Capability Maturity Model Integration (Cmmi) for Small Organizations

Software Process Improvement (SPI) is a large area of expertise that deals with software development standard processes and is a progression of proven methods of process improvement from many different methodologies. Personal Software Process (PSP) and Team Software Process (TSP) complement the implementation of Capability Maturity Model Implementation (CMMI) and can be applied gradually from the individual, to the team, and then to the organization. These solutions from Carnegie Melon\u27s Software Engineering Institute (SEI) are leading edge for the field of process improvement. Solutions like this consume many resources, are very complex, require years to implement, and can be costly. The SEI solutions offer an industry standard for SPI. Three case studies were analyzed to provide insight into the benefits of CMMI for small organizations. Decisions that steer these solutions generally involve scheduling, quality, and cost. Depending on the individual needs of an organization, the CMMI technology can fulfill what is required. The example case studies were examined and concluded that given favorable conditions, implementing CMMI is feasible for small organizations

Towards better organizational analytics capability:a maturity model

Abstract. Data and analytics are changing the markets. Significant improvements in competitiveness can be achieved through utilizing data and analytics. Data and analytics can be used to support in all levels of decision making from operational to strategic levels. However, studies suggest that organizations are failing to realize these benefits. Many of the analytics initiatives fail and only a small partition of organizations’ data is used in decision making. This happens mostly because utilizing data and analytics in larger scale is a difficult and complex matter. Companies need to harness multiple resources and capabilities in a business context and use them synergistically to deliver value. Capabilities must be developed step by step and cannot be bought. Bottlenecks like siloed data, lack of commitment and lack of understanding slow down the development. The focus of this thesis is to gain insight on how these resources and capabilities can be managed and understood better to pursue a position where modern applications of data and analytics could be utilized even better. The study is conducted in two parts. In the first part, the terminology, disciplines, analytics capabilities, and success factors of data and analytics development are examined through the literature. Then a comprehensive tool for identifying and reviewing these analytics capabilities is built through analyzing and combining existing tools and earlier insights. This tool, organizational analytics maturity model, and other findings are then reviewed and complemented with empirical interviews. The main findings of this thesis were mapped analytics capabilities, success factors of analytics, and the organizational analytics maturity model. These results help practitioners and researchers to better understand the complexity of the subject and what dimensions must be taken into account when pursuing success with data and analytics.Kohti parempaa organisaation analytiikkakyvykkyyttä : maturiteettimalli. Tiivistelmä. Datan ja analytiikka muuttaa eri organisaatioiden välistä kilpailua. Huomattavia parannuksia kilpailukyvyssä voidaan saada aikaan oikeanlaisella datan ja analytiikan hyödyntämisellä. Data ja analytiikkaa voidaan käyttää kaikilla päätöksen teon asteilla operatiivisista päätöksistä strategiselle tasolle asti. Tästä huolimatta tutkimukset osoittavat, että organisaatiot eivät ole onnistuneet saavuttamaan näitä hyötyjä. Monet analytiikka-aloitteet epäonnistuvat ja vain pientä osaa yritysten keräämästä datasta hyödynnetään päätöksenteossa. Tämä johtuu pääosin siitä, että datan ja analytiikan hyödyntäminen isossa kontekstissa on vaikeaa ja monimutkaista. Organisaatioiden täytyy valjastaa useita resursseja ja kyvykkyyksiä liiketoimintakontekstissa ja käyttää näitä synergisesti tuottaakseen arvoa. Näitä kyvykkyyksiä ei voida ostaa suoraan, vaan ne joudutaan asteittain kehittämään osaksi organisaatiota. Kehitykseen liittyy myös paljon ongelmakohtia, jotka hidastavat kokonaiskehitystä. Siiloutunut data ja sitoutumisen ja ymmärryksen puute ovat esimerkkejä kehityksen kompastuskivistä. Tämän opinnäytteen tarkoitus on syventää ymmärrystä siitä, miten näitä resursseja ja kyvykkyyksiä hallitaan ja ymmärretään paremmin. Miten organisaatio pääsee tilaan, jossa se voi hyödyntää moderneja datan ja analytiikan mahdollisuuksia? Tutkimus muodostuu kahdesta osasta. Ensimmäisessä osassa käsitellään terminologia, analytiikkakyvykkyydet ja niiden menestystekijät. Sen jälkeen luodaan kokonaisvaltainen työkalu, organisaation analytiikkamaturiteettimalli, kyvykkyyksien tunnistamiseksi ja kehittämiseksi. Tämä malli rakennetaan ensimmäisten löydösten pohjalta. Tutkimuksen toisessa osassa aiemmat löydökset ja rakennettu malli validoidaan ja täydennetään empiirisillä haastatteluilla. Tämän työn päälöydökset ovat kartoitetut analytiikkakyvykkyydet, niiden menestystekijät ja organisaation analytiikkamaturiteettimalli. Nämä löydökset auttavat ammattilaisia ja tutkijoita ymmärtämään paremmin aiheen monimutkaisuuden ja mitä dimensioita tulee ottaa huomioon, kun pyritään menestykseen datan ja analytiikan avulla

