How data champions help form a data culture.
My name is Lewis Prentice, I’m a full time PhD student researching the use of resources in the creation of data-driven value. This piece was produced as part of my fellowship at the ODI and is the result of six interviews with various data professionals, where we discussed data culture and its formation in organisations. Findings from these interviews suggest that the formation of a data culture is driven by an individual I refer to as the “data champion,” whose efforts are the focus of this piece.
Introduction: The need to understand how data culture is formed.
This introductory section aims to provide you with clarity regarding:
· What culture and data culture are
· How this piece will explore the formation of data culture
What culture and data culture are
How to form a desirable type of culture in an organisation is a tricky task to judge. This is largely due culture’s intangible nature. Unlike technologies or people, we can’t feel or see culture as a physical entity, because culture is largely regarded as how a specific group of people collectively view certain customs, ideas, values and behaviours at a given period (Birukou et al, 2009).
Of course, if a specific culture is viewed as positive, then companies can also attempt to reinforce its presence through more tangible means, like written codes of conduct (Meikle, 2023). Google’s highly social culture is a good example, with most of its workers viewing openness and a mix of opinions as key aspects of its innovative success (Tran, 2017). In turn, these beliefs are accompanied alongside rules and guidelines put in place by Google to help direct such a constructive discourse (Wickre, 2017).
Workers can also possess a collective attitude towards data, which is the focus of this piece. When strategy researchers like myself began examining companies around a decade ago to discern how they created, or failed, to create value from data, a pattern emerged. That data culture is a key resource in creating value from data and that its absence was frequently reported as one of the main reasons for data initiative failure (Pappas, 2019) with a general definition of data culture being:
“The extent to which organisational members make decisions based on insights extracted from data.” (McAfee and Brynjolfsson, 2012).
How this piece will explore the formation of data culture
However, what’s missing from this existing work is clarification on how to form a data culture in the first place. Scholars consistently reinforce data culture’s importance in creating value from data (Gupta and George, 2016), but without understanding its formation, we can’t fulfil subsequent stages in deploying it for value purposes. Hence, I believe there’s a need for an initial examination of the dynamics at play in establishing emphasis on data’s use amongst an organisation’s employees.
To answer this question, I undertook six interviews with various data professionals. These participants shared their insights on the formation of data culture across multiple industries at varying stages of data use and maturity, helping to account for any difference of opinion based on unique experiences divulged.
What follows in this piece is my chronicling of this formation across all its aspects as a synthesis of the information collected throughout these interviews.
Initially, given the collective nature of culture, I had expected the main driver of its formation to be a more communal phenomenon. However, my findings consistently highlighted the importance of a more individual effort from a person known as the “data champion”, someone with the skills to identify and promote data’s relevant potential.
This is not to say that formation is entirely orchestrated by a champion alone, but that they are at the heart of efforts to create a positive attitude towards using data; which is played out in a three-part process:
1. Contextualise data’s potential.
2. Communicate data’s potential to people.
3. Enable people’s data curiosity.
These parts culminate in the champion’s role to formulate a data culture by selling data’s use internally to fellow employees; and to get people interested, champions need to link data to what their colleagues’ daily activities entail.
Section 1: Contextualise data’s potential.
This section explores the first part of the champion’s role: establishing data context, and discusses:
· What it means to put data into context.
· Where data champions come from and how their origins aid contextualisation.
What it means to put data into context
Throughout interviews conducted I noticed a recurring theme, that employees who need to be persuaded on data’s use aren’t interested in data per se, but the beneficial changes to their lives that data-based decision-making can bring. This means having to contextualise the positive role data can play within their daily activities to generate some initial interest.
Interviewee descriptions of how champions view their workplace depict data contextualisation like an exercise in gauging a firm’s particular business issues and what datasets could provide insights on these issues; before then ascertaining practical elements like data location, access and development.
This appeared to me as almost like a mapping exercise, akin to figure 1, to discern the process of creating value from data. First by finding where you want data to take you in terms of business objectives before working backwards by exploring the realistic routes to get there via the identification and mixing of relevant datasets and their necessary development.
Of course, most employees already recognise the presence of these datasets. They know their own actions and those of others produce data, so why can non-champions struggle to apply this mapping exercise if they know data is an available asset.
This was made clear by my interviewees, who stressed that employees in non-data orientated roles can struggle to judge how data may provide insights on their tasks. In essence, when lacking knowledge regarding data, it can be difficult to judge which datasets are relevant to your work or their potential benefits.
Instead, it seems data champions are often the first to make this connection, which raises the question of why.
Where data champions come from and how their origins aid contextualisation
The answer appears to lie within interviewee descriptions of who a data champion is and their work histories. Unsurprisingly, it seems champions possess certain skills and backgrounds that allow them to comprehend all elements of the map.
