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.

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.

Business intelligence and management control

The purpose of this study is to explore the possibilities of utilizing business intelligence (BI)systems in management control (MC). The topic of this study is explored trough four researchquestions. Firstly, what kind of management control systems (MCS) use or could use the data and information enabled by the BI system? Secondly, how the BI system is or could be utilized? Thirdly, has BI system enabled new forms of control or changed old ones? The fourth and final research question is whether the BI system supports some forms of control that the literature has not thought of, or is the BI system not used for some forms of control the literature suggests it should be used? The study is conducted as an extensive case study. Three different organizations were interviewed for the study. For the theoretical basis of the study, central theories in the field of management control are introduced. The term business intelligence is discussed in detail and the mechanisms for governance of business intelligence are presented. A literature analysis of the uses of BI for management control is introduced. The theoretical part of the study ends in the construction of a framework for business intelligence in management control. In the empirical part of the study the case organizations, their BI systems, and the ways they utilize these systems for management control are presented. The main findings of the study are that BI systems can be utilized in the fields suggested in the literature, namely in planning, cybernetic, reward, boundary, and interactive control. The systems are used both as the data or information feeders and directly as the tools. Using BI systems has also enabled entirely new forms of control in the studied organizations, most significantly in the area of interactive control. They have also changed the old control systems by making the information more readily available to the whole organization. No evidence of the BI systems being used for forms of control that the literature had not suggested was found. The systems were mostly used for cybernetic control and interactive control, whereas the support for other types of control was not as prevalent. The main contribution of the study to the existing literature is the insight provided into how BI systems, both theoretically and empirically, are used for management control. The framework for business intelligence in management control presented in the study can also be utilized in further studies about the subject.

On advancing business intelligence in the electricity retail market

In recent decades, business intelligence (BI) has gained momentum in real-world practice. At the same time, business intelligence has evolved as an important research subject of Information Systems (IS) within the decision support domain. Today’s growing competitive pressure in business has led to increased needs for real-time analytics, i.e., so called real-time BI or operational BI. This is especially true with respect to the electricity production, transmission, distribution, and retail business since the law of physics determines that electricity as a commodity is nearly impossible to be stored economically, and therefore demand-supply needs to be constantly in balance. The current power sector is subject to complex changes, innovation opportunities, and technical and regulatory constraints. These range from low carbon transition, renewable energy sources (RES) development, market design to new technologies (e.g., smart metering, smart grids, electric vehicles, etc.), and new independent power producers (e.g., commercial buildings or households with rooftop solar panel installments, a.k.a. Distributed Generation). Among them, the ongoing deployment of Advanced Metering Infrastructure (AMI) has profound impacts on the electricity retail market. From the view point of BI research, the AMI is enabling real-time or near real-time analytics in the electricity retail business. Following Design Science Research (DSR) paradigm in the IS field, this research presents four aspects of BI for efficient pricing in a competitive electricity retail market: (i) visual data-mining based descriptive analytics, namely electricity consumption profiling, for pricing decision-making support; (ii) real-time BI enterprise architecture for enhancing management’s capacity on real-time decision-making; (iii) prescriptive analytics through agent-based modeling for price-responsive demand simulation; (iv) visual data-mining application for electricity distribution benchmarking. Even though this study is from the perspective of the European electricity industry, particularly focused on Finland and Estonia, the BI approaches investigated can: (i) provide managerial implications to support the utility’s pricing decision-making; (ii) add empirical knowledge to the landscape of BI research; (iii) be transferred to a wide body of practice in the power sector and BI research community.

