Significance Of Quality Management System In Deutsche Telekom

Discussion

Quality management system involves processes, tools and framework to enhance the proper management of business operations. Quality management ensures improving working practices from production to delivery of products and services so that it meets the requirements and requires of the customer. Implementation of quality management processes makes the business environment productive and better place to work (Bacoup et al., 2018). It further removes unnecessary tasks and assists in waste and inventory management. This further helps the company in gaining customer satisfaction.

The report aims at examining the significance of quality management system in Deutsche Telekom and application of quality models and concepts for enhancing quality at the company. The report further demonstrates how quality management can be created in the company and lastly, key trends in quality management have been suggested to be implemented in Deutsche Telekom.

Deutsche Telekom is a German based telecommunication corporation founded in the year 1995 and headquartered in Bonn. It is the leading provider of telecommunication services in Europe. The company has secured 86^th position in the Fortune 500 list (Deutsche Telekom, 2022). The company operates through segments in countries like United States, Germany, Group services, system solutions and group headquarters.

Critical evaluation of the strategic importance of quality management within Deutsche Telekom

Deutsche Telekom is a telecommunication corporation which operates at several distinct locations. The factor determining success in the telecommunications business is the quality management system in place and how well it supports quality control. Other factors, including such data network, IT systems, and the commercial products, are also important (Deutsche Telekom, 2022). The emphasis is on adding quality processes in order to improve knowledge and transparency over user interactions. It also assists in the identification of opportunities for development and the delivery of services to satisfy the ever-increasing demands of customers (Ross 2017). By minimising cycle times and return rates, guaranteeing consistent delivery, reliability, and defect control, quality management software will assist Deutsche Telekom in demonstrating its dedication to product quality and delivering consumer experience.

Deutsche Telekom offers products like IPTV products and services, mobile communications, internet services, fixed network for business and corporate customers. This requires excellent service quality for ensuring that the operator’s performance is transparent and that customers have a high level of visibility (Quality management at Deutsche Telekom 2022). Deutsche Telekom is known for its quality and it is very vital for the company to implement effective concepts and models for supporting quality management inside the company. Having an effective quality management framework within organizational setting will help the company in producing fault free products and services, gain customer loyalty and trust, enhances brand reputation, impact bottom line of the company by generating more revenue and help in inventory and waste management (Aleksandrova, Vasiliev and Letuchev 2018). However, in order to achieve this objective, it is very vital to implement certain models and principles of total quality management in work culture.

Critical evaluation of the strategic importance of quality management within Deutsche Telekom

Following concepts and principles/models should be implemented inside Deutsche Telekom for supporting quality management inside the organization:

Concepts and models to support of quality management to enhance quality at the company

In recent years, the inclination towards quality has been acknowledged as a competitive advantage. As per prior research, organisations should concentrate on competitiveness in order to survive and thrive in the market. One of the competitive advantages is “quality,” which could be achieved by implementing important TQM concepts and models (Models, Techniques and Indicators of Quality Management 2022). Some of the effective concepts and models for Deutsche Telekom could be following:

Deming model and total quality management (TQM)

A Quality Management System (QMS) is a mechanism for formally documenting the various components expected to undertake a company’s strategies. A QMS enables the organization to document its numerous procedures and processes since policies have Particular objectives to meet (Obeidat et al., 2016). A QMS can also provide a formalised approach for an organisation to designate activities between divisions and processes.

TQM concepts include: employee commitment, customer focus, integrated system, process approach, process management, strategic planning, decision making, enhanced communication, continuous improvement, supplier quality management and more (Obeidat et al., 2016).

Deming model is a Part of TQM and it’s a constant cycle involved in quality management process. This involves logical sequence of four steps like Plan, do, check and Act. This is also known as Deming wheel because it results in continuous improvement of processes (Van Kemenade and Hardjono 2018). The PDCA cycle is used to implement a QMS, and it comprises of the four stages. The cycle allows the QMS to be reviewed and improved on a regular basis. The following is a description of the procedure that was followed. The QMS is initially created in accordance with the organization’s quality requirements and regulations.

Deutsche Telekom can implement this in the following manner:

Plan: The Company should plan at this stage for mapping out what needs to be done or any change to be implemented inside the company. This will help in analysing problems as well as opportunities to implement change, developing hypothesis, resources required and measures of success (Dahlgaard-Park, Reyes and Chen 2018).

Do: This stage is for testing hypothesis which is the proposed solution. This could be achieved by small and incremental stages as it will minimize disruption and resistance.

Check: After completion of trial, management must review and analyse the results of the change process. This will assist in evaluating the effectiveness of the process and allows possible revisions to the solution (Van Kemenade and Hardjono 2018).

Concepts and models to support of quality management to enhance quality at the company

Act: This stage will implement the plan and new processes will act as baseline for future processes.

Figure: Deming model

Source: (Dahlgaard-Park, Reyes and Chen 2018)

This is a platform created intentionally so that the organizations can learn from each other for improving continuously. Implementation of this model helps in gaining economic growth (Gabriela-Livia 2021). EFQM will support the leaders of the company in providing training, idea generation and sharing, and innovating with the help of the model.

This quality management model is aimed for long-term success by emphasising excellence, effectiveness, and sustainability. The principle of Total Quality Management (TQM) is the cornerstone of the EFQM Model. It comprises of a global framework of principles that enables businesses to effectively share information, regardless of the industries, nationalities, or life phases in which they are located (Akkucuk and Gencer 2017). It is divided into five enablers like: policy, people, leadership, Partnerships and processes and four results like: society, people, customer and key performance.

Figure: EFQM model

Source: (Akkucuk and Gencer 2017)

Six-sigma is a total quality management tool which assists in enhancing existing business operations by identification of defects in the products and services (Yadav and Desai 2016). The main objective is to streamline the production process for enhancing customer service.