In my discussions, three of the six interviewees regarded themselves as data champions, so I viewed the creation of a champion through their own work histories.
These three professed to starting their careers in non-data roles, however, they reached a point in these jobs where due to inaccurate and/or incomplete data, they could no longer carry them out sufficiently without broadening their data-specific skills. Thus, these interviewees started learning and delving into areas like data cleaning, engineering and management.
Each described how they in turn became the impetus for increased data use in their respective firms, with a pre-existing understanding of business challenges now combined with data-orientated skills. This gave them the ability to judge which datasets are most relevant to the particular business objectives they’re familiar with and allow them to accurately weigh up the cost of developing and applying this data with its potential benefits, comprehending all elements of the map.
However, I don’t interpret the purpose of this contextualisation as a way to take advantage of data in specific instances, but more of a means to pique the interest of those you’re trying to convince by clarifying the connection between data and positive change. This suggests that to make the most out of data contextualisation, it should be used alongside effective communication.
Section 2: Communicate data’s potential to people.
This section explores the second part of the champion’s role, communicating data’s potential, and focuses on:
· How to get people excited about data
· How to handle people’s reluctance around data
How to get people excited about data
When it comes to using contextualisation to persuade others, most interviewees emphasised that champions should initially focus on data’s potential end benefits. This is because talking about how data may enhance people’s daily lives serves as an effective hook to get them interested in its use, as this is their predominant concern.
Once the potential of data has been conveyed, champions then seem to focus on how this potential is achieved through data’s development, from collection to analysis. This will enable some people to make a connection between data development, like selecting and combining the right datasets, and how this leads to the beneficial data-based insights they seek to improve their work-lives.
Of course, I believe realistically that enthusiasm will vary from person to person and that instilling a mindset of importance on data won’t happen overnight. Regardless, at least some of the employees that champions are trying to persuade will be able to view data as a versatile and valuable tool.
How to handle people’s reluctance around data
Many interviewees, however, insist that it’s more than possible to abate any remaining resistance. Although, this does require reflecting on people’s concerns. To start with, one interviewee was keen to remind me that while data doesn’t pose a threat to most jobs, a small number will be completely automated.
Realistically, most experts believe data will largely benefit our working lives, rather than completely replace us (OAG, 2023). However, even if you’re not one of the few individuals whose role will be entirely automated, all it takes is a minute possibility of eventually losing your job to instil some sense of unease about data.
Considering this, I don’t believe there’s a sure-fire answer that will help dissipate all fears over data. Nonetheless, in dealing with the more common case where data will enhance our jobs yet some fear could remain, it may be best for champions to reiterate an idea of jobs changing, and that data, as one interviewee put it, is “a jetpack to help them do the job better,” not replace them.
Interestingly, I also found a reluctance existed in individuals who believed data could never be better than a human, which seems common in industries where personality and human interaction play a crucial role.
According to interviewees, what wins these individuals over isn’t strictly reiterating data’s potential; but a more practical demonstration of its success. This is obviously easier said than done, as it means deploying data initiatives before even winning employees over to it, or at least doing some testing runs before making a full monetary commitment towards necessary technologies.
But once results are more explicit, successes can begin to break down perceptions that data can’t play any role in a firm dominated by human characteristics and opens the door for further use.
A good example from an interviewee was a story of someone discussing their success in identifying a highly valuable potential client, only for a data champion to point out that this client was flagged by the firm’s data analysis system months earlier. Subsequently, use of this system increased once the overlap between data and people’s tasks became obvious.
Section 3: Enabling people’s data curiosities.
This section explores the third and final part of the champion’s role, enabling curiosity about using data, and focuses on:
· The earliest stages of a data culture
· Ensuring and growing a data culture
The earliest stages of a data culture
Once data’s potential is conveyed, those who are convinced will start to form a more explorative curiosity regarding its use.
Many of these employees apparently go deeper down the data rabbit hole and wish to engage with development activities so as to direct and shape the potential data offers. They ask questions about how to access, combine and modify different datasets for more unique insights to use, for example, or what different analysis techniques can be deployed for beneficial insights that existing techniques didn’t provide.
I was beginning to wonder during my analysis whether a data culture had been successfully formed at this stage, at least on a small scale. I thought if the people that champions are trying to convince are collectively sold on data and desire to use, learn and experiment with it into the future, then a general understanding of its importance and place in the firm has been achieved; thus, a data culture exists. This is best described in one interviewee’s comment on the general attitudes in a firm once data started showing results:
“They talk about how we acquire data, what we do with data, how we process data, who owns data and what are the roles and responsibilities around data. There’s a culture.”
