5 Transition to Platform-based Solutions
This chapter covers transition model development and results. The chapter presents how the development work was conducted and how it integrates the current state analysis findings with the literature review. Lastly, the chapter presents the transition model pro-posal with maturity assessments using the case company’s enterprise maturity model and the data derived from the interviews. The chapter also explains how the model was simulated with the group of companies.
5.1 Development Work
The proposed transition model aims to meet the thesis objective by assessing the trans-formation readiness through characteristics. The following sub-chapters consolidate the key findings from CSA as well as literature and lastly integrate the above-mentioned maturity assessments to provide more depth for the model.
Figure 11. Building blocks for transition model development
Conceptual framework
- Business & organization - System scope & infra - Product
- Industry
Transition model Stakeholder input (Data 2)
- Interview with Program Manager, Mechanical Design & Simulation
- Enterprise maturity assessments - Identification of challenges - Primary deliverables
Experiences from industries
(Data 1)
- Strategic partnerships - PLM system adoption - Centralized IT
organization - Globality
- Customer centricity
As seen in Figure 11, the development work for the transition model consists of three key building blocks. Transition model includes 11 attributes which are derived from the current state analysis and literature review, and furthermore validated with the case com-pany expert interviews. The attributes are structured under four attribute groups repre-senting the conceptual framework:
• Business and organization
• System scope and infra
• Product
• Industry
The current state analysis findings were discussed, and the enterprise maturity assess-ments co-created in the interview with the case company’s expert, Program Manager from Mechanical Design & Simulation. This phase refers to the Data 2 collection, and the objective was to identify the primary deliverables to create a portfolio-focus view for the transition model. Additionally, the conceptual framework that forms the transition model attribute groups and attributes were discussed. The key take-aways of this inter-view are consolidated in the next sub-chapters and within the transition model proposal, visualized in Figure 12.
5.1.1 Business and Organization
Findings from the current state analysis indicate that companies which have adopted the PLM system as a backbone for their product management leverage from transparency and harmonized ways of working, system usage complements organizations business strategy. Hadaya and Marchildon (2012: 4) stated that introduction of PLM enabled or-ganizations to shift from isolated applications to a set of systems. With dedicated PLM teams, organizations can widen PLM adoption, deploy custom solutions and scale fast.
New technology requires talent management, and according to Pessot et al. (2020: 9) it must be priority goal to increase knowledge base with skills aimed at proper use of tech-nology and overcome resistance to change by eliminating lack of expertise among em-ployees. The implementation of PLM requires strategy and competences, and organiza-tions with PLM system in use are more ready for transformation and realized business benefits. The following quotes are from the current state analysis interviews and highlight the benefits of PLM adoption for the organization.
PLM initiative has been driving the harmonization of tools and ways of working (CSA).
Digital transformation is enabling new business models, these are constantly un-der consiun-derations, the goal is to have a seamless digital continuity, PLM plays a major role in this (CSA).
After-sales services generates major revenues and smart service creation is one modern business need driving organizations to transform managerial and operational activities.
Porter and Heppelmann (2014: 3) describes the third wave of IT-driven competition in-cluding IT becoming an integral part of the product itself through connectivity and smart elements, coupled with product cloud where applications can be run. This is driving dra-matic improvements, enabled by increased amounts of product usage data. As an ex-ample, through these smart applications, first-time-fix rate can be increased when field engineer is dispatched with correct parts and tools for maintenance. To succeed with service-oriented product, competences and smart architecture needs to be aligned. Op-timization of customer interaction and integrated services through enabling technologies allows companies to deepen the relationship and induce more empowered end-custom-ers (Pessot et al. 2020: 9-11).
5.1.2 System Scope and Infra
The current state analysis interviews showed that most of the companies aim to harmo-nize system scope by fewer system providers with more strong strategic partnerships. In few cases, current state of disjointed systems and databases is a result from mergers and acquisitions. Although this was not a consensus finding, it shows that in most cases the transformation is driven by restraining the system providers to strategic partners ra-ther than fostering multiple supplier relations. The MIT Sloan Management Review’s re-search with Deloitte underlines that strategy, not technology drives digital transformation (Kane et al. 2015: 6).
Expected key benefits of cloud computing includes greater flexibility, better mobility &
information access, and cost reductions through optimized utilization & ICT employee reduction (Shou et al. 2019: 12). The current state analysis findings indicate that some of the organizations may encounter some restrictions on cloud-based systems and data storing. Industry regulations and contracts between stakeholders can dictate where data needs to be stored, and this could limit usage of public cloud systems. Regardless it is
evident that adoption of cloud-based systems contributes to transformation readiness when the information access is mobilized rather than restrained by stand-alone systems.