Business intelligence – enabling self-service: A case study in a global manufacturing company

Business intelligence (BI) is an information process that includes the activities and applications used to transform business data into valuable business information. Today’s enterprises are collecting detailed data which has increased the available business data drastically. In order to meet changing customer needs and gain competitive advantage businesses try to leverage this information. However, IT departments are struggling to meet the increased amount of reporting needs. Therefore, recent shift in the BI market has been towards empowering business users with self-service BI capabilities. The purpose of this study was to understand how self-service BI could help businesses to meet increased reporting demands. The research problem was approached with an empirical single case study. Qualitative data was gathered with a semi-structured, theme-based interview. The study found out that case company’s BI system was mostly used for group performance reporting. Ad-hoc and business user-driven information needs were mostly fulfilled with self-made tools and manual work. It was felt that necessary business information was not easily available. The concept of self-service BI was perceived to be helpful to meet such reporting needs. However, it was found out that the available data is often too complex for an average user to fully understand. The respondents felt that in order to self-service BI to work, the data has to be simplified and described in a way that it can be understood by the average business user. The results of the study suggest that BI programs struggle in meeting all the information needs of today’s businesses. The concept of self-service BI tries to resolve this problem by allowing users easy self-service access to necessary business information. However, business data is often complex and hard to understand. Self-serviced BI has to overcome this challenge before it can reach its potential benefits.

Business intelligence – enabling self-service: A case study in a global manufacturing company

Business intelligence (BI) is an information process that includes the activities and applications used to transform business data into valuable business information. Today’s enterprises are collecting detailed data which has increased the available business data drastically. In order to meet changing customer needs and gain competitive advantage businesses try to leverage this information. However, IT departments are struggling to meet the increased amount of reporting needs. Therefore, recent shift in the BI market has been towards empowering business users with self-service BI capabilities. The purpose of this study was to understand how self-service BI could help businesses to meet increased reporting demands. The research problem was approached with an empirical single case study. Qualitative data was gathered with a semi-structured, theme-based interview. The study found out that case company’s BI system was mostly used for group performance reporting. Ad-hoc and business user-driven information needs were mostly fulfilled with self-made tools and manual work. It was felt that necessary business information was not easily available. The concept of self-service BI was perceived to be helpful to meet such reporting needs. However, it was found out that the available data is often too complex for an average user to fully understand. The respondents felt that in order to self-service BI to work, the data has to be simplified and described in a way that it can be understood by the average business user. The results of the study suggest that BI programs struggle in meeting all the information needs of today’s businesses. The concept of self-service BI tries to resolve this problem by allowing users easy self-service access to necessary business information. However, business data is often complex and hard to understand. Self-serviced BI has to overcome this challenge before it can reach its potential benefits.

Business Intelligence Competency Centerin perustaminen: Case LähiTapiola

Tässä diplomityössä selvitetään case-tutkimuksena parhaita käytäntöjä Business Intelligence Competency Centerin (BICC) eli liiketoimintatiedonhallinnan osaamiskeskuksen perustamiseen. Työ tehdään LähiTapiolalle, jossa on haasteita BI-alueen hallinnoinnissa kehittämisen hajaantuessa eri yksiköihin ja yhtiöihin. Myös järjestelmäympäristö on moninainen. BICC:llä tavoitellaan parempaa näkyvyyttä liiketoiminnan tarpeisiin ja toisaalta halutaan tehostaa tiedon hyödyntämistä johtamisessa sekä operatiivisen tason työskentelyssä. Tavoitteena on lisäksi saada kustannuksia pienemmäksi yhtenäistämällä järjestelmäympäristöjä ja BI-työkaluja kuten myös toimintamalleja. Työssä tehdään kirjallisuuskatsaus ja haastatellaan asiantuntijoita kolmessa yrityksessä. Tutkimuksen perusteella voidaan todeta, että liiketoiminnan BI-tarpeita kannattaa mahdollistaa eri tasoilla perusraportoinnista Ad-hoc –raportointiin ja edistyneeseen analytiikkaan huomioimalla nämä toimintamalleissa ja järjestelmäarkkitehtuurissa. BICC:n perustamisessa liiketoimintatarpeisiin vastaaminen on etusijalla.

