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Efficient financial reporting is critical for organizational decision-making and agility. As decision-making is becoming increasingly data-driven, companies often find themselves facing challenges, such as high data fragmentation, low process automation, and limited data visualization capabilities. Striving to gain a competitive edge, companies often turn to Business Intelligence (BI) solutions. While adopting BI has become increasingly popular in companies of varying sizes, prior research has focused on larger scale implementations which require substantial resources. Design science research (DSR) was conducted, adopting the perspective of end users within one company’s finance department to address the gap. Further motivation and real-world relevance were ensured by conducting the research as a case study of a Finnish company. Three research questions were formulated to examine (1) current challenges in internal financial reporting, (2) desired improvements and potential risks, and (3) requirements for a BI solution to address them. The research utilized an overarching DSR methodology, complemented by another recently published methodology designed to address project complexity through a new organizing logic. Literature reviews provided support especially in artifact creation. Extensive one-on-one interviews were utilized as the primary data collection method and held with finance department employees. DSR methodologies were interlaced with thematic analysis, all six phases of which were utilized in qualitative analysis of the collected empirical data. Challenges were identified, including laborious data conversion, reporting cycle delays, and elevated risk of human error due to manual importing and exporting of data across systems. Desired improvements were also identified, including advanced data analytics and enhanced data consolidation. Finally, potential risks were identified, including inadequate access to low-delay support and insufficient training regarding BI tools. Analyzed results were discussed and utilized in artifact refinement. Design knowledge contributions included (a) a validated problem statement, which provided answers to the first and second research question; and (b) a validated requirement specification for a BI solution, which answered the third research question and concluded that the abovementioned problem statement could be addressed with a BI solution. It was also concluded that the new DSR methodology is highly suitable for small-scale studies.
Keywords: Financial Reporting, Business Intelligence, Design Science Research, Data-Driven Decision-Making, Process Optimization, Operational Finance
Tehokas sisäinen talousraportointi on keskeinen edellytys organisaatioiden datalähtöiselle päätöksenteolle ja operatiiviselle ketteryydelle. Digitaalisen datan merkitys päätöksenteossa kasvaa ja monet yritykset kohtaavat talousraportoinnissaan haasteita, kuten datan sirpaleisuutta ja hankaluuksia datan visualisoinnissa. Tavoitellessaan kilpailuetua yritykset kääntyvät usein liiketoimintatiedon (Business Intelligence, BI) hallintaratkaisujen puoleen. BI-ratkaisujen hyödyntäminen on yleistynyt kaikenkokoisissa yrityksissä, mutta aiempi tieteellinen tutkimus on keskittynyt suuren mittakaavan implementointeihin, jotka vaativat merkittäviä resursseja. Tämä tutkimus toteutettiin suunnittelutieteellisenä tutkimuksena (Design Science Research, DSR), jonka näkökulmaksi valittiin aiemmasta tutkimuksesta poiketen yksittäisen suomalaisen yrityksen talousosaston loppukäyttäjät. Laadittiin kolme tutkimuskysymystä tarkastelemaan (1) sisäisen talousraportoinnin nykyisiä puutteita, (2) toivottuja parannuksia ja potentiaalisia riskejä, sekä (3) BI-ratkaisulle asetettavaa vaatimusmäärittelyä. Tutkimuksessa hyödynnettiin kokonaisvaltaista DSR-metodologiaa, jota täydennettiin projektin kompleksisuutta uudenlaisella organisointilogiikalla hallitsevalla ja äskettäin julkaistulla DSR-metodologialla. Kirjallisuuskatsaukset tukivat erityisesti artefaktien kehittämistä. Empiirinen aineisto kerättiin kattavilla, yksilöhaastatteluina toteutetuilla teemahaastatteluilla yrityksen taloushallinnon työntekijöiltä. Kerätty aineisto analysoitiin kvalitatiivisesti hyödyntämällä temaattista analyysia, jonka kuusi vaihetta sisällytettiin DSR-viitekehykseen. Tuloksissa tunnistetiin puutteita, kuten datan konvertoinnin työläys ja viiveet raportointisykleissä. Tuloksissa tunnistettiin toivottuja kehitysalueita, kuten kehittyneempi data-analytiikka ja datan parempi konsolidointi. Tuloksissa tunnistettiin myös potentiaalisia riskejä, kuten teknisten tukipalvelujen saatavuuden pitkä vasteaika ja riittämätön koulutus BI-työkalujen käyttöön. Tulokset sisällytettiin vahvistettuun ongelmanmäärittelyyn, joka tuotti vastauksen ensimmäiseen ja toiseen tutkimuskysymykseen. Kolmanteen tutkimuskysymykseen vastattiin tuottamalla vahvistettu vaatimusmäärittely BI-ratkaisulle. Johtopäätöksenä todettiin, että vahvistetun ongelmanmäärittelyn komponentit voidaan ratkaista BI:n avulla. Tutkimus osoitti myös, että uusi DSR-metodologia soveltuu hyvin pro gradun kaltaisiin pienimuotoisiin tutkimuksiin.
