When Clayton Christensen (ironically, a BCG alumna) introduced the definition of Disruptive Innovation, he predicted that management consulting disruption is still “early in the story”. However, one can see the waves have changed.
Management consulting is a prestigious industry. The whole industry is valued nearly $250B in 2018, with incumbents, like BCG, Bain or McKinsey, delivering their solutions to almost every other existing industry.
Fancy as it sounds, one may forget that management consulting is extremely human-centric, a fact that has not changed much ever since James O. McKinsey founded the firm back in 1926. Company assets are valued by the skillful, knowledgeable workforce, clients are billed by consulting hours, and human consultants are involved in the whole project. The empire of a man-run industry now faces the real challenge: will their existence be washed out by technologies, as many other industries were?
The Status Quo
In a report published by CB Insights, the traditional consulting business model revolves around four pillars Information, Expertise, Insight, and Execution. While some of these pillars are disrupted by other business models and/or shift in customer references, one outstanding trend present: Machine Learning tools and data automation systems will eventually dominate, if not wash out, the need for consulting firms in the Information and Expertise pillars.
This emerging trend is slowly invading the industry. Recently, clients of the Swiss bank UBS can now consult Alexa on their wealth-management tactics, according to an article by Harvard Business Review. In 2017, Harley-Davidson adopted Albert, an AI-driven marketing bot, to analyze and execute online marketing campaigns. Not only Amazon but other AI solution providers, such as Microsoft, Apple or AI start-ups, are ramping up to compete and challenge traditional consulting incumbents.
When one objectively judges the situation, the answer is pretty clear: AI can (potentially) perform expertise consulting better than human beings. AI tools can work relentlessly, while even the toughest, will-of-steel consultants would wear down after long work hours. AI can automatically gather and reach out to the essential data, a task which takes traditional consultant hours, or days, to finalize. Most important of all, AI tools are less likely to be biased. In fact, they are just as biased as their data input.
The future of management consulting
After all, does that mean that MBB firms are dying, and that we as BIM students should not apply for these firms? The answer is unlikely. Just as how consulting firms help change the operations of various businesses, its own business model is likely to undergo structural changes. A report by LexisNexis showed that management consulting firms are responding to the market by more automation in their solutions. The landscape of human resources demand is also changing, as management consulting firms are hunting for data-driven and IT gurus that can adapt and thrive with the new systems.
In conclusion, management consulting will remain powerful and impactful, just not in the exact same ways as it is now.
References
CB Insights Research. (2018). Killing Strategy: The Disruption Of Management Consulting. [online] Available at: https://www.cbinsights.com/research/disrupting-management-consulting/?utm_source=CB+Insights+Newsletter&utm_campaign=3ef8d25153-ThursNL_09_27_2018&utm_medium=email&utm_term=0_9dc0513989-3ef8d25153-90345441 [Accessed 6 Oct. 2018].
Libert, B. and Beck, M. (2017). AI May Soon Replace Even the Most Elite Consultants. [online] Harvard Business Review. Available at: https://hbr.org/2017/07/ai-may-soon-replace-even-the-most-elite-consultants [Accessed 6 Oct. 2018].
Power, B. (2017). How Harley-Davidson Used Artificial Intelligence to Increase New York Sales Leads by 2,930%. [online] Harvard Business Review. Available at: https://hbr.org/2017/05/how-harley-davidson-used-predictive-analytics-to-increase-new-york-sales-leads-by-2930?utm_campaign=hbr&utm_source=facebook&utm_medium=social [Accessed 6 Oct. 2018].