Business Intelligence: Microsoft Power BI

Työn tavoitteena on tutkia Business Intelligencen ja BI-työkalujen vaatimusten kehittymistä viime vuosien aikana ja tutkia miten Microsoft Power BI -ohjelmisto vastaa modernin päätöksenteon tarpeisiin. Työ on toteutettu suurimmalta osin kirjallisuuskatsauksena, minkä lisäksi Microsoft Power BI:n toiminnallisuutta on tutkittu käytännössä käyttäen ohjelmiston ilmaisversiota. Tutkimuksessa on havaittu, että tiedon lähteiden määrän ja datan monimuotoisuuden kasvaessa on syntynyt tarve uusille, tehokkaille BI-järjestelmäratkaisuille, jotka hyödyntävät uudenlaisia menetelmiä. Modernissa BI 2.0 -mallissa korostuvat kehittyneemmän verkkoinfrastruktuurin ja ohjelmistotekniikan täysi hyödyntäminen, käytön helppous, tiedon tuottaminen ja jakaminen massoille, tiedon rikastamisen mahdollistaminen ja visualisoinnin ja interaktiivisuuden keskeinen asema tiedon tulkinnassa. Tutkimuksen perusteella Microsoft Power BI vaikuttaisi täyttävän keskeneräisyydestään ja muutamista tiedonhallinnallisista puutteistaan huolimatta lähes kaikki toimivan BI 2.0 -järjestelmän määritelmistä. Ohjelmisto tarjoaa riittävät analyyttiset ja esitystekniset työkalut useimpien tyypillisten käyttäjien tarpeisiin, minkä lisäksi paranneltu Location Intelligence -ratkaisu sekä uudet Q&A ja nopea oivallus -toiminnot luovat mielenkiintoisen tavan selata dataa. Jää nähtäväksi, miten ratkaisu kehittyy vielä tulevaisuudessa.

Die Business Community als CRM-Instrument unter besonderer Berücksichtigung von Business Intelligence Technologien

Das Management von Kundenbeziehungen hat sich in der klassischen Ökonomie unter dem Begriff »Customer Relationship Management« (kurz: CRM) etabliert und sich in den letzten Jahren als erfolgreicher Ansatz erwiesen. In der grundlegenden Zielsetzung, wertvolle, d.h. profitable und kreditwürdige Kunden an ein Unternehmen zu binden, kommen Business-Intelligence Technologien zur Generierung von Kundenwissen aus kundenbezogenen Daten zum Einsatz. Als technologische Plattform der Kommunikation und Interaktion gewähren Business Communities einen direkten Einblick in die Gedanken und Präferenzen der Kunden. Von Business-Communitybasiertem Wissen der Kunden und über Kunden können individuelle Kundenbedürfnisse, Verhaltensweisen und damit auch wertvolle (potenzielle, profilgleiche) Kunden abgeleitet werden, was eine differenziertere und selektivere Behandlung der Kunden möglich macht. Business Communities bieten ein umfassendes Datenpotenzial, welches jedoch bis dato für das CRM im Firmenkundengeschäft respektive die Profilbildung noch nicht genutzt wird. Synergiepotenziale von der Datenquelle "Business Community" und der Technologie "Business Intelligence" werden bislang vernachlässigt. An dieser Stelle setzt die Arbeit an. Das Ziel ist die sinnvolle Zusammenführung beider Ansätze zu einem erweiterten Ansatz für das Management der irmenkundenbeziehung. Dazu wird ein BIgestütztes CRM-Konzept für die Generierung, Analyse und Optimierung von Kundenwissen erarbeitet, welches speziell durch den Einsatz einer B2B-Community gewonnen und für eine Profilbildung genutzt wird. Es soll durch die Anbindung von Fremddatenbanken Optimierung finden: In den Prozess der Wissensgenerierung fließen zur Datenqualifizierung und -quantifizierung externe (Kunden-) Daten ein, die von Fremddatenbanken (wie z.B. Information Provider, Wirtschaftsauskunftsdienste) bereitgestellt werden. Der Kern dieser Zielsetzung liegt in der umfassenden Generierung und stetigen Optimierung von Wissen, das den Aufbau einer langfristigen, individuellen und wertvollen Kundenbeziehung unterstützen soll.

Sistema d'anàlisi financer: tresoreria amb eines Business Intelligence

El projecte tracte d' implementar una solució de Business Intelligence sota la plataforma Microsoft.Aquest projecte va destinat al Departament de Comptabilitat de l' Ajuntament de Cambrils, i està relacionat amb la funció del control de les despeses i els ingressos