Data Scientists v/s Management Consultants - AI is changing the consulting practices (Part 1)

Over the past couple of months as I transition out of my current startup – I have been consulted for various projects on AI, NLP, ML – the cyclical elements of ‘Chatbots or Conversational AI space'. After having worked for a leading consulting firm and a Conversational AI company in the past, I realized that most companies are now coming up with inclusion of AI in their schema to have a perennial effect as per what they foresee the future. 3 years ago I collated information and wrote my opinion on ‘Future of Consulting in 2 parts’. 2 years ago, as an assignment on ‘AI’ – I wrote about how ‘Chatbots can be the future of Technology’. After closely working in both the industries & having seen the wave of technologies battling at all fronts I now believe there are a lot of similarities between the tomorrow’s Consultants and the today’s Data Scientists (at Tech firms)

In this article, I intend to take you through my experience in building internal AI skills, the changing landscape for consulting firms in terms of AI adoption. Also the major questions – can the tech firms turn themselves to become the next giants in the consulting world? With enough data on hand & with excellent tech models, will tech be the next advisory firms for companies to scale up?

Can Amazon, Google and Microsoft take over from McKinsey, BCG and Bain?

Tech companies have Access to information & Better data analysis

Consultants provide expensive insightful advice and guidance based on research. However, a significant part of what is paid for with consulting services is data analysis and presentation. Consultants gather, clean, process, and interpret data from disparate parts of organizations depending on the mission.

Indeed, data challenges have ensured the necessity of a human interface to the data. However, key data is often missing or hard to access. These problems created a situation where companies seeking data-driven answers to key strategic questions required experts (consultants) to create, combine, clean, analyze, and interpret data.

In a growing number of projects, we tend to require more data scientists and fewer consultants.

This particular aspect of the consultant job can be automated to some extent by Machine Learning (ML) algorithms. An ML model can make sense of the complex situations by detecting patterns and inferring rules from data — a process that is very difficult for even the largest and smartest consulting teams.

Prediction:

Decision-makers could leverage smart devices (Alexa…) and ask things like, “Who is the biggest risk to me in our key market?”, “How should we allocate our capital to compete with Amazon?” or “How should I restructure my board?”

Answers are cheap in the age of the internet and AI can reduce the margins of the complete consulting value chain.

Conversational AI uses information discovery, NLP, and other technologies to communicate with human beings, helping them execute tasks, answer questions, and find information more quickly and effectively. Traditionally, NLP has used ontologies and taxonomies with a lot of human linguistic assistance to process dialog and unstructured text properly. However, with the advent of deep learning algorithms and models such as BERT, there is a resurgence of statistical-based NLP that can handle very specific domains

We could argue that management consultants in the age of AI are not surfacing information or running analytics. Rather, they are making sense of the information and analytics that most companies already have access to. Consultants are, often, connecting disparate pieces of information to form a cohesive narrative or guide.

Furthermore, the growing access to information is changing the situation. Today, the kind of information that once existed as closely guarded have become virtually commodified by the internet. Today, the real added-value is about creating new competitive advantages through the data already at your disposal.

Beyond the already existing automation of initial analytic activities, algorithms could also gain access to sections of higher added value — i.e. insight integration and strategy formulation.

With the democratization of AI-based solutions, the risk for consulting firms is to see their clients’ willingness to pay for them — diminish significantly. One could argue that the real value comes from data scientists rather than pure consultants incapable of identifying hidden patterns in data.

Image courtesy: Kore.ai conversational platform.

A business model at risk…

For the below-mentioned elements, AI could really threaten the business model of most consulting firms:

Today’s situation

Based on my experience (depending on the industry and business issue), most consulting missions are related to business issues that can be fixed thanks to clustering, ranking, and classification/prediction algorithms.

For instance, churn prediction is very common and regression models have proven to be quite efficient. Moreover, collaborative filtering or ranking problems are very common. If the business issue is clear, the data available and relevant and the expectations realistic, data scientists can already, through Machine Learning algorithms, bring a solution to many business issues.

AI providers vs Management consultancies

With the growing democratization of AI (no-code/low-code AI solutions, startups, etc.), management consulting firms will face an increasing number of competitors.

Competition from large tech firms

It starts with all three major tech firms that offer pre-trained models that corporate clients can use to build AI-enabled systems.

Indeed, a broad range of tools is available to help mainstream companies build anything from recommendation engines to speech-recognition and translation systems, customer-service bots and more. In these cases, a team of internal consultants and data scientists would be better suited.

For several reasons, large tech firms are better placed to serve mainstream companies in need of help with AI. Some of you might be thinking that such services still require a lot of customization and technical work to make them useful…

In reality, tech firms are already trying to fill the gap by offering consulting services. Google has opened an “Advanced Solutions Lab” that is part consulting service, part tech boot camp. Whole teams from client companies can come to acquire machine-learning skills and build customized systems alongside Google engineers. Tech firms are evolving by becoming less only focused on technical infrastructure but also strategy and people.

Tech firms will increasingly compete with management consulting firms, which charge fat fees for helping clients navigate technological disruption.

In reality, the generalists know they are vulnerable. Depending on the use case, many clients seek advice from tech firms, which are themselves pioneering users of AI. If consulting firms do not react efficiently, more specialized providers are likely to move up the value chain to not only be a data/analysis provider, but also provide the recommendations for overall business strategy.

..... Continued in Part 2 - Emergence of AI driven Startups as an alternative to Management consultants.

Note: The views reflected in this article are the views of the author(s) and do not necessarily reflect the views of any company or organization

#innovation #technology #design #machinelearning #digitaltransformation #analytics #automation #artificialintelligence #datascience #futureofwork #robot  #ai #roboticprocessautomation #chatbot #consultants #managementconsulting

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Thank you

Phani Marupaka