THE END OF MANAGEMENT CONSULTING AS WE KNOW IT?

ABSTRACT - Journal of Management Consulting

The management consulting business model requires new changes in this new era of disruptions. The typical management consulting business mode is based on consultants either training and developing or engaging in actual management consulting. Today, this has been combined due to operational risk management. The reason is that identifying problems and providing solutions to senior managers is not enough today - consultants need to also be able to offer and execute solutions. Artificial Intelligence (AI) has placed consultants in what is known as a dual role. In this article, we examine the challenges of the management consulting business model and provide an alternative way for large consulting companies and those medium to small organizations to re-emerge with sustenance. These challenges were found in our interviews with 81 senior management consultants at McKinsey & Company and Boston Consulting Group, Inc. in the United States, Australia, Hong Kong, and the United Arab Emirates.

INTRODUCTION

Unfortunately, the current management consulting business model has been immune to change for years (Nissen, 2019; Nissen, & Dittler, 2019; Oesterle, Buchwald & Urbach, 2019; Shaw, 2020). The inertia that management consultants have been trying to debunk has hit home (Deelmann, 2019; Deelmann & Nissen, 2019; Nissen & Müllerleile, 2019). This business model, which relies on sending consultants to organizations, finding problems, and providing solutions, has worked in the same way for more than a century (Curuksu, 2018a; Marsh, 2009a; Marsh, 2009b; Weiss, 2019). But now, with the onslaught of disruptions and AI, the tried-andtrue business model has seriously endangered the survival and continuity of management consulting organizations (Curuksu, 2018b; Curuksu, 2018c; Marsh, 2009c; Marsh, 2009d). Our conversations with 81 senior management consultants at McKinsey & Company and Boston Consulting Group, Inc. in the United States, Australia, Hong Kong, and the United Arab Emirates revealed that many senior management consultants still believe in the outdated business model and underestimate the disruption in the management consulting industry. Perhaps the survival and continuity of both large and small companies will be to engage in more agile and adaptable models that offer a full suite of services from human resource management to strategic management consulting.

THE INCREASING RISE OF ARTIFICIAL INTELLIGENCE FOR BUSINESS

By leveraging AI, businesses are able to make real-time decisions, streamline processes, reduce costs, and increase efficiency (Demir, 2022; Enholm, et al., 2022; Davenport, et al., 2020). With a more distributed decision-making process, organizations can empower people to make decisions faster and more accurately utilizing the data available (De Mauro, Sestino & Bacconi, 2022; Sarker, 2022; Sousa, de Barros & Tavares, 2022). Businesses around the world are automating their processes to improve customer relationships, allowing them to respond faster and more efficiently, increasing customer satisfaction, and creating a competitive edge (Choudhary & Karmel, 2022; Itagi, et al., 2022; Sharma & Kumar, 2022). There is a minimal rate of error in Google's algorithms, which is why Google is regarded as the apex of high-tech artificial intelligence. With AI technology, organizations can move beyond existing limitations and gain access to innovative business models and by utilizing AI and continuous learning, organizations can reach a high level of excellence. Alibaba's success serves as an inspiration to other businesses looking to leverage the power of AI for their own success. Algorithms, by introducing consistency and accuracy, allow businesses to reduce mistakes, optimize processes, and ultimately reach the ambitious goals of Six Sigma: having few errors. AI programs are not considered in most corporate strategies by top executives. A company without an AI strategy, while its competitors are quickly advancing in the market, is like a Formula One (F1) race where all the competitors are driving high-tech F1 cars, but one team is driving a fast but regular streetcar. Just as the streetcar cannot compete with the advanced technology of the F1 cars, the company without an AI strategy will fall behind its competitors who are leveraging AI (Barriga, Rutle & Heldal, 2022; Belhadi, et al., 2021; Kersting, 2018). Are CEOs at risk to be replaced if they do not consider AIpowered strategy? We don’t have the answer, but what is more than reasonable is realizing that AI is needed to enable businesses to gather and analyze data, to make better and quicker decisions. What are the actions to be undertaken? • Identify dynamic capabilities to support continuous growth through exploiting competitive advantages and being agile, considering limited or not full availability of strategic resources. (Fabrizio, Kaczam, & De Moura, 2021) • Design, develop, and align people and IT / Digital systems through a digital mindset embedded into organisational culture. (Neeley & Leonardi, 2022) • Create a flexible and resilient workforce • Implement an effective knowledge management system to ensure that companies have the experience retained to adapt and perform in a changing environment and use double-loop learning to augment the experience (Gribbin, Aftab, Young, & Park, 2016 ) Ineffective knowledge management leads to the loss of expertise and knowledge, delays, and inefficiencies in communications, which limits innovation and collaboration, resulting in lower productivity and success. RPA, chatbots, and AI will allow the creation of data supported by a data culture that can be coupled and enhanced by AI for strategy development. (Neeley & Leonardi, 2022). Digital core knowledge includes technical and digital literacy skills that are essential to using and interacting with digital tools and technologies effectively and efficiently. This is how digital core knowledge enables data-driven decisions that are more accurate and reliable than ever before. CEOs must consider cost benefits and determine if and what AI-enhancing software is the most effective and efficient solution for their business needs. Otherwise, any further development of AI-powered strategies can be hampered if the software is not efficiently evaluated and implemented. Additionally, in order to streamline and automate many processes, organizations must redesign their current processes. To ensure buy-in and successful implementation, CEOs should emphasize the importance of leveraging AI and other automation tools to augment and enhance human capabilities. This can help to foster a culture of collaboration between human resources and technology, allowing for greater efficiency and innovation.

