Evaluating the Maturity of Data Management Practices in a Major Energy Provider Company

Data is the most important asset of a company in the information age. Other assets, such as technology, facilities or products can be copied or reverse-engineered, employees can be brought over, but data remains unique to every company. As data management topics are slowly moving from unknown unknowns to known unknowns, tools to evaluate and manage data properly are developed and refined. Many projects are in progress today to develop various maturity models for evaluating information and data management practices. These maturity models come in many shapes and sizes: from short and concise ones meant for a quick assessment, to complex ones that call for an expert assessment by experienced consultants. In this paper several of them, made not only by external inter-organizational groups and authors, but also developed internally at a Major Energy Provider Company (MEPC) are juxtaposed and thoroughly analyzed. Apart from analyzing the available maturity models related to Data Management, this paper also selects the one with the most merit and describes and analyzes using it to perform a maturity assessment in MEPC. The utility of maturity models is two-fold: descriptive and prescriptive. Besides recording the current state of Data Management practices maturity by performing the assessments, this maturity model is also used to chart the way forward. Thus, after the current situation is presented, analysis and recommendations on how to improve it based on the definitions of higher levels of maturity are given. Generally, the main trend observed was the widening of the Data Management field to include more business and “soft” areas (as opposed to technical ones) and the change of focus towards business value of data, while assuming that the underlying IT systems for managing data are “ideal”, that is, left to the purely technical disciplines to design and maintain. This trend is not only present in Data Management but in other technological areas as well, where more and more attention is given to innovative use of technology, while acknowledging that the strategic importance of IT as such is diminishing.

Improving the inventory management and valuation process, Case: The Switch Drive Systems

The goal of this study is to create a new inventory valuation process for The Switch Drive Systems and to improve its inventory management practices. In the matter of inventories the main problems in the case company are that it doesn’t have consistent valuation methods throughout the company and that information received in ERP system isn’t trustful. The research is qualitative case study. The empirical data is gathered through observing and unstructured interviews. The research shows that material flow process and the inventory valuation must be divided and handled separately but they should interact with each other. The result is a new inventory valuation process which takes many factors of material process under the consideration in order to receive reliable value for inventories.

Adaptive Routing Approaches for Networked Many-Core Systems

Through advances in technology, System-on-Chip design is moving towards integrating tens to hundreds of intellectual property blocks into a single chip. In such a many-core system, on-chip communication becomes a performance bottleneck for high performance designs. Network-on-Chip (NoC) has emerged as a viable solution for the communication challenges in highly complex chips. The NoC architecture paradigm, based on a modular packet-switched mechanism, can address many of the on-chip communication challenges such as wiring complexity, communication latency, and bandwidth. Furthermore, the combined benefits of 3D IC and NoC schemes provide the possibility of designing a high performance system in a limited chip area. The major advantages of 3D NoCs are the considerable reductions in average latency and power consumption. There are several factors degrading the performance of NoCs. In this thesis, we investigate three main performance-limiting factors: network congestion, faults, and the lack of efficient multicast support. We address these issues by the means of routing algorithms. Congestion of data packets may lead to increased network latency and power consumption. Thus, we propose three different approaches for alleviating such congestion in the network. The first approach is based on measuring the congestion information in different regions of the network, distributing the information over the network, and utilizing this information when making a routing decision. The second approach employs a learning method to dynamically find the less congested routes according to the underlying traffic. The third approach is based on a fuzzy-logic technique to perform better routing decisions when traffic information of different routes is available. Faults affect performance significantly, as then packets should take longer paths in order to be routed around the faults, which in turn increases congestion around the faulty regions. We propose four methods to tolerate faults at the link and switch level by using only the shortest paths as long as such path exists. The unique characteristic among these methods is the toleration of faults while also maintaining the performance of NoCs. To the best of our knowledge, these algorithms are the first approaches to bypassing faults prior to reaching them while avoiding unnecessary misrouting of packets. Current implementations of multicast communication result in a significant performance loss for unicast traffic. This is due to the fact that the routing rules of multicast packets limit the adaptivity of unicast packets. We present an approach in which both unicast and multicast packets can be efficiently routed within the network. While suggesting a more efficient multicast support, the proposed approach does not affect the performance of unicast routing at all. In addition, in order to reduce the overall path length of multicast packets, we present several partitioning methods along with their analytical models for latency measurement. This approach is discussed in the context of 3D mesh networks.

