In this day and age, the world is marked by rapid technological development. Subsequently, educational institutions face an unprecedented dilemma: how to tackle the power of artificial intelligence (AI) to stay ahead in the game. I had the opportunity to interview IT consultant, Bauke van der Weijden – who serves secondary schools as a client – to shed light on this matter. The conversation gave me new insights and created a clear picture of the current state of AI in education – or, perhaps more accurately, the lack thereof – as well as the elements that keep educational institutions from embracing and implementing game-changing innovation. This raises an important question: Are schools prepared and willing to educate and mentor students in this modern day of artificial intelligence?

Catching the AI Wave

One of the most striking findings from the interview was the blatant ignorance about digitalisation within schools. Many educational institutions appear to be behind in implementing AI, although this technology continues to transform sectors all around the globe. IT consultant Van der Weijden notes that “Educational institutions are very reactive”. This reactivity is demonstrated by how these institutions often play catch-up, particularly in the area of AI. This brings about a digitalisation knowledge gap since schools find it difficult to keep up with their technically proficient students. The gap in understanding places schools at a noticeable disadvantage, while educational institutions should actually be leading ahead of the curve in digitalisation and educating students for a future in which AI will undoubtedly be a crucial part.

Tackling Educational Apathy

Besides the lack of awareness, within educational institutions, there is also a reluctance that prevents the implementation of AI. IT consultant Bauke van der Weijden faces this a lot in his daily work. The staff at schools do not see the benefits of implementing AI, as they have other priorities. This lack of motivation is one of the biggest obstacles to integrating AI into educational institutions. Many teachers and other school staff appear uninterested in the notion of digitalisation, thereby also ignoring the opportunities that AI can bring to them. For IT consultants wanting to introduce AI into the educational industry, the apathy among school staff presents a significant hurdle.

AI as a Classroom Cop

Many educational institutions have yet to fully grasp the potential that AI provides in today’s quickly digital environment. Academic integrity worries have been a major factor in many institutions’ decision to introduce AI into the classroom. As a result, the widespread opinion within education is centred around employing AI as a safety precaution, a watchdog looking out for possible risks like plagiarism. Van der Weijden emphasizes that schools primarily consider AI from a security standpoint, utilizing technologies like ChatGPT to screen for potential violations of academic sincerity. But is this the real potential of AI in education? Hardly.

Exploring AI’s Potential

The application of AI in education goes beyond mere plagiarism detection. According to Van der Weijden, “There are also increasingly better AI tools,” not just for detection but also to completely alter how subjects are educated and evaluated. Schools need to be receptive to the opportunities that AI can bring. However, according to Van der Weijden, it is still unpredictable what AI will exactly bring in the future: “The applications are so versatile. All we know is that the ones who start using it first will be the frontrunners in what they do.” While students quickly adopt AI, schools frequently fall behind, behaving in response rather than inventing. Institutions of higher learning require a paradigm shift rather than just trying to “keep up with what the market will do.”

From Digital Guard to Guide

The interview with Van der Weijden sheds light on the need for educational institutions to close the digital gap. AI shouldn’t be viewed as solely a detecting tool. It should be seen as a collaborator with the potential to completely alter how we transmit and consume knowledge. The incorporation of AI into the curriculum is not only advantageous but also necessary given its capacity to offer individualized learning experiences, immediate feedback, and data-driven insights. Schools should begin educating staff members and students on the advantages and disadvantages of this disruptive technology as well as how to use it effectively to navigate and code a new curriculum.

Consultant’s Call to Action

What is the real problem? Reactivity versus Proactivity. Educational institutions can no longer afford to remain spectators in a world where AI is pervasive. Schools need to change from being reactionary institutions to becoming proactive ones. Consultants should also take on this proactive role. Before technologies like ChatGPT become commonplace among students, consultants should speak with schools about the possible uses and abuses of these platforms, as Van der Weijden accurately puts it. The difference between what students already know and what they need to know about AI might be bridged with a proactive approach. IT consultants need to do more than just share their technical insight and expertise to increase schools’ adoption of AI. They should take an active role in engaging schools in discussion about the revolutionary possibilities of AI, as well as providing practical learning approaches, like workshops and training. A practical approach will aid educational institutions in gaining the knowledge and confidence to effectively incorporate AI into their curricula.

Broadening Horizons

Thus, to entirely tackle the power of AI, schools should change their perspective. It’s time to embrace AI as an ally, a tool that can not only discover errors but also improve the educational environment, rather than viewing it only as a danger or a gatekeeper. It’s an appeal to lead, create, and establish a standard for the future rather than merely keeping up with the times. The future of education with AI is not just promising—it is exhilarating—from where we stand right now.

Acknowledgement Statement

This blog is part of the student writing competition in Management Consulting Master Program at the School of Business and Economics.

Disruption has been a fearful term that is used more and more often when talking about the transformative force of Generative artificial intelligence (GenAI) in Professional Service Firms (PSFs), under which Consultancy firms. Why fearful? The popularity of natural language processing (NPL) technologies – which is a type of Generative AI – is growing increasingly. It has the astonishing ability to generate novel content (images, text, etc.) to answer complicated questions and give solutions with such a speed that the human mind cannot match. GenAI systems make use of models that have been trained on extensive datasets to comprehend the patterns and relationships found in the data. This enables the tool to only produce solutions and answers that are similar to the training data. As a result of this fearful disruption, consultancy firms are increasingly adopting this state-of-the-art technology to assist them in their daily work. Certainly, this will have an impact on the status quo of consultancy firms and their corporate hierarchy. However, is this new technology so advanced that it will replace the trust in human expertise completely? Today, public and in-house language tools are progressively used in consultancy, but not all ethical and practical implications are yet overcome. To analyze this in more detail, a Senior Consultant operative in the Netherlands was asked to share her insights and point out what exactly is fearful using the two types of GenAI.

