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An Introduction to Data Analytics Consulting

  • Rishab Krishanmurthy
  • Oct 21, 2020
  • Updated on: Feb 11, 2021
An Introduction to Data Analytics Consulting title banner

Business Analytics has unleashed a whole new world to us and raised decision making to radically different strata. Today the informed decision is being made by slicing, dicing, and scrutinizing the data. But will this analysis have any value if we ignore the business aspect of the problem at hand? Not really. 



What is Data Analytics Consulting


A whole new tweak in revolutionizing Business Analytics, Data Analytics Consulting Services adopts a whole collection of methods that streamlines a series of business intelligence tasks by using prevailing data. 


Data Analytics Consulting Services is responsible for balancing business and hardcore analytics with the aim of delivering value-added analytical solutions.


In the present day, most analytics firms cater to clients with data analytics consulting services across varying business domains like Telecom, Financial Services, Retail, Pharmaceuticals, Consumer Goods, etc., enhancing the urgency of properly understanding and addressing business needs. 


Big Data Analytics Consulting


Each time a business faces a complicated challenge involving a large data volume to be analyzed and processed in real time through advanced analytics tools while adopting a fresh structured and unstructured level of data, we would need to employ Big Data Analytics Consulting. 


Big Data Consulting Services facilitate strategic engineering and analytics to aid businesses in enhancing their data insights. The Big Data consulting firm you select will be laying all the data in a roadmap form, to help the user in comprehending their customers as well as the demographics the user is catering to with their specific business.


As a result, the big data consultants are required to formulate strategies and programs for gathering, analyzing, and visualizing data from different sources of particular projects.



Analytics Consultant vs Analytics Practitioner


Data analytics consulting services is a vast field with a hierarchical structure. An Analytics consultant is a level above the Analytics practitioner, who (consultant) aside from having the necessary technical knowledge, needs to possess a high level of consulting skills, which means Problem-solving, Communication, and Presentation. These other soft skills come with experience and practice.


Responsibilities of an Analytics Consultant


  • Understanding the need of the client, developing innovative solutions, orchestrating the entire life cycle of the project, and presenting the solution to the end-user.

  • Tapping the organizations existing knowledge base and capabilities to identify the best solution to the client’s needs according to their timelines, budget, and constraints.

  • Recognizing new business opportunities for the organization to secure new projects from new or existing clients



Skills of a Data Analytics Consultant

The primary skills required by a data analyst consultant generally include knowledge of Data visualization, Microsoft Excel, R programming knowledge and SQL.

Exceptional problem-solving skills are a pre-requisite for Analytics Consulting. So let us see how do analytics consultants approach a problem?


1. Problem framing


Before solving any problem one needs to frame the problem. Framing the problem means answering the question “What is the problem that I am trying to solve here”? 


HP’s Strategic Planning and Modeling team have also explained a three-dimensional approach while solving a problem. Firstly, addressing the higher issues which are the root cause of the problem, addressing the parallel issue, which also needs attention side by side, and lastly addressing the lower issues which could be a deterrent while solving the problem.


To define the problem, it is useful again to use a valuable framework called the SCQA framework. The SCQA Acronym stands for:

  • Situation

  • Complication

  • Question

  • Answer

This picture shows the four steps in the SCQA Process

The SCQA Process Illustrated


The situation and complication are the first steps to assessing a problem and figuring out what is happening and getting the correct framing of the problem. Problem framing is also the part where you want to look beyond symptoms and identify the root cause problem. 


Let’s say you are working for a University that is losing money. You might first define the problem as “The University is Losing Money.” Once you ask a few questions, you might discover this is not an actual problem, but a symptom of a deeper issue.


A good step when you are new to the consulting process is to write out two columns:


  • The situation

  • The complication


In the University case, you find that the reason they are losing money is that the state government has passed a new long-term budget that will keep funding at current levels for the next five years and that given your expected rising costs, the University will either have to figure out how to increase revenue from other sources or cut expenses. The situation and complication could be:


  • Situation: The University has been successful and has a growing student body and a strong reputation nationally for its academic excellence

  • Complication: Despite the success of the University, the state is facing budget challenges and is making cuts across the Board. The University will have to identify a way to close this gap in the next twelve months.


Resulting in a defined problem:


Problem Statement: “While the University has been successful in attracting students and building a national profile, a funding shortfall due to state budgetary reasons means the University has to make decisions to close the budget gap in the next twelve months."


You can also sneak a peek at our blog on Expansionary Fiscal Policy


2. Problem structuring


Each of the business problems that a client faces is complex as well as ambiguous in nature. By taking the problem structuring approach, the consultant breaks down the issue into smaller questions and finds answers by targeting the issue with precision. The model followed by HP’s Strategic Planning and Modeling team involves developing an initial hypothesis of the problem and addressing the sub-issues through data and analysis.


