A Maturity Model for a Digital Transformation
Abstract
Various disruptive digital technologies such as IoT, Artificial Intelligence, Big Data and Analytics, 3D Printing, Augmented Reality, Cybersecurity, Clouding, Autonomous Robots, Simulation, Horizontal and Vertical Integration challenge the traditional means of doing business. Also, factors such as fierce price competition due to price transparency, the increased demand for customized product and services, and so on force organizations to adapt to the rapid change in digital technologies. However, many companies have doubts about where to start their transformation process. In order to develop a roadmap, the companies should first identify their weaknesses and strengths in the context of digital transformation. Maturity models have been used for years in order to identify companies’ weaknesses and strengths. In this work, we proposed one such maturity model to determine the current readiness level of the companies in the context of digital transformation. Overall, we defined 5 dimensions and developed/adopted 76 questions for assessing digital maturity. These dimensions include “Leadership”, “Strategy”, “People”, Partnership and Resources”, and “Product, Process, and Services”. The proposed maturity model is among the few models that are based on sound theoretical frameworks already validated in earlier studies and/or widely used in the literature and practice.
1. Introduction
Increasing competition with digital technologies, transparency of prices, customer's power and the importance of online reputation have forced companies to adapt to the rapid transformation of digital technologies and enter a digital transformation (DT) process. By using digital technologies, we can define new business models and strategies to earn a competitive advantage and create efficiency in the corporate value chain. To achieve these goals, companies are trying to be more digital in their internal vertical processes and external horizontal processes. In addition, they attempt to improve their work efficiencies by using data-based services. Companies employ technologies and their tools such as IoT, virtual reality, big data, and financial technologies to efficiently serve customers. Conversely, considering that technology constantly renews itself, even those who have begun to experience this transformation must also constantly change. Moreover; digital transformation needs many technological platforms such as IOT, mobile devices, cloud computing, augmented reality, big data analytics, smart sensors, 3D printings, advanced human-machine interfaces, and location detection technologies.
However, using these technologies is insufficient for this transition process from the third industrial revolution to the fourth. Companies should also consider other dimensions such as human resources, strategy, and financial situations.
Furthermore, most companies lack knowledge about the transformation process. Their knowledge is not enough to evaluate their current conditions in terms of digitalization. Consequently, companies should identify their weaknesses and strengths in terms of digitalization before they start their transformation processes. When they find the main weaknesses in the work area, they can easily obtain an action plan to improve their weaknesses.
To satisfy this gap, the literature contains multiple maturity models related with other disciplines. Maturity models measure the ability of companies in terms of becoming more digital in their work areas. The model evaluates companies from different points of view and offers ideas about the current situation of enterprises. Maturity models have some important elements:
- Dimensions, and Sub-sections of dimensions, Number of levels to measure maturity, and Questions to evaluate current conditions
Firstly, dimensions are identified by experts. Dimensions are the main points of focus in the transformation process. For example, we can consider the use of technologies as a dimension of transformation. Moreover, to obtain a level of maturity in terms of dimensions, it should be divided into parts called sub-sections. Dimensions cannot be examined unaided. To examine the different point of view of the dimensions, they should have sub-sections. Also, maturity models need levels to measure the level of maturity. Besides, the maturity level can be determined with the help of the questions and check-lists. Before obtaining a maturity model, questions should be identified. Companies should establish their weaknesses with the help of these questions. In the next chapter, we discuss related maturity models in the literature. We will review these papers in terms of dimensions, sub-sections, levels, their weaknesses and their strengths in terms of digital transformation.
1.1. Maturity Models
Maturity models are used to define the current condition of a situation and determine the capability level of a company in terms of any discipline. Maturity models have been developed to help organizations increase software quality. One of the most famous maturity models in the literature is CMM (Capability Maturity Model) from the Software Engineering Institute [1]. CCM became a standard for the software engineering field. After the usage of MM in software engineering, maturity models became famous in all areas requiring assessment. Besides, maturity models have two vital phenomena which are dimensions and levels. Dimensions are used to define which type of main points should be considered while we assess the current level of the company. Deciding dimensions is an issue to consider before obtaining a maturity model because if we want to assess the current level of a company, we should not have a missing point in our model. Also, levels are another issue that should be given attention so as to determine where the company is processing its own procedures. To find the current level of the companies in terms of digital transformation, maturity models have been commonly used in the literature.
