BDALC attributions and representative quotes
| Competency | Attributions in the BDA context | Representative quote |
|---|---|---|
| Analytical skills | ||
| Interpretation skills | Leaders need to be capable in interpreting the data that is given to them. They need to apply meaning to it. They need to understand the results and their impact on the business | “I guess it may be my interpretation of it. Data is just data till you apply meaning to it. And I think that's the job with the leader.” (C7) |
| Pattern recognition | Leaders have a keen sense for recognizing patterns and correlations within the data | “If you love data and figures you will see the patterns in the data. The first time maybe.” (B5) “You need to be able to recognize patterns. There is a huge amount of data that you need to process, or you need to process the information that is contained in the data very strictly.” (C5) |
| Data Self-efficacy | ||
| Basic statistics | Leaders have a basic understanding of statistical methods. Especially descriptive statistics. They should be able to read data and understand data quality issues. Understanding correlations, knowing how to do a regression analysis, read graphs, and knowing how to formulate hypothesis. The actual doing instead, they can leave to their data experts | “I would say that whoever is doing metrics like data-driven management, or architecting, or pretty much in any position of leadership, or analysis, needs to understand statistical analysis. Needs to understand the biases that their data can gather. They need to understand the way that the metrics can actually negatively or positively affect the output, or change the behavior of people, so that their output is moving.” (B14) |
| Basic technical infrastructure management | Leaders have a basic understanding of the technical infrastructure. Especially, how the data is collected, stored and managed. This is needed to understand the possibilities and boundaries of data collection, data processing and data management. The actual doing, they can leave to their IT experts | “Understand the sources of data to have a real view of where data comes from. So, there is understanding the sources. Then, understanding how data is managed. What type of technologies, or processes the data goes to in the company.” (B6) |
| Basic skills in BDA tools and software | Leaders need to know how to use big data analytics tools and software3 from a user perspective. They need to be capable in navigating through the tools and extracting insights from it. The implementation and management of the tools, they can leave to their experts | “If you would like to include smart data, big data, any kind of data to your leadership decisions and to your daily work, you have to have a certain skillset to be able to use the different tools. And it might be that you don't even have impact on what tools you have available. So, therefore the more educated you are in different tools, or in basic knowledge, how these tools are working, will help you in any situation throughout your professional career.” (B7) |
| Experimental design | Leaders are capable in setting-up an experiment for hypothesis testing | “So, they understand how the experiments are designed, and like ether the experiments or the data gathering is happening. So, this is not you building it, but you understand how it is done. (B14) You want to gather the right data points you want to collect. And so, setting up an experiment, let's say we want to test a thousand people if they are … if corona is significant or not. So, then we have to understand how this experiment is really set up and which implications it has and what means benchmark and what means significant and what means boarders and what means alpha value and so on and so forth.” (C3) |
| KPI development skills | Leaders are capable in defining key performance indicators and other metrics to evaluate success and to measure performance. The KPIs should be strongly tied to the business objectives and are required to put data into perspective. Depending on whether KPIs are achieved, this affects the decision-making of leaders | “… and something I haven't touched here a lot is the ability to having actually good and relevant metrics. So, being a … what I tell you is, like twenty-five years ago the mindset was, “We measure developers for their lines of code they produce”. So, we have prolific developers and like non so prolific and the ability to write more lines of code was sometimes, I mean in many companies tied to their bonuses, more than before their base. Fortunately, most companies until now are like that are successful now, completely bunked it out as a myth. So, metrics that are relevant to actually the goal that you are trying to get is necessary.” (B14) |
| Problem spotter | ||
| Business acumen | Leaders have a general understanding of the business they are in and the organizational values and processes that drive it. They translate the company business objectives into their own business objectives to contribute to the overall goal | “First of all, you need to understand the business you are in. I think that is the fundamental basis. You need to understand the business in general. And how things are in general related. Because when you do analytics at the end of the day what you want to understand is correlations, right?” (C2) |