Digital Transformation and Improvement of Business Processes with Internet of Things: A Maturity Model for Assessing Readiness

Companies of all industrial sectors are increasingly integrating Internet of Things (IoT) technology into their processes to realize a data-driven transformation of their businesses. The generation and use of comprehensive process data in real-time and the connection of process entities enables an improvement and beneficial redesign of business processes of all kinds. However, a goal-oriented exploitation of IoT technology for digital transformation and Business Process Improvements (BPI) is challenging due to the complexity of integrating IoT into existing processes. Companies require appropriate guidance to evaluate and scope their initiatives regarding IoT-based BPI. We therefore propose a holistic IoT-based BPI Maturity Model that assists organizations to determine their current state and get assistance to optimize or develop specific capabilities. This paper provides an overview about the structured development process of the maturity model comprising an extensive literature review and a six-round Delphi study

A model of quality service management for information systems

Tese de mestrado. Mestrado em Engenharia Electrotécnica e de Computadores (Área de especialização Tecnologias da Informação para Gestão Empresarial). Faculdade de Engenharia. Universidade do Porto. 200

A Systematic Consideration of the Human and Technical Elements in the Implementation of Lean Manufacturing Cells

Some manufacturing companies are successful, while many others fail in their efforts to implement lean philosophies and practices into their manufacturing operations. Although the technical process flows and cell designs meet the standards and criteria specified in the literature, these companies most often do not fully consider the impact of the human element in the management of change. It is hypothesized that an approach that combines the implementation of lean manufacturing cells with technical, human and lean practices considerations will result in improved cell performance. This research investigates how to create and implement such a system and evaluate its impact on a manufacturer’s cell performance. A questionnaire is developed, based on literature and industry research, to collect employee perceptions regarding the importance rating and implementation levels of the technical, human and lean practices within a manufacturing cell. Manufacturing cell performance data is collected and analyzed in concert with the questionnaire to prove the hypothesis. The approach is piloted at an aero engine manufacturer and the results are provided. The findings indicate that as a foundation, manufacturing cells must achieve a certain level of implementation in the technical areas of machines, methods, and materials. With all else equal, manufacturing cells that achieve higher implementation levels of the human and lean practices, also achieve higher cell performance

KM Facing Simultaneous Obstacles and Strategic Benefits Realization: A Continuing Conundrum

This research identifies and establishes the most common and persistent obstacles faced by organisations in the development and implementation of knowledge management (KM) strategies, and strategic benefits that are realised. This study discloses a conundrum in the pattern in the maturity level of the KM initiative and simultaneous obstacles faced by the organisation at these maturity levels. This paper provides a background to the study, analysis of survey results, discussion and conclusion. Survey responses indicate both major themes and those that are lesser reported. The most common and ubiquitous challenge an organisation faces in the present time is the widespread lack of understanding of what KM is. Of only slightly lesser importance to that are obstacles within the organisational culture to effective implementation of KM, ‘commitment to cause’ and absence of formalised knowledge processes are major themes. Discussion further sheds light on the strategic benefits realised and attributed to KM. This research study findings may guide in examining theory and practice in the preparation and implementation of knowledge management initiatives

Evaluation and Development of Selection Criteria to Guide Organizational Selection of a Project Management Maturity Model

Organizations wishing to measurably and continuously improve processes often look towards maturity models, such as OPM3 and CMMI, as their panacea. However, selecting the wrong model for the organizations goals and resources can result in project failure. This study, focusing on OPM3 and CMMI, proposes a guidance tool that can help organizations select the right maturity model. The study is framed in the state government context due to the complexity and relative insularity of that environment. In addition to being a limited based, state governments have several limiters that factor into project selection, namely budget and taxpayer transparency. Using several core methods of technology selection, best practices from business process improvement, and the OPM3 and CMMI-Services models, this paper reviews these components to identify what elements of a Project Management Maturity Model project could assist prospective government agencies in selecting a model that is appropriate to their situation and goals. The study identifies several factors, outside of the maturity models themselves that have effect on the outcome of the maturity model project itself. These factors should be taken into consideration by project sponsors early on in the project\u27s conception. Failure to do so risks selection of an inappropriate model, or one that exceeds the budget of the governmental organization. Finally, the selection questionnaire presented is intended to provide guidance regarding the purposes and functionalities of the OPM3 and CMMI-Services maturity models. Additionally, specific project success factors are framed in such as way as to generate additional discussion within the organization. These additional questions are intended to provide talking points related to the maturity model project in general, rather than for a specific model. In this way, the government organization can accurately reflect on and plan their Project Management Maturity Model project