Research Data within the Qualification Program of the Project Digital Coach Intelligence

The task of the digital coach is to support the members of the organisation in developing and implementing AI solutions in order to improve quality management. In doing so, it is crucial for them to know what resistances and potentials exist in the development and implementation in each individual case of a small and medium-sized enterprise (SME). • What challenges or resistance could arise in the development and implementation of AI solutions in the context of promoting quality management? • How should these resistances be weighted? • To what extent are these resistances classified as changeable by the respective members of the organisation? • Which activities or action strategies prove to be particularly suitable for dealing with resistance appropriately? Your opinion is important to us! How do you rate the following potentials and resistances in terms of their importance? In your opinion, to what extent can the factors mentioned be utilised or expanded (in relation to potential) and changed (in relation to resistance)? 0= not at all IMPORTANCE not important Very important =5 FACTORS REF. Business Understanding UTILISATION/EXPANDABILITY (FOR POTENTIAL) CHANGEABILITY (FOR RESISTANCE) None Opinion 0%= ga Not high Very high =100% 0 1 2 3 4 5 Potentials Χ 0 20 40 60 80 100 There is already experience with regard to digitalisation projects There is already sufficient data collection and analysis Employees are trained for future tasks with support systems Costs are saved through the use of AI AI can serve as a solution for a specific challenge (concrete vision) The members of the organisation have sufficient AI knowledge We have sufficient skills in dealing with AI solutions in our organisation 0 1 2 3 4 5 Resistors Χ 0 20 40 60 80 100 It is difficult to define the business problem that forms the basis for the AI use case. There is no budget available for future qualification requirements and training courses There is no strategy on how to deal with AI in the future. The business objectives required for the implementation of AI solutions are not clearly formulated Subscribe to DeepL Pro to edit this document. Visit www.DeepL.com/pro for more information. The benefits of AI solutions in terms of costs are difficult to measure There are reservations about AI because members of the organisation fear for their jobs What solutions do you know for utilising the potential and dealing with resistance? (Specify as selectively as possible) General comments / questions regarding business understanding Which questions remain unanswered in the Business Understanding (Which) (tools) (help) (you) (further) (and) (why?)? 1. 2. 3. How do you rate the following potentials and resistances in terms of their importance? In your opinion, to what extent can the factors mentioned be utilised or expanded (in terms of potential) and changed (in terms of resistance)? Where do you see the strengths and weaknesses of the business understanding tools? And if so, which topics are the most important for you? most important? How do you rate the following potentials and resistances in terms of their importance? In your opinion, to what extent can the factors mentioned be utilised or expanded (in terms of potential) and changed (in terms of resistance)? IMPORTANCE 0= not important at all Very important =5 FACTORS REF. Data Understanding UTILISATION/EXPANDABILITY (FOR POTENTIAL) CHANGEABILITY (FOR RESISTANCE) None Opinion 0%= not high at all Very high =100% 0 1 2 3 4 5 Potentials Χ 0 20 40 60 80 100 The data quality is very good, which the organisation can draw on during implementation The members of the organisation know which data is required. The data required for the AI solution is available in sufficient quantities. AI solutions are already scaled and used across the organisation There is already sufficient data quality and data analysis. 0 1 2 3 4 5 Resistors Χ 0 20 40 60 80 100 There are reservations because the organisation members do not trust the new technology. There are concerns among members of the organisation about the security of the data There is no strategy for data use and quality assurance in the organisation. The importance of collecting data is not yet generally present in the organisation. There are no experts in the organisation who can analyse and assess the data. There are insufficient time and financial resources available to conduct interviews with stakeholders. There are strict rules in the country regarding the establishment of new services. The need to adapt market research questionnaires and segmentations to country-specific circumstances is high. What solutions do you know for utilising potential and dealing with resistance? (Specify as selectively as possible) General comments / questions regarding data understanding What questions remain unanswered when understanding data? Which tools help you and why? 1. 2. 