1 Introduction
The digitalization process creates new data and information. The digital transformation of a company has the potential to generate new knowledge. Data thereby lays the foundation for the application of digital information technologies within the company. (1) Digital solutions serve as an important lever for long-term growth, profitability, competitiveness and value creation (2, 3). The integration of information technologies offers strategic advantages through the simplification and optimization of business processes. Numerous industries already benefit from optimized coordination of capacities and resources. (4) The German quarrying industry, which is predominantly represented by small and medium-sized enterprises (SMEs), has a low level of digitalisation compared to other industries (5). Digital transformation is impaired in particular by high investment and utilization costs, high implementation efforts, and heterogeneous machine fleets (6). Thereby the use of digital platforms can lead to higher sales, greater customer acquisition, or the company’s general costs being reduced through efficiency gains (7). An increase in efficiency within the quarrying industry can, e. g., be achieved on the basis of data-based forecasts, which enable the demand-oriented adjustment of operating resource capacities at peak loads (8). In this article, the functions of the data-centric platform demonstrator “PROmining”, developed in the AiF research project, are tested and validated on the basis of a case study with three companies in the sector. The platform shall lead to the improvement of the forecasting ability and increase the capacity of SMEs in the quarrying industry. The platform demonstrator provides marginally digitalized companies with a tool with functions ranging from simple operational data collection, over capacity utilization evaluation, to regional demand scenario development, that can be used as a blueprint within their own company. This provides companies in the quarrying industry with a low-cost entry into the digital transformation and contributes to their long-term competitiveness.
2 Functionality of the platform demonstrator
The methodology for developing a data-centric platform and a corresponding operator model for SMEs in the German quarrying industry is described in detail in earlier publications of the PROmining research project (8, 9). Therefore, the aim of this paper is to test and validate the developed web-based demonstrator of a platform in a company-specific manner and to describe the transformation process through participation in a digital platform solution. The web-based platform demonstrator offers companies in the quarrying industry various tools and services for standardised data acquisition and evaluation. In addition, a demonstration tool for regional demand forecasting is provided. This will be presented and published in detail at the Conference on Production Systems and Logistics (CPSL) 2023 in Mexico, yet is not considered in the case study described in chapter 3 and 4. The relevant tools and services for this paper are briefly described below.
2.1 Identities
Identities and their roles within the platform are defined on the basis of company-typical hierarchical levels and thus form the Identity Management. Each individual role is guaranteed an appropriate level of access rights to create an optimum between free access to information and verification (10). Furthermore, identity determination serves to divide individual decision-making units into their areas of competence, thereby driving an increase in productivity through the specialization of different groups in terms of knowledge levels and skills (11). As a result, three suitable identities were designed in the research project – Management, Quarry Manager, Operator – to enable all necessary personnel levels within the quarrying company to use the platform. A precise breakdown of the role definition can be reviewed in the journal “Sonderheft Nachhaltigkeit und Digitalisierung 2022” (12).
2.2 Data capture
The German quarrying industry faces a major challenge regarding data acquisition and processing. Heterogeneous plant and asset inventories cause data compliance deficiencies, making data analysis difficult. Expert interviews show that, in particular condition data of mobile equipment is currently recorded in an analogous fashion using pen and paper, although manufacturer-based platforms are available. High technical and monetary entry barriers as well as reservations about profit-oriented operator models, prevent participation in such pioneering technologies. (7) Analog data entry with pen and paper leads to multiple handling of data records and can result in incorrect entries due to missing plausibility checks. The application developed in the research project enables the digital-manual entry of condition data and ensures standardized and uniform data management in the platform database, with the result that multiple entries are avoided. Equipment data as well as shift-related information are directly fed into the platform by machine operators.
2.3 Data evaluation
The company is presented with standardized and relevant key performance and consumption indicators, which are visualized on the platform’s dashboard. Based thereon, unused capacities in plants and operational equipment can be analysed and identified. By utilizing the relative performance indicators of operational equipment and plants, certain correlations can be made recognizable. Since the performance indicators are meaningfully related to each other, e. g., litres per ton or tons per person-hours, performances can be compared over a fixed period of time (13). The “management” identity can define performance targets for individual production sites in order to maximize capacity utilization. By analysing the available data and performance indicators, companies increase their forecast accuracy regarding resource availability and thus improve their planning capabilities. The obtained condition data can be used to make statements about the utilisation, efficiency and effectiveness of an operation.