Public/Open Language Tools

Changing the status quo, is there a transformative paradigm?

The use of publicly owned and openly used language models such as ChatGPT, Bard, Quillbot or Agros Multilingual are growing for consultants’ daily tasks, such as paraphrasing, enhancing sentence structure, translations and the writing of introductions. Indeed, these technologies greatly help consultants do the same amount of work, in a shorter amount of time. You need less and less people to complete the tasks: The status quo of consulting is bound to change. The interview with a senior consultant confirmed this transformative paradigm: “Consultants will likely lose their jobs; as a result, layers of the corporate hierarchy will get thinner, but they won’t disappear.” Your level in the corporate hierarchy is a representation of your responsibility, based on your expertise and build-up trust, in the firm and by your clients.

The operational gap

Clearly, an operational gap should be identified between the rather simple and efficient tasks that GenAI is allowed to perform, and the tasks for which the human eye remains essential. Ethical considerations are the reason that this gap still exists. The use of GenAI remains an ethical uncertainty, as its trustworthiness cannot be determined or guaranteed. This is the reason that the public GenAI operates with a confidentiality risk. At the firm of an interviewed expert: “Open language tools, such as ChatGPT and Google Translate are not allowed to be used. Because it can give too much client information, even sharing the smallest bits, is not allowed.”

All data you enter, you are giving consent to become available training data, on which other answers and possible solutions generated by that tool will be based. In addition, opacity is the lack of transparency that AI algorithms are able to provide, regarding generating operations and reasoning to their users. This contradicts directly a core responsibility of the consultant, being able to explain your sources and information at all stages of their consulting research. A connecting hazard to this is the mixture of factual and non-factual data that makes the credibility of information generated through language tools questionable. Evidently, the use of open GenAI is still quite limited in presumably taking over all tasks of a consultant. The human eye is required to be the controlling factor ensuring the trustworthiness and accountability of the firm towards clients.

Private/in-house Language Tools

In-house language tools:

“Bullshit in, is bullshit out…” as was quoted by the interviewed expert. She reflected upon the tendency of PSFs to make large investments in GenAI in-house tools. For instance, PwC has invested 1 billion dollars in their own (pilot) ChatGPT and EY 1.4 billion dollars in an AI platform and announced future spending in their language model tools. Manifestly, creating a more contained, secured, transparent, and controllable GenAI tool that can solve most security and confidentiality issues, while generating solutions on valid data. As confirmed by the interviewed expert, this disruption would hypothetically have a great impact on the transformative paradigm as it could close the operational gap. Noteworthy, the ability to have this great impact will be limited to the individual large (international) PSFs that have abundant sets of data and the funds to create, manage and improve these language models continuously. But again, not without (ethical) risks.

A limited investment

All language models will be as big or limited as their dataset itself is. This means that the quality of your in-house generated solutions will be based and trained on the companies’ data only. Hence, the idea of bullshit in is bullshit out. To add, external factors and awareness are excluded to keep the data contained, limiting the ability to research or find undiscovered information, a quality for which a public language tool like ChatGPT is explicitly valued. Most disappointingly, it will depend on client confidentiality agreements whether their data can be shared (anonymously) with the in-house tool. “With current strict security and confidentiality agreements, sometimes team members are not allowed to view all data available” let alone all employees of a large (international) consultancy firm. Despite the promising efforts by large PSFs, overcoming a predominant confidentiality problem with an in-house trustworthy GenAI tool is not yet guaranteed.

In conclusion, the application of Generative Artificial Intelligence (GenAI) in consulting raises both the prospect of a paradigm shift and ethical issues. Public language tools improve productivity and effectiveness but pose concerns about confidentiality and transparency. Large corporations are investing a lot of money in in-house technologies to address the operational gap and offer solutions that are transparently and securely regulated. The phrase “bullshit in, bullshit out” perfectly captures the problem of only using data that is internally confined. In-house GenAI technologies have a lot of work to do before they can be fully trusted and accounted for, despite their potential. To maintain its credibility while negotiating the changing context of human-machine collaboration, the consultant industry must still strike a balance between productivity and ethical considerations, to ensure its trustworthiness.

Acknowledgement Statement: This blog is part of the student competition in Management Consulting Master Program at the School of Business and Economics.

The world as we know it today is developing at a rapid pace, where technological advancements appear like wildflowers, transforming our technological landscape. One of the most actual developments has been that of Artificial Intelligence (AI), with tools like OpenAI’s chatbot ‘ChatGTP’ gaining a bigger user base by the day, including consultants not shying away from using it. With AI being able to perform lightning-fast idea formulation and data analytics on big data, it has become interesting for consultancies to explore developing their own AI tool.

However, as with every new and hot topic that seems to conquer our world and revolutionize it with its benefits, also AI comes with certain complications. Firstly, a complication that is often not spoken about is the energy usage of AI. The development and maintaining of AI systems comes not only with financial costs but also with environmental costs. Secondly, the aspect of human factors should not be overlooked. Especially with the work of consultants, in which thoroughly considered solutions are formed through a deep and detailed understanding of the problem and situation at hand.

So, an important question arises when thinking of the future of consultancies in light of AI implementation. Should consultancies explore the possibility of using AI to take over their workload and take the environmental effects for granted? To answer this question, I interviewed Ton Metselaar, experienced management consultant at a successful business and technology consulting firm. The conclusion is that we cannot let this rapid development run on its own without looking at the consequences. Every innovation should be assessed on its environmental impact and ways to limit the energy usage should be explored. Furthermore, the human factor in consultancy work is crucial due to their expertise and relationship with the client and this should stay at the core of the value they bring to clients.

