Data management as a part of performance management: Case study about production reporting development project

Because of the increased availability of different kind of business intelligence technologies and tools it can be easy to fall in illusion that new technologies will automatically solve the problems of data management and reporting of the company. The management is not only about management of technology but also the management of processes and people. This thesis is focusing more into traditional data management and performance management of production processes which both can be seen as a requirement for long lasting development. Also some of the operative BI solutions are considered in the ideal state of reporting system. The objectives of this study are to examine what requirements effective performance management of production processes have for data management and reporting of the company and to see how they are effecting on the efficiency of it. The research is executed as a theoretical literary research about the subjects and as a qualitative case study about reporting development project of Finnsugar Ltd. The case study is examined through theoretical frameworks and by the active participant observation. To get a better picture about the ideal state of reporting system simple investment calculations are performed. According to the results of the research, requirements for effective performance management of production processes are automation in the collection of data, integration of operative databases, usage of efficient data management technologies like ETL (Extract, Transform, Load) processes, data warehouse (DW) and Online Analytical Processing (OLAP) and efficient management of processes, data and roles.

Research Data Management in the Cloud

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

Private Equity Fund Performance Determinants: Evidence From Fund Characteristics

The purpose of this thesis is to investigate whether different private equity fund characteristics have any influence on the fund performance. Fund characteristics include fund type (venture capital or buyouts), fund size (sizes of funds are divided into six ranges), fund investment industry, fund sequence (first fund or follow-on fund) and investment market (US or EMEA). Fund performance is measured by internal rate of return, and tested by cross-sectional regression analysis with the method of Ordinary Least Squares. The data employs performance and characteristics of 997 private equity funds between 1985 and 2008. Our findings are that fund type has effect on fund performance. The average IRR of venture capital funds is 2.7% less than average IRR of buyout funds. However, We did not find any relationship between fund size and performance, and between fund sequence and performance. Funds based on US market perform better than funds based on EMEA market. The fund performance differs across different industries. The average IRRs of industrial/energy industry, consumer related industry, communications and media industry and medical/health industry are higher than the average IRR of other industries.

Tietovaraston uudelleensuunnittelu ja toteuttaminen

Tietovarastointi on yleistynyt yritysten raportoinnin tietolähteenä. Tietovarastojen avulla voidaan kehittää monipuolisia raportointiratkaisuja. Datamäärän ja käyttäjämäärän kasvu sekä raporttien monipuolistuminen aiheuttavat suorituskykyhaasteita. Tässä työssä käydään läpi tietovaraston uudelleensuunnittelu suorituskykyhaasteisiin keskittyen. Työn tavoitteena oli sekä tietovaraston käytön että ylläpidon tehostaminen. Työvaiheina olivat arkkitehtuurin kehittäminen, faktan ja dimensioiden optimointi, ETL-prosessin tehostaminen, paikallisvarastojen rakentaminen sekä osioinnin, indeksien ja aggregaatiosummien tehokkaampi hyödyntäminen. Tavoitteen toteutumista mitattiin toistamalla työn eri vaiheissa suorituskykytestejä. Tuloksena saavutettiin merkittävä suorituskyvyn parantuminen erityisesti työn aikana luoduissa paikallisvarastoissa. Tietovarastoon tehtävien kyselyiden ja hallintatoimenpiteiden kesto pieneni yleisesti noin kolmannekseen. Erillisiin käyttötarkoituksiin räätälöityihin paikallisvarastoihin tehtävien kyselyjen kesto pieneni noin kymmenykseen tai parhaassa tapauksessa jopa sadasosaan