Six-sigma involves fives phases known as DMAIC (extracted from reading materials). The steps involve:

• Defining the problems
• Measuring the main points of the existing processes
• Analysing the collected data
• Improving the existing process
• Controlling the process by eliminating defects.

Figure: Six-sigma

Source: (Yadav and Desai 2016)

Lean manufacturing is a tool that is based on the principle to maximize productivity while reducing waste in the production process. Deutsche Telekom can implement this to reduce billing errors, enhancing call quality, mobile network, reducing customers concerns, enhancing productivity of sales, enhancing internet quality and more (Sarria Yépez, Fonseca Villamarín and Bocanegra-Herrera 2017).

Figure: Lean manufacturing

Source: (Sarria Yépez, Fonseca Villamarín and Bocanegra-Herrera 2017)

This technique is focused on setting acceptable performance standards for various internal and external processes that may then be used to determine whether or not those processes can be upgraded further. The process measures internal processes like production, warehousing, inventory and other as well as external processes like sales, customer satisfaction, customer service and other (Sreedharan and Sunder 2018). This helps in formulating strategies and implementing it for continuous improvement.  The steps will include planning, analysing, integrating and taking action.

 

Figure:

Source: (Sreedharan and Sunder 2018)

This is a philosophy originated from Japan which aims at enhancing productivity by employee involvement and improving the workplace setting. It involves 5s namely:

• Seiri: means sorting
• Seiton: means organizing
• Seiso: means cleaning the place (García-Alcaraz, Oropesa-Vento and Maldonado-Macías 2017)
• Seiketsu-Seiketsu: means standardization
• Shitsuke: indicates self-discipline

Deming model and total quality management (TQM)

Figure: 5S of Kaizen

Source: (García-Alcaraz, Oropesa-Vento and Maldonado-Macías 2017)

This will assist the company in determining the extent at which resources are being utilized so that it prevents defects, poor quality and product failure. This method can be used to calculate the cost incurred during the production process and also products that fail to meet quality standards (Dimitrantzou, Psomas and Vouzas 2020). This is incorporated to understand in what manner quality impacts bottom line of the company. Four types of costs are internal and external cost, prevention cost and appraisal cost.

Figure: Cost of quality

Source: (Dimitrantzou, Psomas and Vouzas 2020)

Models/principles	Advantages	Limitations	References
Deming model/TQM	ü  Process improvement ü  Waste reduction ü  Staff development ü  Managing effective change ü  Staff engagement	ü  Resistance to change ü  Expensive process ü  High management and training cost ü  Demands strong leadership	Obeidat, B.Y., Hashem, L., Alansari, I., Tarhini, A. and Al-Salti, Z., 2016. The effect of knowledge management uses on total quality management practices: A theoretical perspective. Journal of Management and strategy, 7(4), pp.18-29. Dahlgaard-Park, S.M., Reyes, L. and Chen, C.K., 2018. The evolution and convergence of total quality management and management theories. Total Quality Management & Business Excellence, 29(9-10), pp.1108-1128. Van Kemenade, E. and Hardjono, T.W., 2018. Twenty-first century total quality management: the emergence paradigm. The TQM Journal.
EFQM	ü  Involves entire organization ü  Activates processes	ü  Dependant on acceptance ü  Abstract and complex	Gabriela-Livia, C., 2021, May. EFQM Excellence Model–European Foundation for Quality Management. In Proceedings of the 6th International Conference on Education Reform and Modern Management (ERMM 2021). Akkucuk, U. and Gencer, Y.G., 2017, April. EFQM Model and Sustainability of Organizations. In International Conference on Advances in Management Engineering and Information Technology.
Six-sigma	ü  Customer satisfaction ü  Cost reduction ü  Process improvement	ü  Increases overhead cost ü  create bureaucracy  ü  focuses on rigid processes	Yadav, G. and Desai, T.N., 2016. Lean Six Sigma: a categorized review of the literature. International Journal of Lean Six Sigma.
Lean manufacturing	ü  reduces lead time ü  enhanced product quality	ü  inconsistent delivery ü  failure of equipment	Sarria Yépez, M.P., Fonseca Villamarín, G.A. and Bocanegra-Herrera, C.C., 2017. Methodological model in the implementation of lean manufacturing. Revista Ean, (83), pp.51-71.
Benchmarking	ü  enhance company’s standards ü  enhance productivity	ü  dependency ü  lack of proper information ü  time taking	Sreedharan V, R. and Sunder M, V., 2018. Critical success factors of TQM, Six Sigma, Lean and Lean Six Sigma: A literature review and key findings. Benchmarking: An International Journal, 25(9), pp.3479-3504.
Kaizen	ü  enhance teamwork ü  achieves target ü  builds leadership skills ü  improve standards	ü  problems to be implemented in current systems ü  making change is difficult	García-Alcaraz, J.L., Oropesa-Vento, M. and Maldonado-Macías, A.A., 2017. Kaizen planning, implementing and controlling. Springer International Publishing.
Cost of quality (CoQ)	ü  enhanced sales ü  enhanced profit ü  customer satisfaction ü  market share	ü  defect in calculation ü  difficult to collect data	Dimitrantzou, C., Psomas, E. and Vouzas, F., 2020. Future research avenues of cost of quality: a systematic literature review. The TQM Journal.

To achieve the telecommunications company requirements for hardware, software, and services, there is a need for strong quality management standards. Through increasing visibility of service quality and user experiences, this will assist in addressing crucial service concerns (Khanam, Siddiqui and Talib 2016). It ensures compliance by streamlining processes in accordance with relevant regulatory requirements.

In order to create quality and align it with company’s objectives there is a need to implement quality standards inside Deutsche Telekom. Some of the suggested quality standards for the company are:

ISO 9000

ISO 9000 is a set of quality management standards which was created as a worldwide recognised benchmark for commercial and other organisations’ performance. ISO 9000 standards were developed to assist businesses in efficiently recording the quality system features that must be implemented in order to keep a quality system running smoothly (Javorcik and Sawada 2018). They’re being used in a growing number of businesses and industries.

