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Why Consulting Firms need Data Scientists

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AnonymousBy Yogita Malik Arora 3 years ago
Home  /  Consulting  /  Why Consulting Firms need Data Scientists
Data-Scientist–Consulting-Firms

In 2012, the Harvard Business Review labeled the Data Scientist as “The Sexiest Job of the 21st Century.” It is not the job title, however, but what exactly a data scientist can achieve that makes the difference. With the right tools, data scientists can combine machine data and people data to expertly guide businesses and consultants towards profitability.

In essence, the job of a data scientist is to extract knowledge, and more specifically actionable knowledge, from large volumes of data drawn from various sources and in various forms. Navigating unknown fields and drawing connections between them, data scientists can discover potential opportunities businesses could be missing, both externally and internally.

Account renewals and expansion

While securing new clients is important, creating lasting relationships with existing clients that result in account renewals and expansion are crucial for a consulting firm’s growth. Data scientists can use people data that is collected and processed through software to determine where there is scope for improvement within a current project. People data can also point to how vested a consultant is in a project.

For instance, data scientists can pull together datasets and information from social interactions and score the health of the relationship between consultants and their clients. They can predict the probability of an account renewal and also scope out opportunities for account expansion.  Most importantly, data scientists can use data to point out what was done right and what went wrong within a certain account.

More opportunities in the industry

Similarly, data scientists can navigate bigger datasets and analyze a firm’s position in the industry. When surveying the industry, many might ask:Are we doing the same thing that another firm is doing? How well are we differentiated from our competitors? What are some of the opportunities within our industry we can go after?

In many cases, when a data scientist mines insights that are gained by asking the relevant stakeholders and employees of a consulting firm, he or she can point to potential opportunities that may have otherwise been missed. What’s more, data scientists can combine both machine data and people data to predict outcomes more accurately.

Data scientists and the systems they build can also be apparatuses to expand business pipelines. Lots of companies employ business development executives to generate leads, but the job can be supported by data scientists. Using a pool of successful leads as a model, data scientists can match different characteristics, such as finance, customer-base, and product function to filter out unlikely leads from a vast potential client base. People data can further refine this process by adding information about alignment of a potential opportunity with factors such as goals, missions, and culture. When this process is automated, it can allow business development executives more time to actually connect with their existing or potential clients.

Going beyond an industry

The beauty of data lies in the capacity of comparison and the potential to spot patterns. The same set of data can be compared to thousands of different ones; the infinite combinations subsequently provide a wide variety of insights. For instance, one pattern in a data set might show an increase in tourists in one place, while another might explain that a reputed hospital has recently expanded its campus in the area. A data scientist’s expertise comes into play here, where he or she could identify an unlikely relationship between the two and spot an opportunity for growth. A data scientist could find that medical tourism is flourishing in the area and a consulting firm is well-poised to enter this new industry. Further, the data scientist can evaluate the resources, talent, and time you need to foray into a new industry.

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  Consulting
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