3. How do you rate the following potentials and resistances in terms of their importance? In your opinion, to what extent can the factors mentioned be utilised or expanded (in terms of potential) and changed (in terms of resistance)? Where do you see the strengths and weaknesses? (Is there a (need) (for) (further) (tools?) If yes, which key topics are most important to you? How do you rate the following potentials and resistances in terms of their importance? In your opinion, to what extent can the factors mentioned be utilised or expanded (in terms of potential) and changed (in terms of resistance)? IMPORTANCE 0= not important at all Very important =5 FACTORS CONCERNING Data preparation UTILISATION/EXPANDABILITY (FOR POTENTIALS) CHANGEABILITY (FOR RESISTANCE) None Opinion g 0%= not high at all Very high =100% 0 1 2 3 4 5 Potentials Χ 0 20 40 60 80 100 The organisation regularly analyses data in order to make decisions It is clear where the data used for AI solutions comes from. The data sources for potential AI solutions are trustworthy The organisation has usable data sets even after cleansing the data Key figures are already available for analysis There are experts in the organisation who can perform data cleansing if required. A network of experts has been established that can be called upon when required for the development of AI solutions. can be called upon when developing AI solutions. Adapting the data format is very simple in the specific individual case of the AI solution 0 1 2 3 4 5 Resistors Χ 0 20 40 60 80 100 The problem is that experts are not available or not available in sufficient numbers. The prerequisites for cross-departmental collaboration within the organisation are not met. The data used for the AI solution is only available in the organisation in poor quality The resources required to recruit experts for the use of AI solutions are too high. There is no network available to access potential experts. The framework conditions, e.g. in terms of time, prove to be difficult to find experts. What solutions do you know for utilising potential and dealing with resistance? (Specify as selectively as possible) General comments / questions regarding data preparation Which questions remain unanswered in data preparation? Which tools help you and why? 1. 2. 3. How do you rate the following potentials and resistances in terms of their importance? In your opinion, to what extent can the factors mentioned be utilised or expanded (in terms of potential) and changed (in terms of resistance)? Is there a need for further data preparation tools? Where do you see the strengths and weaknesses? (Preparation) (?) If yes, which key topics are most important for you? most important for you? QUESTIONS ABOUT YOURSELF What tasks do you have in the development and implementation of AI solutions? (multiple choice possible) Other: ... CEO of the company CDO/ CFO of the company Organisation of the implementation of AI solutions Production manager of the company IT and AI specialist Your opinion is important to us! How do you rate the following potentials and obstacles in terms of their importance? In your opinion, to what extent can the factors mentioned be utilised or expanded (in terms of potential) and changed (in terms of resistance)? 0= not at all IMPORTANCE not important Very important =5 FACTORS BEZ. Modelling UTILISATION/EXPANDABILITY (FOR POTENTIALS) CHANGEABILITY (FOR RESISTANCES) None Opinion 0%= ga not high Very high =100% 0 1 2 3 4 5 Potentials Χ 0 20 40 60 80 100 We have already gained experience with simple AI models or statistical analyses. The programmes and computing resources required for model development are available or easily accessible. Our employees have basic knowledge to create or understand AI models. We already use initial key figures that could be relevant for model development. We can understand how initial AI models arrive at their results. 0 1 2 3 4 5 Resistors Χ 0 20 40 60 80 100 We find it difficult to select the right AI model for our specific problem. We lack the time and financial resources as well as the budget for training and external support. We don't yet have a clear idea of how to ensure the quality of the AI models during development. The potential benefits of the models are difficult for us to express in figures before implementation. We don't have a contact person or network that can support us with questions about AI modelling. Our teams are concerned that AI models are too complex and that the way they work is not transparent. What solutions do you know of for utilising the potential and dealing with resistance? (Specify as selectively as possible) 1. 2. 3. How do you rate the following potentials and resistances in terms of their importance? In your opinion, to what extent can the factors mentioned be utilised or expanded (in terms of potential) and changed (in terms of resistance)? Where do you see the strengths and weaknesses of the modelling tools? And if so, which key topics are most important to you? most important for you?