In Telecommunication Company like Deutsche Telekom, it helps in fostering the system for protection and integrity of software, hardware and services. It further assists in defining suitable cost and performance-based metrics to monitor efforts and assess QMS implementation outcomes (Hoyle 2017). Improve consumer interactions through driving continuous improvement and Use the compliance evaluation procedure in the industry to its advantage.

ISO 9001: 2015

ISO 9000:2015 outlines the basic concepts and principles of quality management that apply all of the following principles to make the company achieve quality standards:

• It helps in organizing processes
• Enhance the efficacy of the processes
• Continuous improvement
• Product reliability is used to measure performance (Militaru and Zanfir 2016).
• Development and life-cycle management of software
• Specified service functions, like installation and engineering, have specific requirements.
• Standards for dealing with customer-supplier communications
• Data on quality measurement is reported to a centralized database.
• Documented information, scheduling, and determining process relations are all necessities for a QMS (Jasiulewicz-Kaczmarek 2016).
• The procedure of transporting a product to market, from design to delivery.

ISO 27701

Deutsche Telekom operates in telecommunication industry which necessitates data privacy and security of confidential information. This standard will help the company in addressing security concerns, maintain accurate data and privacy of its customers, accessibility of information to approved customers and maintains guidelines to collect client’s data and prevent unauthorized usage.

QMS components	Relevance to case organization	References
ISO 9000	ü  Helps in fostering the system for protection and integrity of software, hardware and services. ü  assists in defining suitable cost and performance-based metrics ü  Improve consumer interactions through driving continuous improvement	Hoyle, D., 2017. ISO 9000 quality systems handbook: increasing the quality of an organization’s outputs. Routledge. Javorcik, B. and Sawada, N., 2018. The ISO 9000 certification: Little pain, big gain?. European Economic Review, 105, pp.103-114.
ISO 9001:2015	ü  It helps in organizing processes ü  Enhance the efficacy of the processes ü  Continuous improvement ü  Product reliability is used to measure performance ü  Development and life-cycle management of software ü  Standards for dealing with customer-supplier communications ü  Data on quality measurement is reported to a centralized database.	Militaru, C. and Zanfir, A., 2016. The vision of new ISO 9000: 2015 standards. Knowledge Horizons. Economics, 8(1), p.131. Jasiulewicz-Kaczmarek, M., 2016. ISO 9000: 2015 quality management principles as the framework for a maintenance management system. Zeszyty Naukowe Politechniki Pozna?skiej. Organizacja i Zarz?dzanie.
ISO 27701	ü  Data privacy ü  Ensures security ü  Prevents unauthorized usage of customer’s data	Lachaud, E., 2020. ISO/IEC 27701 Standard: Threats and Opportunities for GDPR Certification. Eur. Data Prot. L. Rev., 6, p.194.

European foundation for quality management (EFQM)

In order to gain competitive edge, it is very significant for a company to understand and implement key trends prevailing in the industry. This wills help the company in upgrading its processes and staying ahead in the competition. As per the case study, The “Integrated Management System Policy” incorporates Deutsche Telekom’s quality control, environmental protection, and occupational health and safety standards (IMS). This implies that it is committed towards quality management. However, there are many key trends in quality management that need to be adopted by the company in order to support its business objectives. Some of the trends are as follows:

Quality 4.0 offers a multitude of options for automating certification. Modern day Technology Company offers highly flexible, computerized, and networked QMS systems, as well as validating automation tools (Carnerud 2018). Companies should evaluate their present compliance methods and practices to see where they can make changes.

Quality 4.0 is more than technology ad it is a method to be used by quality experts for managing quality with the help of digitalized tools and also to examine in what to way to implement them for attaining excellence. Quality experts might transform their roles from regulators to navigators through speaking the digital language and constructing the case for quality in times of disruption. Systems and processes would be disrupted, requiring the training of the next generation of workers in order to implement new procedures and tactics (Quality 4-0 | ASQ, 2022). For digital change to be sustainable, quality must be considered at the strategic level.

Some of the tools used in quality 4.0 are: artificial intelligence, block chain, deep learning, big data, machine learning, enabling technologies like cloud computing, 5G  and other and data science.

Sustainability and quality management are inter-related. Sustainability makes sure that resources are utilized in a proper manner so that it does not compromise the need of future generation. Similarly, implementation of total quality principles makes sure that resources, processes and other aspects are properly aligned and used in a proper manner, so that maximum productivity is gained and waste generation is reduced (Boiral, Heras-Saizarbitoria and Brotherton 2019). Since it helps to decrease waste and boost efficiency, sustainability is critical in quality improvement. Organizations should learn how to use resources effectively if they are to be successful in business. This includes lowering the quantity of waste produced while boosting production per unit of input.

Quality management has an influence on all dePartments, classifications, and responsibilities. Its measures and resources are always developing, and they are being completely integrated into numerous project management components in order to efficiently produce fresh and innovative concepts (Carnerud 2018). Strong tools, processes, and high-quality templates are now the backbone of various projects, driving them ahead to achievement. In order to gain total quality, there is a need to create synergy between processes and every components of the organization.

Six-sigma

Instead of handling risk as a single component, Risk-Based Thinking is a systematic approach to risk that must be integrated across entire Quality system. This encourages one to be proactive than reactive, therefore motivates one to improve on a regular basis. While designing processes, controls, and improvements in a Quality Management System, companies need to use risk-based thinking (Ezrahovich et al., 2017). Risk-based thinking can also be used to recognize opportunities, which are the positive side of risk. Risk-based thinking should be adopted from the start and throughout the system, with preventative action becoming an integral Part of planning, operations, analysis, and assessment. 

Quality management systems incorporate many risks at every level. This could be technology failure, employee resistance, processes ambiguity, lack of resources and many others. Every structures, procedures, and operations involve hazards (Ezrahovich et al., 2017). All through the design and application of the quality management system, risk-based thinking makes sure that these risks have been acknowledged, addressed, and mitigated.

