Section 1: Working relationships
Reservations, differences and challenges
Our partners indicated that the main difference of working with academics, as opposed to their usual working relations, was the academics’ ability to bring a breadth of expertise into a coherent team: “I was always very impressed with the sort of collaborative set up that they had, that they were able to bring all these disciplines together in quite a small team […] it certainly changed my outlook […] I had not dealt with other bodies or organisations that brought that width or breadth of outlooks” [RSPB, MT]. One of the main differences of these collaborations was that it brought the partner organisations in close contact with academic disciplines new to them: “the simplest and most obvious way it differs, I guess is […] that it […] involves […] working with disciplines, particularly in the computer sciences, that we would never normally work with. I mean that’s […] the single biggest difference, I think” [RSPB, ET].
The academics were seen as generally more independent than the organisations’ usual working partners: “dot.rural are more self-sufficient in a way than a lot of other partners we had to do a lot of involvement with […] we had to collaborate quite a lot but once set up the dot.rural [team] has been able to keep it going almost independently from us.” [BBCT, MT]. Although co-working was perceived to be at the centre of the work by interviewees, the independent working style of academics meant that progress was ongoing: “the tool evolves without us saying […] because there’s constantly improvements being made” [BBCT, ET]. The downside of this was that instead of investing time managing the work, partners had to invest in catching-up: “things can move on at a fast pace so sometimes you’ve got to spend a bit of time just trying to keep up with how people are developing things” [SMI, ET].
A recurrent reservation expressed about working with academics related to the more ad-hoc nature of the collaboration compared with their regular working partners: “…with a change of staff, if there hadn’t been a handover period when our Chief Exec left us we [wouldn’t have been] quite sure what the history of the relationship had been [including] who are these Aberdeen folk and what is it they’re doing for us and why have we not written down what we expect to get and what they expect to get?” [BBCT, ET]. This situation repeated itself with further personnel changes and prompted the organisation to make explicit the working arrangements and objectives of the collaboration to ensure the sustainability of the project: “So I’ve come into a project part-way through without the required history. So that was the major challenge for me […] to start from the beginning and to understand […] what has happened, what was the priorities for the project, where was it going. So I didn’t have that information. So that was […] the key challenge for me” [BBCT, ET].
Interviewees mentioned that one further challenge of this type of collaboration was the marrying of different objectives: academic and organisational. Ultimately these all seemed to relate to communication within the team: “Communication can be a challenge, its mainly communication between what the practical manager wants, a practitioner wants and what does an academic want […] there were certain times when there were strains between staff, practitioners and dot.rural staff about how the database was developed and how it looked on the screen […] so that’s sometimes where I had to kind of intervene a little bit to sit and talk to actually try and find out what are the ways of being able to solve this, what was the actual nature of the problem” [SMI, ET].
Interviewees brought out different learning outcomes as a result of the collaboration, ranging from the individual: “I finally realised the potential of the internet and […] crowd-sourcing in particular in solving problems to do with ecology” [BBCT, MT]; to the organisational: “from an organisational point of view we’ve discovered with the help of dot.rural because they’ve really, really, really helped us develop it to the point where I think we’ve got a […] kind of unique system in that we can produce the kind of reports that we’re producing, we can also feedback to the volunteers as well” [SMI, MT]. Furthermore, in some cases the collaborations pushed the partner organisations into adopting new areas of expertise: “I’d never come across phpMyAdmin before. […] So therefore I’ve never had a strong desire to learn how to use it […] But I know for a fact that once I can do what I need to be able to do I will enjoy it, because I’ll know […] I’ll feel more in control and less dependent on other people” [SMI, MT].
The collaboration with academics also gave partners a better understanding of applications from the research world: “[…] the sort of initial results that have come out of the research that’s been happening as to how much feedback you give to people, and how that affects whether they repeat use, is really useful for all of our communications […] if we don’t give enough or we give too much information that can affect our blogs, our E-newsletters, what we put in our members magazine, it’s not just how much you feedback through the BeeWatch tool. […] it’s useful feedback for any communication with people regarding citizen science or nature conservation generally.” [BBCT, ET]; and “I’ve learnt a lot about what is possible to do and what could be possible to do and I’m quite excited about that. […] I do think it’s the way to go in terms of […] getting more effective and more efficient management systems is to get these closer links with the research” [SMI, ET].
Section 2: The organisational impacts of collaborating with academia
In general, the identified social impacts discussed by the interviewees revolved around volunteer engagement and citizen science. Interviewees from both SMI and BBCT indicated that the systems created through the collaborations allowed them to monitor volunteer engagement and retention: “this system ties […] identification of priority areas where we can actually say […] if volunteers are going to start getting bored and dropping off then we can start looking at which of the areas we really need to put an effort into [to] make sure they stay on-board and stay monitoring those areas.” [SMI, MT]. For the BBCT, the system developed was a multi-faceted tool to be used to train novices as well as the more experienced users in a supportive environment: “the tool’s a great sort of first step into it, if you get somebody who’s enthusiastic about bumblebees but doesn’t feel confident enough to go out and walk a transect once a month you can introduce them to it by saying: right well if you’re out on a walk take a picture, go on use the online training tool. Then once you feel a bit more confident […] sign up and do a transect once a month, you can still be using the tool to identify the specimen that you see on your walk so if you see something and you’re not sure take a picture, use the tool to identify it and put that on your records” [BBCT, ET].