Exploring the benefits AI can offer

The speed and completeness of the answers AI bots currently provide is impressive, to say the least. The convenience of having a little AI helper when doing your work can help to initiate ideas and save time when doing routine tasks. But the future lies further, where consultancies will try to reap the benefits of using AI to analyse huge chunks of data within seconds, where normal data analysis would take significantly longer. These ways of saving time come with saving costs as well of course, making it interesting to explore the possibilities.

Unravelling the environmental threats of AI

Yet, where people picture a world where AI can perform all their tasks and we do not have to do any work ourselves anymore, it is not without drawbacks. Like other technological advancements, AI models have a certain carbon footprint. The humongous amount of data that is stored by data center servers requires a lot of energy and water usage to run the servers, equipment, and the cooling systems. Ton Metselaar explains that it’s like calculating the transactions for Bitcoin, which is known to consume large amounts of energy. AI models produce CO2 emissions in three ways. The initial training of the model is the first and most energy consuming way, with researchers calculating the CO2 emission at 626,00 tons of CO2 which can be compared to the CO2 emissions of 119,000 cars (Strubell et al., 2019). Furthermore, the carbon footprint of keeping the generative models running and letting people interact with it are slightly below these emissions. The last way is through the updating and tailoring of the model to a consultancies’ specific information, which uses the least amount energy.

Analysing the importance of the human factor

Next to the fact that AI has certain drawbacks, it also contains flaws. As Ton Metselaar accurately puts it: “AI can make a lot of suggestions and have ideas on how to make things simpler but as a model it can never be completely without mistakes”. AI might interpret certain factors wrong or miss out on contextually important details which can lead to wrong outcomes and bad solutions. It is therefore not a reliable source. In addition, the absence of human empathy and understanding is also lacking with AI since they are unable to genuinely understand the client concerns. Clients always seek an emotional and human understanding that AI cannot offer. This can make clients feel like they are treated as data points rather than individuals with unique requirements and specific concerns to be addressed. AI cannot establish trust or build reputation with clients through meaningful conversations, active listening, and the human touch that comes from genuine interactions, which are the cornerstones of client relationships.

Proposing a sustainable way of AI usage

But what should our future look like then?

Ton Metselaar continues to explain that for a good consultant, it is essential to be an expert in their field. Therefore, it is vital that they can carefully listen to what a client needs and what specific situation they are in. Subsequently, this information should be mindfully analysed to come to the optimal solution. Ultimately, this needs to be properly communicated to the client, with which the relationship and the maintaining of that relationship is indispensable. All these aspects show that AI cannot replace the human factors consultants bring to the table. Furthermore, with our world being threatened by drastic environmental issues, “We should not only save the planet, but also save ourselves. The climate will likely kill us before it will kill the planet”, as Ton Metselaar alarmed in the interview. When looking in further detail at the solutions we should not aim for every consultancy to build their own specialised AI model but rather build on existing ones to limit energy usage. Moreover, it is needed to incorporate AI usage in the monitoring of a company’s emissions to be aware of its magnitude. To really seek for responsible improvement, environmental-friendly AI developments should be sought instead of creating completely personalized ones.

Reference list

Kumar, A., & Davenport, T. (2023, July 20). How to Make Generative AI Greener. Harvard Business Review. https://hbr.org/2023/07/how-to-make-generative-ai-greener?autocomplete=true

Strubell, E., Ganesh, A., & McCallum, A. (2019). Energy and Policy Considerations for Modern Deep Learning Research. Proceedings of the AAAI Conference on Artificial Intelligence, 34(09), 13693–13696. https://doi.org/10.1609/aaai.v34i09.7123

Acknowledgement Statement

This blog is part of the student writing competition in Management Consulting Master Program at the School of Business and Economics

AI is changing the world

AI is changing the world. Maybe, experiencing these changes from the inside, as citizens of the game changer superpowers, we don’t really realize the violent impact of disruption on our daily life. The violent impact will come when, while cooking dinner for our beloved family we realize that an Artificial Intelligence, linked to the watch of our children, through monitoring pulse rate, body heat and oxygen in the blood, will be able to recommend the best cartoon for them to watch or the best vegetable to eat. And just at that point we will really think “ok, what’s happening here?”. But for now, seeing these changes in “rallenty”, reading about one “small” innovation at a time (just because we can’t read simultaneously more than one word at a time), doesn’t really seem to shake us. Well, long story short, the world (and the business world firstly) is changing and it’s changing fast.

When speaking about innovative practices, people can lag behind, Businesses can’t

We, as people, can surely remain back a few steps without risking bankruptcy. Businesses can’t. Nevertheless, when the businesses on which we focus are consultancy societies that, in order to survive, formulate strategies to make other societies stand out, within a sea of competitive societies backed up by other societies. In this mess,it is inevitable that consultancy firms must not only keep up with innovation, but even direct and guide it. Regarding this last statement I’m pretty sure they will. How? Well for two main reasons, they are constantly immersed in a network of stakeholders (clients and partners) who are informed or need to be informed regarding cutting-edge technologies and trends and because of their human-centered nature (with relatively low fixed assets) that allows them to implement new methodologies or sell new products in a fast and nimble way. Now, when we speak of implementing new methodologies and selling new products, what are we referring to? Well, in this article, we are referring to implementing and selling Artificial Intelligence languages.

