Organisational Silos

A common complaint from anyone working in universities (or any large organisation) is the impact of organisational silos.  Since the 1950s most organisations have been structured hierarchically (Cilliers & Greyvenstein, 2012). Inherent to any hierarchical organisation is the vertical and horizontal clustering of people based on function (Cilliers & Greyvenstein, 2012). On the surface, the clustering of people affords a practical way for organisations to operate efficiently, whereby accountabilities and responsibilities are clearly delineated and communicated. However, in reality, these organisational delineations can become “tribal”, whereby people identify with and feel comfortable and secure with “their community”, which leads to a culture or mindset that inhibits cross-boundary collaboration and cooperation (Cilliers & Greyvenstein, 2012). Silos are barriers to achieving organisational goals and can often pose a threat to internal cooperation (Bento et al., 2020).

In my experience, one of the more debilitating examples of organisational silos is the separation of education and technology that is common with university organisational structures. The educators are typically clustered into faculties, disciplines and programs, while the IT folk will most often sit within a separate branch of the organisational hierarchy. Each of these departments will have different reporting lines, performance indicators, goals, perspectives on problems, problem-solving methods and so forth. Over time, this separation becomes a cultural norm that becomes deeply entrenched in our mental models; it becomes what we perceive as normal, and we accept it as such. I often see the problems caused by this arbitrary separation whereby it manifests as day-to-day decision-making that is either heavily biased towards technology considerations or heavily biased towards education considerations. In either case, internal politics, power games and inter-silo warfare are often evident, resulting in decision-making that more heavily biases the perspective of one party over the other.

However, no matter which party happens to dominate at a point in time, this is where the Dunning-Kruger effect can be seen in action. The Dunning-Kruger effect is a cognitive bias in which people with limited competence in a particular domain overestimate their knowledge and abilities. Perhaps a more brutal explanation of the Dunning-Kruger effect:

“The rationally ignorant fail to overcome their ignorance not just because they face steep costs and lack incentives to improve, but because they are unaware that they are relatively ignorant.”

(Dunning, 2011)

In other words, either the technology folk are overestimating their knowledge of learning and teaching or are dismissive of the educator perspective, or the educators are ignorant of,  or dismissive of the impact of technology on learning and teaching. From my (limited) perspective, I tend to see the pendulum sway either way rather than straddle the “compromise” space in between, which is where I think it needs to be.

Tim Fawnes puts forward the idea of entangled pedagogy where he suggests that pedagogy is not just methods, and technology is not just a vehicle for implementing these methods, but they are entangled and interdependent (Fawns, 2022). Neil Selwyn reinforces this perspective by stating that technologies can influence the way that people do things while at the same time are profoundly shaped by those who design, develop, implement and use them (Selwyn, 2019). Jon Dron presents the idea of orchestration where “it is the ways that the machine is orchestrated by humans, with humans, and for humans that makes it educational” (Dron, 2021, p. 10). Whichever theoretical or philosophical lens is preferred, it is clear that education (pedagogy) and technology are symbiotic and mutually influencing, and the arbitrary and active maintenance of their separation is fundamentally flawed.

There is a wealth of research around organisational silos and silo-busting strategies – ironically, the same genre of literature that gave us organisational silos in the first place. Unsurprisingly, much of the research around silo-busting tends to focus on things like shared organisational values, collaborative operating models, collaborative environments, leadership, reward and development (Bento et al., 2020; Cilliers & Greyvenstein, 2012; de Waal et al., 2019). Much of this is what my more cynical colleagues would label the “yay team” approach used by HR departments when they try to shift the staff culture. While I am likely exhibiting the same ignorance mentioned above in association with the Dunning-Kruger effect, I wonder if there are other ways that we could think about organisational performance.

Our organisation’s departments are driven to achieve predetermined and measurable goals that are meticulously aligned with the university’s strategic plan. Each department’s operational plan includes measurable outcomes that funnel upward to the university’s operational plan, something we’re all likely very familiar with. I think this is where the wheels start to fall off; it is too prescriptive. One such example relates to student retention, an ever-present and growing problem here in Australia. I haven’t seen the IT department’s operational plan, but I doubt that it includes student retention, even though almost every aspect of the student experience is mediated by technology to varying degrees. Likewise, my department, an academic department, does not have a performance metric around cybersecurity, when it is without question a shared responsibility.