Similarly, the RSPB highlighted the citizen science impacts: “I expect that the people who looked at it and I know when we put out the publicity […] a lot of folk came back and said oh this is brilliant! This is really interesting so perhaps the same […] light bulb that went off in my mind went off in lots of other people’s minds as well and they thought oh that’s quite good […] with something like this I think it’s very well set up to go to schools with and you could talk to them about the kites and you can talk to them about satellite tracking, but you can talk to them about technology as well and yeah […] all those people will know a lot more about technology than I do!” [RSPB, MT].
However, for SMI, the digital solution generated tension with some of their volunteers who did not wish to move onto the digital platform: “a lot of our volunteers are ghillies, gamekeepers, that sort of people which […] tend to be fairly conservative and resistant to change. So you know they’re typical… ‘I’m not going to report things on line; I like talking to people!’” [SMI, ET].
Professional practice impacts
All collaborations led to the adoption of digital technologies and innovation in products and services, as systems were created that streamlined the processes around data workflows: submission, handling and archiving. The new data workflows allowed one partner organisation to have, for example, “a better understanding of the distribution of the bees because one thing we really need to understand is just exactly where the bees are” [BBCT, MT]. The streamlining of data submission meant that there was less space for error because the data went into the database without staff intervention: “instead of manually do all the stuff and put it in Excel spreadsheets and so on, the dot.rural team set it up so it does it all automatically, so the data comes in and its mapped” [RSPB, MT]; and “it’s fundamentally changed how we operate […] because its provided an online resource that instead of people reporting directly to us and us compiling the information they report directly to the database and we compile it from the database, which is a lot easier and a lot more efficient for us to do” [SMI, ET].
Another aspect of professional practice was that these new systems helped reshape organisational priorities by providing them with the means for new ways of operating: “We’ve been changing to become more scientific […] in general—more of a data provider than just doing conservation management […] [the new platform] and the data that we get out of that is a major part of that, alongside data that we get from other sources” [BBCT, MT].
One downside of the new workflows for SMI and BBCT was that it created dependency on the new system by shaping the workload priorities of staff, for example: “in the height of the summer we do have to bring other staff in […] so our outreach officer had to feed into doing some of the IDs over the summer just because there were so many records and we were falling behind and we didn’t want there to be a delay between people uploading and getting the feedback. […] But you know the data we get from it and the engagement aspect of it it’s worth it. Um…its…you know it’s part of…we just have to plan that in that that’s part of our workload now” [BBCT, ET]; and “reporting is my least favorite thing because…of the process, you know, I’ve got to tidy it up before I can use it. Well, I dunno, maybe that’s normal, but, ehm…it just slows everything down. But also, I need to…you know, I need to improve my skills so as I can use it better, because there are queries that we could run, that would save me…counting stuff in Excel” [SMI, ET].
Staff/capacity building impacts
The collaboration with academics generated impacts related to efficiency, performance and organisational sustainability, and was seen to benefit the organisations by delivering expertise that helped them save time, get more accurate data and release staff from duties that now could be achieved through automated systems: “it’s made a difference just in terms of other things that I’m able to do, so instead of spending time on constantly answering queries I can be answering questions about other things or delivering events” [BBCT, MT]. Indeed, the freeing up of direct and additional staff time was a recurrent perceived benefit flowing from the collaborations: “a member of dot.rural will be logging in and identifying species one day per week which is great, so that’s probably one of the few projects where we’ve got somebody from an external organisation logging in and helping us do our work” (BBCT, ET); and “they were doing us a service because they were dealing with all this stuff that we didn’t have time to deal with” (RSPB, MT).
The collaborations appeared to have helped the organisations realise avenues for future work: “There’s been a realisation that there’s a lot of potential there, which the RSPB simply doesn’t explore and doesn’t understand how to make the best of at the moment. I think that… in terms of mind set and […] opening of eyes you could say there has been an impact.” [RSPB, ET]. Similarly, they resulted in noticeable changes to individual staff members in terms of personal development and skill-sets, but this came at the cost of having to invest in re-skilling and training staff. For example: “looking at things from a research point of view I see the need now to think of clear questions that you need answered and guiding how you produce the database and things like that […] to answer the questions that you need to be answered so I think that’s really important. I mean personally I’ve learnt so much about database management, data management, tidying data and that sort of thing and that’s invaluable to me” [SMI, MT]; and “I’ve kind of finally realised the potential of the internet and crowd sourcing, in particular in solving problems to do with ecology […] it’s just been a real introduction to ways in which those can be fixed” [BBCT, MT].