| Learning ability | Leaders are continuous learners. They are never satisfied with the status quo and want to frequently improve themselves, their team, and the entire organization. They install feedback loops wherever possible to uncover bias. They have the ability to fail and revise until they finally achieve their objective | “People who didn't grow up with it, it doesn't stop them, and it shouldn't stop them learning about it. But I think there is a learning … you have to be prepared to learn something which you are possibly unfamiliar with and actually sit there and say, “Well, I need to understand how to use this like these guys do. You can't hide from it. You can't say no one not doing it. But I think it's maybe slightly more of a challenge because it's more to learn.” (B19) |
| Open-mindedness | Leaders are eager to try something new. They are open for the ideas of others. They want to understand everything that gives them a competitive edge, whether it is a new technology or a new way of thinking | “I think another, but also another important skill is that you are able to be open for other approaches and ideas. Because, on the other hand if you are too much in your own business world and you understand your business very deeply, there is a risk that you overlook approaches, ideas, or trends from other industries.” (C2) |
| Monitoring | Leaders scan the internal and external environment for information. Internally, they try to understand how the organization is performing against certain metrics (e.g. customer data, financial data etc.). Externally, they monitor how competition is performing and how they adapt to change. Finally, they benchmark their own company metrics against competitive metrics to understand in what areas the competition does better and why | “So, for us the competition information and data is really important. And we already understand, and we identify with which kind of information do we need to collect about our competitors.” (B15) “They are delivering really high margin, so perhaps that's a number that you need to look at, or you use it for segmenting your customers as well. And again, tie that in with your customer segments, tying that in with your financial data. Then it enables you to look at what ports of good business to move into or to develop into.” (B19) |
| Influencer | ||
| Storytelling | Almost any decision leaders make, they need to justify to other stakeholders. Storytelling helps them to convince people to buy into their decision. Mainly, it is reducing the data to a key message. The story has two parts. it's what the leader says and what is on the presented slides as well. So, on the one hand building a deck where anyone can flip through and get it immediately and on the other hand being able to explain what the data is saying, where it derived from and how it supports leader's decision | “You know, it starts with like just picking the right types of charts, but it goes beyond. You know, how do you tell … for every decision that you are making you always need to justify it. You know, you have to provide the rational and providing the rational is essentially like a mini story. Like from an elevator pitch to a 50-page PowerPoint deck, you know it's gonna be somewhere in between. And you have to tell the story and that story needs to be driven by data. You know, it needs to use data at its core to convince people why they should follow you in making that decision.” (B13) |
| Data visualization | Data visualization is important for presenting the results of a data analysis to a broader audience, in a visual format that is easy to understand. Visualization should be chosen in such a way that it fits the leader's key messages as well as possible. Leaders need to be able to read, interpret and present the different types of data visualizations and gear it towards his audience. They need to understand the different types of visualizations. The actual doing of visualizing the numerical data they can leave to their experts. Data visualization can not only be used for presenting the results, but also at the very beginning, to explain the data, to uncover trends and to detect anomalies | “Because at the end of the day data itself is not the important thing. The important thing is what is the insight you gain from it. And the more you can work with visual information the better. Obviously, you need to gear it towards the audience. There are some people who really love numbers. They like to get numbers. But I would say that's the exception and for most cases I think visualization is really true.” (C2) |
| Social perceptiveness | Leaders understand the values, motivations, and backgrounds of their audience. Based on this information, they prepare their data, story and visualization in such a way that the audience understands to best supports their decision. Leaders need to connect with the people on an emotional level. For example, if their audience is other leaders, leaders need to be able to present it in a management compatible way. If their audience is data scientists, or people with a mathematical background they can strongly focus on numerical data. If the audience is mixed, leaders need to find the balance | “… emotional just in a good way, you know? Emotional in a way that you have to connect with people. To understand them. Make clear to them that it is the best to do this right now, because it will be a lot of success.” (B17) “… for me it is important that the leader has the right empathy to understand how the counterparts … how the sides of the counterpart are to provide the data and the information in the right way. That it fits into the mindset of these one that he wants to address with the information.” (B4) |