I do not believe that the major problems faced by contemporary universities (like those the separation of educators and technologists creates) can be solved through administrative leadership. Our formal structures are not designed to foster the internal collaboration and innovation required to solve problems that are increasingly complex and entangled (Uhl-Bien et al., 2007). I would argue that some of the problems facing universities today have been created by or at least sustained by the inflexibility inherent in our formal organisational structures. Perhaps more accurately, it is the rigidity of our thinking about these structures that is the bigger problem. I think there are some clues in the complexity leadership literature, but shifting our thinking, shifting from long-entrenched ideas of what is normal is going to be the bigger challenge. I don’t have the answers, but the following are some ideas I came across while thinking about this post:

• Decentralise decision-making
• Decentralise problem identification and rectification approaches
• Flatten the organisational structure
• Create more project teams and cross-functional teams centred around initiatives or problems. Allow these teams to develop organically
• Focus on skills and expertise, not titles or formal positions
• Promote a learning environment where knowledge is shared
• Encourage innovation and experimentation outside of formal structures
• Shift from episodic performance evaluation (reports) to continuous and transparent assessment
• Shift from leaders as managers to leaders as facilitators or coaches
• Recognise that leadership exists at all levels of the organisation
• Accept ability and uncertainty
• Rely on values to guide decisions rather than policy

References

Bento, F., Tagliabue, M., & Lorenzo, F. (2020). Organizational silos: a scoping review informed by a behavioural perspective on systems and networks. Societies, 10(3), 56.

Cilliers, F., & Greyvenstein, H. (2012). The impact of silo mentality on team identity: An organisational case study [Systems psychodynamics; physical environment; structure; intragroup relations; experiences of management; intergroup relations]. 2012, 38(2). https://doi.org/10.4102/sajip.v38i2.993

de Waal, A., Weaver, M., Day, T., & van der Heijden, B. (2019). Silo-busting: overcoming the greatest threat to organizational performance. Sustainability, 11(23), 6860.

Dron, J. (2021). Educational technology: what it is and how it works. AI & SOCIETY. https://doi.org/10.1007/s00146-021-01195-z

Dunning, D. (2011). The Dunning–Kruger effect: On being ignorant of one’s own ignorance. In Advances in experimental social psychology (Vol. 44, pp. 247-296). Elsevier.

Fawns, T. (2022). An Entangled Pedagogy: Looking Beyond the Pedagogy—Technology Dichotomy. Postdigital Science and Education. https://doi.org/10.1007/s42438-022-00302-7

Selwyn, N. (2019). What’s the Problem with Learning Analytics? Journal of Learning Analytics, 6(3), 11–19-11–19.

Uhl-Bien, M., Marion, R., & McKelvey, B. (2007). Complexity leadership theory: Shifting leadership from the industrial age to the knowledge era. The Leadership Quarterly, 18, 298-318. https://doi.org/10.1016/j.leaqua.2007.04.002

Some thoughts on the universities accord

This week saw the interim release of the Australian Universities Accord. The accord aims to “drive lasting and transformative reform in Australia’s higher education system” – a worthy goal. The interim report reminds us of the fundamental public good of higher education and its transformative potential for individuals, communities and the nation. It applies a critical lens to the sector and suggests that the existing system lacks the “institutional resilience and metabolic rate required” to successfully tackle our national priorities.

The interim report calls for five priority actions to be immediately considered while further large-scale consultations are underway. The five priority actions are:

1. Extend visible, local access to tertiary education by creating further Regional University Centres (RUCs) and establish a similar concept for suburban/metropolitan locations.
2. Cease the 50% pass rule, given its poor equity impacts, and require increased reporting on student progress.
3. Ensure that all First Nations students are eligible for a funded place at university by extending demand-driven funding to metropolitan First Nations students.
4. Provide funding certainty through the extension of the Higher Education Continuity Guarantee into 2024 and 2025 to minimise the risk of unnecessary structural adjustment to the sector. Interim funding arrangements must prioritise the delivery of support for equity students to accelerate reform towards a high equity, high participation system.
5. Through National Cabinet, immediately engage with state and territory governments and universities to improve university governance, particularly focusing on:
   • universities being good employers
   • student and staff safety
   • membership of governing bodies, including ensuring additional involvement of people with expertise in the business of universities.

