Product master data (PMD) can be defined as a set of data that represents a selection of characteristics and aspects of its accompanying physical product. For several reasons, these data sets are increasingly exchanged between organizations within supply chains. Although this process is traditionally often supported by non-automated technologies such as Excel spreadsheet, telephone, email, and fax, the adoption of data pools is on the rise. These inter-organizational systems allow the data supplying party to publish a product’s master data set in one centralized system after which it can be accessed by all subscribed data recipients.

Management of Technology

Abstract Products and services are critical for companies as they create the foundation for companies’ financial success. Twenty per cent of company products typically account for some eighty per cent of sales volume. Nevertheless, the product portfolio decisions — how to strategically renew company product offering — tend to involve emotions, pet products and who-shout-the-loudest mentality while facts, numbers, and quantitative analyses are missing. Profitability is currently measured and reported at a company level, and firms seem unable to measure product-level profitability in a constant way. Consequently, companies are unable to maintain and renew their product portfolio in a strategically or commercially balanced way. The main objective of this study is to provide a data-driven product portfolio management (PPM) concept, which recognises and visualises in real-time and based on facts which company products are concurrently strategic and profitable, and what is the share of them in the product portfolio. This dissertation is a qualitative study to understand the topical area by the means combining literature review, company interviews, observations, and company internal material, to take steps towards data-driven decision-making in PPM. This study indicates that company data assets need to be combined and governed company-widely to realise the full potential of company strategic assets — the DATA. Data must be governed separately from business IT technology and beyond it. Beyond data and technology, the data-driven company culture must be adopted first. The data-driven PPM concept connects key business processes, business IT systems and several concepts, such as productization, product lifecycle management and PPM. The managerial implications include, that the shared understanding of the company products is needed, and the commercial and technical product structures are created accordingly, as they form the backbone of the company business as the skeleton to gather all product-related business-critical information for product-level profitability analysis. Also, product classification for strategic, supportive and non-strategic is needed, since the strategic nature of the product can change during the entire product lifecycle, e.g. due to the technology obsolescence, disruptive innovations by competitors, or for any other reason.

Tiivistelmä Tuotteet ja palvelut ovat yrityksille kriittisiä, sillä ne luovat perustan yritysten taloudelliselle menestykselle. Kaksikymmentä prosenttia yrityksen tuotteista edustaa tyypillisesti noin kahdeksaakymmentä prosenttia myyntimääristä. Siitä huolimatta tuoteporfoliopäätöksiin — kuinka strategisesti uudistetaan yrityksen tuotetarjoomaa — liittyy tunteita, lemmikkituotteita ja kuka-huutaa-kovimmin -mentaliteettia faktojen, numeroiden ja kvantitatiivisten analyysien puuttuessa. Kannattavuutta mitataan ja raportoidaan tällä hetkellä yritystasolla, ja yritykset eivät näyttäisi pystyvän mittaamaan tuotetason kannattavuutta johdonmukaisesti. Tämä estää yrityksiä ylläpitämästä…

Abstract Master data describes business objects that are shared across an entire enterprise. Master data is a single source of information that should be used across the IT systems and business processes without changing. Definitions and understanding of common data and how well it is understood forms the basis for understanding the master data. The main objective of this study is to clarify how one product data should be understood and defined and to identify the main challenges and the best practices for managing the one product data for business processes. This study approaches one product data for integrated business processes from several perspectives by focusing on one product master data, data ownership, and the importance of a governance model for managing the master data. The means also to determine business value of master data and to ensure that a company’s success in reaching this business value is analysed. The findings of this study reveal the need for balance between business processes, data, and IT systems. The study indicates that a governance model is necessary in conjunction with business processes, data, and IT systems to ensure that an adequate foundation is created for one product data. One product data is the sum of product-related business data and one product master data. One product master data is the “DNA” of a product that is created by the product portfolio management process and is stored and controlled by a Product Lifecycle Management IT-system that updates the receiving systems in business processes with the common product data. One product data forms the basis for integrated business processes. In the product life cycle context, this means that data must be in place from the new product development phase to the maintenance phase, as well as across sales processes, supply chains, and care/service processes. Discontinuous data is harmful as it causes extra costs in management and slows down data analysis, as well as affects the reaction speed around changes on the business side. New business opportunities such as digitalisation may become very difficult if centralised one product data is not in place. It is important to keep in mind that if data integrity and quality are not in place in a company, adding new business models might be very challenging.

Tiivistelmä Master data on informaatiota, joka on määritelty yksiselitteisesti ja sitä käytetään muuttumattomana ylitse eri IT- järjestelmien ja -prosessien. Datamäärityksillä tuetaan liiketoiminnan prosesseja. Datan määritelmät ja yleinen datan ymmärtämisen taso yrityksessä ovat tärkeitä elementtejä, muodostaen pohjan Master data -käsitteelle. Tämän tutkimuksen päätarkoituksena on selkiyttää kuinka yksiselitteinen tuotetieto tulisi ymmärtää ja määritellä. Samalla identifioidaan suurimmat haasteet ja parhaat käytänteet yhdenmukaisen tuotetiedon hallinnalle. Tutkimuksessa keskitytään yhtenäisen master datan käsitteistön, datan omistajuuden, sekä hallinnointimallin tärkeiden näkökulmien kautta kokonaisuuden ymmärtämiseen useista eri…

Abstract The productivity of projects in the construction sector has not developed as well as in other sectors. One factor contributing to this low productivity is the weak digital intensity of the construction sector. Often, the implementation of construction projects is fragmented, and the objectives of the project stakeholders’ conflict with those of the whole project. Existing research has highlighted the importance of the use of building information modelling in the construction industry. In some other sectors, the product data lifecycle management has an essential role in their business, but in the construction industry, product data management has less attention. The motivation for this dissertation is to help the construction industry to gain the benefits that the use of BIM can provide. The focus is on enhancing data utilisation because late and fragmented management of information during the project lifecycle leads to defects and rework. This dissertation’s aim is on how to enhance data utilisation in construction projects by enabling early integration of stakeholders. The technical description of the data transfer format has not been in the scope of this research. This dissertation does not either include descriptions of all the commercial project delivery models. This compilation dissertation consists of qualitative studies with literature reviews, focus group interview, survey, and interviews. It identifies practical obstacles to the wider use of information modelling, how information modelling supports early involvement and integration, and the benefits of early integration. Finally, it produces a model for data and information management for construction projects. The main contribution of this study is that it identifies a need to design a unique project product data model in the early phases of the project, according to the information of all stakeholders. One master data enables data sharing with different applications. Design for X (DfX) can be used for early integration. The client is responsible that the project delivery agreements support the well-organised use of data and information flow throughout the project’s lifecycle. The most significant barrier for achieving the benefits of BIM is that the data needs and the overall process of BIM utilisation are not planned proactively. The practical implications are written mainly from the infrastructure construction project angle. The main impact is that the project product data model is better to design specially for each unique project that matches the capability level of the project team, available data, software and hardware, project delivery type, and team motivation.

Tiivistelmä Rakennusalla hankkeiden tuottavuus ei ole kehittynyt yhtä hyvin kuin muilla aloilla. Yksi tähän alhaiseen tuottavuuteen vaikuttava tekijä on rakennusalan heikko digitaalinen intensiteetti. Rakennusprojektien toteutus on usein hajanaista, ja hankkeen sidosryhmien tavoitteet ovat ristiriidassa koko projektin tavoitteiden kanssa. Olemassa oleva tutkimus on korostanut…