Digital revolution has transformed the working practices of every sector. Incorporating digital technologies like artificial intelligence, big data machine learning and other with TQM tools can help in gaining better results.  It generates flexibility and adaptability, more secured information, data privacy; structure the work processes and better cooperation among employees.

Organizations could manage continuous improvement activities, create process standards, achieve compliance, and drive other quality initiatives from anywhere with cloud-based quality management systems (Vasiliev, Aleksandrova and Aleksandro 2017). Advanced analytics have been used to find redundancies in processes, make better decisions, spot patterns, and measure quality improvement. Machine learning is increasingly has been used to detect product faults on the production line before they become costly refunds.

Digitalization speed up the quality management process because whenever an organization decides to move to cloud base, quality systems are used to make sure that processes are optimized, hazards are identified and compliance requirements are satisfied causing least disruption in the organizational processes (Mayakova 2019).

QMS trends	Advantages	Limitations	Relevance to case organization	References
Quality 4.0	ü  Competitive advantage ü  Enhance operational efficiency	ü  High risk of failure ü  High investment ü  Cyber threat ü  Market disruption	ü  Better products and services ü  Growth in new market	Asq.org. 2022. Quality 4-0 | ASQ. [online] Available at: <https://asq.org/quality-resources/quality-4-0> [Accessed 24 March 2022]. Carnerud, D., 2018. 25 years of quality management research–outlines and trends. International Journal of Quality & Reliability Management.
Integrated sustainability	ü  Proper resource utilization ü  Waste management	ü  Huge investment ü  Time consuming ü  Data risks	ü  decrease waste and boost efficiency ü  brand reputation ü  competitive advantage ü  resource management ü  quality improvement	Boiral, O., Heras-Saizarbitoria, I. and Brotherton, M.C., 2019. Assessing and improving the quality of sustainability reports: The auditors’ perspective. Journal of Business Ethics, 155(3), pp.703-721.
Collaboration	ü  Team working ü  Enhanced communication	ü  Creates ambiguity	ü   Clear tools, processes, and high-quality templates ü  create synergy between processes	Carnerud, D., 2018. 25 years of quality management research–outlines and trends. International Journal of Quality & Reliability Management.
Risk-based thinking	ü  risk identification ü  mitigation at early stage	ü  lack of reliable information ü  lack consistency	ü  Occurrences of risks will be reduced ü  Enhance processes ü  Help in fixing the loop holes in the process ü  Time consuming task	Ezrahovich, A.Y., Vladimirtsev, A.V., Livshitz, I.I., Lontsikh, P.A. and Karaseva, V.A., 2017, September. Risk-based thinking of ISO 9001: 2015—the new methods, approaches and tools of risk management. In 2017 International Conference” Quality Management, Transport and Information Security, Information Technologies”(IT&QM&IS) (pp. 506-511). IEEE.
Digitalization	ü  Streamline processes ü  Quality and consistency ü  Higher agility	ü  Complex ü   Technology failure ü  Security concerns	ü  Reduces error ü  Reduce operational costs ü  Reliability and governance	Vasiliev, V.A., Aleksandrova, S.V. and Aleksandrov, M.N., 2017, September. Integration of quality management and digital technologies. In 2017 International Conference” Quality Management, Transport and Information Security, Information Technologies”(IT&QM&IS) (pp. 454-456). IEEE. Mayakova, A., 2019. Digital transformation of modern quality management. ??????????? ???????-???, 180(11-12), pp.138-145.

Conclusion

The above paper critically analyses various factors on quality and it concludes that having an effective quality management system in place enables an organization in gaining maximum benefits and enhance customer satisfaction by delivering quality products and services. The report clearly demonstrates the strategic importance of quality management for Deutsche Telekom which is supported by concepts and models of QMS like Deming model, six-sigma, lean manufacturing, benchmarking and other to be implemented in the organization. Furthermore, recommendations have been provided on the creation of quality management system by implementing International standards like ISO 9000, ISO 9001 and ISO 27701 so that the company is able to identify and tackle the risks on priority basis. This will further help Deutsche Telekom enhance its control over various other business operations. It is also very vital for every organization to be adaptive towards trends prevailing in the industry. There are certain key trends like digitalization, adoption of 4.0, sustainability, risk bearing and other to make the quality management system more effective. Hence, Deutsche Telekom should consider the above mentioned factors in QMS in order to remain sustainable and gain competitive edge in the market.

References

Akkucuk, U. and Gencer, Y.G., 2017, April. EFQM Model and Sustainability of Organizations. In International Conference on Advances in Management Engineering and Information Technology.

Aleksandrova, S.V., Vasiliev, V.A. and Letuchev, G.M., 2018, September. Digital technology and quality management. In 2018 IEEE International Conference” Quality Management, Transport and Information Security, Information Technologies”(IT&QM&IS) (pp. 18-21). IEEE.

Asq.org. 2022. Quality 4-0 | ASQ. [online] Available at: <https://asq.org/quality-resources/quality-4-0> [Accessed 24 March 2022].

Bacoup, P., Michel, C., Habchi, G. and Pralus, M., 2018. From a quality management system (QMS) to a lean quality management system (LQMS). The TQM Journal. 112.

Boiral, O., Heras-Saizarbitoria, I. and Brotherton, M.C., 2019. Assessing and improving the quality of sustainability reports: The auditors’ perspective. Journal of Business Ethics, 155(3), pp.703-721.

Carnerud, D., 2018. 25 years of quality management research–outlines and trends. International Journal of Quality & Reliability Management.

Coussement, K., Lessmann, S. and Verstraeten, G., 2017. A comparative analysis of data preparation algorithms for customer churn prediction: A case study in the telecommunication industry. Decision Support Systems, 95, pp.27-36.