Personally, I am moderately happy with what I have seen so far about the Accord, especially since the majority of my university’s students are from regional and, most often, low-ses backgrounds. While my opinion is that it goes nowhere near far enough, I think it is a step, perhaps a glance, a hat tip, in the right direction. Taking a step back and reflecting on how the sector aligns with its core purpose is a useful exercise that can break through the crust of stagnant thinking that develops over time. I was also pleasantly surprised that one of the five priority action areas recognised the current employment conditions at Australian universities and noted an immediate need for change.

The report touches on the psychological well-being of students, staff, workloads, conditions, rigid workload arrangements, remuneration, wage theft and even the complex industrial agreements and government policy around funding arrangements. It acknowledges a need to address these issues if the sector is to attract and retain the highly-skilled workforce that is required now and into the future. Based on my observations over the last 17 years, I couldn’t agree more. However, as someone who sits in that uncomfortable, often unwelcome and almost always misunderstood space between education and technology in a university (we call it the 38th parallel), there are some intrinsically entangled challenges (dare I say sacred cows) that give rise to some cynicism about the future. Dragging the Australian Higher Education sector away from the corporate/commercial path it is on is not going to be easy.

Limited funding and increased demand have driven the pursuit of efficiency improvements across all parts of the typical university (not a bad thing in theory). However, the myopic pursuit of efficiency gains has, in many respects, come at the expense of effectiveness. We now have any number of departments, all clearly delineated by function, we have vast student administration systems, learning management systems, library systems, HR systems, payroll systems, project management systems, customer relationship management systems, timetabling and accreditation systems, we have large marketing departments that flood the airways with aspirational messaging, we have entire areas dedicated to policy development, we have student communication departments dedicated to the messaging to our students and so on, and so forth. All of this is aimed at or was justified by, improving efficiency.

We have all of this “stuff”, but we find ourselves with a tertiary education system that “values assessment over engagement, learning management over discovery, content over community and outcomes over epiphanies” (Morris & Stommel, 2018). We find ourselves with a tertiary education system that has become “economically rational” at the expense of its role as a vessel for public good (Hil, 2015), and lacks the systems, tools and methods to measure its value and quality in valid and reliable ways (Bain & Zundans-Fraser, 2017).

References

Bain, A., & Zundans-Fraser, L. (2017). The self-organizing university. Springer.
Hil, R. (2015). Selling Students Short: Why you won’t get the university education you deserve. Allen & Unwin.
Morris, S. M., & Stommel, J. (2018). An urgency of teachers: The work of critical digital pedagogy. Hybrid Pedagogy.

How do we design the need for design?

This post is loosely linked to the previous post about university doctrine and strategy and centres around learning, teaching and the application of technology. Part of the imperative for universities to become more adaptable and less bureaucratic is to take a critical and holistic look at our approach to IT and human systems. Is how we currently think about and integrate people and IT working for us? Is it fit for purpose now, and will it be fit for purpose tomorrow? I would suggest not, but maybe I’m cynical. However, I do think the almost complete absence of design thinking in how universities approach educational technology is holding us back, both at the design and implementation and the operational phases.

Perhaps my favourite explanation of design thinking comes from an interesting business consulting company called “Crazy might work“. They say design thinking is “an iterative process that generally begins by identifying a human centre and seeking to deeply understand what is important to that person. Having identified some of the challenges and aspirations that are most critical, the more enlightened design thinking practitioners amongst us then seek to engage those stakeholders in a co-design process, using a variety of methods to generate innovative solutions and then prototype and iterate these to perfection, or at least pilot” (see https://www.crazymightwork.com/design-thinking/). While I really like this explanation, it suggests that design thinking only applies in the initial pilot or prototype stages, whereas I think it needs to be an ongoing process.