Integration of Electronic Commerce and Enterprise Systems

The necessity of EC (Electronic Commerce) and enterprise systems integration is perceived from the integrated nature of enterprise systems. The proven benefits of EC to provide competitive advantages to the organizations force enterprises to adopt and integrate EC with their enterprise systems. Integration is a complex task to facilitate seamless flow of information and data between different systems within and across enterprises. Different systems have different platforms, thus to integrate systems with different platforms and infrastructures, integration technologies, such as middleware, SOA (Service-Oriented Architecture), ESB (Enterprise Service Bus), JCA (J2EE Connector Architecture), and B2B (Business-to-Business) integration standards are required. Huge software vendors, such as Oracle, IBM, Microsoft, and SAP suggest various solutions to address EC and enterprise systems integration problems. There are limited numbers of literature about the integration of EC and enterprise systems in detail. Most of the studies in this area have focused on the factors which influence the adoption of EC by enterprise or other studies provide limited information about a specific platform or integration methodology in general. Therefore, this thesis is conducted to cover the technical details of EC and enterprise systems integration and covers both the adoption factors and integration solutions. In this study, many literature was reviewed and different solutions were investigated. Different enterprise integration approaches as well as most popular integration technologies were investigated. Moreover, various methodologies of integrating EC and enterprise systems were studied in detail and different solutions were examined. In this study, the influential factors to adopt EC in enterprises were studied based on previous literature and categorized to technical, social, managerial, financial, and human resource factors. Moreover, integration technologies were categorized based on three levels of integration, which are data, application, and process. In addition, different integration approaches were identified and categorized based on their communication and platform. Also, different EC integration solutions were investigated and categorized based on the identified integration approaches. By considering different aspects of integration, this study is a great asset to the architectures, developers, and system integrators in order to integrate and adopt EC with enterprise systems.

What are the opportunities and challenges of cloud computing technology in the healthcare information systems

This thesis discusses the opportunities and challenges of the cloud computing technology in healthcare information systems by reviewing the existing literature on cloud computing and healthcare information system and the impact of cloud computing technology to healthcare industry. The review shows that if problems related to security of data are solved then cloud computing will positively transform the healthcare institutions by giving advantage to the healthcare IT infrastructure as well as improving and giving benefit to healthcare services. Therefore, this thesis will explore the opportunities and challenges that are associated with cloud computing in the context of Finland in order to help the healthcare organizations and stakeholders to determine its direction when it decides to adopt cloud technology on their information systems.

On state and parameter estimation in chaotic systems

State-of-the-art predictions of atmospheric states rely on large-scale numerical models of chaotic systems. This dissertation studies numerical methods for state and parameter estimation in such systems. The motivation comes from weather and climate models and a methodological perspective is adopted. The dissertation comprises three sections: state estimation, parameter estimation and chemical data assimilation with real atmospheric satellite data. In the state estimation part of this dissertation, a new filtering technique based on a combination of ensemble and variational Kalman filtering approaches, is presented, experimented and discussed. This new filter is developed for large-scale Kalman filtering applications. In the parameter estimation part, three different techniques for parameter estimation in chaotic systems are considered. The methods are studied using the parameterized Lorenz 95 system, which is a benchmark model for data assimilation. In addition, a dilemma related to the uniqueness of weather and climate model closure parameters is discussed. In the data-oriented part of this dissertation, data from the Global Ozone Monitoring by Occultation of Stars (GOMOS) satellite instrument are considered and an alternative algorithm to retrieve atmospheric parameters from the measurements is presented. The validation study presents first global comparisons between two unique satellite-borne datasets of vertical profiles of nitrogen trioxide (NO3), retrieved using GOMOS and Stratospheric Aerosol and Gas Experiment III (SAGE III) satellite instruments. The GOMOS NO3 observations are also considered in a chemical state estimation study in order to retrieve stratospheric temperature profiles. The main result of this dissertation is the consideration of likelihood calculations via Kalman filtering outputs. The concept has previously been used together with stochastic differential equations and in time series analysis. In this work, the concept is applied to chaotic dynamical systems and used together with Markov chain Monte Carlo (MCMC) methods for statistical analysis. In particular, this methodology is advocated for use in numerical weather prediction (NWP) and climate model applications. In addition, the concept is shown to be useful in estimating the filter-specific parameters related, e.g., to model error covariance matrix parameters.

