Empowered Consulting: The Future of Decision-Making with Data Analytics and AI

Suppose you are the CEO of a consulting firm: the fabric of your work is a result of interwoven insights, and the value of your work comes from your ability to deliver expertly crafted outcomes. Like all highly value and sought-after pieces of clothing are made from uniquely treated wool or cotton or silk, decision-making in the corporate world can be reduced to the quality and accuracy of the data used to inform them. The past decade of cultivating cutting-edge technologies and systems has changed today’s business environment because clients expect more from consulting firms than ever; companies want to identify trends, forecast outcomes, and optimize operations with sharp precision and narrow margins of error. Leading consulting firms understand that leveraging data and AI analytics is the decision they must make to enhance efficiency and experiences for their clients.  

Traditional market research involves number-crunching and analysis of financial statements, market research reports, industry data; surveys; interviews; and questionnaires. Firms rely heavily on framework-based problem solving like SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis, or McKinsey 7S Framework, BCG Growth-Share Matrix, and the list goes on. These overwhelmingly manual forms of deriving insight place too heavy a burden on the experience and judgment of certain professionals. Not to mention, these deliberation-focused methods require time and an extensive input of resources, especially human capital.  

If you, as CEO, noticed various limitations to the status quo in consulting––despite the practices in use being tried and true––odds are you would like to find a notably streamlined and scalable alternative. This is exactly why consulting firms are championing machine learning. The evidence-based pivot the industry is making is partly due to businesses demanding data-backed recommendations, but it is difficult to deny that data analytics is primarily being adopted on its own merits. Consultants are now enabled to uncover deeper insights, make reliable predictions, and offer personalized solutions tailored to clients' specific needs.  

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At Xpo, we view data and AI analytics tools as assistants and informers, not as autonomous virtual consultants.  AI can process large datasets with speed while uncovering opportunities and risks that might be missed due to human error. Natural Language Processing (NLP) gives AI the capability to interpret text-based data from reports, social media, customer reviews, and even internal communications, sparing consultants the pain of making sense of unstructured data.  

Continuing with our opening simile: a clothing retailer desires a brand refresh and hires a consulting firm to define their new marketing strategy. The old approach would prescribe a qualitative analysis rooted in an appraisal of historic case studies. Regardless of the intellectual capacities of the personnel involved, without concrete facts to illuminate their findings, this approach can––at best––give you a very educated gamble. The new approach allows consultants to tether their recommendations to real-time data, and analytical tools reveal patterns, trends, and correlations in the transaction data to identify patterns in customer behavior, seasonality effects, and sales drivers. At the same time, an NLP model trained in sentiment analysis scans social media posts, news articles, and customer feedback, identifying positive or negative trends and suggesting actions to improve brand perception. McKinsey Global Institute approximates that 45% of activities performed by consultants could be automated using existing technology. The sheer quantity and quality of the insights gleaned using data and AI is unmatched.  

It would be erroneous to discount the expertise of consultants––and of qualitative analysis in general––because their human touch is consequential. With these tools, consultants can hone their skills and remain unbothered by repetitive and time-consuming tasks, boosting efficiency company-wide and the value of individual consultants’ time. AI and data are not ends but means. From optimizing research to helping generate insights, we utilize an approach that balances leveraging leading technologies while ensuring responsible management of client data and sensitive information. 

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Big consulting firms have been aware of analytical tools, invested in R&D themselves, and pioneered their use cases. Indeed, over 50% of large enterprises are already using AI consulting services. They now look to the future with GenAI, the next industry disrupter. McKinsey describes four archetypes of use cases: code generation, content generation, human engagement, and the virtual knowledge worker. While most companies are only experimenting with bots and synthetic data creation, in our rapidly developing environment, it seems only a matter of time before ‘the new approach’ is the only viable one that can drive competitive advantage in an increasingly digital economy. Before considering GenAI, however, consulting firms must highlight and prioritize their data infrastructure and products.  We believe in pushing the boundaries as to how AI and GenAI are utilized to help drive value for our clients. If you, as CEO of the consulting firm in question, embrace data and AI analytical tools now, you not only unlock future possibilities but gain confidence that every decision you make is the most informed one you can make––because the better the data, the better the decisions.