Dahlgaard-Park, S.M., Reyes, L. and Chen, C.K., 2018. The evolution and convergence of total quality management and management theories. Total Quality Management & Business Excellence, 29(9-10), pp.1108-1128.

Dimitrantzou, C., Psomas, E. and Vouzas, F., 2020. Future research avenues of cost of quality: a systematic literature review. The TQM Journal.

Ezrahovich, A.Y., Vladimirtsev, A.V., Livshitz, I.I., Lontsikh, P.A. and Karaseva, V.A., 2017, September. Risk-based thinking of ISO 9001: 2015—the new methods, approaches and tools of risk management. In 2017 International Conference” Quality Management, Transport and Information Security, Information Technologies”(IT&QM&IS) (pp. 506-511). IEEE.

Forbes. 2022. Deutsche Telekom. [online] Available at: <https://www.forbes.com/companies/deutsche-telekom/?sh=28747b586ddd> [Accessed 24 March 2022].

Gabriela-Livia, C., 2021, May. EFQM Excellence Model–European Foundation for Quality Management. In Proceedings of the 6th International Conference on Education Reform and Modern Management (ERMM 2021).

García-Alcaraz, J.L., Oropesa-Vento, M. and Maldonado-Macías, A.A., 2017. Kaizen planning, implementing and controlling. Springer International Publishing.

Hoyle, D., 2017. ISO 9000 quality systems handbook: increasing the quality of an organization’s outputs. Routledge.

Jasiulewicz-Kaczmarek, M., 2016. ISO 9000: 2015 quality management principles as the framework for a maintenance management system. Zeszyty Naukowe Politechniki Pozna?skiej. Organizacja i Zarz?dzanie.

Javorcik, B. and Sawada, N., 2018. The ISO 9000 certification: Little pain, big gain?. European Economic Review, 105, pp.103-114.

Khanam, S., Siddiqui, J. and Talib, F., 2016. Role of information technology in total quality management: a literature review. Khanam, S, Siddiqui, J. and Talib, F.(2013),“Role of Information Technology in Total Quality Management: A Literature Review”, International Journal of Advanced Research in Computer Engineering and Technology, 2(8), pp.2433-2445.

Lachaud, E., 2020. ISO/IEC 27701 Standard: Threats and Opportunities for GDPR Certification. Eur. Data Prot. L. Rev., 6, p.194.

Mayakova, A., 2019. Digital transformation of modern quality management. ??????????? ???????-???, 180(11-12), pp.138-145.

Militaru, C. and Zanfir, A., 2016. The vision of new ISO 9000: 2015 standards. Knowledge Horizons. Economics, 8(1), p.131.

Models, Techniques and Indicators of Quality Management Dpublication.com. 2022. [online] Available at: <https://www.dpublication.com/wp-content/uploads/2018/09/ijarme-V131-13.pdf> [Accessed 24 March 2022].

Obeidat, B.Y., Hashem, L., Alansari, I., Tarhini, A. and Al-Salti, Z., 2016. The effect of knowledge management uses on total quality management practices: A theoretical perspective. Journal of Management and strategy, 7(4), pp.18-29.

Quality management at Deutsche Telekom Vmware.com. 2022. [online] Available at: <https://www.vmware.com/files/de/pdf/customers/VMware-DeutscheTelekom-14Q3-DE-Case-Study.pdf> [Accessed 24 March 2022].

Ross, J.E., 2017. Total quality management: Text, cases, and readings. Routledge.

Sarria Yépez, M.P., Fonseca Villamarín, G.A. and Bocanegra-Herrera, C.C., 2017. Methodological model in the implementation of lean manufacturing. Revista Ean, (83), pp.51-71.

Sreedharan V, R. and Sunder M, V., 2018. Critical success factors of TQM, Six Sigma, Lean and Lean Six Sigma: A literature review and key findings. Benchmarking: An International Journal, 25(9), pp.3479-3504.

Van Kemenade, E. and Hardjono, T.W., 2018. Twenty-first century total quality management: the emergence paradigm. The TQM Journal.

Vasiliev, V.A., Aleksandrova, S.V. and Aleksandrov, M.N., 2017, September. Integration of quality management and digital technologies. In 2017 International Conference” Quality Management, Transport and Information Security, Information Technologies”(IT&QM&IS) (pp. 454-456). IEEE.

Yadav, G. and Desai, T.N., 2016. Lean Six Sigma: a categorized review of the literature. International Journal of Lean Six Sigma.

Quality management has emerged as a factor in gaining competitive advantage ever since organizations realized the benefits of delivering high-quality products and services to gain customer loyalty.in this, companies have adopted wide range of quality management tools for processes efficiency. Companies have realized that customer satisfaction and loyalty is not only dependent on time delivery of products and services but delivering products of superior quality (Sartor and Orzes 2019). The incorporation of quality management tools in the operational processes will enable Deutsche Telekom in achieving its business objectives.

The report aims at examining various quality management tools which could be implemented by Deutsche Telekom in order to support its business objectives. Furthermore, the report also demonstrates in what manner the quality management tools might contribute towards problem solving in the company.

Quality management tools and techniques available to the Deutsche Telekom to support its business objectives

The business objective of Deutsche Telekom is to become a leader in telecommunication industry. However, it had fulfilled its objective of dominating the European telecom industry. However, market trends, customer demands and technology is changing at faster pace. In this regard, Deutsche Telekom must refine its business strategy and make investments to enhance its network and involve more customers to be a Part of digital life. The core of Deutsche Telekom’s business strategy involve designing and administering the best networks wherein fixed-network and mobile services integrate flawlessly and become “internally consistent” Digitalization of the company’s own products and operations is at the heart of its strategy (AG, 2022).

Companies have been driven to embrace innovative methods and strengthen existing business processes to attain quality excellence as the telecommunications market has become more competitive. In order to pursue its business objectives, Deutsche Telekom should be capable in implementing various quality management tools to gain superiority in the products and delivery of its products and services.