5.1.3 Product
Porter and Heppelmann (2015: 9) says that the smart connected products require re-thinking of design. Core functions like product development, IT, and manufacturing are being redefined by the changes in the work procedures and new functions are emerging to answer the needs of, for example increasing quantities of product data available. In-terviews showed that companies are aware of the impact of product characteristics to their business, and in many cases identified that increased complexity in products has resulted in increased complexity in system requirements. Complexity of a configurable product can stratify over time so that the maintenance costs of product configurator ele-vates in an uncontrollable way. Complexity needs to be managed top-down, considering the business needs, rather than just expanding complexity in accordance with techno-logical possibilities.
Deployment of digital twin technology is an excellent utilization of new rich data gener-ated by smart connected products. It provides inputs into how products can be better designed, manufactured, and serviced (Porter and Heppelmann 2015: 9). High level of complexity and smartness in the product drives transformation rather than very simple product composed of physical parts alone.
5.1.4 Industry
From the current state analysis interviews it was found that there are significant differ-ences on regulations between industries, and this affects how companies must produce, maintain, and distribute product information and data, especially during the beginning- and middle-of-life. These requirements vary a lot depending on the industry, healthcare and construction represents one of the most regulated. Power of customers is a similar external force affecting the product development and engineering systems. Customer centricity is one of the key findings from the industries. Requirements and expectations have changed and to foster the relations, organizations must re-assess the applicability of current systems and processes against customer needs.
5.2 Transition Model Proposal
Based on the findings from the literature as well as the current state analysis, the follow-ing attributes compose the transition model, assessfollow-ing readiness for transformation to-wards platform-based approach. Table 6 consolidates attribute groups, attributes, attrib-ute statements and research sources for the transition model.
Table 6. Transition model attributes
Attribute
group Attribute Attribute statement Source
Business &
organization
PLM adoption Adoption of PLM system drives transformation through processes, competences, and ways of working
Hadaya, P. and Marchil-don, P. (2012).
Pessot, E. et al. (2020).
System management Centralized IT organization is more effective for transformation than distributed
CSA & Development work
Service business Service oriented product and business needs of smart services drives transformation
Porter, M. and Hep-pelmann, J. (2014).
Pessot, E. et al. (2020).
System scope and infra
IT system providers Transformation is driven by restraining the sys-tem providers to strategic partners rather than fostering multiple supplier relations
Kane, G. et al. (2015).
Cloud-based systems
Adoption of cloud-based systems contributes to transformation readiness when the infor-mation access is mobilized rather than re-strained by stand-alone systems
Shou, Y. et al. (2019).
Systems interoperability
Jointed systems are essential for global opera-tions and part of technical foundation for digital transformation
Case company internal documentation
Systems support pro-duction prospects
Current system scope is supporting the devel-opment and manufacturability of prospective new products
Zhang, Q. et al. (2019)
CSA & Development work
Product
Complexity Complexity and configurability in the product drives transformation rather than standard product
Porter, M. and Hep-pelmann, J. (2015).
CSA & Development work
Level of smartness High level of smartness in the product drives transformation rather than very simple product composed of physical parts alone
Porter, M. and Hep-pelmann, J. (2015).
CSA & Development work
Industry
Power of customers Changes in customer behavior and expecta-tions are at the core of digital transformation
Porter, M. and Hep-pelmann, J. (2014).
CSA & Development work
External forces In highly regulated industries organizations must adapt to fulfil external requirements and systems must support this
CSA & Development work
As Table 7 presents, the scoring method is built for the transition model attributes for simulating the model with the group of companies on the interview scope. The scores are given from based on the data derived from the current state analysis interviews.
Furthermore, the results of the simulation are validated with the case company’s experts.
Table 7. Transition model attribute scoring method
Attribute
PLM adoption No Yes
System
Figure 12 consolidates the maturity assessments co-created with the case company’s expert within the Data 2 collection and the transition model simulation outcome. The simulation addresses the business potential by identifying the three portfolio-focus stages.
Figure 12. Transition model proposal
Portfolio-focus stages identifies the key deliverables of the case company. The group of companies are positioned on the x-axis based on their score using the scoring method built for the simulation. The next chapter addresses the transition model proposal valida-tion with the case company.
6 Final Proposal
This chapter addresses the validation of the transition model proposal and refers to the Data 3 collection according to the research design. The chapter describes how the pro-posal validation is conducted and what are the changes applied to the transition model.
Lastly, the chapter presents the validated final proposal of the transition model.