How can new languages be created? A chat with Carlo

In order to understand how new languages are created, I interviewed my long-time friend Carlo, Master of Science in Machine Learning and Research Engineer at CISPA Helmholtz Center for Information Security. In simple words Carlos’s daily job involves adjusting leaks and improving the state of the art of AI and deep learning models. I interviewed Carlo in order to understand what it means for Consultancy Firms to create their own AI language and what are the variables involved. Speaking with Carlo I understood that there are two main protagonists in this process, the data (the oil) and the model (the engine). While the parameters of the models can be obtained and used by all, since societies such as Meta make them public and useable (we are speaking of pre-trained, large and generalized language models), the data needed to make the model speak the “consultancy language” (through the “fine-tuning” process) is more difficult to be found. For this reason it is more likely that big companies such as PwC, EY, KPMG, that already have tons of terabytes of in-house data can more easily get the engine to work. Small companies instead, are obligated to download it from public online sources such as Kaggle or Wiki English that still provide great quantities of good quality data. This doesn’t mean that small companies can’t do it, it just means that for them it’s probably going to be more costly. So once the consultancy company in object has on the one hand Meta’s pre-trained AI model and, on the other hand, the data, Carlo takes the field. His role is to use the data collected making the model speak the strategic consulting or marketing consulting or HR consulting language (depending on the data collected), delivering a product that can increase the efficiency of work within these companies. And how does he do this? Through the fine-tuning; a process that consists in training the pre-trained, large and generalized language model and making it better suited for a particular application.

Deep diving the apparently impossible process

This process involves the use of more than 20 GPUs (Graphic Processing Units, the billions of operations needed to train these models are performed on specialized computers built for quick and parallel processing). Once the model has been trained to serve a particular mansion or “speak” a particular language, the model can be prompted and used to generate new text or voice. What happens in this second step (called inference or prediction) is often referred to as a black box, since the human mind can’t really understand what is going on under the hood and why exactly the model is generating a single specific output (but this is another story). So once the fine tuned model is created, it needs to be put in production. Putting a fine-tuned model into production is a complex process. Through CI/CD pipelines, which means Continuous Improvement and Continuous Development, the model is updated and trained with data and questions, and every time a new output is generated, feedback on that output is feeded back to the model, to ensure the full lifecycle of the CI/CD pipeline. This helps ensure the model works effectively and doesn’t give unwanted answers (such as racist answers or information on how to conduct illegal activities). Finally, after completing this phase, the model is ready to be used by the consultancy firms (while needing continuous training with new and updated data).

The outputs of the impossible process, the case of Lilli

This process, which seems long and expensive, is actually doable, thanks to the work of specialized engineers and consultants, such as Carlo, that concludes the interview making his own prediction: “I think the major consultancy companies, in five years, will all have ad hoc fine tuned AI models integrated into their systems. Their employees will use them to boost their performance working in a more efficient and data driven environment.” And someone already started! McKinsey, this year launched “Lilli,” an own generative AI solution that aggregates all Mckinsey’s knowledge and capabilities in one place. The data used to train Lilli relies on more than 100.000 documents and interview transcripts that the firm collected during years of hard work. For Adi Pradhan, an associate partner who specializes in technology strategy and transformations, Lilli is “a thought-sparring partner” ahead of meetings and presentations. He uses Lilli to look for weaknesses in arguments and anticipate questions that may arise, to tutor himself on new topics and make connections between different areas on the projects.

Acknowledgement Statement

This blog is part of the student writing competition in Management Consulting Master Program at the School of Business and Economics.

References

• How Professionals Adapt to Artificial Intelligence: The Role of Intertwined Boundary Work, Journal of Management, 2023
  [https://onlinelibrary.wiley.com/doi/epdf/10.1111/joms.12936]
• How professional services firms dodged disruption, MIT Sloan Management Review, 2023
  [https://sloanreview.mit.edu/article/how-professional-services-firms-dodged-disruption/]
• Consultants Emerge as Early Winners in Generative AI Boom, The Wall Street Journal, 2023
  [https://www.wsj.com/articles/consultants-emerge-as-early-winners-in-generative-ai-boom-8df71d38]
• Killing Strategy: The Disruption Of Management Consulting, CBINSIGHTS, 2020
  [https://www.cbinsights.com/research/disrupting-management-consulting/ ]
• Revolutionizing Decision-Making: How AI and Data Analytics are Transforming Management Consulting Practices, Medium.com, 2023
  [https://medium.com/accelerated-analyst/revolutionizing-decision-making-how-ai-and-data-analytics-are-transforming-management-consulting-94b98a8b1e1b]
• Meet Lilli, our generative AI tool that’s a researcher, a time saver, and an inspiration – McKinsey Blog, 2023
  [https://www.mckinsey.com/about-us/new-at-mckinsey-blog/meet-lilli-our-generative-ai-tool]

Think of organizations as intricate networks of communication channels—meetings, reports, calls, workshops, and other interactions. Communication channels are especially important in organizations that are organized into specialized units or departments. They help to align with strategic objectives, ensuring that each unit’s efforts contribute to the organization’s overarching goals. How this network is structured significantly shapes what leaders and other members find crucial, how they direct their day-to-day efforts, and where they focus their attention. The “pipes and prisms” of this attention architecture determine when, where, and how decisions are discussed and made, involving specific individuals and adhering to certain protocols.

While this organizational architecture might seem unchanging and dictated by upper management based on their vision and preferences, our study published in the journal Strategic Organization reveals that these ‘pipes’ aren’t rigid. They respond not only to top management teams but also to other organizational actors, adding dynamism to our understanding of attention architecture and the agency of mid-level actors.

Strategic shifts within an organization lead to changes in attention architecture

When an organization alters its strategy as a consequence of new technologies, emerging players, or shifts in the external environment, the attention of leaders naturally shifts too, resulting in changes to attention structures. However, such changes can bring both positive and negative outcomes for those who work with communication channels – mid-level employees. The communication channels they contribute to can gain or lose its importance. This was evident in our study of professional strategists at Ericsson (large telecommunication firm) who, despite losing their central role initially due to strategic transformation, managed to regain their position. Two strategies aided their resurgence.