The hypothesis development process gets done by the latter half of the SCQA Framework:


Once you define the problem, the next thing to do is start developing hypotheses. Put more simply, we start asking questions.


Yes, these are the same hypotheses you learned in your fifth-grade science class that are part of what we call the “scientific method.” A hypothesis is something falsifiable, meaning that through research or analysis it can be disproven. A good example of this would be the hypotheses: “all companies are profitable.” As soon as you encountered one company that was not profitable, you know that your hypothesis was wrong.


Within the context of a business problem, you want to pose a question that you can answer through different means.


Let’s pose a question to address the problem we defined earlier:


Question: Can the University cut costs to cover its budget?


This might lead to sub-questions that are even more specific…


  • Sub-Question 1: Can the university raise tuition for students to meet costs?

  • Sub-Question 2: Are there other government funding options available?

  • Sub-Question 3: Can the university appeal to run a deficit in the next year?


During a typical consulting project, this is only the start. You may begin with high-level questions that enable you to do quick research and refocus the project with a better framing (or even in some cases to adjust your problem definition).


As you become more confident that the questions you are asking are the right questions, you would start grouping the questions across MECE themes that might also serve as a good way to divide the work across a team.


For the University team, you might have three separate “workstreams”


  1. Tuition & Revenue

  2. Government & financial

  3. Cost-cutting & restructuring


The next step is to figure out how to communicate the story to your audience.


Recommended blog - People Analytics


3. The Pyramid principle


The default way of using the pyramid principle is to start with the “answer.” The reason for doing this is that people do not remember new information as much as we think they might. We are also at the disadvantage of knowing our material deeply and underestimate how challenging some of the new content might be to someone.


Research has shown that people can only hold four “chunks” of information in their working memory at one time. Thinking back to the pyramid principle, if your audience can remember the main takeaway as well as your three key insights, this is probably the best-case scenario. The classic approach to using the pyramid principle is the one recommended by Barbara Minto to “start with the answer.” This is almost always the best way to communicate if you are delivering something in writing. 


If you read the most compelling persuasive essays, they typically start with a powerful thesis detailing what will be discussed. While this can be most effective for memory and impact, it is not always ideal. Sometimes the audience may not be ready for what you are about to tell them. 


In that case, you can be more indirect.


Here’s how to think about deploying these two types of storytelling:


  1. Direct storytelling where you start with the answer and then follow up with the arguments and supporting evidence is best for:

    1. Friendly client situations where there is a high level of trust

    2. Impatient clients who are saying “just tell me what to do!”

    3. Big picture / strategic discussions where there has been some initial level of “buy-in” around the proposed recommendations 

  2. Indirect Storytelling is subtler and can be used to ease the audience into accepting your final recommendation if you fear there may be some pushback on your proposed solution. This is best used for:

    1. When your recommendation may be controversial

    2. Hostile audiences

    3. Analytical organizations and personalities

    4. Audiences who are fascinated by data & not impatient


Using these methods we can convince people to accept our proposals, the next thing to do is the actual implementation.



4. Project management, facilitation, and collaboration skills


While leading a project, an Analytics consultant needs to be unbiased. He has to allocate tasks in a team according to each analyst’s area of specialization. He needs to communicate the problem in detail to the team members, brainstorm the solutions, motivate and instill a sense of ownership in the team members to perform the tasks. This also calls for good co-ordination skills and multitasking because in large analytics firms a consultant could be managing more than one project at a time across different verticals.


You can also spare a glance at our blog on HR Analytics


5. Good presentation skills


An Analytics Consulting professional has a client-facing role. After completion and testing of the project, he needs to make a structured report. The recommendations need to be presented in a manner so that the management or client can easily understand and be convinced. A good presentation report is one where each conclusion is backed by deep insights. No matter how complex the problem had been, the solution needs to look very simple and logical.



What does it take to get into Analytics Consulting?


  • A bachelor’s degree in mathematics and statistics

  • Proficiency in data analysis tools such as Big Data – Hadoop (Check out our blog on Hadoop vs Mango DB), Hive, Data Visualisation – Tableau, Qlik as well as Traditional Business Intelligence – SAP Business Objects, IBM Cognos, and Oracle Business Intelligence

  • Concrete knowledge of Predictive and Descriptive Analytics

  • Around 6-8 years of experience in analytics reporting with domain specialization

  • Industry certification in business analytics/ data science from a reputed institute

  • Strong interpersonal skills to understand the client needs and communicate the designed solution





Analytics consulting is one of the most coveted and financially rewarding profiles today. They are in huge demand by global giants like Accenture, HP, BNY Mellon, Dell, etc. Sound domain knowledge, rich experience, and exceptional communication skills pave the way for it.

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