The improve phase allows for the implementation of the action plans. Monitoring and reviewing of the process performances occur during the control phase. For the successful performance of the initiative, the distinctive nature of the software process is not overlooked. Software opportunities and defects are identified in order to allow for the calculation of six-sigma performance indicators.
Enhancing enterprise information integration using six-sigma
Continuous improvement is vital when enhancing enterprise information integration. Moreover, companies make an effort to lower costs and increase productivity through continuous improvement of their enterprise systems. Therefore, six-sigma doctrine plays a critical role in the integration process.
However, it must take into account the functions that underlie such as maintaining records and providing real-time information. Chau, Liu, and Ip (2009, p.539) have the opinion that the integration of every quality improvement team must be mapped against the six-sigma project in order to achieve results.
In the presence of strong management and leadership, the DMAIC process starts with the consolidation of the target performance indicators. The consolidation brings about the understanding of the process parameters pertinent to the expected results. Next, determination of variations in the performance indicators allows for the prioritization of the quality deficiencies.
Customer responses and complains become the focus of the DMAIC measure phase. Defects within the enterprise system are identified during the analyze phase prior to the implementation of the prioritized quality improvement actions. Finally, there is the monitoring of the improvement projects as well as maintenance through pertinent initiatives such as staff training and acquisition of new technologies.
Six-sigma for website response time
Website response is a key factor that affects customer satisfaction especially in the service industry. For the case of the company experiencing slowness and loss of transaction in the online system, implementation of six-sigma project proves to be very effective. The first phase of the six-sigma project is to understand the target parameters of the system and define the project metrics and goals that can lead to achieving the expected performance of the system.
As Kirzhner and Vikhman (2006) note, this can be achieved by monitoring the current performance of the system about the issues surrounding slow response time. To avoid creating new problems, the project moves towards measuring the actual level of defects arising from the system. Now, a critical review of the system configuration and monitoring of performance characteristics leads to full confirmation of the system defects.
The analyze stage entails refining the performance metrics that have greater impact on the customers and referring them to relevant weaknesses of the system. Possible solutions to the problems are identified and implemented on the system during the improve phase. The control phase is about monitoring the improved system performance and making relevant changes as the customer base widens.
Reducing help-desk turnaround time
Like many other IT areas, the help desk is vital to the performance of an enterprise. Therefore, high help-desk turnaround time (TAT) is unacceptable. As a result, the company in the case study experienced higher costs and low productivity, hence needed to adopt six-sigma approach to tackle the issue.
Like the case above, Stansbury (2005) highlights that the implementation of the approach begun by reviewing the whole environment to identify the problematic areas as pertaining to the help desk. Most important for this define phase is to identify the impact of all stakeholders on help-desk TAT.
Data from the analysis of the scenario allows for the calculation of the six-sigma performance indicators. During the analyze phase, the information gathered is filtered with reference to the indicators and action plans identified. Next, the best corrective actions such as improving the hardware and software, upgrading client server, and developing SOPs are implemented. The schedule and tasks to monitor and improve the corrective actions form the control phase of the six-sigma process.
Conclusion
The research on using six-sigma in information technology application is mature. Six-sigma has been beneficial to service concerns particularly for information technology. It is evidently advantageous to various IT fields with little changes as per the service needs.
The DMAIC roadmap offers every area the opportunity to consolidate the IT system requirements with the operative functions and business strategic vision. It is suggested to research on other areas in IT technology for implementation of six-sigma where projects consolidation is a challenge.
References
Bigio, D., Edgeman, R. L. & Ferleman, T. (2004). Six-sigma availability management of information technology in the office of the Chief Technology Officer of Washington, DC. Total Quality Management, 15(5/6), 679-687.
Chau, K., Liu, S. & Ip, W. (2009). Enhancing enterprise information integration using six-sigma. Total Quality Management, 20(5), 537-546.
Hallowell, D. L. A six-sigma case study-tutorial for IT call center. Web.
Harrington, H. J. & McNellis, T. (2001). Six-sigma for internet application development. Software Quality Professional, 4(1), 7-18.
Hong, G. Y., & Goh, T. N. (2003). Six-sigma in software quality. The TQM Magazine, 15(6), 364-373.
Hsieh, C., Lin, B. & Manduca, B. (2007). Information technology and six-sigma implementation. The Journal of Computer Information Systems, 47(4), 1-10.
Kirzhner, I. & Vikhman, M. (2006). Website response time. ISixSigma Magazine, 2(5), 1-7.
Stansbury, W. (2005). Reducing help desk turnaround time. ISixSigma Magazine, 1(2), 1-7.