The interviewees described economic impacts in terms of efficiency-savings, income generation and staff time. For example: “because of the automated system it means we can answer queries quite quickly […] from maybe three or four minutes down to about 30 seconds” [BBCT, MT]; and “data entry used to be […] somewhere around 25 % or more of their time […] and data analysis was just a nightmare. […] Using the data we can draw out of it now […] we’re down to less than 10 % of our time.” [SMI, ET]. SMI required the newly developed infrastructure to be used by all its partner organisations involved in mink control across large parts of Scotland, which generated efficiency-savings on a range of fronts (data entry, archival and analysis, reporting): “all trusts that submit data ought to use the system as a condition for payment” [SMI, ET]. Yet, for the RSPB, “the collaboration is […] probably […] you know, too small-scale in a large organisation for it to be measureable at that [economic impact] level” [RSPB, ET].
Where occurring, the economic impacts did not necessarily stop within the boundaries of the organisations; for the BBCT the collaboration with academics may have given them the competitive edge to secure further funding: “we have a three-year grant from the Esmèe Fairbairn Foundation for a project and we mentioned in our funding application that we have this tool we developed and what it does. Part of the role of the person funded by this would be to manage that tool and help expand it […] so whether they thought that was a beneficial aspect of the project and that was part of the reason they gave us the three years of funding I don’t know” [BBCT, ET].
Despite the emergence of general ‘cost savings’, there was also recognition that the collaborations had a significant cost “it’s a hell of a lot of work especially if you don’t have anyone in the project that is that kind of…computer savvy or doesn’t have the time available or something like that” [SMI, MT] and that once the collaborations ended, the organisations would have to absorb the cost of running the new technologies: “to the detriment, in the future, I think it might!! [Laughs] ‘Cause we’re going to have to […] resource things that […] now they’re coming to the end of dot.rural, that we […] we hadn’t anticipated” [BBCT, ET].
The interviewees generally felt that policy impacts had not yet been realised: “Simply too early to expect to be able to see those sorts of impacts” [RSPB, ET]; and “we should have to be careful on what sort of timeframes we look at to get these quite […] large impacts because if you’re looking for an impact on policy it can take you years to get that” [SMI, ET]. At the same time, however, the interviewees indicated that it would only be a matter of time before their organisations would start influencing policy through the new workflows. All of the collaborations were building up a data corpus in order to influence policy in the longer term; for example: “the idea is that it [the work with dot.rural] will feed into the government recording schemes [such as the] National Pollination Strategy which DEFRA are working on at the moment […]. We’re involved with some of the outcomes from that and data provision. Because essentially, that’s the only way that we’ll know […] what bee species are where—we’ve not got enough data on them at the moment […] and this is a way of filling in those gaps” [BBCT, MT].
The second phase of data analysis brought out three further emergent nodes outside the focus of our impact framework, namely awareness raising, expectation management and data accuracy.
The collaboration helped the partners understand the possibilities and limitations of IT infrastructures: “some of the […] staff on our side were a little bit naive in terms of how simple people think it is to set up an online database […] any database actually because everybody thinks ‘oh digital stuff, no problem, database’, you just do the database and it will work, nah it never works like that!” [SMI, ET]. It also taught the interviewees about practicalities of their own organisations’ culture: “you just hit the glue sometimes […] it was very easy those first few years because it was me and dot.rural in Aberdeen and we would just email or phone and say can we meet up next week and we would do it. But moving into this next phase I cannot do that myself, […] we don’t have the authority to go and do that just in this office” [RSPB, MT].
Through working together the teams had a window into each other’s daily demands, thus allowing them to set manageable expectations: “I think there’s [now] a lot better understanding between the two different groups [academics and practitioners] of what the pressures on each of them are. I think that’s the main thing and we certainly have a better understanding of the pressures the dot.rural group are under” [SMI, ET]; and “with academia, that things can move away from their original focus because […] other ways have come up or more research […] more viable research has come up. So, it’s more like shifting sand” [BBCT, ET].
The infrastructures developed with the partners enhanced their organisation’s confidence in the accuracy of (biological) records generated and therefore their value for nature conservation: “the problem with this species is that we don’t know very much about their distributions […] because the country is so big and because so few people are really good at identifying them… we want to be able to identify them ourselves but not have to go out in the field and look for them everywhere so this really just allows us to effectively cover the whole country in terms of surveying because we can see where things are” [BBCT, MT]; and “it’s definitely increased the amount of records that we’re getting in so we get better from an overall project management point of view. We can clearly see now from looking at the data that some areas are clearing [from American mink], some areas are increasing and some there haven’t been any catches. […] so that’s really improved it because we can clearly see patterns now in the data” [SMI, MT].