The transition model proposal was validated with two separate, one-on-one interviews with the case company’s experts. The author organized the proposal validation first with the MU Finland Engineering business Head. The presentation included a logical flow on what were the objectives, how the work was conducted, what were the phases and the work units, what are the key findings and the data sources that comprise the transition model, and how the transition model is simulated. The presentation was followed by a discussion on the work and the results. The changes were made to the portfolio-focus stages, by adding identifying names for the stages that represent the overall situation of an organization in given stage. Additionally, the business potential view that addressed the timespan was added to clarify the difference between the three portfolio-focus stages.
This was followed by the second validation, which was held by the author with the case company’s Sales Manager. The validation interview followed the same structure as the first one, but with more focus on the simulation outcome. The objective was to assess the reliability of the transition model simulation outcome as well as the co-created ma-turity assessments conducted within the Data 2 collection. There were no changes made to the simulation outcome nor the maturity assessments, as they were found reliable.
The adjusted portfolio-focus stages are next discussed, and the validated final proposal presented in Figure 13.
The business potential is categorized in three stages, where the portfolio-focus and the timespan alternates as a function of the score. The three portfolio-focus stages are Con-cept, Build, and Expand. For the Concept portfolio-focus stage it is too soon to start adopting platform-based solutions right away, but the focus should be on creating digital strategy and building roadmaps for the transition. By consulting services and incremental approach, the smooth transition from the application-based disjointed systems can be achieved so that the operations of product development and engineering are not discon-tinued.
The Build stage benefits by PLM processes for the key departments, so that the new rich data is captured, especially during the beginning-of-life phase of the product. The Ex-pand stage needs to utilize the product data from all the lifecycle phases to achieve end-to-end digital continuity. The organization wide PLM adoption adds value during the whole lifecycle, and external connections are important to assess, for integrating part-ners and customers to the design phase, as an example.
Figure 13. Transition model simulation
As Figure 13 visualizes, most of the companies are in the Expand stage, and have at least partially the platform-based approach to product development and engineering. Ac-cording to the two validation rounds with the case company’s experts, the results of the simulation are realistic and most-likely presents the current situation of the companies in a preferably validated level.
7 Conclusions
This thesis explored product development and product engineering within the manufac-turing industry, with an objective to create a model for assessing readiness for transfor-mation to platform-based approach with IT systems and tools. The point-of-view for the thesis research represented the case company’s view, an IT and Engineering service provider with strong resourceful capabilities for the manufacturing industry. The scope of the work was considerably large, and the work included a substantial amount of data collection and analysis. The following sub-chapters addresses the assessment of the work and the reliability and validity of the results.
7.1 Assessment of the Work
Research design was built for ensuring that all the objectives of the thesis were met, and that the work conducted was based on reliable elements. The starting point after setting the scope and the objectives was to conduct the interviews for a large group of respond-ents. Planning and organizing of the interviews, as well as transcripts took a considerable amount of time, and led to a comprehensive overview on the current state within the industries. Although, the demographics of the respondents could have been more even, regardless of the author’s efforts in given time, respondents from IT organization repre-sented most of the population over R&D and business sides.
The literature review was initiated when half of the interviews were done. The idea behind this approach was to first gain some understanding, what are the common and favorable approaches to product development and engineering, and to have an approach by liter-ature based on these findings. In retrospect, the literliter-ature review could have also been done before conducting the interviews, focusing on the topics around digital transfor-mation. When searching for previous research, it was found that many of the discovered publications were only related to the business challenge, which made research relevant and insightful but somewhat difficult to execute.
Overall, the co-operation with the author and both the case company as well as Metropo-lia side went successfully and the support given for the author was on a praiseworthy level throughout the thesis execution. Even earlier initiation of the literature review and language check process by the author could have shortened the overall throughput time of the thesis project.
The objective of the thesis was to propose a model for assessing readiness for transfor-mation to platform-based approach. The objective was met, a transition model was de-veloped, and its usability simulated with a group of companies. As its best it can be used to assess the transformation and business potential and used as a tool in the pre-sales phase of consulting services.
7.2 Reliability and Validity
The work was conducted by the author, co-operating with the case company’s experts.
Throughout the thesis execution, the author held weekly meetings with respective ex-perts from the case company, to review and steer the progress of the work and iterate the deliverables. Additionally, the author held meetings with the thesis supervisor on-demand, to steer the work and to make sure academic requirements were met.
The research design had a significant impact on the outcome of the thesis. Together with more precise plans for the work units it helped the author to stay on track and to focus on the relevant tasks. Also, the data collection plan was used to guide the work and prevent collection of non-relevant data throughout the execution.
The reliability of the transition model development work was ensured by the combination of three core data elements. Using different data sources and gathering methods it was ensured that the development work is not biased, but rather enforced by several inputs.
The information gathered from the industries by interviews was brought together with the literature and case company’s internal documentation, setting a solid base for address-ing the business challenge. Lastly, the development work was assessed, and the out-come validated by two iterations with the case company’s experts.
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