This study is structured as follows: Section two, describes frameworks such as EFQM [2], SAP BTS Model [3], Bosch DDM [4], and others as well as how we used these frameworks in our model. Section three develops our maturity model (its dimensions, levels, and questions). In section four, based on our survey questions obtained in previous sections, the evaluation system is presented to find the final score of a company’s digitalization level. In section five, we developed a pilot study for our own model on two SME companies. Finally, section six, concludes this work.
2. Background And Methodology
When we defined our maturity model dimensions and their levels, we used a particular framework methodology. We decided to use different methodologies for our particular dimensions.For example, to decide upon our dimensions, we used EFQM Excellence model dimensions [2] because their dimensions are well-defined and they also review all aspects of a company. Furthermore it is suitable to be transformed as a digital transformation maturity model. For levels and evaluation of dimensions, we used different tools for dimensions. Bou-Llusar et. al.’s empirical assessment of the EFQM Excellence Model [5] is applied for leadership and strategy. Also, we decided to use BITTMASS HRM Module [6] to evaluate the people dimension. Additionally, Digital SCM Agenda Survey Results defined by SAP BTS (Business Transformation Service Team) [3] was used to evaluate partnership and resources, and process, product and services.
After we chose our dimensions and level identification tools, we prepared a questionnaire to evaluate these aspects.
Also while defining our levels we used other tools:
- Bosch Data-Driven Manufacturing Model [4]: It is a concept that we used to decide our levels.
- OODA Loop [7]: It is a decision-making tool that enables individuals and organizations to strategize in every circumstance.
2.1. EFQM Excellence Model
EFQM Excellence model is a framework that shows how a company can achieve excellence. It has 5 enablers for evaluation [2].
2.2. BITTMASS Human Resources Management (HRM) Module
HR activities can be considered under 6 sub-dimensions:
- Recruitment and selection activities, Orientation activities, Training and development activities, Performance management and appraisal activities, Activities related to compensation and benefits, and HR data gathering and information creation
2.3. SAP BTS (Business Transformation Service Team) Digital SCM Agenda Survey Results and BCG Nine Enabler Technologies for Digital Transformation
SAP BTS defines 17 use cases [3] via industry experts and proved their applicability. We decided to use these 17 use cases to obtain our questionnaire for process, product, and services, as well as partnership and resources. Also, we used five levels (none-descriptive-predictive-prescriptive-self optimized) that are defined by [4] to measure the level of these use-cases. To easily decide which level the company can present, we used Nine Enablers technology defined by BCG [8]. BCG related technologies are shown in the table below.
Table 1: BCG Related Technologies
17 use-cases on Porter’s value chain are the followings (Figure 1):
Figure 1: 17 Use-cases of SAP BTS Team
2.4. Bosch GmbH Conceptual DDM Model [4]
*Concept of Data Driven manufacturing (Gröger, C. (2018). Building an Industry 4.0 Analytics Platform. Datenbank-Spektrum, 1-10.)
Figure 2: DDM Concept
It refers to the application of data analytics in manufacturing. It consists of the following steps:
- Real-world data, data integration, analysis, optimization, and adapted Process.
Firstly, data are gathered from the manufacturing process level via sensors. After this process, a huge amount of data is integrated (collection, cleaning, integration, and historization of big data) for the analysis. With the help of the data analytics tools mentioned above, data are analyzed and optimized (changing specific machine parameters). Optimized steps send to the enterprise control level as an adapted process. After this stage, optimized data at the enterprise level should be implemented to process level. The manufacturing control level (manufacturing executions systems) will help to construct a bridge between the enterprise and process level. This loop will always continue to obtain continuous improvement. Furthermore, to obtain continuous improvement, both organizational and IT-technical aspects should be considered.
2.5. OODA Loop
Figure 3: OODA Loop
Another framework that we used is the OODA Loop to determine the level of people questions. OODA Loop is a decision-making tool developed by military strategist John Boyd for information about how individuals and organizations regard every decision focused circumstance [7]. This cycle defines a process that we currently perform every minute of our lives. OODA Loop can also be considered as a model of individual and organizational learning and adaptation. This Loop consists of 4 steps as:
- Observe, Orient, Decide, and Act
While making a decision in the business area, we apply the following path in our decision-making processes. For example;
- Firstly, data is gathered via sensors.
- Secondly, giving meaning to (otherwise meaningless) data
- Thirdly, choosing the alternative that fits “best” to our objectives
- Finally, we realize the decision.