In my experience, the approach to education technology in universities is fundamentally flawed in that the focus is invariably on the IT system rather than deeply understanding what is important to the people, not so much what they want, but what they need. In Australian universities, at least, it seems that most often, the wetware (people) are expected to adapt and bend to fit the affordances and limitations of the systems. Without getting into the arguments about buy-versus-build or one-size-fits-all approaches, I think there is an argument to be made that we have been neglecting the core purpose of information systems, which is to combine people and computers to process and interpret information. We often overlook the people bit. The almost exclusive focus on technology and technical factors often comes at the expense of a deep understanding of the tasks, goals and information needs of the humans involved, the social side of information systems, and we’ve seen this time and time again (Beer et al., 2019; Dawson et al., 2019; Ferguson et al., 2019; Macfadyen et al., 2014). Tim Fawnes puts it most elegantly when he suggests that both technology-dominant and pedagogy-dominant perspectives decontextualise technology and make us vulnerable to different forms of determinism (Fawns, 2022). I would argue that technological determinism dominates how Australian universities approach their learning and teaching technologies, albeit to varying degrees. Needless to say that there are any number of commercial entities and internal power brokers capitalising on what Selwyn et al. call this “technological hubris” (Selwyn et al., 2022).

My PhD is around learning analytics implementation and how universities decide to implement or develop product X to solve problem Y (quick update – they aren’t doing it well). I would argue that a key feature of any type of learning analytics is about knowing what is happening in our learning environments (and perhaps less about what has already happened, but that’s a whole other story). This relates to a common concept from the human factors domain called situational awareness – an individual psychological model that is the fundamental awareness that people have of what is going on around them (Endsley, 1995; Salmon & Plant, 2022).  Expanding on the idea of situational awareness (SA) is the idea of distributed situation awareness (DSA) where it is acknowledged that SA is an emergent property of socio-technical systems and is distributed across human and non-human agents (Salmon & Plant, 2022). So rather than treating SA as something that happens in operators’ minds, it is a systems phenomenon that resides in the interactions between system components, including humans (Salmon & Plant, 2022). So, from a learning analytics perspective or even just an LMS perspective, our knowledge of what is happening in our learning and teaching environments, our “better understanding of learners and the environments in which they learn“, is distributed across humans and socio-technical systems.

Now consider the individual teacher who is teaching their online class using their own pedagogical approach, centred on their discipline, their experience, and their knowledge of their students. The teacher’s ontology consists of the items in their reality. Their epistemology acts as the information processor and filter, and creator of new ontological elements. Their axiology (values and goals) is the basis for deciding what information matters, what is useful, and what they do next. In other words, their knowledge will change because they experience new pieces of reality, and it will also be driven in directions influenced by the teacher’s interests. Neither the teacher’s ontology, epistemology or axiology are static; they are coevolving as learning and knowledge develop and as they interact with information. As the teacher’s information needs evolve, the IT systems meet less and less of the person’s needs (Allen & Varga, 2006). Because our IT systems tend not to evolve (they become concrete lounges), the reality is always far ahead of IT systems. The information systems have, in some ways, become the epistemology of the individuals and the organisation (Allen & Varga, 2006). In short, our IT systems are limiting (Allen & Varga, 2006), and yet we exclusively rely on them to sense the reality of our learning and teaching environments.

I think there are some key points in the preceding paragraphs:

• our individual and collective ability to perceive or sense our learning and teaching reality is distributed across people and socio-technical systems and is evolving.
• our individual and collective information systems (systems of information) are also distributed across people and socio-technical systems and are evolving.

So getting back to design thinking, I think it could be easily argued that we have a clear need to apply design-thinking approaches to the development and implementation of our information systems and that one-size-fits-all approaches just do not work (Dede, 2008). However, I don’t think this goes anywhere near far enough. Once the systems are “released into the wild”, they need the generative capability to evolve with the ecosystem. Perhaps the question here is an organisational question more than a philosophical or technology-related question; how do we shift our thinking away from heavy-weight approaches to technology to light-weight, generative, and perhaps federated technology (Bygstad, 2017)? I think we have some understanding of the problem, but how do we move beyond the dogma of the status quo?

References

Allen, P. M., & Varga, L. (2006). A co–Evolutionary Complex Systems Perspective on Information Systems. Journal of Information Technology, 21(4), 229-238. https://doi.org/10.1057/palgrave.jit.2000075

Beer, C., Jones, D., & Lawson, C. (2019). The challenge of learning analytics implementation: Lessons learned. Personalised Learning. Diverse Goals. One Heart, Singapore.