Expanding and Connecting ‘Pipes’

First, the group we studied reinvented some of the communication channels. They explored digital tools, recognizing the potential of involving new actors in established practices, such as understanding industry trends. Traditionally, this task was performed by experts. Mid-level employees also harnessed existing connections with core customers, proposing a Customer Engagement Group to align with top management’s focus on customer satisfaction. This experimental approach aims to add novel elements to existing channels, often by broadening participation through digital tools like crowdsourcing or online communities. Such experimental thinking is the underlying logic of reinvention – what is the novel aspect we can add to the existing channel? Extending the number of participants involved in a communication channel could be one of the promising ways to reinvent or expand the existing ‘pipe’. The availability of digital  tools like crowdsourcing or online communities and chats are useful in it.

Reviving and Repurposing ‘Pipes’

Another way to align communication channels with the evolving architecture is by revitalizing outdated channels. We called this renewal. To reintegrate old practices, it’s essential to identify gaps or areas where communication channels can bring value. Networking skills are crucial here. We observed how forming alliances with groups entrenched in the new attention architecture is the key. The group of professional strategists partnered with the technologists, who managed essential communication channels for top management decisions. The professional strategists’ strategic knowledge and industry expertise complemented the technological prowess of the technologists, successfully reintroducing joint strategy meetings into the new communication architecture. This approach of repurposing channels involves identifying how and when channels can be useful in addressing new strategic challenges. The selective reuse of familiar practices is the underlying logic of renewal. It is important to consider: what are the core communication channels for Top Management Team? Who is the core player in them? And what value can we add by partnering with those players? The ability to evaluate the new communication structure and clear value proposition for potential partners plays a pivotal role in reviving old ‘pipes.

Organizational shifts might be an opportunity for different professional groups to regain their importance

Any transformation that an organization undergoes in its structure, culture, processes, strategies, or other fundamental aspects present opportunities for diverse professional groups to reclaim significance. The story of Ericsson’s strategists exemplifies how organizations can adapt to significant changes through flexibility and innovation. When traditional structures are disrupted, various employee groups, from strategy professionals to HR, Finance, and Marketing, can maintain their importance by creatively redesigning communication channels. As technologies like AI increasingly challenge professional roles, the ability to reinvent and renew communication channels empowers employees to strengthen their position, amidst major organizational changes.

The Covid-19 pandemic and subsequent government measures decreased the number of people who wanted to or could become entrepreneurs in Africa. At the same time, the crisis yielded innovativeness and resilience among new and existing business owners. How can entrepreneurs and policy makers turn crisis into opportunity, and build back better through entrepreneurship?

The global crisis affected entrepreneurs all around the world, and Africa was no exception. Much focus was on the negative impact of the crisis: several relief funds were released by the donor community in the global North to support African entrepreneurs in these difficult times, and the pandemic was dubbed a “gendered” crisis as women entrepreneurs were said to be disproportionately affected through the increased time spent on childcare and other unpaid care tasks. There was little space for discussing the resilience demonstrated by African entrepreneurs, and the opportunities Covid-19 unlocked. The four studies in the edited volume ‘Entrepreneurial Responses to Covid-19 in Africa’ take a closer look at these two contrasting effects on entrepreneurship and Covid-19 in Africa: crisis on the one hand, and opportunity and resilience on the other.

Entrepreneurial intentions go down

Although the impact of the pandemic varied greatly across the continent, African economies generally were hit hard by the Covid-19 pandemic and subsequent measures, such as lockdowns and market closures. Entrepreneurial intentions and activities had a broad downturn due to substantial risks on both demand and supply side. Entrepreneurs were forced to downsize or (temporarily) quit their businesses, while fewer novel entrepreneurs started their own companies. Those that did engage with entrepreneurship seemingly did so out of necessity. A survey conducted by Hanâa Benchrifa and Steven Kator Iorfa amongst Moroccan university students (chapter 1), for example, found that students who felt threatened about their future due to the lockdown and subsequent scarcity of resources developed more positive attitudes towards entrepreneurial activities – considering it as the only viable option in a depleting job market.

On the other side of the continent, Magnus Godvik Ekeland (chapter 2) spent one year in a South African township during Covid-19 times to better understand how the Covid-19 pandemic impacted the lives and livelihoods of young township residents. Specifically, his research aimed to uncover whether a government-dispensed Basic Income Grant would increase entrepreneurial intentions. Based on conversations with unemployed young men and observations on how they spent a temporary Covid-19 grant, Ekeland explains that entrepreneurial intentions are not likely to increase because of specific contextual dimensions. For these men, it was for instance less than desirable to become dependent on a (female) relative. This fear kept them from viewing entrepreneurship as a short-term solution to unemployment.

Entrepreneurial resilience and innovation go up

In both studies described above, entrepreneurship is considered second best to salaried employment in times of crisis. The final two chapters, however, shed light on a different outcome of the pandemic. These studies showcase entrepreneurs’ resilience in crisis, and the ability to come up with innovative solutions. When export numbers declined, Mercy Mwende, a Kenyan agri-business woman, developed a new product (affordable porridge) to appeal to the local community and diminish dependence on external markets. Mercy was part of a larger interview study conducted by Lotte-Marie Brouwer comprising twenty Kenyan female agri-entrepreneurs (chapter 3). Her chapter explores how these entrepreneurs demonstrated entrepreneurial resilience: “the ability of an entrepreneur to manage difficult personal and market conditions as well as destabilising events, and be future-oriented”^[1]. Short-term strategies included reducing costs and working side jobs, and long-term adaptation strategies were changing target markets and implementing digital solutions. For this specific group of entrepreneurs, the Covid-19 pandemic even provided new markets that otherwise would have been more difficult to enter as they would have had to compete with (Northern) imported products.