3. Maturity Model Of Digital Transformation
In our model, we constructed 5 dimensions to evaluate the digital maturity level of the companies. All these dimensions are taken from enablers of the EFQM excellence model. Our dimensions are the following:
- Leadership, Strategy, People, Partnership and Resources, and Process, Product, and Services
Table 2: Dimensions of the Maturity Model
After deciding the dimensions with the help of the EFQM excellence model, another major point is about how to measure their maturity levels. In this stage we used different frameworks for the questionnaire for dimensions. A questionnaire is prepared based on the followings (Table 3):
Table 3 indicates the significance of the questions in terms of what they measure
Table 3: Main crucial points of the dimensions
Some frameworks are used as level strategy of the dimensions:
- Grading scale (from zero to four) is used to determine the level of questions in leadership and strategy.
- OODA loop is used to determine the level of questions in People
- Bosch GmbH is used to determine the level of process, product and services, as well as partnership and resources
Also, BCG Nine digital enabler technologies easily determine which level the company can succeed in process, product and services, and partnership and resources dimensions
3.1. Leadership
Leadership is one of the major factors for the successful transformation of companies. Leadership style, support by top management, communication skills of the management team, and open-mindedness regarding risk taking are important phenomena for successful leadership. In this dimension we used Bou-Llusar et. all’s empirical assessment on EFQM for the questionnaire. The company level is evaluated with a grading scale from zero to four.
Also, all these levels have been measured into the scale of zero to four and the final score of the approach is obtained as the average of all these sub-levels. Table 4 contains some of the self-assessment questions for Leadership.
Table 4: Example questions for leadership
3.2. Strategy
Strategy is another important factor in the journey to digitalization since setting up a digital company starts with a clearly identified strategy. According to Tabrizi, leaders aim to improve their technological tools in their transition stage but hidden under this idea is the most important factor: which digital transformation should be guided by strategy. (Tabrizi et.al., “Digital Transformation is not about technology”, 2019). Based on the finding by Kane [9], digital strategy drives digital maturity and the power of a digital transformation strategy lies in its scope and objectives.
Strategies are also evaluated in the EFQM model in terms of both questionnaire and levels. Scoring is the same with the leadership. Some of the self-assessment questions for Strategy can be found in Table 5.
Table 5: Example questions for strategy
3.3. People
In this section, the crucial phenomena are the interaction between questions and digital technologies. According to the BITTMASS HRM module, human resources can be first reviewed under 5 sub-dimensions such as recruitment and selection activities, orientation activities, training and development activities, performance management and appraisal activities, activities related to compensation and benefits, and HR data gathering and information creation. Based on these dimensions, critical questions are defined. Table 7 offers the example questions for People in.
We used OODA loop levels and Bosch DDM levels to assess these sub-dimensions. If there is an action plan related with the question, there will be no level on this section and other levels are the following (Table 6):
Table 6: Meaning of each level
Table 7: Example questions for People
3.4. Process, Product and Services
At this section, we employed 11 use cases defined by the SAP BTS Model as a questionnaire to assess. They are the following:
- Business network for commodity parts, Business network for engineered parts, Additive manufacturing for plastic parts, Additive manufacturing for metal Parts, High volume equipment reliability analysis for predictive maintenance, High volume equipment reliability analysis for predictive product quality, Intelligent product, Augmented reality for warehousing, Augmented reality for production, Automated commissioning and packing, and Digital product history.
Also, while some use cases can be applicable for a company, they cannot be applicable for serving other sectors. Therefore, we added an applicable or not section for all use cases.
We defined our levels based on Bosch DDM as follows:
- None, Descriptive, Predictive, Prescriptive, and Self - optimized
Additionally, nine digital technologies related with these levels are defined in Section 2.3. Also, all digital technologies corresponding to these levels are indicated in Table 8.
Table 8: BCG 9 Technologies Defining Levels
However, if we only consider data analytics technologies, while some tools of the data analytics refer to descriptive levels, another tool can refer to predictive, prescriptive or self-optimized level(s). Also, we used these figures for partnership and resources dimensions at the same time. To make this tool clear, Table 9 is created:
Table 9: Data Analytics tools defining Levels
Based on the 11 use cases, Bosch DDM Levels, and BCG nine technologies, some examples of questions used in the model are defined in Table 10.