However, there’s one aspect I had initially overlooked. Just because people have formed an interest in data, this doesn’t mean this interest will last long-term without additional action. What we’re witnessing at this stage is the beginning of data culture’s formation, because without also putting in place some sort of social and technological system that enables people to sufficiently interact with data, then their curiosities could dissipate.
Ensuring and growing a data culture.
This system involves instilling and aligning areas like necessary technologies, rules and governance procedures; allowing people to move on from just having an idea about data’s potential to being able to practically realise said potential.
After replacing what one interviewee called the “nebulous” of data with this comprehendible socio-technical system, people will then be able to explore, apply and challenge data now that they’re confident regarding the tools, rules and lines of communication governing its use.
Interviewees also advised that this system is often built around the idea of open data use, with curiosities leading to the sharing of data, expertise and opinions. Of course, open data is a whole concept itself, in which the ODI’s guide on forming open data standards in organisations is a useful resource: (https://standards.theodi.org/).
However, I was also warned that data training programs must accompany any system instilled, not just so people can continue to improve their skills, but so that they also understand the rules and risks involved with data development.
With a suitable system in place, reinforced through appropriate training, those convinced of data’s use will be able explore their curiosities in an environment that will both reap financial/practical benefits and solidify trust in data, helping a culture around it to prosper.
Caveats and Conclusions.
This final section concludes this piece’s investigation on the champion’s efforts in forming a data culture and focusses on:
· How this three-part process operates in an organisation
· Final thoughts on the data champion
How this three-part process operates in an organisation
Of course, while this three-part role of a champion provides a logical path to forming a data culture, it’s important to clarify how I think it relates to the more practical aspects of company life. To start, the champion is just one person, and it’s unrealistic to assume they can perform every task on their own. A key ally in these efforts according to interviewees is management, who often take up the role of data managers within their respective departments and help reiterate the message of data’s potential.
This will vary from department to department, however, which introduces the issue that some areas of an organisation will embrace data more openly than others. In such a scenario, an interviewee advised that it was best for champions to focus their efforts within more data-friendly departments, and slowly build data’s acceptance as a series of spokes that make up a wheel representing a firm’s data culture as a whole.
To actually initiate any part of this process, however, means acquiring support from the C-suite. This tended to conclude my discussions, as interviewees were eager to emphasise that any system that a data culture will be built on is dependent on funding from senior employees.
Reflecting on this piece, I think my preeminent thoughts on how a champion goes about their role is whether the three-part process is a sequential or nonsequential exercise. At first, I largely saw these efforts through the eyes of those a champion is trying to convince, leading to a consecutive idea of how culture goes from theoretical projections about data’s potential to increasing curiosity and then desire to use it. But, as I began viewing this process from the practical perspective of the data champion, I believe the three parts I’ve just described are performed more simultaneously. This is largely because of the third task in enabling data curiosity, as it seemed unrealistic in terms of time to first hype people up about data’s potential and then engage in the long, drawn-out process of setting up a system to capitalise on this hype.
Final thoughts on the data champion
I hope this has provided you, regardless of what your profession or place in a firm may be, a chance to reflect on what goes into setting up an effective data culture. Again, I think of this as an initial start on researching data culture’s formation, which people should consider if aiming to apply these findings practically. Further, if anyone reading this is interested in collaborative research into additional areas of data culture, data champions or this three part-process, feel free to contact me at my ODI email address (lewis.prentice@theodi.org).
In reviewing the interviewee’s descriptions, I found two consistent themes that seem to clarify how champions formulate a data culture. The first is using the potential of data as a constant motivator, whether that’s identifying potential, talking about potential or putting in place systems to realise potential. The second is the idea of a champion pivoting between business and data-focussed competencies as they carry out this process, which is rooted in their unique backgrounds.
So, does this mean a data champion is the only person who can deliver data culture as described? The answer I think is that a champion is a fundamental component of forming a healthy data culture, but it isn’t a one-person effort. Instead, champions just spearhead these required tasks, but with a number of people around them acting on their behalf or in their interest — from the C-suite whose support is vital in setting up necessary data-systems to the managers who act as data stewards, and most importantly the regular employees who will become the vessels of data culture.
References:
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Gupta, M. & George, J. (2016) Toward the Development of a Big Data Analytics Capability. Information & Management, 53 (8), pp. 1049–1064.
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Pappas, I. Sjusdal, A. & Lunde, T. (2019) Organizational Culture Challenges of Adopting Big Data: A Systematic Literature Review. Trondheim, Norway: FIP Conference on e-Business, e-Services and e-Society. Available from: https://www.researchgate.net/publication/334702716_Organizational_Culture_Challenges_of_Adopting_Big_Data_A_Systematic_Literature_Review
Tran, S. (2017) GOOGLE: A Reflection of Culture, Leader, and Management. International Journal of Corporate Social Responsibility, 2 (10).
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