Energy-efficient control strategies for variable speed driven parallel pumping systems based on pump operation point monitoring with frequency converters

The pumping processes requiring wide range of flow are often equipped with parallelconnected centrifugal pumps. In parallel pumping systems, the use of variable speed control allows that the required output for the process can be delivered with a varying number of operated pump units and selected rotational speed references. However, the optimization of the parallel-connected rotational speed controlled pump units often requires adaptive modelling of both parallel pump characteristics and the surrounding system in varying operation conditions. The available information required for the system modelling in typical parallel pumping applications such as waste water treatment and various cooling and water delivery pumping tasks can be limited, and the lack of real-time operation point monitoring often sets limits for accurate energy efficiency optimization. Hence, alternatives for easily implementable control strategies which can be adopted with minimum system data are necessary. This doctoral thesis concentrates on the methods that allow the energy efficient use of variable speed controlled parallel pumps in system scenarios in which the parallel pump units consist of a centrifugal pump, an electric motor, and a frequency converter. Firstly, the suitable operation conditions for variable speed controlled parallel pumps are studied. Secondly, methods for determining the output of each parallel pump unit using characteristic curve-based operation point estimation with frequency converter are discussed. Thirdly, the implementation of the control strategy based on real-time pump operation point estimation and sub-optimization of each parallel pump unit is studied. The findings of the thesis support the idea that the energy efficiency of the pumping can be increased without the installation of new, more efficient components in the systems by simply adopting suitable control strategies. An easily implementable and adaptive control strategy for variable speed controlled parallel pumping systems can be created by utilizing the pump operation point estimation available in modern frequency converters. Hence, additional real-time flow metering, start-up measurements, and detailed system model are unnecessary, and the pumping task can be fulfilled by determining a speed reference for each parallel-pump unit which suggests the energy efficient operation of the pumping system.

Business intelligence viewpoint on managerial decision-making : Ill-structured problems and decision support systems