Ensuring the efficient utilization of Business Intelligence

In recent years, chief information officers (CIOs) around the world have identified Business Intelligence (BI) as their top priority and as the best way to enhance their enterprises competitiveness. Yet, many enterprises are struggling to realize the business value that BI promises. This discrepancy causes important questions, for example: what are the critical success factors of Business Intelligence and, more importantly, how it can be ensured that a Business Intelligence program enhances enterprises competitiveness. The main objective of the study is to find out how it can be ensured that a BI program meets its goals in providing competitive advantage to an enterprise. The objective is approached with a literature review and a qualitative case study. For the literature review the main objective populates three research questions (RQs); RQ1: What is Business Intelligence and why is it important for modern enterprises? RQ2: What are the critical success factors of Business Intelligence programs? RQ3: How it can be ensured that CSFs are met? The qualitative case study covers the BI program of a Finnish global manufacturer company. The research questions for the case study are as follows; RQ4: What is the current state of the case company’s BI program and what are the key areas for improvement? RQ5: In what ways the case company’s Business Intelligence program could be improved? The case company’s BI program is researched using the following methods; action research, semi-structured interviews, maturity assessment and benchmarking. The literature review shows that Business Intelligence is a technology-based information process that contains a series of systematic activities, which are driven by the specific information needs of decision-makers. The objective of BI is to provide accurate, timely, fact-based information, which enables taking actions that lead to achieving competitive advantage. There are many reasons for the importance of Business Intelligence, two of the most important being; 1) It helps to bridge the gap between an enterprise’s current and its desired performance, and 2) It helps enterprises to be in alignment with key performance indicators meaning it helps an enterprise to align towards its key objectives. The literature review also shows that there are known critical success factors (CSFs) for Business Intelligence programs which have to be met if the above mentioned value is wanted to be achieved, for example; committed management support and sponsorship, business-driven development approach and sustainable data quality. The literature review shows that the most common challenges are related to these CSFs and, more importantly, that overcoming these challenges requires a more comprehensive form of BI, called Enterprise Performance Management (EPM). EPM links measurement to strategy by focusing on what is measured and why. The case study shows that many of the challenges faced in the case company’s BI program are related to the above-mentioned CSFs. The main challenges are; lack of support and sponsorship from business, lack of visibility to overall business performance, lack of rigid BI development process, lack of clear purpose for the BI program and poor data quality. To overcome these challenges the case company should define and design an enterprise metrics framework, make sure that BI development requirements are gathered and prioritized by business, focus on data quality and ownership, and finally define clear goals for the BI program and then support and sponsor these goals.

Improving reporting management with relational database management system

Data management consists of collecting, storing, and processing the data into the format which provides value-adding information for decision-making process. The development of data management has enabled of designing increasingly effective database management systems to support business needs. Therefore as well as advanced systems are designed for reporting purposes, also operational systems allow reporting and data analyzing. The used research method in the theory part is qualitative research and the research type in the empirical part is case study. Objective of this paper is to examine database management system requirements from reporting managements and data managements perspectives. In the theory part these requirements are identified and the appropriateness of the relational data model is evaluated. In addition key performance indicators applied to the operational monitoring of production are studied. The study has revealed that the appropriate operational key performance indicators of production takes into account time, quality, flexibility and cost aspects. Especially manufacturing efficiency has been highlighted. In this paper, reporting management is defined as a continuous monitoring of given performance measures. According to the literature review, the data management tool should cover performance, usability, reliability, scalability, and data privacy aspects in order to fulfill reporting managements demands. A framework is created for the system development phase based on requirements, and is used in the empirical part of the thesis where such a system is designed and created for reporting management purposes for a company which operates in the manufacturing industry. Relational data modeling and database architectures are utilized when the system is built for relational database platform.