| Communication skills | Leaders have verbal and non-verbal communication skills to communicate the insights and results derived out of data. They need to reduce the complexity of data analysis to a core message, expressing the findings in an easy and plausible way. Communication is key to make the audience understand the reasons behind a decision and to gain their trust | You have to have absolute communication skills, verbally and non- verbally, to communicate either the result, the data, or the interpretation, i.e. human factor, the interpretation of it, and that's really part of the excellent communication skills. Because when you are just sending out a number it is easy, but do you achieve the goal by doing this? Mostly not.” (B22) |
| Knowledge facilitator | ||
| Knowledge sharing | Leaders have to stimulate a data-driven conversation with other leaders. They find peers at suppliers, customers and like- minded non-competing corporates to encourage knowledge transfer and best practice sharing about data topics regularly. They provide room for other leaders and subordinates to share their experience on data openly, creating an environment of trust and healthy conflict | “… the leader needs to be open to share his experience and be willing to do that. So, that needs to be an environment where you have room for trust, for healthy conflict, where people can openly share their experiences, speak up and talk about their experiences.” (C1) “What you are doing is, you are enabling a data driven conversation with other leaders, right? And make them bring their data story.” (B1) |
| Liaison | Leaders function as a liaison person between business oriented, IT and analytical staff. They translate business questions into analytical questions and vice versa. They act as an interface helping the organization to build the skills to interact with the data experts | “Normally you don't find people who cover all the skills and therefore you have to install interfaces in the team. To try to solve the problem, like business owners or managers who are familiar with data processing and the data business, but they are not necessarily data experts. But they bring along a lot more social skills usually and can act like a translator. You have the data nerd in your team and the translator.” (B5) “It is building and working in a team with the data analytics and IT people which sometimes have a different language, different way of thinking, but creating that interface, with himself or herself and with helping the organization to have those skills to interact with the data-driven experts.” (B6) |
| Role model | Leader lead by example leveraging data whenever possible in their day-to-day business. They use all data streams available to them to derive data-driven decisions and they are only satisfied with other people's decisions when they are backed by data | “I think the leader has to be a role model and show the company as well as his employees how the benefits can produce success and how the benefits of doing a really good data collection and data analysis can support the success of the company and can support the success of each employee in the company.” (B4) |
| Facilitating collective learning | Leaders explain to other stakeholders the benefits of being data-driven and the success it can bring on an individual and organizational level. They teach subordinates and coworkers how to leverage data and how to extract insights from it. To take away many people's fear of change, leaders must be sensitive and patient | “I think that one of the key challenges, something that needs to be done is to teach, but to explain, to give ideas of the concept to other leaders to make sure you have a common understanding of what is at stake, how you put this in place. If you assume everyone understands what you are trying to achieve with such projects, there is a high likelihood that you get some people that freak out, that don't understand, or they think they understand and they do the other way around.” (B8) “I think especially if it's somewhat new to the company, one of your biggest challenges will be to gain access, to explain the reasons why, to explain the outcomes, to go into discussion of what could be done.” (C4) |
| Disseminator | Leaders share data openly and freely within their organization within the guidelines of GDPR and compliance, so everyone can make use of it | “One of the things that I have seen is prevalent in companies that are data-driven is that the line managers take responsibility of being part of the community. So, what they do is remember that they don't hoard data.” (B1) “democratize the data in your organization, so everyone can make use of it.” (B13) |
| Visionary | ||
| Strategic thinking | Leaders need a clear vision, mission and strategy and execute on it. They foresee new challenges arising on the horizon and apply data-driven decision making to adjust their strategy. They ensure that all team members understand the vision, mission and strategy and play a role in it | “… if the leader is strategic enough, then data will give him or her a great edge. Because if they know how to win or if they know how to pick their road for winning for the company, data gives them more strength.” (B6) |