Bygstad, B. (2017). Generative Innovation: A Comparison of Lightweight and Heavyweight IT. Journal of Information Technology, 32(2), 180-193. https://doi.org/10.1057/jit.2016.15

Dawson, S., Joksimovic, S., Poquet, O., & Siemens, G. (2019). Increasing the impact of learning analytics. Proceedings of the 9th International Conference on Learning Analytics & Knowledge,

Dede, C. (2008). Theoretical perspectives influencing the use of information technology in teaching and learning. In International Handbook of Information Technology in Primary and Secondary Education (pp. 43-62). Springer. https://doi.org/10.1007/978-0-387-73315-9_3

Endsley, M. R. (1995). Toward a theory of situation awareness in dynamic systems. Human Factors, 37(1), 32-64. https://doi.org/10.1518/001872095779049543 (Situation awareness)

Fawns, T. (2022). An Entangled Pedagogy: Looking Beyond the Pedagogy—Technology Dichotomy. Postdigital Science and Education. https://doi.org/10.1007/s42438-022-00302-7

Ferguson, R., Clow, D., Griffiths, D., & Brasher, A. (2019). Moving Forward with Learning Analytics: Expert Views. Journal of Learning Analytics, 6(3), 43–59-43–59.

Macfadyen, L. P., Dawson, S., Pardo, A., & Gasevic, D. (2014). Big Data in Complex Educational Systems: The Learning Analytics Imperative and the Policy Challenge [Journal Article]. Research & Practice in Assessment, 9(Winter, 2014), 11. http://go.galegroup.com/ps/i.do?action=interpret&v=2.1&u=cqu&it=JIourl&issn=2161-4210&authCount=1&p=AONE&sw=w&selfRedirect=true

Salmon, P. M., & Plant, K. L. (2022). Distributed situation awareness: from awareness in individuals and teams to the awareness of technologies, sociotechnical systems, and societies. Applied Ergonomics, 98, 103599.

Selwyn, N., Hillman, T., Bergviken-Rensfeldt, A., & Perrotta, C. (2022). Making Sense of the Digital Automation of Education. Postdigital Science and Education. https://doi.org/10.1007/s42438-022-00362-9

Doctrine or Dogma?

Thinking aloud and hopefully allowed:

In a cycle familiar to anyone working at a university, my university is currently working up a new strategic plan, and so there has been an uptick in conversations about strategic direction, vision, values, purpose and so forth. I quite like the process of developing a strategic plan at my university in that it tends to be open, transparent and collegial, even if the decision-making authority is ultimately concentrated among a handful of people. However, as I’ve often argued with colleagues, I think universities are generally pretty good at developing strategy, but unfortunately, they are generally really bad at operationalising said strategy, and I’ve often wondered why. I think part of the problem is how we understand, or perhaps don’t understand, the concept of doctrine and its relationship to a broader ecosystem.

Doctrine tends to be defined in a military-like way as the fundamental principles by which organisations guide their actions in support of objectives (Høiback, 2011). Doctrine is based on a set of assumptions about an organisation and their context and includes varying degrees of theory, culture and authoritativeness (Høiback, 2011). Generally speaking, doctrine is not a hard and fast set of rules but a guide to action that links theory, history, experimentation and practice. Strategic plans could perhaps be broadly interpreted as the manifestation of doctrine in university environments. It is important to understand that strategy is a plan of action to achieve particular objectives, while doctrine is the philosophical framework that encapsulates the strategy.

Perhaps a useful tool to help think about doctrine involves a sports metaphor. In team sports, there are two ways to make the most of the team (Høiback, 2011).

1. We gather the best players we can afford, position them based on their skills and competence, and allow them to exercise their judgement and abilities on the field, with some real-time shouted advice from the sidelines.
2. We pick, position and train the players according to a predetermined plan, and they play in strict accordance to the plan (think of the movie Moneyball).

In both cases, doctrine is the broad recipe that tells us how to play in order to win and encompasses theory (explanations and rationales), culture (the players and their motivations) and authority (who is authorised to do what) (Høiback, 2011). I think the sports metaphor above helps to understand the bottom-up versus top-down application of doctrine but doesn’t scale to an organisational context. A sport will be played on a clearly defined field, with a defined number of players governed by rules that are universally defined, understood and applied. Organisations, like universities, have many more internal and external moving parts and any number of unknown and unknowable variables and influences.