Similarly, two medical innovations from Tanzania and Kenya were exemplary of how innovative responses can offer coping mechanisms in times of crisis. Neema Komba and Chanyoung Park (chapter 4) show us that, rather than becoming paralyzed by the fear that was instigated by the pandemic, the entrepreneurs in these cases were able to ‘fight’ instead of ‘flight’, provided they receive proper support. This resulted in the founding of Tiba-Vent, a low-mechanical ventilator built by fifteen students of Kenyatta University in Nairobi, and the Cubic Bupiji Sauna – a steam inhalation treatment invented by George Buchafwe of Star Natural Products from Tanzania. The development cycles of these inventions were quite different due to differences in institutional or policy support. Whereas Tiba-Vent had to wait a long time to receive the proper certification, the Bipiji Sauna was endorsed by local politicians and public media instantly, and as a result the invention was adopted by hospitals a lot sooner.

From crisis to opportunity – three tips for practitioners

On the one hand, the Covid-19 pandemic decreased entrepreneurial intentions in Africa. On the other hand, entrepreneurs illustrated entrepreneurial resilience and innovativeness in responses to the crisis. Based on our findings, we end with three tips for practitioners who want to build back better through entrepreneurship.

1. Design proper entrepreneurial education.

In entrepreneurship education, it is important to consider the different motivations students have to engage in entrepreneurship. Students who consider entrepreneurship as the only viable option because there are no jobs, are inherently different from students who are opportunity-driven. Benchrifa and Iorfa encourage entrepreneurship educators to design educational programs such that both groups of students are activated to effectively increase entrepreneurial behaviour.

2. Take contextual dimensions into consideration.

Entrepreneurs come in all shapes and sizes. On a continent with more than 50 unique countries, there are many factors such as gender, class, sector, and national context that play a role in how well entrepreneurs respond to crises. Whereas schemes such as Basic Income Grants might have been proven successful in other regions to promote entrepreneurial behaviour, Ekeland’s research shows that it is important to also consider local notions of personhood whilst designing these policies. Depending on contextual perspectives of for example masculinity and dependency, programs that are supposed to increase entrepreneurial behaviour might not prove effective.

3. Foster entrepreneurial resilience and innovation.

Policy makers and ecosystem stakeholders have the potential to create positive framework conditions to foster entrepreneurial resilience. Brouwer, for example, demonstrates how the Northern donor community should be careful in approaching “African women entrepreneurs” as a homogenous group portraying them as “victims” during crises. Instead, they should analyse them in their specific context to uncover their particular needs while acknowledging their adaptive resilience. Komba and Park also show the importance of peer- and institutional support in fostering resilient entrepreneurial communities.

^[1] Fatoki, O. (2018). “The Impact of Entrepreneurial Resilience on the Success of Small and Medium Enterprises in South Africa,” Sustainability 10-7: 2527.

The Flow of Management Concepts

In today’s fast-paced business world, organizations strive to adapt and thrive by exploring innovative approaches. Influential management concepts like Lean, Agile, and Corporate Social Responsibility (CSR) have gained considerable attention in the past two decades and have had profound effects on our work environments. Previous research has highlighted the significance of intermediary actors who play a crucial role in driving organizational change and acting as translators. However, existing studies have offered limited insights into the diverse roles of translators and the strategies they employ to adapt concepts within organizations. Our research, published in the Scandinavian Journal of Management, takes a fresh perspective by adopting a brokerage work approach and develops a more comprehensive understanding of how intermediary actors shape the translation processes.

Unveiling the Role of Intermediary Actors

Traditionally, the role of intermediary actors in translating management concepts has been viewed as a linear process, with concepts flowing down from top-level managers to lower-level employees. In the traditional linear understanding of translation, the concept would be refined and modified by top-level managers before being communicated down the hierarchy to lower-level employees. However, our research reveals a more complex picture. We find that key intermediary actors, such as middle managers, play a crucial role in shaping the translation process. These middle managers, positioned between top-level management and front-line employees, have the unique opportunity to interact with and influence both parties. Instead of simply relaying information downward they affect the interaction between the organizational levels by which and the interpretative abstraction at which translation activities are performed, purposely drawing on each of those two to affect the other. Or in other words: intermediary actors actively use their position to affect both the way people interact within the organization and how they understand and interpret information.

Unraveling Modes of Translation

Through in-depth interviews with intermediary actors responsible for Lean implementation in a hospital setting, our research uncovers three distinct modes of translation: stretching, shielding, and synthesizing. These modes demonstrate how managers strategically position themselves as carriers of ideas and employ specific tactics to navigate the translation process:

1. In the stretching mode, translation tactics focus on promoting interaction between different organizational levels, but they primarily revolve around abstract conceptualizations of the idea.
2. In the shielding mode, translation tactics are aimed at creating a disconnect in the interaction across hierarchical boundaries. This allows for diverse interpretations of how the concept is translated into specific local practices within the organization.
3. In the synthesizing mode, translation tactics are geared towards enhancing interaction across hierarchical boundaries by integrating the interpretations of different parties involved. This mode seeks to find a common ground and understanding among the various perspectives on the concept.

We delve into the conditions under which each mode is enacted and identify the translation tactics utilized within them, such as positioning, labeling, and channeling. Our findings reveal that these tactics are closely intertwined with the social positions of intermediary actors and significantly shape the translation of management concepts within organizations. Contrary to the conventional belief that alignment is the primary goal of translation, our study highlights the importance of purposeful misalignment through “shielding” between high-level management and front-line professionals.

ctices.