| Forecasting skills | Leader need forecasting skills to give an adequate business outlook to upper management and other stakeholders about their team's future operational performance | “And especially when you analyze trends or other things, based on any data, big data, it helps the leadership team to make well informed adjustments, decisions and in some areas, forecasting is also used for production insights.” (B7) “… you have to be able to forecast and look ahead. See, to make informed decisions. But I just think if you are data-driven that's probably one of the key things you are using it for. To help you forecast ahead.” (B20) |
| Team leader | ||
| Resource allocator | Leaders provide the resources to their team empowering them to be data-driven. The resources can be specific trainings, infrastructure investments as well as in the form of time that is dedicated to work on data problems | “It's to provide resources for it. Because if nobody has time for it … It needs time to work on data. So, for me it is automation and for others it is maybe resources.” (B17) “… first you need to invest a lot of money also in the infrastructure and IT setup. So, I think high level leaders can help to support by investing, if reasonable.” (B16) “Try to equip them with the resources that they need, the trainings they need, or maybe get hold of new staff especially for that role. I guess it's both in the end but … yeah.” (C4) |
| Empathy | Leaders are empathic towards their subordinates and respect their feelings and emotions. They do not evaluate their subordinates purely on their numerical performance, but also consider the human component which is multi- facetted and thus difficult to measure. During performance reviews, or employee appraisals leaders shall not embarrass their subordinates by only telling them the hard facts, but rather want to understand the reasons behind a poor performance which can include multiple factors (e.g. private issues, health issues etc.) which often cannot be explained by data alone | “But on the same hand, you are working with humans and you cannot tell them, “Oh, we have to do it differently” and then they will tell you, “But we have been doing this for ten years. Why?” You cannot be so cold hearted to them. So, you have to be rationally, but you have still to connect with these people. And to understand the impact that you are doing when you are trying to generate results with your data-driveness. So, you have to be rational and kind, I guess.” (B17) “I think it's always a balance in the feedback conversation you need the rational and you need the emotional and depending on which … what your preference is, or what your style is of the leader you have to take care of the other one. So, if you are using big data to give feedback, you need to really take care of the emotional side of the conversation.” (C7) |
| Contingent rewarding | Leaders incentivize their subordinates for applying the data-driven approach. This further stimulates their staff to integrate the system in their day-to-day work | “The incentives of people are important, if people are incentivized, just for doing what they have always done, then you are not going to get them to try something new. It is just not going to happen. You know, they might provide some lip service, or they may do it for a couple of months but they going to fall back.” (B13) |
| Build data-driven talent | Leaders hire the right talent to complete the data-driven skill set within the team. They need experts in their team which complement other members | “The right people around you … You have some skills of his own or her own, that, you know, you have, too. But there will be some things … you can't be an expert in everything. But the challenge is to find the expert to build them within your team. So that you have effectively all your pieces covered.” (B19) “having the single point of truths available in a reliable fashion, having applications on top, that actually tell you something about your data, at your fingertips whatever you need, that all just needs to be build. You know, every company needs to build and develop this. Starting from the talent that we need to hire.” (B13) |
| Competency | Attributions in the BDA context | Representative quote |
|---|---|---|
| Interpretation skills | Leaders need to be capable in interpreting the data that is given to them. They need to apply meaning to it. They need to understand the results and their impact on the business | “I guess it may be my interpretation of it. Data is just data till you apply meaning to it. And I think that's the job with the leader.” (C7) |
| Pattern recognition | Leaders have a keen sense for recognizing patterns and correlations within the data | “If you love data and figures you will see the patterns in the data. The first time maybe.” (B5) |
| Basic statistics | Leaders have a basic understanding of statistical methods. Especially descriptive statistics. They should be able to read data and understand data quality issues. Understanding correlations, knowing how to do a regression analysis, read graphs, and knowing how to formulate hypothesis. The actual doing instead, they can leave to their data experts | “I would say that whoever is doing metrics like data-driven management, or architecting, or pretty much in any position of leadership, or analysis, needs to understand statistical analysis. Needs to understand the biases that their data can gather. They need to understand the way that the metrics can actually negatively or positively affect the output, or change the behavior of people, so that their output is moving.” (B14) |