Optimization and Applications of Large-Scale Biomedical Event Networks

The overwhelming amount and unprecedented speed of publication in the biomedical domain make it difficult for life science researchers to acquire and maintain a broad view of the field and gather all information that would be relevant for their research. As a response to this problem, the BioNLP (Biomedical Natural Language Processing) community of researches has emerged and strives to assist life science researchers by developing modern natural language processing (NLP), information extraction (IE) and information retrieval (IR) methods that can be applied at large-scale, to scan the whole publicly available biomedical literature and extract and aggregate the information found within, while automatically normalizing the variability of natural language statements. Among different tasks, biomedical event extraction has received much attention within BioNLP community recently. Biomedical event extraction constitutes the identification of biological processes and interactions described in biomedical literature, and their representation as a set of recursive event structures. The 2009–2013 series of BioNLP Shared Tasks on Event Extraction have given raise to a number of event extraction systems, several of which have been applied at a large scale (the full set of PubMed abstracts and PubMed Central Open Access full text articles), leading to creation of massive biomedical event databases, each of which containing millions of events. Sinece top-ranking event extraction systems are based on machine-learning approach and are trained on the narrow-domain, carefully selected Shared Task training data, their performance drops when being faced with the topically highly varied PubMed and PubMed Central documents. Specifically, false-positive predictions by these systems lead to generation of incorrect biomolecular events which are spotted by the end-users. This thesis proposes a novel post-processing approach, utilizing a combination of supervised and unsupervised learning techniques, that can automatically identify and filter out a considerable proportion of incorrect events from large-scale event databases, thus increasing the general credibility of those databases. The second part of this thesis is dedicated to a system we developed for hypothesis generation from large-scale event databases, which is able to discover novel biomolecular interactions among genes/gene-products. We cast the hypothesis generation problem as a supervised network topology prediction, i.e predicting new edges in the network, as well as types and directions for these edges, utilizing a set of features that can be extracted from large biomedical event networks. Routine machine learning evaluation results, as well as manual evaluation results suggest that the problem is indeed learnable. This work won the Best Paper Award in The 5th International Symposium on Languages in Biology and Medicine (LBM 2013).

R&D Expenditures and Firm Performance: Empirical Evidence on Finnish Data

Tutkielman tavoitteena on tutkia yrityksen tutkimus- ja tuotekehitystoiminnan (T&K) vaikutuksia yrityksen suorituskykyyn. Tutkielmassa tarkastellaan myös lyhyesti T&K- toimintaa osana yrityksen toimintoja ja ympäristöä. Tutkielman empiirisessä osassa tutkitaan poikkileikkausmenetelmää käyttäen T&K- menojen vaikutusta yrityksen kasvuun, kannattavuuteen ja osakkeen hintaan (tuottoon). Tutkielman empiirinen osa toteutettiin keräämällä tilinpäätös- ja osaketiedot 65 yritykselle vuosilta 1999-2005. T&K- menojen vaikutusta yrityksen kasvuun, kannattavuuteen ja osakkeen tuottoon tutkittiin eri aikavälejä käyttäen, jotta mahdolliset syy-seuraussuhteet voitaisiin luotettavasti osoittaa. Tutkimustulokset osoittavat, että yrityksen T&K- menoilla on positiivinen vaikutus yrityksen kasvuun ja kannattavuuteen ja,siten tulokset tukevat kahta tutkimuksen päähypoteesia. Yrityksen T&K- menoilla ja osakkeen tuoton välillä ei kuitenkaan käytetyllä aineistolla empiiristä yhteyttä löytynyt, joten kolmas päähypoteesi hylättiin.

Information integration and its impacts on logistics performance - Using information technology and systems to facilitate information integration

Fast changing environment sets pressure on firms to share large amount of information with their customers and suppliers. The terms information integration and information sharing are essential for facilitating a smooth flow of information throughout the supply chain, and the terms are used interchangeably in research literature. By integrating and sharing information, firms want to improve their logistics performance. Firms share information with their suppliers and customers by using traditional communication methods (telephone, fax, Email, written and face-to-face contacts) and by using advanced or modern communication methods such as electronic data interchange (EDI), enterprise resource planning (ERP), web-based procurement systems, electronic trading systems and web portals. Adopting new ways of using IT is one important resource for staying competitive on the rapidly changing market (Saeed et al. 2005, 387), and an information system that provides people the information they need for performing their work, will support company performance (Boddy et al. 2005, 26). The purpose of this research has been to test and understand the relationship between information integration with key suppliers and/or customers and a firm’s logistics performance, especially when information technology (IT) and information systems (IS) are used for integrating information. Quantitative and qualitative research methods have been used to perform the research. Special attention has been paid to the scope, level and direction of information integration (Van Donk & van der Vaart 2005a). In addition, the four elements of integration (Jahre & Fabbe-Costes 2008) are closely tied to the frame of reference. The elements are integration of flows, integration of processes and activities, integration of information technologies and systems and integration of actors. The study found that information integration has a low positive relationship to operational performance and a medium positive relationship to strategic performance. The potential performance improvements found in this study vary from efficiency, delivery and quality improvements (operational) to profit, profitability or customer satisfaction improvements (strategic). The results indicate that although information integration has an impact on a firm’s logistics performance, all performance improvements have not been achieved. This study also found that the use of IT and IS have a mediocre positive relationship to information integration. Almost all case companies agreed on that the use of IT and IS could facilitate information integration and improve their logistics performance. The case companies felt that an implementation of a web portal or a data bank would benefit them - enhance their performance and increase information integration.