In my opinion, publicly funded universities in Australia lean towards the government end of the government / private enterprise spectrum because they tend to be heavily bureaucratic and are insulated from the adapt-or-die pressures private enterprises face. Arguably, the process of natural selection is less brutal for universities than for private enterprises, so flawed strategy, or flawed attempts at operationalising strategy, are perhaps less impactful than they might otherwise be for an equivalent privately funded organisation. In short, the survival of publicly funded universities is not necessarily tightly tethered to their performance and their ability to operationalise strategy. I would argue that this manifests in some of the “functional stupidity” that we see – the absence of adaptivity, a reluctance to use available intellectual capability, and the avoidance of justifications for decisions (Alvesson & Einola, 2018; Alvesson & Spicer, 2016; Hil, 2015; Paulsen, 2017).

There is, I think, an argument to be made that we are seeing an approach to strategy that somewhat alines with Max Weber’s doctrine of bureaucracy that is characterised by principles like hierarchical structures, with firmly established chains of command, strict regulation, rigid divisions of labour and a strong focus on measurable outputs (Weber, 2016). Consequently, the strict adherence to rules, regulations, policies and procedures has a tendency to suppress creativity, innovation and collaboration and likely accentuates the organisational silo problem (Bento et al., 2020; Cilliers & Greyvenstein, 2012; de Waal et al., 2019; Jeong, 2012). In short, the focus is on stability and maintaining the status quo.

This is not to say that I think universities should all be privatised and turned into for-profit organisations so they can be subjected to Darwinian competitive pressures; far from it. To me, education is a public good and represents an unbelievably valuable long-term investment to society. However, so long as we continue to think that we live in a static, economically rational bubble whereby our strategic plan links neatly into our operational plan, which links to our divisional and unit plans, which links to our individual performance indicators, which are nicely encapsulated by policy and process, we will continue to not evolve. What is missing is an underpinning acknowledgement of the need for adaptability, innovation and change. COVID, AI, the Australian Universities Accord and even the recent report on Teacher Education are examples of how our strategic and operational environments are part of a broader ecosystem that is changing and adapting, often in contrast with our strategy. I don’t think our doctrine, our current ideology and our resulting strategy are necessarily equipping us with the adaptivity we need or are going to need.

Further reading:

The systems view of life (Capra & Luisi, 2014)

The Education Ecology of Universities: Integrating Learning, Strategy and the Academy (Ellis & Goodyear, 2019)

Gravity-free Decision-making: Avoiding Clausewitz’s Strategic Pull (Zweibelson, 2015)

References

Alvesson, M., & Spicer, A. (2016). The stupidity paradox: The power and pitfalls of functional stupidity at work. Profile Books.

Bento, F., Tagliabue, M., & Lorenzo, F. (2020). Organizational silos: a scoping review informed by a behavioral perspective on systems and networks. Societies, 10(3), 56.

Capra, F., & Luisi, P. L. (2014). The systems view of life: a unifying vision. Cambridge University Press.

Cilliers, F., & Greyvenstein, H. (2012). The impact of silo mentality on team identity: An organisational case study [Systems psychodynamics; physical environment; structure; intragroup relations; experiences of management; intergroup relations]. 2012, 38(2). https://doi.org/10.4102/sajip.v38i2.993

de Waal, A., Weaver, M., Day, T., & van der Heijden, B. (2019). Silo-busting: overcoming the greatest threat to organizational performance. Sustainability, 11(23), 6860.

Ellis, R. A., & Goodyear, P. (2019). The Education Ecology of Universities: Integrating Learning, Strategy and the Academy. Routledge.

Hil, R. (2015). Selling Students Short: Why you won’t get the university education you deserve. Allen & Unwin.

Høiback, H. (2011). What is Doctrine? Journal of Strategic Studies, 34(6), 879-900. https://doi.org/10.1080/01402390.2011.561104

Jeong, C. H. (2012). Principles of public administration: Malaysian perspectives. Pearson Malaysia Sdn Bhd.

Paulsen, R. (2017). Slipping into functional stupidity: The bifocality of organizational compliance. Human Relations, 70(2), 185-210. https://doi.org/10.1177/0018726716649246

Weber, M. (2016). Bureaucracy. In Social Theory Re-Wired (pp. 287-292). Routledge.

Zweibelson, B. (2015). Gravity-free Decision-making: Avoiding Clausewitz’s Strategic Pull. Australian Army.