Table 10: Example questions for process, product, and services
3.5. Partnership and Resources
Within this dimension we used 6 remaining use cases from SAP BTS Model as our questionnaire to assess. They are the following:
- Supply Chain Control Tower, Flexible on-demand business IT, Geo-located shipping, Selling pattern analysis, Customer buying behavior analysis, and Trend mining
Although these cases are the crucial part of our work to assess, there are some points that did not discuss it, and so we added these cases as our assessment questionnaire. They are the following:
- Usage of social media, and Customer complaint data
When we consider all these resources, some points cannot be useful for some industries, so we added an applicable or not stage for the evaluation parts. Also, we used Bosch DDM levels to evaluate the maturity level as we did in the product, process, and services section(s). BCG nine technologies defining levels and data analytics tools defining levels figures remain the same for this section. Based on these eight use cases and our evaluation levels, the questionnaire is defined in Table 11.
Table 11: Example questions for partnership and resources
4. Evaluation System
When evaluating the final level of a company in terms of digital maturity, we considered all dimensions equally weighted. The total point will be 1000 points and all dimensions can have 200 points maximum. However, all dimensions have a different number of questions. To make all dimensions equally weighted, we multiply the final score of each dimension with a coefficient equalizing the final score to 200 points. All numbers are shown in Table 12.
Table 12: Evaluation System
In the end, the maturity level of a company can have a maximum of 1000 points. Based on the 5 different final levels of our model, the current level of a company is the following table (Table 13):
Table 13: Current Level of a company
5. Pilot Study
Also, we conducted a pilot study with two companies in Turkey. One of them is a SME and it has 200 employees serving in the textile industry. Second of them has 60 employees working in the automotive parts supply industry. It is one of the suppliers of the many established companies in Turkey. We conducted pilot studies with face-to-face communication. Even if this study can also serve as a self assessment tool, we thought face-to-face communication is the best way to make our outputs more reliable because we implemented our model as a pilot study.
First output is to determine maturity levels of all dimensions. According to the calculations final point of all dimensions are determined. (Figure 4).
Figure 4: Maturity Levels of all dimensions
Also, we try to see detailed results for all dimensions in terms of main points. Main points of the leadership were determined by the EFQM excellence model earlier. We try to see their weighted score by averaging the questions related with the relevant main point (Figure 5). For example, the first four questions of leadership are related to how the leaders establish vision, mission, values, and ethics. Then we take the average of these questions to determine the final score of the main point.
Figure 5: Detailed results for the leadership
When we make a comment about the results of the surveys, even if both companies have better grades in terms of leadership and strategy, they could not reflect perspectives of these areas in terms of technical issues and human resources management in the company.
Besides, we have received feedback on the clarity and consistency of the questions from these two enterprises. As a future work, we can make some small changes in our questions according to the feedback we have received but mostly they evaluated our questionnaire positively.
6. Concluding Remarks And Future Work
In conclusion, digital technologies will reshape the future of ways of doing business. In order to best respond to the changing needs of the companies and customers, the opportunities offered by modern technologies in the field of information and communication are suggested. More effective organizations and more effective service to customers as well as transforming business processes with the assistance of the digital technologies will help companies more quickly reach growth targets. Also, the increasing integration of the world and digital transformation produces unimaginable potential for technology and business so even if the digital transformation remains at the entry level, defining weaknesses and strengths is a crucial issue for all companies. This work aims to develop a maturity model for digital transformation to assess the current level of the companies in terms of digitalization. This model has been developed with the help of the different frameworks including a systematic literature review. This model will allow us to collect data about the current level of a company in terms of five different dimensions (Leadership, Strategy, People, Product, process, and services, Partnership and resources). According to the questionnaire obtained from this study, a company’s current effectiveness level can be identified in the context of digital transformation. Questionnaires are distributed to companies as a survey and according to their answers, weaknesses and the strengths of the companies can be detected. Companies can also use the questionnaire as a self-assessment tool. While developing this model, we consider the maturity model from two different points of view: one is technical aspects (product, process, and services, partnership and resources); and the other relates with the managerial and cultural side of the process (leadership, strategy, and people). In contrast to other models, this model has been developed to prove our questionnaire with the help of the different frameworks that have been previously validated.
Furthermore, managing digital transformation processes of the supply chain management is one of the key issues to pursue in the goal of digitization. In this target, it is essential to define crucial use cases and their level of the digital maturity. In this work we define supply chain management into product, process, and services, and partnership and resources dimensions. Also, 17 use cases are our sub-dimensions to be evaluated.
Future research activities may consist of implementing this model on companies and validating our model as a whole. Also, a strategy roadmap can be developed based on the results obtained from the maturity model. A strategy roadmap may focus on the weakness points of a company as defined in this model.
References
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