Following are QMs tools and techniques that need to be implemented in the company for supporting its business objectives in the long-run:

Ishikawa seven basic quality tools

Dr. Kaoru Ishikawa proposed seven basic quality tools for process improvement and problem solving in an organization. The seven basic tools are as follows:

Histograms: In order to manage quality, quality specialists are often required to assess and analyse the activities of different categories of data. That’s when tools like the histogram, which are used for quality control, come into the equation. This tool can help the quality analyst represent data collected in a concise manner. This further helps in identification of areas of improvement inside the business processes (Ishikawa’s Seven Quality Tools 2022). This represents numerical data in a visual manner and assists the business in representing its statistics, economics as well as other disciplines for analysing trends and data. Data which are complex, discrete and continuous can easily be represented and analysed through this tool.

Using histogram will help in comparing previous and current data and make the organization identify areas that are lagging behind. However, it shows difficulty when comparing two different data sets.

Figure: Histogram

Source: (Ishikawa’s Seven Quality Tools 2022)

Cause and effect diagrams: This is also known as fish bone diagram. The elements of this tool are grouped into six categories like resources, measurements, environment, personnel, machines and methods. These elements when structured properly will help in problem identification. This assists quality analyst in categorizing the potential reasons of the problems in a visual manner. This is basically used to classify the root cause of the problems. This is mainly used for root cause analysis and involves brainstorming session (Coccia 2020). When the root cause of the problems is identified by the company, it assists in improving the process and quality issues.

Root cause analysis can be used for resolving issues in an organization by problem identification and sorting ideas or solutions in useful categories. It supports organizations in knowing that an influence is the result of multiple factors. It visually portrays the association among the causes and the effects, as well as amid the sources and one another (Gartlehner et al., 2017).

Figure: Cause and effect diagram

Source: (Coccia 2020)

Check sheets: This is used to present both qualitative and quantitative data. This helps in data analysis in a structured manner. When it is used for analysing quantitative data, it is called tally sheet (Ishikawa’s Seven Quality Tools 2022). A check sheet captures data in the form of check or tally marks which signify how many times a exact value has appeared, allowing one to quickly locate mistakes or errors in the product or a procedure, problem trends, and even Particular defect sources.

Figure: Check sheets

Source: (Ishikawa’s Seven Quality Tools 2022)

Pareto diagrams: This tool works on the principle of 80-20 rule. The Pareto chart is the statistical graphical tool for mapping and ranking organizational process issues from most common to least common, with the eventual aim of concentrating on the aspects which have the biggest overall influence. The Pareto Chart is among the most effective management tools, and that might be used to identify processes for defining priorities (Prístavka, Kotorová and Savov 2016). This permits management to regulate the severity and root causes of concerns and to organize work, hazards, operations, and causes.

Figure: Pareto chart

Source: (Prístavka, Kotorová and Savov 2016)

Stratification: This is a quality management tool which is used to sort data, people and objects into discrete and distinct groups. Using stratification to distinct the data might support to figure out what it signifies, exposing patterns which would not be visible otherwise when it’s all jumbled together (Ishikawa’s Seven Quality Tools 2022).

Figure: Stratification

Source: (Ishikawa’s Seven Quality Tools 2022)

Control charts: This quality management tool assists quality analyst in evaluating whether a procedure is consistent and predictable, making it simple to detect variables which might lead to variances or faults. This helps in making a comparison among historical and current data and help organizations in predicting performance.

Figure: Control charts

Source: (Ishikawa’s Seven Quality Tools 2022)

Scatter diagrams: This tool helps in determining relation among two variables. The range of data flow, minimum and maximum values could be determined with this tool. This helps business take better project decisions by identification of underlying problem causes. It can determine whether a cause and effect are linked objectively (Ishikawa’s Seven Quality Tools 2022).

Figure: Scatter diagram

Source: (Ishikawa’s Seven Quality Tools 2022)

This is service quality model and used in the development of quality in products and services. This is basically used to capture expectations of customers and their perceptions on the basis of five dimensions of service quality. The five dimensions include: reliability, assurances, tangibles, empathy and responsiveness. This is basically conducted by conducting a survey and asking customers to rate the product or service as per their expectations (Midor and Ku?era 2018). It enables service providers with identical output to give higher value, profitability, service growth opportunities, and customer contentment.

Figure: Servqual

Source: (Midor and Ku?era 2018)

SPC is a quality control technique that practices statistical methodologies for constantly monitoring a procedure. This assists in the effective execution of the system, resulting in more accurate output and less wastage (Qiu 2018). SPC Software will help organizations follow a data-driven philosophy of quality improvement which prioritises defect avoidance over detecting defects, as well as measure the return on investment. Organizations make use of this tool to control production process and identify variation in the process.

Figure: Statistical process control

Source: (Qiu 2018)

This tool is used to define customer needs and help the business to convert them into comprehensive design requirements and plans for producing products that meet those requirements. It’s a method for establishing customer preferences or specifications and turning them into detailed plans for producing items that match those objectives (Sivasamy et al., 2016). This further assists in making trade-off decisions based on customer preferences. It involves four stages namely: product planning, design deployment, process planning and production planning. This is basically focused on satisfying customers.

Figure: Quality Function Deployment (QFD)

Source: (Sivasamy et al., 2016)

This is a comprehensive and feasible approach for process review in order to determine when and how it might collapse as well as to quantify the comparative impact of different failures, in order to determine the elements of the process which need to be changed the most. This tool helps in reviewing steps in the procedure, modes of failure, causes of failure and impacts of failure (Huang et al., 2020). Businesses make use of this tool for detecting possible failures and prevent it by corrective measures in spite of reacting to adverse events after failure takes place. This is common quality analysis tool that detects error.

Figure: FMEA tool

Source: (Huang et al., 2020 )

The PDCA cycle is used to implement a QMS, and it comprises of the four stages. The cycle allows the QMS to be reviewed and improved on a regular basis. This involves logical sequence of four steps like Plan, do, check and Act.