3 Methodology and design of the study
In order to be able to generate a meaningful validation and testing of the platform demonstrator, a case study with three companies in the quarrying industry will be conducted. The method and design of the study are shown in figure 1.
Fig. 1. Methodology and study design for the company-specific implementation, testing and validation of the platform solution as well as for the investigation of the transformation process. // Bild 1. Methode und Design der Fallstudie zur unternehmensspezifischen Implementierung, Testung und Validierung der Plattformlösung sowie zur Untersuchung des Transformationsprozesses. Source/Quelle: MRE
Firstly, the initial situation of the companies is recorded using the morphology developed in the research project (8). Subsequently, the companies become participants of the platform. For this purpose, the successful accession is tested via various interfaces and identities of the platform. A guideline-based survey of the different corporate identities will be conducted to test the effectiveness of the platform functions. The inclusion of extensive feedback from all relevant participants enables the iterative adaptation of the web-based demonstrator according to the specific user requirements. Finally, the transformation process in the company is evaluated via the accession of the platform, using the Business Transformation Canvas according to Gudergan et al. (14).
4 Results of the case study
4.1 Recording of the initial situation
The participating companies of the case study are considered on the basis of internal assessment dimensions “company structure”, “company processes” and “company development” (10) by applying the morphological matrix (Figure 2).
Fig. 2. Morphology for identifying the business typology according to its digital maturity (8). // Bild 2. Morphologie zur Bestimmung der Unternehmenstypologie nach der digitalen Reife (8).
In the morphological method, the problem at hand is first analysed, then it is broken down into relevant parameters. These parameters are constituent features of the issues to be addressed. Subsequently, possible expressions are identified for each parameter. (15) Finally, the companies are assigned a specific enterprise type.
By interviewing the management, the position of the considered company is classified into the morphology (Figure 2). In addition, company parameters are systematically recorded using a standardised questionnaire and then compared with the categories of the morphology. Following the first classification the companies are differentiated into three types, “digitally expandable”, “digitally advanced” and “digital pioneer” (Figure 3) (8).
Fig. 3. Typification of companies by defining their digital maturity (8). // Bild 3. Typisierung der Unternehmen anhand der digitalen Reife (8).
Thereby some similarities, especially in the areas of “corporate structure” and “corporate processes” become evident. Deviations are particularly noticeable in the digital maturity of the companies. In all companies, the access to manufacturer platforms is available, yet shift-related information is additionally recorded with pen and paper. Based on the developed typification, the companies included in the case study are ranked as the type “digitally advanced” (Figure 3).
4.2 Company-specific implementation
The companies become participants of the platform demonstrator. For this purpose, the successful accession via the various interfaces of the platform is tested in three steps:
- Entry of master data regarding locations, operating resources, facilities and employees by the identity “Management” using a desktop PC.
- Input of shift information (date, start of work, end of work, location, activity), as well as status data on equipment and facilities – e. g., fuel consumption, operating hours, tonnages – by the identity “Operator” using mobile devices (tablet and smartphone).
- Auditing the inputs from step 2 and evaluating the calculated and visualised key performance indicators by the identity “Quarry Manager“, using a desktop PC and mobile devices.
4.3 Validation of the platform solution through guideline-based expert interviews
The survey method used to validate the platform solution is the guided expert interview, which is considered the primary instrument for obtaining data on company knowledge. In this context, experts are persons with specific knowledge about the interviewed company, i. e. detailed knowledge about internal structures and events. (16) For the successful design of an expert interview, a thematic guidance of the interview with the help of a guideline is necessary (17). As part of the testing and validation of the platform solution, developed in the research project, the participants of the case study were questioned within three categories about the expected acceptance, usability and operability of the platform. The thematically relevant statements of the expert survey are listed below:
- The acceptance of digital analytics software is generally increasing within the company, but is strongly dependant on the digital skills of the employees. Initially, a defensive attitude towards a new digital tool is to be expected.
- Intuitive usability of the platform, as the functions are structured in a sensible way for individual processes.