FROM BIG TEACH TO DISRUPTIVE MANAGEMENT CONSULTING IN THE AI AND AUTOMATION ERA

Issues facing clients of management consulting companies include the exorbitant fees they have to pay for features that don’t add tremendous value for them (Chowdhury, 2019a; Chowdhury, 2019b; Crișan & Stanca, 2021; Czerniawska, 1999a; Czerniawska, 1999b). Successful management consulting companies such as Business Talent Group (BTG), which rely on providing special consulting packages for each client, challenge large companies such as McKinsey and Boston Consulting Group (BCG) that provide an integrated business model for alltheir clients. Even the big consultant companies are getting on board with this new model which is more compatible with the emergence of AI in organizations. AI coupled with data analysis and digital core transforms every organization into an identity, in that decisions rely on data analysis instead of relying on intuition (Curuksu, 2018d; Curuksu, 2018e; Muzio, Ackroyd & Chanlat, 2008). The business model used in BTG management consulting company has made management consulting more dependent on data analysis and has increased the possibility of more cooperation with companies and start-ups related to these new technologies. Management consulting firms like KPMG, Deloitte, PwC and BCG, use a variety of automation and AI. The technologies are based on data analytics, intelligent automation, machine learning, natural language processing, computer vision, and chatbots to business process optimisation, trend identification, forecasting and strategies related, enabling micro-decision making (Ross & Taylor, 2018). On a different level than the Big 4, the application of artificial intelligence for management and strategy purposes seems to be nearer than from a conceptual perspective only, e.g. “Robo-advisors” (RAs) (Davenport et al., 2020). In fact, the utilization of RAs is a trend which brings a low level of disruption based on the trust in algorithm as authority aids in legitimating RAs as innovation, thus guaranteeing and protecting the consulting knowledge domain. It is worth bringing two other examples of disruption of the classic management consulting business model supplied by AI services providers for consulting. Praioritize1 can be allocated in a middle level between pure RAs and standardised knowledge. It is a SaaS (Software as a Service), company owned and operated by the Dutch company Transparency Lab, who started with generative A.I. in 2020. They present digital consulting solutions (AI empowered) very close to RAs. Their technical proposal disrupts the classic consultancy business model as AI draws knowledge from a huge database of white papers (11,000) and real case studies (23,000) to solve problems. The first disruption is related to standardized knowledge while AI does assessments and generates proposals utilizing RAs. The second disruption is related to the company’s targets which are both consultants and companies, thus creating a possible way to cut-off consulting starting from their knowledge management for clients (Libert & Beck, 2017) On another side, AI solutions allows for knowledge domain protection and partial utilisations of automation. The disruption is evident when automating certain tasks, such as the consulting lifecycle, while maintaining and improving the engagement based on clientconsultant relationships. Mindset.ai2 uses AI to deliver property knowledge and services such as consulting, change management, and coaching, with a dedicated machine learning repository for each professional, utilizing the AI model ChatGPT 4. Here knowledge is delivered by AI according to customised and tailored services for specific client needs. Recently, ChatGPT has started dominating the scene for multiple businesses. At a lower level, based on the research of O'Mahoney (2023), consulting packages should stand on the assumption that AI ChatGPT should be:

• Used to interrogate clients' documents.

• Connected to the internet and clients' documentation.

• Used to improve clients' marketing operations.

• Used with bots to answer common questions from clients.

• Used to process large amounts of data to recognize patterns and trends; and

• Finally, used to analyse consulting data better and faster.

From these examples a major disruption in the management consulting industry can be predicted with big changes that will impact many aspects of the industry. This disruption will cause the separation of management consulting companies from the integrated model and will result in their using more adaptive management consulting packages for clients. This is "the end of management consulting as we know it" (Garcia, 2021) . The integrated model will invite managers and staff to learn about AI and will highlight the importance of intellectual property and human capital. AI also raises new needs for clients (Bankins & Formosa, 2023). These new needs manifest themselves in using AI to provide more accurate data analysis and make more accurate forecasts for clients (Weber, 2023a; Weber, 2023b). Thus, disruptive management consulting in the AI era needs to offer more adaptive management consulting packages for clients to meet these new needs. Following the predictions of Christensen, Dina, and Derek (2013) the impact of DT on the MC services have received an increased level of analysis (Deelmann ,2019) even if it is not possible to speak yet about maturity models (Crișan & Stanca, 2021). The number of startups will increase as the great resignation persists along with quiet quitting and quiet firing (Bala Subrahmanya, 2022; Cavallo, Ghezzi & Rossi-Lamastra, 2021; Hura, et al., 2022; Savin, Chukavina & Pushkarev, 2022). The dependence on outside consultants will increase and cause management consulting companies to focus on the intersection of knowledge management and innovation. This huge disruption will cause a close relationship between management consulting companies and startups related to artificial intelligence as showed above for Praioritize and Mindset. Thus, management consulting companies will turn to using artificial intelligence to serve clients and advise them more effectively to better understand environmental threats and respond to them better in real-time. Recurring to AI will be a huge pill to swallow for consulting industry (Libert & Beck, 2017) anyway. In addition to this, the increase of automation, both partial or total, will assist the evolution of the trust models and clientconsultants’ relationships, for virtual and digital consultancy along the consultancy life-cycle (Collina, 2021), and the additional trust element for AI and automation adoption for innovative technology (Bedué & Fritzsche, 2022).

CONCLUSION

If you dismissed the possibility of disruption in the management consulting industry, then turn to the corporate life cycle and find your position on that chart and prepare your organisation for a new workplace that is technologically challenged and prone to use AI to do the work. If you keep doing what you always have done, then you will continually get what you always got and if that is not working then inertia has set in. Since management consulting impacts every industry, every business will eventually be realizing some form of disruption.

Do not ignore the beginning signs of this disruption because they are visible to many.

Institute of Consulting

Mostafa Sayyadi, Luca Collina, & Michael J. Provitera