Plan: The Company should plan at this stage for mapping out what needs to be done or any change to be implemented inside the company. This will help in analysing problems as well as opportunities to implement change, developing hypothesis, resources required and measures of success (Dahlgaard-Park, Reyes and Chen 2018).

Do: This stage is for testing hypothesis which is the proposed solution. This could be achieved by small and incremental stages as it will minimize disruption and resistance.

Check: After completion of trial, management must review and analyse the results of the change process. This will assist in evaluating the effectiveness of the process and allows possible revisions to the solution (Van Kemenade and Hardjono 2018).

Act: This stage will implement the plan and new processes will act as baseline for future processes.

Figure: PDCA cycle

Source: (Van Kemenade and Hardjono 2018)

QM tools	Advantages	Limitations	References
Ishikawa seven tools	·         Data analysis ·         Arranges complex data ·         Identifies areas of improvement ·	·         Only used for continuous data ·         Difficult to compare two data sets. ·         Sometimes difficult to interpret ·         Misinterpretations of data ·         Confusion can be caused by irrelevant apparent reasons. ·         Complex challenges might result in a cluttered diagram.	Escholarship.org. 2022. [online] Available at: <https://escholarship.org/content/qt2kt3x0th/qt2kt3x0th.pdf?t=ong6dw#:~:text=These%20seven%20basic%20quality%20control,diagrams%3B%207)%20Control%20charts.> [Accessed 25 March 2022]. Coccia, M., 2020. Fishbone diagram for technological analysis and foresight. International Journal of Foresight and Innovation Policy, 14(2-4), pp.225-247. Prístavka, M., Kotorová, M. and Savov, R., 2016. Quality control in production processes. Acta technologica agriculturae, 19(3), pp.77-83.
	·         Help to identify customer expectation ·         Assist in improving products and service quality	·         Difficult to know customer expectation ·         Not up to service standards	Midor, K. and Ku?era, M., 2018. Improving the service with the servqual method. Management systems in production engineering.
SPC	·         follow a data-driven philosophy ·         defect avoidance	·         unambiguity in the process	Qiu, P., 2018. Some perspectives on nonparametric statistical process control. Journal of Quality Technology, 50(1), pp.49-65.
QFD	·         Customer satisfaction ·         Identifies customer’s preferences	·         Ignores factors like cost, growth objectives and resource availability	Sivasamy, K., Arumugam, C., Devadasan, S.R., Murugesh, R. and Thilak, V.M.M., 2016. Advanced models of quality function deployment: a literature review. Quality & quantity, 50(3), pp.1399-1414.
FMEA	·         Reduces time and cost ·         Early detection of error	·         It needs constant updating ·         Sometimes under-estimate the risk	Huang, J., You, J.X., Liu, H.C. and Song, M.S., 2020. Failure mode and effect analysis improvement: A systematic literature review and future research agenda. Reliability Engineering & System Safety, 199, p.106885.
PDCA	·         Process improvement ·         Waste reduction ·         Staff development ·         Managing effective change	·         Resistance to change ·         Expensive process ·         High management and training cost ·         Demands strong leadership	Van Kemenade, E. and Hardjono, T.W., 2018. Twenty-first century total quality management: the emergence paradigm. The TQM Journal. Dahlgaard-Park, S.M., Reyes, L. and Chen, C.K., 2018. The evolution and convergence of total quality management and management theories. Total Quality Management & Business Excellence, 29(9-10), pp.1108-1128.

In problem solving, high-quality tools could be used for a variety of purposes. They could be used for quality improving in the process, decision-making and conducting root causing analysis. The tools further assists in brainstorming sessions, disseminate information and information sharing among team members. When more than one possible answer is accessible, it also assists in picking the optimal one (Combining Quality Tools for Effective Problem Solving, 2022). A problem-solving or quality-improvement project might also benefit from the use of quality tools.

According to Topham and Drew (2017) CAPA management is very significant process for the companies operating in telecommunication industry. This involves root cause analysis for problem identification. In this regard, cause and effect diagram can be used for effective CAPA management. CAPA stands for corrective and preventive actions to be undertaken by an organization to improve process and eliminate causes of non-conformities or other undesirable concerns (Raj 2016). For problem resolution, it is very vital to identify the root cause of the problem at early stage. Deutsche Telekom can implement cause and effect diagram as well as Pareto rule for problem solving.

Deutsche Telekom can utilise CAPA Management for telecommunications to discover, analyse, and eliminate the core cause of systemic problems so they don’t happen again. It’s a robust solution with a variety of investigation tools for dealing with serious problems quickly and effectively. The information users supply is automatically recorded by the solution for reference in the future, evaluations, and inspections. One can quickly follow the events and activities performed to fix an issue using the audit log. 

Implementing Pareto tool will assist in effective decision making of enhancing processes to achieve superior quality. This could be achieved by problem identification, resolving customer concerns and other factors that hinder the growth process (Prístavka, Kotorová and Savov 2016). By applying Pareto tool will help in separating significant problems from trivial ones. A manager will assess where to focus their improvement efforts by graphically distinguishing the elements of a problem.

In a telecommunication company, complain management is a significant process to gain customer trust and satisfaction. It allows telecom businesses to record, handle, and monitor consumer complaints and feedback regardless of where they are located. The entire cycle time is reduced by streamlining and standardising the complaints process, providing businesses additional time to concentrate on core functions. Constant complains from the customer indicates serious problem in the products or service delivered. In the same manner, Quality Function Deployment tool will make the organization analyse root cause of the problem and develop strategies to resolve it. Quality Function Deployment tool helps in identifying customer’s preferences and concerns (Sivasamy et al., 2016). This also assists in the decision-making process when it comes to trade-offs depending on the customer expectations.