Conclusion: Driving Organizational Change through Effective Translation

Our research sheds light on how implementation managers, acting as intermediary actors, play a crucial role in intra-organizational translation. We present a conceptual model of brokerage work that provides insights into the three modes of translation and their associated tactics. In practical terms, our research offers valuable recommendations for individuals in change intermediary roles. By embracing the translation tactics identified in our model, middle managers can enhance their work during organizational change. One valuable recommendation is to consider using ‘shielding’, even if it goes against established norms. Shielding allows managers to intentionally create a disconnect between high-level management and front-line professionals, creating room for different interpretations and adapting concepts to local practices.

A new approach towards teaching business ethics

In the past decades, ethical scandals and widespread critique on shareholder based capitalism have drawn more attention to business ethics education. In the business ethics classroom, students have the opportunity to become critical moral agents. However, classical approaches to teaching business ethics – often relying on teaching abstract moral philosophy – have been criticized for not involving students on a personal level. This stimulated the development of new pedagogical approaches towards business ethics. We studied such a new pedagogical approach. In our inductive case study, published in Academy of Management Learning & Education, we explored how students experienced a course where world literature was the main source of study material. Every week students read and discussed a piece of world literature taking place in different times and cultural contexts – from ancient Greece to modern America, from colonial times in Africa to the aftermath of WWII. They analyzed the texts, applied moral theory on the different narratives, and made links to moral challenges in modern day business. For more information about this pedagogical approach see Sucher (2007).

The benefits of a narrative approach

Students reported a deeper way of learning compared to regular business ethics courses, even case studies. They felt absorbed in the narratives and were emotionally involved with the protagonists and their moral predicaments. In the class room there was laughter, but also crying. Narratives also offered a safe arena in which students could explore different moral concepts and practice their moral imagination. Not only reading the narratives was beneficial for the learning experience for students – discussing the stories in a group setting illustrated how people can interpret the same moral challenge in a different way. This was often eye opening for students.

Developing ‘moral muscle’

When we asked students how they experienced the course, they indicated they had developed ‘moral muscle’ – a dynamic moral capability that needs to be developed through regular reflection and practice. Moral muscle consists of a gradual increase of moral awareness, the motivation to practice moral decision-making on a day-to-day basis, and the desire to build moral character. Having a strong moral muscle means being at ease in taking a moral stance and feeling equipped to make moral decisions. Similar to regular muscle, moral muscle needs regular attention and practice to grow stronger. People showed different starting points and learning routes of moral development. Some students started the course with a rather rigid conception of ‘right versus wrong’. After the course, this group showed a stronger appreciation for the complexity of moral decision-making and the value of other moral perspectives than their own. Another group started the course from moral relativism (there is no right or wrong) and during the course this group started to realize that developing their own moral code was important in order to make moral decisions. In the context of moral development, these different learning paths illustrate that people in the same course can learn different – at times opposite – moral capabilities. This is in contrast with existing theory that assumes that all people go through similar developmental steps of moral development.

Practice moral muscle

The gradual development of moral muscle and its similarity to regular muscle also suggests that without moral awareness and regular practice, moral muscle will likely decline. Students thus realized that in order to be effective moral leaders later in their future career, they would have to start now with practicing their moral decision-making. And they would have to keep paying attention to the moral complexities of organizational life. Our study suggests that exposing yourself to a variety of moral challenges via world literature – and ideally discussing this literature with other people – could be a valuable way to practice or your moral muscle and broaden your moral horizon.

More information

• Here you can find our research study, published in Academy of Management Learning and Education. (Link: https://doi.org/10.5465/amle.2020.0072)
• For more pedagogical information on how to use world literature in the business ethics classroom, see the book of Sandra Sucher (Harvard Business School): Sucher, S. J. (2007). The moral leader: Challenges, tools and insights. Routledge.

Why are emotions important during M&As?

Emotions are transient feelings everyone experiences, with an identified trigger or target shaped by sensemaking practices, resulting in emotional experiences and responses. During a sensemaking process, an individual cognitively appraises emotional triggers based on positive or negative effects on their well-being. This emotional process is especially triggered by disrupting events. Therefore, particularly relevant in times of change, such as M&As.   

Emotional experiences can be broadly categorized into two groups, negative emotions and positive emotions. Research shows that negative emotional experiences are associated with negative attitudes and behaviors, such as indifference and sabotage. In contrast, positive emotions are associated with positive attitudes and behaviors, such as openness and cooperation. Thus, making emotional dynamics during M&As important factors concerning alignment or resistance towards organizational set M&A goals and initiatives, thereby impacting M&A success or failure.

Different kinds of emotions during M&As

Not much is known concerning emotional dynamics during M&A times and their effects, and what is known is mostly fragmented and incohesive. To resolve this problem, we made a review of the existing literature. First, we divided the M&A process into three phases, the pre-M&A, during-M&A and post-M&A. Secondly, we examined per phase what emotional triggers were salient, which emotions were experienced, what the emotional outcomes and attitudes were, and how these emotional dynamics were managed. Finally, we summarized the literature in a process framework.

What came to light after the review was that emotional experiences are extremely diverse and range from positive to negative and everything in between. Employees can also experience multiple (conflicting) emotions at the same time. Examples of observed emotions are happiness, excitement, frustration, indifference, anger, hostility, jealousy, fear, anxiety, stress and many more.

