If we assess McKinsey & Company’s mission through a modern lens, it becomes clear that to help business leaders achieve sustainable competitive advantage, data and analytics must drive advisory. The influx of data-driven needs across industries (Figure 1) comes with tremendous implications to the traditional consulting model:
- Rapid feedback cycles – consistent engagement with clients
- Modularized products and services – a greater need for specialization
- Enter the CTO/CDO/CMO – conversations with a wider client base
- An implementation orientation – recommendations alone become insufficient value drivers
- Bespoke solutions with a focus on individual consumers
- Data structure and analytics platforms as key competitive levers
The longstanding clients of McKinsey – Fortune 500 C-Suites – are feeling the pressure. 71% call themselves “tech companies”. Within technology, they are most interested in mobile computing, cloud computing, and AI/machine learning, all of which require advanced data analytics capabilities. 73% cite the rapid pace of technological change as their “greatest fear”. Figure 2 underscores this trend, illustrating global digital consulting spend of $5B in 2016.
A Traditional Supply Chain
The consulting supply chain (Figure 3) is like many others: materials (talent) are sourced from suppliers (leading universities, prestigious firms), a product is developed (bright, resourceful problem-solvers) and delivered to the customer (strategic solutions). In this context, several areas of McKinsey’s supply chain are vulnerable to digital disruption:
- Raw Materials – do traditional sources of talent satisfy needs of an increasingly technical, specialized world?
- Preparation – do existing training methods and frameworks prepare “inventory” (consultants) for the digital world?
- Orders / Distribution – will customers associate McKinsey with complex data-oriented solutions?
- Product Delivery – Can McKinsey own best-in-class talent to justify price? Will standalone strategic recommendations constitute sufficient deliverables?
- Delivery Reception – is the existing “descend and depart” model sufficient in the future?
“The Firm” Responds…
McKinsey has made several splashy moves in preparation for the digital wave. These efforts fall broadly into two camps: (1) short term, awareness generation and (2) long term, proof-of-competency.
McKinsey has produced hundreds of articles, research papers, and case studies communicating their unique point-of-view and capabilities in the digital arena. High visibility projects also serve to drive awareness (e.g. in November 2017, McKinsey Digital was selected to advise Sri Lankan on building countrywide digital infrastructure). While these efforts begin to address the credibility gap and increase client awareness, publications and headlines alone fall short in proving competency.
Long-term plans center around making numerous small bets for more opportunities to observe, learn, and iterate. McKinsey New Ventures houses these efforts, with a focus on incubating and commercializing packaged digital solutions for clients. Currently, there are over 800 data scientist and analysts under the New Ventures umbrella.
Further, since 2013, McKinsey has acquired over a ten data/analytics firms, with the hopes that new capabilities can be tested with clients as digital needs continue to rise. These include: Pricemetrix, a wealth management analytics solution, 4tree, a big data analytics firm for retail, and QuantumBlack, a data analytics and visualization firm.
The Future Ahead
If we return our eyes to Figure 3, of critical importance is “raw material sourcing”, or access to talent (as a predeterminant of product quality). The traditional talent pools are likely underpreparing students for the next 30 years, where a lack of data and analytics familiarity will spell failure. Look, for example, to top-tier MBA programs, a key supplier to McKinsey, with hundreds of new hires each year. None of them have incorporated basic data and analytics education into their core curriculum. McKinsey (and other consultancies) wield tremendous lobbying power over the universities which they frequent come hiring season – it’s incumbent upon the “purchaser” to demand that their materials are up to specifications.
Beyond structured recruiting, McKinsey must explore more flexible talent acquisition to broaden access beyond their traditional field of influence. Rethinking the talent pool with the gig economy in mind and exploring JVs with industry partners, large and small, may become necessary (e.g. PWC Talent Exchange, a platform for independent consultants).
Lastly, we must consider the implication of faster feedback loops on product delivery. Current engagement models are lumpy, with fixed contracts over short periods of time. In a world where customer needs and millennial attention spans are equally fleeting, should clients put up with fixed-term, fixed-fee, fixed-time advisors?
- Is McKinsey the best owner of complex, data-driven solutions? Does the risk of moving into a foreign, highly-technical space jeopardize their core, market-leading position?
- In a world of startups and tech giants, how can McKinsey attract the best in class digital/analytics talent? What are the implications if they can’t?
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