Question: I want to work as an Analytical / Analytics Consultant in the future. What skills should an MBA student cultivate in 2 years of the program? Also, can you name a few companies for this role in India?
AI Monks Response:
Business analytics has opened doors to a whole new world and raised decision making to a radically different stratum. Today, any organization makes an informed decision by slicing, dicing, and dissecting the data. But will this analysis hold any value if we completely ignore the business aspect of the problem at hand? We don’t think so. Analytics consulting is a functional role that aims to maintain a balance between business and hardcore analytics with an intention to deliver value-added analytical solutions.
Let us understand the role of an analytics consultant.
Usually, when we talk about consultants, the first thing that strikes our mind is an external expert who visits a company to solve a specific current or potential problem. And they leave the company(clients, as they are called) once they have done the task. However, there is another role that may not be very explicit, but plays a somewhat similar role; an internal consultant.
The external and internal consultants are substantially similar in the kind of work they do. Whereas, the significant difference lies in the way the company engages or hires them.
External consultants are usually employed for specific projects; while, the internal consultants are full-time employees.
Apart from how the company hires the external and internal consultants, almost all other functions stay the same.
Globally, corporate spending on analytics consulting had seen a surge of $43 billion in 2017. Companies evenly split the investment between developing in-house capabilities and spending on external consultants. With 91% of executives convinced that analytics have already generated substantial value for their firm, we could expect a rise in both.
Let’s talk about some of the projects that consultants work on:
- Automating reports or developing dashboards from scratch for a company using tools such as Tableau, PowerBI, Qlikview or custom-dashboards using scripting languages such as Python
- Identify avenues to improve logistics performance of a logistics company (or logistics unit of a manufacturing or retail company)
- Reduce the inventory held by a retail chain
- Analyze the campaign performance of a company
- Reduce the customer churn for a telecom client
- Identifying the target customer personas/segments
- Reduce the uninstall rate for app-driven companies
- Cannibalization effect on sales of one store due to the opening of another store
- Impact of A/B tests
- Analyze the results of sampling or experimental designs
We can notice through the list mentioned above that all these projects start with a robust descriptive and diagnostic analysis.
- The diagnostic analysis helps in identifying the root causes of areas where the company is not doing good.
- Whereas, the descriptive analysis helps in identifying and assessing the performance of the company.
- Once you understand the overall context and underlying problem, you should move to predictive analysis.
Hence, for anyone aspiring to become an analytics consultant, it is essential to develop a strong understanding of descriptive and diagnostic analysis. Having identified the problem, the next step is to identify and provide a solution to the company. Now, this solution can come in the form of process changes or by building a predictive model that can help the company understand the potential situations that can arise beforehand.
Therefore, it becomes essential for an analytics consultant to have a basic understanding of statistics and predictive modeling techniques. As a consultant, you may not be required to go very deep into statistical analysis or in-depth mathematics of predictive models, but it’s helpful to know the basic principles.
Analytics Consultant Skills
Let’s further understand what skills an analytics consultant will require:
Soft Skills
- Ability to breakdown the business problem into small problems
- Ability to read and comprehend data
- Good communication skills
- Great presentation skills (Powerpoint)
Technical Skills
- SQL
- Any visualization tool such as Tableau, PowerBI, Qlikview or any other
- Any ETL tool such as Alteryx
- Excel
Programming Language
- R or Python
Statistical Concepts
- Sampling
- Hypothesis testing
- Data distribution
- ANOVA
- Different types of data
Read: Impact of Recession on Data Science Industry
How can you acquire these skills?
1. Soft Skills
Developing soft skills is more like running a marathon and not sprint. “Practice makes perfect” is not just a saying. You can develop these skills with practice over a period of time. The best source to develop these skills is case studies. Practice case studies as much as possible.
- Form a group with friends, pick up case studies from whatever source you can, and get into it.
- Try to solve them end-to-end as if you were presenting to an audience.
- Right from breaking down the problem statement, analyzing data to creating presentations – do all of that.
- Find yourself a mentor who can guide you in improving your analysis and presentation.
- Present the analysis to your mentor as if you were presenting to the CEO of your company. That will prepare you for real-world scenarios.
If you are keen on improving your ability to read and comprehend data quickly, read as much as possible. Understand what are the different KPIs companies track regularly. Learn about different use cases that different companies work on. This will help you in developing data understanding.
2. Technical Skills
Understanding of technical skills is vital because you want to work on data eventually. From extracting to cleaning to manipulation to analysis, you should have expertise in all four areas. In a lot of scenarios, you will be given access to SQL systems where you will have to query data yourself; hence SQL becomes essential. DO NOT disregard SQL – it’s one of the most important skills if you want to work in the world of data.
- Alteryx, as an ETL tool, can help you carry out basic data transformation and data manipulation easily. Knowledge of a visualization tool can help you analyze data quickly and present it beautifully and insightfully.
- Learn any one of two languages (R or Python). They help significantly in building predictive models and much more complex data analysis where your other options may not work out. Hence they come very handily.
- Basic statistical concepts can help you in developing an understanding of the data collection process. Additionally, it can help you work on different types of datasets, such as sample data, survey data, experimental data, etc. Hence, learning these basic statistical concepts is essential.
3. Latest Happenings
Additionally, staying updated with the latest happenings in the industry would help you stay ahead of the game.
Conclusion
Summing up, we could ascertain that Analytics consulting is one of the most financially rewarding and coveted profiles today. Analytics consultants are in hugely sought after by global giants like Accenture, HP, Dell, BNY Mellon etc. Sound domain knowledge, rich experience and exceptional communication skills paves the way for it.
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