Interestingly, employees do not respond to emotional triggers in the same way. What is good for one might be bad for someone else. This is due to individual differences concerning emotional sensemaking. Moreover, we observed that negative and positive emotional experiences do not always have similar outcomes. For example, negative emotions are sometimes used as correcting mechanisms, whereas positive emotions sometimes result in overconfident- self-serving behaviors. Employees further exhibit huge differences in emotional resilience, coping, intelligence, labour and psychological capital, making emotions and outcomes challenging to manage and predict.

Finally, we observed that during the pre-M&A and during-M&A phases, emotions are contained within the upper echelons of an organization and are mostly positive. However, as soon as the rumour mill starts running and the M&A is announced in the post-M&A integration phase, emotions spread rapidly throughout the organization and shift from positive to negative.

A bright M&A future might lie around the corner

With our article, we offer valuable insights for managers and other practitioners. Firstly, by championing the importance of emotional dynamics within an organization and the trajectory of an emotional trigger, registration, experience and response. Understanding these mechanisms makes adjusting corporate strategy towards emotional value creation easier. Focusing on the organization’s human capital reduces stress and anxiety and, ultimately, the high (human) costs associated with turnover and burnout.

Secondly, there are huge opportunities to prevent negative emotions by correctly managing emotions during the post-M&A integration phase, as emotions become endemic. Negative emotions need to be felt, heard and acknowledged. Moreover, negative emotions can act as correction mechanisms for faulty strategies. It is vital for employees to feel responsible, fairly treated, certain and in control. These states can be achieved if managers offer their employees respect, motivation, inspiration, empowerment, communication, reward, recognition, and accountability. During M&A times, it is vital to offer a clear plan in which these dimensions are touched upon, combined with describing what will happen for the foreseeable future, e.g., three years. In doing so, one of the most harmful emotions, uncertainty, will be mitigated. A valuable lesson is that negative emotions must be felt and closed off instead of lingering like the sword of Damocles.

Finally, there is much-untapped potential concerning positive emotions. The main focus of organizations and societies is oriented towards negative emotions. Our article shows positive emotions’ positive effects on M&As and employees. Positive emotions prevent and can counter negative emotions; positive emotions broaden the mind making employees open to change, and positive emotions, such as enthusiasm, make employees actively cooperate with M&A initiatives. Leaders should therefore focus on preventing negative emotions by actively fostering and cultivating positive ones. This can be done by creating a safe environment in which dialogues between employees and management result in a continuous feedback loop. Why cure a sick patient if the patient does not need to be sick in the first place?

The research was conducted by Onno Bouwmeester, Professor of Consulting and Business Ethics at Durham University Business School, and Director of VU Knowledge Hub for Consulting and Professional Service Firms at Vrije Universiteit Amsterdam. His study finds that, whilst clients are typically portrayed within industry guidance as the biggest victims of ethical failures by consultants, media reporting, accepted industry attitudes and conversations with consulting staff reveal a very different reality.

Professor Bouwmeester says,

“The media typically positions both consultants and clients as partners in crime in various ethical scandals reported by journalists; from helping their clients to find loopholes in the law or facilitating tax avoidance practices, to links to corrupt officials. Clients are not the only, and certainly not the most vulnerable stakeholder in situations where ethical transgressions occur.”

Current consulting guidance and literature, he states, pays little attention to this, focusing instead on how to deliver a service that is up to agreed professional standards to protect clients. However, there currently is little guidance or protection in place that considers other, more vulnerable stakeholders impacted in instances when ethical behaviour falls short.

Professor Bouwmeester continues,

“In reality, client staff and junior consultants can often be the ones most impacted by such ethical dilemmas. In addition, these realities have become the theme of popular jokes within the consulting community, seemingly with little action taken on addressing these shortcomings.”

His study contributes to the business ethics debate by widening the discussion. By reviewing interviews given by more than 100 Dutch consultants, the study identifies the top five ethical transgressions commonly made in consulting. Then, by analysing a sample of almost 100 popular critical consultant jokes found on the internet, Bouwmeester illustrates each issue to provide perspective on the problematic wider attitudes.

The Top Five Ethical Transgressions are;

1. Being Detrimental to Client Staff: Described as situations whereclients ask consultants for an opinion on individual employees. Consultants, in attempting to avoid assessing employees behind their backs may give enough vague indicators to where they think problems within a department or team can originate, so that clients draw their own conclusions.

• Jeopardising Professional Independence: Defined as instances of consultants being manipulated when preparing their assignment conclusions, either because the client may want to hear a certain outcome for which the grounds are insufficient, or when a consultant does not agree professionally with the client’s preferred approach, but overlooks this to keep the peace.

• Overbilling and Selling Juniors as Seniors: Exemplified by instances where consultants overpromise in client proposals by offering more hours or delivery than they actually plan to provide, or enhancing junior staff CVs in order to secure a higher fee.

• Fake it ’til You Make it: Described as consultants suggesting they have more experience, expertise, and capacity then they really have. Or taking on more work than capacity allows for, bluffing to clients and trying to catch up during the assignment. One key consequence of this is junior consultants struggling to cope with the pressure of keeping up pretences and feeling insecure with the expectations placed upon them.

• Being Engaged in Unnecessary Work: For example, instances where consultants take on assignments specified as vital by clients, despite feeling such projects will lead nowhere or have minimal impact. Instead of voicing such concerns or stepping back, consultants go through the motions, agreeing with the client to secure the fee and keep the peace, but ultimately offer very little value.

Professor Bouwmeester says,

“While codes of conduct focus on the consultant-client relationship, and in particular on the primary client who pays, who owns the problem and who is mentioned in the contract between consultant and client, consultant ethics should include more stakeholders. The jokes and interviews reviewed in this study provide much evidence for this call, just like investigative journalists.”

The full study “What Jokes Can Tell: A Top 5 of Ethical Transgressions in Consulting” is available to read in the Management Consulting Journal.