Vaikka liiketoimintatiedon hallintaa sekä johdon päätöksentekoa on tutkittu laajasti, näiden kahden käsitteen yhteisvaikutuksesta on olemassa hyvin rajallinen määrä tutkimustietoa. Tulevaisuudessa aiheen tärkeys korostuu, sillä olemassa olevan datan määrä kasvaa jatkuvasti. Yritykset tarvitsevat jatkossa yhä enemmän kyvykkyyksiä sekä resursseja, jotta sekä strukturoitua että strukturoimatonta tietoa voidaan hyödyntää lähteestä riippumatta. Nykyiset Business Intelligence -ratkaisut mahdollistavat tehokkaan liiketoimintatiedon hallinnan osana johdon päätöksentekoa. Aiemman kirjallisuuden pohjalta, tutkimuksen empiirinen osuus tunnistaa liiketoimintatiedon hyödyntämiseen liittyviä tekijöitä, jotka joko tukevat tai rajoittavat johdon päätöksentekoprosessia. Tutkimuksen teoreettinen osuus johdattaa lukijan tutkimusaiheeseen kirjallisuuskatsauksen avulla. Keskeisimmät tutkimukseen liittyvät käsitteet, kuten Business Intelligence ja johdon päätöksenteko, esitetään relevantin kirjallisuuden avulla – tämän lisäksi myös dataan liittyvät käsitteet analysoidaan tarkasti. Tutkimuksen empiirinen osuus rakentuu tutkimusteorian pohjalta. Tutkimuksen empiirisessä osuudessa paneudutaan tutkimusteemoihin käytännön esimerkein: kolmen tapaustutkimuksen avulla tutkitaan sekä kuvataan toisistaan irrallisia tapauksia. Jokainen tapaus kuvataan sekä analysoidaan teoriaan perustuvien väitteiden avulla – nämä väitteet ovat perusedellytyksiä menestyksekkäälle liiketoimintatiedon hyödyntämiseen perustuvalle päätöksenteolle. Tapaustutkimusten avulla alkuperäistä tutkimusongelmaa voidaan analysoida tarkasti huomioiden jo olemassa oleva tutkimustieto. Analyysin tulosten avulla myös yksittäisiä rajoitteita sekä mahdollistavia tekijöitä voidaan analysoida. Tulokset osoittavat, että rajoitteilla on vahvasti negatiivinen vaikutus päätöksentekoprosessin onnistumiseen. Toisaalta yritysjohto on tietoinen liiketoimintatiedon hallintaan liittyvistä positiivisista seurauksista, vaikka kaikkia mahdollisuuksia ei olisikaan hyödynnetty. Tutkimuksen merkittävin tulos esittelee viitekehyksen, jonka puitteissa johdon päätöksentekoprosesseja voidaan arvioida sekä analysoida. Despite the fact that the literature on Business Intelligence and managerial decision-making is extensive, relatively little effort has been made to research the relationship between them. This particular field of study has become important since the amount of data in the world is growing every second. Companies require capabilities and resources in order to utilize structured data and unstructured data from internal and external data sources. However, the present Business Intelligence technologies enable managers to utilize data effectively in decision-making. Based on the prior literature, the empirical part of the thesis identifies the enablers and constraints in computer-aided managerial decision-making process. In this thesis, the theoretical part provides a preliminary understanding about the research area through a literature review. The key concepts such as Business Intelligence and managerial decision-making are explored by reviewing the relevant literature. Additionally, different data sources as well as data forms are analyzed in further detail. All key concepts are taken into account when the empirical part is carried out. The empirical part obtains an understanding of the real world situation when it comes to the themes that were covered in the theoretical part. Three selected case companies are analyzed through those statements, which are considered as critical prerequisites for successful computer-aided managerial decision-making. The case study analysis, which is a part of the empirical part, enables the researcher to examine the relationship between Business Intelligence and managerial decision-making. Based on the findings of the case study analysis, the researcher identifies the enablers and constraints through the case study interviews. The findings indicate that the constraints have a highly negative influence on the decision-making process. In addition, the managers are aware of the positive implications that Business Intelligence has for decision-making, but all possibilities are not yet utilized. As a main result of this study, a data-driven framework for managerial decision-making is introduced. This framework can be used when the managerial decision-making processes are evaluated and analyzed.

Mitigating uncertainty in logistics outsourcing with ERP systems

Outsourcing is a common strategy for companies looking for cost savings and improvements in performance. This has been especially prevalent in logistics, where warehousing and transporting are typical targets for outsourcing. However, while the benefits from logistics outsourcing are clear on paper, there are several cases companies fail to reach these benefits. The most commonly cited reasons for this are poor information flow between the company and the third party logistics partner, and a lack of integration between the two partners. Uncertainty stems from lack of information, and it can cripple the whole outsourcing operation. This is where enterprise resource planning (ERP) systems step in, as they can have a significant role in improving the flow of information, and integration, which consequently mitigates uncertainty. The purpose of the study is to examine if ERP systems have an effect on a company's decision to outsource logistics operations. Along the rapid advancements in technology during the past decades, ERP systems have also evolved. Therefore, empirical research on the subject needs constant revision as it can quickly become outdated due to ERP systems having more advanced capabilities every year. The research was conducted using a qualitative single-case study of a Finnish manufacturing firm that had outsourced warehousing and transportation operations in the Swedish market. The empirical data was gathered with use of semi-structured interviews with three employees from the case company that were closely related to the outsourcing operation. The theoretical framework that was used to analyze the empirical data was based on Transaction Cost Economics theory. The results of the study were align with the theoretical framework, in that the ERP system of the case company was seen as an enabler for their logistics outsourcing operation. However, the full theoretical benefits from ERP systems concerning extended enterprise functionality and flexibility were not attained due to the case company having an older version of their ERP system. This emphasizes the importance of having up-to-date technology if you want to overcome the shortcomings of ERP systems in outsourcing situations.