| Basic technical infrastructure management | Leaders have a basic understanding of the technical infrastructure. Especially, how the data is collected, stored and managed. This is needed to understand the possibilities and boundaries of data collection, data processing and data management. The actual doing, they can leave to their IT experts | “Understand the sources of data to have a real view of where data comes from. So, there is understanding the sources. Then, understanding how data is managed. What type of technologies, or processes the data goes to in the company.” (B6) |
| Basic skills in BDA tools and software | Leaders need to know how to use big data analytics tools and software3 from a user perspective. They need to be capable in navigating through the tools and extracting insights from it. The implementation and management of the tools, they can leave to their experts | “If you would like to include smart data, big data, any kind of data to your leadership decisions and to your daily work, you have to have a certain skillset to be able to use the different tools. And it might be that you don't even have impact on what tools you have available. So, therefore the more educated you are in different tools, or in basic knowledge, how these tools are working, will help you in any situation throughout your professional career.” (B7) |
| Experimental design | Leaders are capable in setting-up an experiment for hypothesis testing | “So, they understand how the experiments are designed, and like ether the experiments or the data gathering is happening. So, this is not you building it, but you understand how it is done. (B14) |
| KPI development skills | Leaders are capable in defining key performance indicators and other metrics to evaluate success and to measure performance. The KPIs should be strongly tied to the business objectives and are required to put data into perspective. Depending on whether KPIs are achieved, this affects the decision-making of leaders | “… and something I haven't touched here a lot is the ability to having actually good and relevant metrics. So, being a … what I tell you is, like twenty-five years ago the mindset was, “We measure developers for their lines of code they produce”. So, we have prolific developers and like non so prolific and the ability to write more lines of code was sometimes, I mean in many companies tied to their bonuses, more than before their base. Fortunately, most companies until now are like that are successful now, completely bunked it out as a myth. So, metrics that are relevant to actually the goal that you are trying to get is necessary.” (B14) |
| Business acumen | Leaders have a general understanding of the business they are in and the organizational values and processes that drive it. They translate the company business objectives into their own business objectives to contribute to the overall goal | “First of all, you need to understand the business you are in. I think that is the fundamental basis. You need to understand the business in general. And how things are in general related. Because when you do analytics at the end of the day what you want to understand is correlations, right?” (C2) |
| Learning ability | Leaders are continuous learners. They are never satisfied with the status quo and want to frequently improve themselves, their team, and the entire organization. They install feedback loops wherever possible to uncover bias. They have the ability to fail and revise until they finally achieve their objective | “People who didn't grow up with it, it doesn't stop them, and it shouldn't stop them learning about it. But I think there is a learning … you have to be prepared to learn something which you are possibly unfamiliar with and actually sit there and say, “Well, I need to understand how to use this like these guys do. You can't hide from it. You can't say no one not doing it. But I think it's maybe slightly more of a challenge because it's more to learn.” (B19) |
| Open-mindedness | Leaders are eager to try something new. They are open for the ideas of others. They want to understand everything that gives them a competitive edge, whether it is a new technology or a new way of thinking | “I think another, but also another important skill is that you are able to be open for other approaches and ideas. Because, on the other hand if you are too much in your own business world and you understand your business very deeply, there is a risk that you overlook approaches, ideas, or trends from other industries.” (C2) |
| Monitoring | Leaders scan the internal and external environment for information. Internally, they try to understand how the organization is performing against certain metrics (e.g. customer data, financial data etc.). Externally, they monitor how competition is performing and how they adapt to change. Finally, they benchmark their own company metrics against competitive metrics to understand in what areas the competition does better and why | “So, for us the competition information and data is really important. And we already understand, and we identify with which kind of information do we need to collect about our competitors.” (B15) |