Let's do data research work: the creation of a portal with research information from Catalan Universities

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

Evaluation of performance analysis software for Linux computing cluster

Tietokonejärjestelmän osien ja ohjelmistojen suorituskykymittauksista saadaan tietoa,jota voidaan käyttää suorituskyvyn parantamiseen ja laitteistohankintojen päätöksen tukena. Tässä työssä tutustutaan suorituskyvyn mittaamiseen ja mittausohjelmiin eli ns. benchmark-ohjelmistoihin. Työssä etsittiin ja arvioitiin eri tyyppisiä vapaasti saatavilla olevia benchmark-ohjelmia, jotka soveltuvat Linux-laskentaklusterin suorituskyvynanalysointiin. Benchmarkit ryhmiteltiin ja arvioitiin testaamalla niiden ominaisuuksia Linux-klusterissa. Työssä käsitellään myös mittausten tekemisen ja rinnakkaislaskennan haasteita. Benchmarkkeja löytyi moneen tarkoitukseen ja ne osoittautuivat laadultaan ja laajuudeltaan vaihteleviksi. Niitä on myös koottu ohjelmistopaketeiksi, jotta laitteiston suorituskyvystä saisi laajemman kuvan kuin mitä yhdellä ohjelmalla on mahdollista saada. Olennaista on ymmärtää nopeus, jolla dataa saadaan siirretyä prosessorille keskusmuistista, levyjärjestelmistä ja toisista laskentasolmuista. Tyypillinen benchmark-ohjelma sisältää paljon laskentaa tarvitsevan matemaattisen algoritmin, jota käytetään tieteellisissä ohjelmistoissa. Benchmarkista riippuen tulosten ymmärtäminen ja hyödyntäminen voi olla haasteellista.

Reporting Framework: Implementation and Performance Analysis

Fenix on suuri metsäteollisuuden tuotannonohjausjärjestelmä. Fenix-järjestelmän raportointi- ja tulostuspalvelut elävätvaihdekautta. Aikaisemmin käytetyt raportointityökalut ovat vanhentumassa ja neon korvattava uusilla. Uusi raportointialusta, Global Printing System (GPS), onrakennettu StreamServe Business Communication Platformin ympärille. Uuden alustan on tarkoitus hoitaa Fenixin tulostus sekä raportointitehtävät. Työ kuvaa raportointialustan toteutuksen sekä sen tärkeimmät ominaisuudet. Uuden alustan suorituskyvyssä on ollut toivomisen varaa. Etenkin suurien raporttien generoiminen on kestänyt joskus toivottoman pitkään. Työssä analysoidaan raportointialustan suorituskykyä ja etsitään mahdolliset pullonkaulat. Suorituskyvyn heikkouksiin pyritään löytämään ratkaisut ja annetaan ehdotuksia suorituskyvyn parantamiseksi. XML pohjaisena järjestelmänä GPS:n suorituskyvyssä suurta osaaesittää XML:n tehokkuus. GPS sisääntuleva data tulee XML-muodossa ja sisääntulon parsimisen tehokkuus on avaintekijöitä koko GPS:n tehokkuuden kannalta. Suorituskyvyn parantamisessa keskitytäänki vahvasti XML:n tehokkaampaan käyttöön ja esitetään ehdotuksia sen parantamiseksi.