In search of information systems value : a case study of the EHR benefits realisation efforts of three Swedish hospitals.

The Swedish public health care organisation could very well be undergoing its most significant change since its specialisation during the late 19th and early 20th century. At the heart of this change is a move from using manual patient journals to electronic health records (EHR). EHR are complex integrated organisational wide information systems (IS) that promise great benefits and value as well as presenting great challenges to the organisation. The Swedish public health care is not the first organisation to implement integrated IS, and by no means alone in their quest for realising the potential benefits and value that it has to offer. As organisations invest in IS they embark on a journey of value-creation and capture. A journey where a costbased approach towards their IS-investments is replaced with a value-centric focus, and where the main challenges lie in the practical day-to-day task of finding ways to intertwine technology, people and business processes. This has however proven to be a problematic task. The problematic situation arises from a shift of perspective regarding how to manage IS in order to gain value. This is a shift from technology delivery to benefits delivery; from an ISimplementation plan to a change management plan. The shift gives rise to challenges related to the inability of IS and the elusiveness of value. As a response to these challenges the field of IS-benefits management has emerged offering a framework and a process in order to better understand and formalise benefits realisation activities. In this thesis the benefits realisation efforts of three Swedish hospitals within the same county council are studied. The thesis focuses on the participants of benefits analysis projects; their perceptions, judgments, negotiations and descriptions of potential benefits. The purpose is to address the process where organisations seek to identify which potential IS-benefits to pursue and realise, this in order to better understand what affects the process, so that realisation actions of potential IS-benefits could be supported. A qualitative case study research design is adopted and provides a framework for sample selection, data collection, and data analysis. It also provides a framework for discussions of validity, reliability and generalizability. Findings displayed a benefits fluctuation, which showed that participants’ perception of what constituted potential benefits and value changed throughout the formal benefits management process. Issues like structure, knowledge, expectation and experience affected perception differently, and this in the end changed the amount and composition of potential benefits and value. Five dimensions of benefits judgment were identified and used by participants when finding accommodations of potential benefits and value to pursue. Identified dimensions affected participants’ perceptions, which in turn affected the amount and composition of potential benefits. During the formal benefits management process participants shifted between judgment dimensions. These movements emerged through debates and interactions between participants. Judgments based on what was perceived as expected due to one’s role and perceived best for the organisation as a whole were the two dominant benefits judgment dimensions. A benefits negotiation was identified. Negotiations were divided into two main categories, rational and irrational, depending on participants’ drive when initiating and participating in negotiations. In each category three different types of negotiations were identified having different characteristics and generating different outcomes. There was also a benefits negotiation process identified that displayed management challenges corresponding to its five phases. A discrepancy was also found between how IS-benefits are spoken of and how actions of IS benefits realisation are understood. This was a discrepancy between an evaluation and a realisation focus towards IS value creation. An evaluation focus described IS-benefits as well-defined and measurable effects and a realisation focus spoke of establishing and managing an on-going place of value creation. The notion of valuescape was introduced in order to describe and support the understanding of IS value creation. Valuescape corresponded to a realisation focus and outlined a value configuration consisting of activities, logic, structure, drivers and role of IS.

OpenAIRE Guidelines for Literature Repositories, Data Archives and CRIS managers

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

E-thesis repository – processes and data

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Rising to the impossible challenge: the storage of all research data, forever?

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Preparing for CRIS: Challenges and Opportunities for Systems Integration at Finnish Universities

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Data Flows and Engaging Visualisations for Your Repositories

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014