| Storytelling | Almost any decision leaders make, they need to justify to other stakeholders. Storytelling helps them to convince people to buy into their decision. Mainly, it is reducing the data to a key message. | “You know, it starts with like just picking the right types of charts, but it goes beyond. You know, how do you tell … for every decision that you are making you always need to justify it. You know, you have to provide the rational and providing the rational is essentially like a mini story. Like from an elevator pitch to a 50-page PowerPoint deck, you know it's gonna be somewhere in between. And you have to tell the story and that story needs to be driven by data. You know, it needs to use data at its core to convince people why they should follow you in making that decision.” (B13) |
| Data visualization | Data visualization is important for presenting the results of a data analysis to a broader audience, in a visual format that is easy to understand. Visualization should be chosen in such a way that it fits the leader's key messages as well as possible. Leaders need to be able to read, interpret and present the different types of data visualizations and gear it towards his audience. They need to understand the different types of visualizations. The actual doing of visualizing the numerical data they can leave to their experts. Data visualization can not only be used for presenting the results, but also at the very beginning, to explain the data, to uncover trends and to detect anomalies | “Because at the end of the day data itself is not the important thing. The important thing is what is the insight you gain from it. And the more you can work with visual information the better. Obviously, you need to gear it towards the audience. There are some people who really love numbers. They like to get numbers. But I would say that's the exception and for most cases I think visualization is really true.” (C2) |
| Social perceptiveness | Leaders understand the values, motivations, and backgrounds of their audience. Based on this information, they prepare their data, story and visualization in such a way that the audience understands to best supports their decision. Leaders need to connect with the people on an emotional level. For example, if their audience is other leaders, leaders need to be able to present it in a management compatible way. If their audience is data scientists, or people with a mathematical background they can strongly focus on numerical data. If the audience is mixed, leaders need to find the balance | “… emotional just in a good way, you know? Emotional in a way that you have to connect with people. To understand them. Make clear to them that it is the best to do this right now, because it will be a lot of success.” (B17) |
| Communication skills | Leaders have verbal and non-verbal communication skills to communicate the insights and results derived out of data. They need to reduce the complexity of data analysis to a core message, expressing the findings in an easy and plausible way. Communication is key to make the audience understand the reasons behind a decision and to gain their trust | You have to have absolute communication skills, verbally and non- verbally, to communicate either the result, the data, or the interpretation, i.e. human factor, the interpretation of it, and that's really part of the excellent communication skills. Because when you are just sending out a number it is easy, but do you achieve the goal by doing this? Mostly not.” (B22) |
| Knowledge sharing | Leaders have to stimulate a data-driven conversation with other leaders. They find peers at suppliers, customers and like- minded non-competing corporates to encourage knowledge transfer and best practice sharing about data topics regularly. They provide room for other leaders and subordinates to share their experience on data openly, creating an environment of trust and healthy conflict | “… the leader needs to be open to share his experience and be willing to do that. So, that needs to be an environment where you have room for trust, for healthy conflict, where people can openly share their experiences, speak up and talk about their experiences.” (C1) |
| Liaison | Leaders function as a liaison person between business oriented, IT and analytical staff. They translate business questions into analytical questions and vice versa. They act as an interface helping the organization to build the skills to interact with the data experts | “Normally you don't find people who cover all the skills and therefore you have to install interfaces in the team. To try to solve the problem, like business owners or managers who are familiar with data processing and the data business, but they are not necessarily data experts. But they bring along a lot more social skills usually and can act like a translator. You have the data nerd in your team and the translator.” (B5) “It is building and working in a team with the data analytics and IT people which sometimes have a different language, different way of thinking, but creating that interface, with himself or herself and with helping the organization to have those skills to interact with the data-driven experts.” (B6) |