Companies have been driven to embrace new ideas and improve existing business processes in order to attain quality excellence as the telecommunications market has become more competitive. Customers’ satisfaction is measured in terms of quality. The higher the process quality, the more delighted customers company will have (Carnerud 2018). Streamlining and improving business processes are the key to enhance profitability, quality, market share, operational efficiency and gain customer trust. In this regard, for continuous improvement and problem resolution, PDCA cycle can be used by Deutsche Telekom. This will assist in better planning, developing and testing strategies, reviewing and acting as per the interventions developed (Dahlgaard-Park, Reyes and Chen 2018). It offers a direct and practical method towards problem-solving and change management. Before upgrading measures and operational methods, the model could be used to test development measures on a small scale. This will further prevent resistance to change.

By implementing the above quality management tool Deutsche Telekom could achieve its business objective of becoming a leader in the industry. Deutsche Telekom aspires to be the company of choice for multinational enterprises, assisting them with their global connectivity needs. In order to achieve this, it has to strengthen its delivery capacity by assuring quality in every product and services (Carnerud 2018). Hence, quality management tools will prove beneficial in enhancing productivity and quality of the business processes.

QM tools	Implementation in the case organization	Key issue addressed	References
Pareto tool and cause and effect tool	ü  It will help in identifying frequent defects in software and other processes at Deutsche Telekom. ü  It will further assist in resolving customer complains. ü  Help in decision making	ü  Bugs in the software programs ü  Resolves network issues	Prístavka, M., Kotorová, M. and Savov, R., 2016. Quality control in production processes. Acta technologica agriculturae, 19(3), pp.77-83.
Quality Function Deployment tool	ü  Identifies customer needs and preferences	ü  Customer complains ü  Customers satisfaction	Sivasamy, K., Arumugam, C., Devadasan, S.R., Murugesh, R. and Thilak, V.M.M., 2016. Advanced models of quality function deployment: a literature review. Quality & quantity, 50(3), pp.1399-1414.
PDCA cycle	ü  Process improvement ü  Better planning ü  Process review	ü  Minimizes resistance to change ü  Error identification ü  Help in developing strategies towards problems identified	Dahlgaard-Park, S.M., Reyes, L. and Chen, C.K., 2018. The evolution and convergence of total quality management and management theories. Total Quality Management & Business Excellence, 29(9-10), pp.1108-1128.

Conclusion

The above discussion concludes that quality is an area of expertise every organization desires to achieve. Quality management tool is incorporated by companies in not only enhancing products and service quality but also assist the businesses with decision making capability, problem solving and continuous improvement. Deutsche Telekom can gain competitive advantage in the industry if it is capable to implement quality management tool in an effective manner. The above recommended quality management tool will make the business resiliency from various aspects like uncertainties and unprecedented risks in future. Quality management tools are cost effective and will include benefits like customer satisfaction, enhance efficiency, improve business processes, improve triple bottom line, help in waste management by reducing errors and streamlining processes in an effective manner. Hence, it is evident from the analysis that quality management is very significant in developing a culture that is quality conscious across all layers of the corporation.

References

AG, D., 2022. Strategy. [online] Telekom.com. Available at: <https://www.telekom.com/en/company/strategy> [Accessed 25 March 2022].

Carnerud, D., 2018. 25 years of quality management research–outlines and trends. International Journal of Quality & Reliability Management.

Coccia, M., 2020. Fishbone diagram for technological analysis and foresight. International Journal of Foresight and Innovation Policy, 14(2-4), pp.225-247.

Dahlgaard-Park, S.M., Reyes, L. and Chen, C.K., 2018. The evolution and convergence of total quality management and management theories. Total Quality Management & Business Excellence, 29(9-10), pp.1108-1128.

Gartlehner, G., Schultes, M.T., Titscher, V., Morgan, L.C., Bobashev, G.V., Williams, P. and West, S.L., 2017. User testing of an adaptation of fishbone diagrams to depict results of systematic reviews. BMC medical research methodology, 17(1), pp.1-9.

Huang, J., You, J.X., Liu, H.C. and Song, M.S., 2020. Failure mode and effect analysis improvement: A systematic literature review and future research agenda. Reliability Engineering & System Safety, 199, p.106885.

Ishikawa’s Seven Quality Tools Escholarship.org. 2022. [online] Available at: <https://escholarship.org/content/qt2kt3x0th/qt2kt3x0th.pdf?t=ong6dw#:~:text=These%20seven%20basic%20quality%20control,diagrams%3B%207)%20Control%20charts.> [Accessed 25 March 2022].

Midor, K. and Ku?era, M., 2018. Improving the service with the servqual method. Management systems in production engineering.

Prístavka, M., Kotorová, M. and Savov, R., 2016. Quality control in production processes. Acta technologica agriculturae, 19(3), pp.77-83.

Qiu, P., 2018. Some perspectives on nonparametric statistical process control. Journal of Quality Technology, 50(1), pp.49-65.

Qualitydigest.com. 2022. Combining Quality Tools for Effective Problem Solving. [online] Available at: <https://www.qualitydigest.com/inside/lean-article/combining-quality-tools-effective-problem-solving-102317.html#:~:text=Quality%20tools%20can%20serve,sharing%20ideas%20with%20a%20team.> [Accessed 25 March 2022].

Raj, A., 2016. A review on corrective action and preventive action (CAPA). African Journal of Pharmacy and Pharmacology, 10(1), pp.1-6.

Sartor, M. and Orzes, G. eds., 2019. Quality management: Tools, methods and standards. Emerald Group Publishing.

Sivasamy, K., Arumugam, C., Devadasan, S.R., Murugesh, R. and Thilak, V.M.M., 2016. Advanced models of quality function deployment: a literature review. Quality & quantity, 50(3), pp.1399-1414.

Topham, D. and Drew, D., 2017. Quality improvement project: replacing the numeric rating scale with a clinically aligned pain assessment (CAPA) tool. Pain Management Nursing, 18(6), pp.363-371.

Van Kemenade, E. and Hardjono, T.W., 2018. Twenty-first century total quality management: the emergence paradigm. The TQM Journal.