- Time saving, especially for the role management, as information previously noted in analogue form does not have to be transferred to Excel or other software solutions.
- Plausibility check enables the avoidance of errors during data entry.
- Functions enable low-effort input and analysis of recordable data.
- Application as a digital operational log is realistic and sensible.
- Necessity of an operating point with constant internet connection for digital data input.
- Export of the database in various file formats and integration into the in-house software via various interfaces is necessary for the extensive use of the platform solution in digitally advanced companies.
At the end of the validation, the usability of the platform is assessed using an evaluation questionnaire. A total of nine people (3x management, 3x quarry manager, 3x operators) from three companies are interviewed. The average usability rating of the platform by the case study participants is shown in figure 4.
Fig. 4. Average usability ratings of the platform by the case study participants. // Bild 4. Durchschnittliche Nutzbarkeitsbewertungen der Plattform durch die Teilnehmer der Fallstudie. Source/Quelle: MRE
4.4 Business Transformation Canvas
In the last step of the case study, the business transformation as a result of the platform integration is assessed with the participants of the role “management“ using the Business Transformation Canvas according to Gudergan et al. (14). The Canvas pursues the goal of supporting business transformations. It includes the steps of creating a transformation strategy, designing the new system and the path towards it, as well as the implementation. The transformation is divided into fields of action that have a significant influence on the success of the transformation. In a compact presentation, as shown in figure 5, the canvas allows a quick overview of relevant areas and factors (14).
Fig. 5. Business Transformation Canvas – Impact of digital platforms on quarrying companies. Own Illustration based on (14). // Bild 5. Business Transformation Canvas – Auswirkung digitaler Plattformen auf Steine- und Erdenunternehmen. Eigene Darstellung nach (14)
Participants of the case study were asked about fields which acutely affect a platform introduction. There is particular agreement on the influence on structures and processes. Structurally, the redistribution of tasks, up to and including the creation of a digitalisation officer, is a foreseeable change. Resultingly competences for digital systems have to be created, which in contrast free up capacities for data collection. From a process perspective, changes in process duration are expected. Therefore, the possibility arises that the work process for individuals (operators) is prolonged, yet the overall process can be shortened. In addition, the use of the platform will have to be focused on the process side, and specific processes may have to be elaborated.
5 Conclusion and outlook
The case study for the PROmining research project was conducted with three digitally advanced companies in the quarrying industry. The results show that shift-related information regarding operational equipment and employees in particular, is currently still recorded in an analogue form in an operation log. The functions of the platform demonstrator enable the digital acquisition and visual evaluation of this condition data. The validation process by means of interviews with experts has resulted that, the application is intuitive to use, processes are simplified and an error free, standardised as well as unique method of recording data is enabled. The platform offers companies with, in particular, previously low levels of digitalisation an entry into digital business transformation.
The utilisation of digital information technologies, changes the company culture and processes and requires new skills and qualifications. Therefore, the objective must be to appropriately adapt the digital maturity of the company to the increasing digital competitive environment and thus draw advantages from digitalisation (18). The platform solution developed in the PROmining research project consequently represents an entry into digital transformation for quarrying companies, that have hardly been digitalised to date, and can be used as a digital operations diary. Furthermore, it is recommended to take the initiative in intensifying the digital business transformation, as digitalisation is not expected to abate in the future.
Acknowledgment
We would like to thank all the companies that have participated in the PROmining research project over the last two years. Their participation has laid the foundation for a successful development process. We would like to thank Benjamin Diebels (MRE – RWTH Aachen University) and Julius Tischbein, Nick Lober, Maximilian Lucas and Janick Diercks (all FIR e. V.) for their active support in carrying out the research project and developing the platform demonstrator.
Annotation
The research project 21480 N is funded by the AiF within the framework of the program for the promotion of joint industrial research (IGF) of the Federal Ministry of Economics and Climate based on a resolution of the German Bundestag. Any opinions, findings, and recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the correspondent institutions.
References / Quellenverzeichnis
References / Quellenverzeichnis
(1) Jacob, M. (2019): Digitalisierung & Nachhaltigkeit. Zweibrücken: Springer Vieweg. https://doi.org/10.1007/978-3-658-26217-4
(2) Deloitte (2022): Perspektiven 2030. Wachstumschancen für Deutschland.