| Role model | Leader lead by example leveraging data whenever possible in their day-to-day business. They use all data streams available to them to derive data-driven decisions and they are only satisfied with other people's decisions when they are backed by data | “I think the leader has to be a role model and show the company as well as his employees how the benefits can produce success and how the benefits of doing a really good data collection and data analysis can support the success of the company and can support the success of each employee in the company.” (B4) |
| Facilitating collective learning | Leaders explain to other stakeholders the benefits of being data-driven and the success it can bring on an individual and organizational level. They teach subordinates and coworkers how to leverage data and how to extract insights from it. To take away many people's fear of change, leaders must be sensitive and patient | “I think that one of the key challenges, something that needs to be done is to teach, but to explain, to give ideas of the concept to other leaders to make sure you have a common understanding of what is at stake, how you put this in place. If you assume everyone understands what you are trying to achieve with such projects, there is a high likelihood that you get some people that freak out, that don't understand, or they think they understand and they do the other way around.” (B8) “I think especially if it's somewhat new to the company, one of your biggest challenges will be to gain access, to explain the reasons why, to explain the outcomes, to go into discussion of what could be done.” (C4) |
| Disseminator | Leaders share data openly and freely within their organization within the guidelines of GDPR and compliance, so everyone can make use of it | “One of the things that I have seen is prevalent in companies that are data-driven is that the line managers take responsibility of being part of the community. So, what they do is remember that they don't hoard data.” (B1) |
| Strategic thinking | Leaders need a clear vision, mission and strategy and execute on it. They foresee new challenges arising on the horizon and apply data-driven decision making to adjust their strategy. They ensure that all team members understand the vision, mission and strategy and play a role in it | “… if the leader is strategic enough, then data will give him or her a great edge. |
| Forecasting skills | Leader need forecasting skills to give an adequate business outlook to upper management and other stakeholders about their team's future operational performance | “And especially when you analyze trends or other things, based on any data, big data, it helps the leadership team to make well informed adjustments, decisions and in some areas, forecasting is also used for production insights.” (B7) |
| Resource allocator | Leaders provide the resources to their team empowering them to be data-driven. The resources can be specific trainings, infrastructure investments as well as in the form of time that is dedicated to work on data problems | “It's to provide resources for it. Because if nobody has time for it … It needs time to work on data. So, for me it is automation and for others it is maybe resources.” (B17) |
| Empathy | Leaders are empathic towards their subordinates and respect their feelings and emotions. They do not evaluate their subordinates purely on their numerical performance, but also consider the human component which is multi- facetted and thus difficult to measure. During performance reviews, or employee appraisals leaders shall not embarrass their subordinates by only telling them the hard facts, but rather want to understand the reasons behind a poor performance which can include multiple factors (e.g. private issues, health issues etc.) which often cannot be explained by data alone | “But on the same hand, you are working with humans and you cannot tell them, “Oh, we have to do it differently” and then they will tell you, “But we have been doing this for ten years. Why?” You cannot be so cold hearted to them. So, you have to be rationally, but you have still to connect with these people. And to understand the impact that you are doing when you are trying to generate results with your data-driveness. So, you have to be rational and kind, I guess.” (B17) |
| Contingent rewarding | Leaders incentivize their subordinates for applying the data-driven approach. This further stimulates their staff to integrate the system in their day-to-day work | “The incentives of people are important, if people are incentivized, just for doing what they have always done, then you are not going to get them to try something new. It is just not going to happen. You know, they might provide some lip service, or they may do it for a couple of months but they going to fall back.” (B13) |
| Build data-driven talent | Leaders hire the right talent to complete the data-driven skill set within the team. They need experts in their team which complement other members | “The right people around you … You have some skills of his own or her own, that, you know, you have, too. But there will be some things … you can't be an expert in everything. But the challenge is to find the expert to build them within your team. So that you have effectively all your pieces covered.” (B19) |
Source(s): Author's own creation
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