Talousraportointi, liiketoimintatiedon hallinta, suunnittelutieteellinen tutkimus, datalähtöinen päätöksenteko, prosessioptimointi, operatiivinen taloushallinto
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As decision-making is becoming increasingly data-driven, companies often find themselves facing challenges, such as high data fragmentation, low process automation, and limited data visualization capabilities. Striving to gain a competitive edge, companies often turn to Business Intelligence (BI) solutions. While adopting BI has become increasingly popular in companies of varying sizes, prior research has focused on larger scale implementations which require substantial resources. Design science research (DSR) was conducted, adopting the perspective of end users within one company\u2019s finance department to address the gap. Further motivation and real-world relevance were ensured by conducting the research as a case study of a Finnish company. Three research questions were formulated to examine (1) current challenges in internal financial reporting, (2) desired improvements and potential risks, and (3) requirements for a BI solution to address them. The research utilized an overarching DSR methodology, complemented by another recently published methodology designed to address project complexity through a new organizing logic. Literature reviews provided support especially in artifact creation. Extensive one-on-one interviews were utilized as the primary data collection method and held with finance department employees. DSR methodologies were interlaced with thematic analysis, all six phases of which were utilized in qualitative analysis of the collected empirical data. Challenges were identified, including laborious data conversion, reporting cycle delays, and elevated risk of human error due to manual importing and exporting of data across systems. Desired improvements were also identified, including advanced data analytics and enhanced data consolidation. Finally, potential risks were identified, including inadequate access to low-delay support and insufficient training regarding BI tools. Analyzed results were discussed and utilized in artifact refinement. Design knowledge contributions included (a) a validated problem statement, which provided answers to the first and second research question; and (b) a validated requirement specification for a BI solution, which answered the third research question and concluded that the abovementioned problem statement could be addressed with a BI solution. It was also concluded that the new DSR methodology is highly suitable for small-scale studies.\n\nKeywords: Financial Reporting, Business Intelligence, Design Science Research, Data-Driven Decision-Making, Process Optimization, Operational Finance", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Tehokas sis\u00e4inen talousraportointi on keskeinen edellytys organisaatioiden datal\u00e4ht\u00f6iselle p\u00e4\u00e4t\u00f6ksenteolle ja operatiiviselle ketteryydelle. Digitaalisen datan merkitys p\u00e4\u00e4t\u00f6ksenteossa kasvaa ja monet yritykset kohtaavat talousraportoinnissaan haasteita, kuten datan sirpaleisuutta ja hankaluuksia datan visualisoinnissa. Tavoitellessaan kilpailuetua yritykset k\u00e4\u00e4ntyv\u00e4t usein liiketoimintatiedon (Business Intelligence, BI) hallintaratkaisujen puoleen. BI-ratkaisujen hy\u00f6dynt\u00e4minen on yleistynyt kaikenkokoisissa yrityksiss\u00e4, mutta aiempi tieteellinen tutkimus on keskittynyt suuren mittakaavan implementointeihin, jotka vaativat merkitt\u00e4vi\u00e4 resursseja. T\u00e4m\u00e4 tutkimus toteutettiin suunnittelutieteellisen\u00e4 tutkimuksena (Design Science Research, DSR), jonka n\u00e4k\u00f6kulmaksi valittiin aiemmasta tutkimuksesta poiketen yksitt\u00e4isen suomalaisen yrityksen talousosaston loppuk\u00e4ytt\u00e4j\u00e4t. 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