(3) McKinsey & Company (2021): Industrielles IoT und führende Technologien als Treiber der digitalen Transformation in der Produktion.
(4) Erner, M. (2019): Management 4.0 – Unternehmensführung im digitalen Zeitalter. Heilbronn: Springer Gabler. https://doi.org/10.1007/978-3-662-57963-3
(5) Deloitte (2018): Tracking the trends 2018: The top 10 issues shaping mining in the year ahead.
(6) Braun, T.; Hennig, A. (2016): Untersuchungen zur Betriebsstruktur deutscher Natursteintagebaue. In: Berg- und Huettenmaennische Monatshefte 161, S. 181 – 186.
(7) Kofler, T. (2018): Das digitale Unternehmen. München: Springer Vieweg. https://doi.org/10.1007/978-3-662-57617-5
(8) Lassen, J. et al. (2021): Das Potential digitaler Plattformlösungen. In: Sonderheft Nachhaltigkeit & Digitalisierung 2021, S. 8 – 12.
(9) Müller, J. et al. (2022): Improving Forecasting Capability and Capacity Utilization in Less Digitized Industries Through Participation in the Platform Economy. In: Camarinha-Matos, L. M.; Ortiz, A.; Boucher, X.; Osório, A. L. (Hg.): Collaborative Networks in Digitalization and Society 5.0. PRO-VE 2022. IFIP Advances in Information and Communication Technology, vol 662. Springer, Cham. https://doi.org/10.1007/978-3-031-14844-6_12
(10) Silberberger, H. (2003): Collabrotive Bubsiness und Web Services. Heidelberg: Springer Berlin. https://doi.org/10.1007/978-3-642-19028-5
(11) Schuh, G.; Kampker, A. (2011): Strategie und Management produzierender Unternehmen. 2. Auflage. Aachen: Springer Berlin. https://doi.org/10.1007/978-3-642-14502-5
(12) Lassen, J. et al. (2021): Fortschritt beim Projekt PROmining. Eine digitale Plattform zur standardisierten Datenaufnahme und -auswertung für die Steine-und-Erden-Industrie entsteht. In: Sonderheft Nachhaltigkeit & Digitalisierung 2022, S. 6 – 9.
(13) Günther, T. (2015): Baustellenmanagement im Anlagenbau. Lünen: Springer Vieweg.
(14) Gudergan et al. (2017): Ordnungsrahmen für den Prozess der Business-Transformation. In: Pollety, W.; Blaeser-Benfer, A. (Hg.): Digitalisierung: Betriebliche Handlungsfelder der Unternehmensentwicklung. 1. Auflage. S. 155-173.
(15) Schawel, C.; Billing F. (2017): Morphologischer Kasten. In: Schawel, C.; Billing, F. (Hg.): Top 100 Management Tools. Wiesbaden: Gabler. https://doi.org/10.1007/978-3-8349-4691-1
(16) Meuser, M.; Nagel, U. (1989): Experteninterviews – vielfach erprobt, wenig bedacht: ein Beitrag zur qualitativen Methodendiskussion. (Arbeitspapier/Sfb 186, 6). Bremen: Universität Bremen, SFB 186 Statuspassagen und Risikolagen im Lebensverlauf. https://nbn-resolving.org/urn:nbn:de:0168-ssoar-57737
(17) Meuser, M.; Nagel, U. (2009): Das Experteninterview – konzeptionelle Grundlagen und methodische Anlage. In: Pickel, S.; Pickel, G.; Lauth, H. J.; Jahn, D. (Hg.): Methoden der vergleichenden Politik- und Sozialwissenschaft. VS Verlag für Sozialwissenschaften. https://doi.org/10.1007/978-3-531-91826-6_23
(18) Gudergan et al. (2021): Digitale Transformation durch die Entwicklung datenbasierter Dienstleistungen – Erforschung von Transformationsmustern und Merkmalen datenbasierter Dienstleistungen für die Ableitung des Smart Service Engineerings als Handlungsleitfaden für Unternehmen. In: Dienstleistungsinnovationen durch Digitalisierung, 2021, S. 49 – 105. Berlin, Heidelberg: Springer Gabler. https://doi.org/10.1007/978-3-662-62144-8