How I learned to Manage a Business P&L (1/2)

Introduction

Let’s say you are working in an EdTech company, and have been mandated to launch an online Data Science Course. You will need to build the course and manage the entire P&L. The start date for your first cohort is decided and non-negotiable, and you have targets on quarterly revenues that you need to hit. This is how you could approach the problem:

Conduct Market Research

The very first thing on the agenda will be to do extensive market research:

• Why would one purchase an online Data Science Course? Is there enough demand in the market which is unmet by the traditional education system? Is it a frequently searched topic on Google? (remember 60% of any online shopping starts with a Google search)
• Who is searching for this course- freshers or working professionals? If it is working professionals, are these people looking to upskill or looking to switch industries?
• What are the current online courses offering? What is the USP of each online course provider and how will you differentiate yourself?

The idea to launch a particular course is mostly a management decision, decided based on:

Looking at the current demand. Tools such as Google Keyword Planner and Ahrefs, which show the traffic on relevant keywords, are a good starting point. If you are an established platform, chances are you already see the demand coming in from your current traffic. This can be observed through:

• The search queries on your platform.
• The queries about new courses on your chat, customer surveys, etc.

Forecasting the future demand (e.g., demand for AI/ML courses in 2023). Again the source of truth would be the trending topics on Google, and gathering insights from recruiters, communities, and companies.

In case you are asked to do the above research, this can be a good market sizing exercise as well. It will help you get connected to a lot of relevant stakeholders (as part of your primary research) who can later become your instructors, content creators, or mentors for the course.??

As an example, let us compare the Google search volume for a Data Science course against other courses in India (as of 17th Oct 2023).?

As per Google, we find

• A very high search volume of data science courses when compared to other courses.
• Highest page bid for data science, indicating that other players are willing to pay top dollars for ads associated with this keyword, with the potential to bring in valuable customers.

Create User Persona

Given the high demand for Data Science courses, it is important to find your niche. You need to define who the potential learner is. Talk to recruiters, and candidates looking for data science courses to understand which age demographic you should target and where the skill gap lies. This will help you figure out what needs to be built into the course curriculum and also define the audience that you need to target.?

Always remember that you cannot have a general course appealing to many, because you will then end up appealing to none. Following can be some of the personas for an online Data Science Course.

Persona 1: Aspiring Data Analyst

Background:

Bhavna is a recent graduate with a degree in statistics. She has a strong foundation in mathematics and statistics but lacks practical experience in data analysis and programming. Bhavna is eager to transition her theoretical knowledge into practical skills and pursue a career as a data analyst.

Goals:

• Gain practical data analysis skills using tools like Excel, SQL, and Python.
• Understand machine learning concepts and applications.
• Build a portfolio of projects to showcase to potential employers.

Challenges:

• Limited programming experience.
• Needs guidance in applying statistical concepts to real-world data.
• Looking for hands-on projects to build a portfolio.

Persona 2: Career Switcher - IT Professional

Background:

Mohan is an IT professional with three years of experience in software development in the service industry. He is interested in transitioning his career into data science to leverage his programming skills in a new domain. Mohan has a decent understanding of algorithms and data structures but lacks expertise in statistics and machine learning.

Goals:

• Learn statistical analysis and probability theory.
• Master data manipulation and analysis using Python and SQL.
• Develop expertise in machine learning algorithms and their implementations.

Challenges:

• Limited background in statistics and mathematics.
• Needs to bridge the gap between software development skills and data science applications.
• Looking for a course that offers practical, hands-on learning experiences.

Persona 3: College Graduate - Business Major

Background:

Esha recently graduated with a degree in business administration. She has a keen interest in understanding customer behaviour, market trends, and business analytics. Esha has minimal programming experience but is motivated to learn data science techniques to analyze business data and make data-driven decisions.

Goals:

• Acquire fundamental data analysis skills using tools like Excel and SQL.
• Learn programming fundamentals and explore Python for data analysis.
• Apply data science techniques to solve business-related problems.

Challenges:

• Limited programming background.
• Needs practical examples related to business applications.
• Looking for a beginner-friendly course with a clear learning path.

By tailoring your course to meet the needs of these personas, you can create a learning experience that resonates with your target audience, addressing their specific goals and challenges in the field of data science.

Set Course Objectives and Build the Course Curriculum

By now, you have figured out that there is a demand for online data science courses in the market. You have also identified the personas whom you will be targeting. Therefore, it is time to get started on building the course curriculum.?

Begin by defining the objectives for the course. Remember to keep the objectives SMART. For example, it is evident that the personas defined above need to master fundamental concepts of data science, given that they are just starting out or in the early years of their career. One of the objectives could be:

Objective: Master Fundamental Concepts

• Specific: Understand and explain key concepts in statistics, mathematics, and data science methodologies.
• Measurable: 80% of the cohort learners should score at least 80% on the statistics and mathematics assessments.
• Achievable: Provide resources like video lectures, practice problems, and quizzes for understanding fundamental concepts. Keep assessing them periodically.
• Relevant: This fundamental knowledge is essential for advanced data analysis and modelling.
• Time-bound: The target will need to be achieved within the first ten weeks of the course.

Defining multiple objectives for your course will give you clarity on what modules to include. These can also become your talking points when promoting the course. Moreover, it will set the expectations for the potential learners and help them decide if the course is relevant for them.

Once your objectives are finalized, you need to prepare your course modules. I sat down with my friend, Parinitha Chowdary Sadineni , to detail the different modules that would go into an online Data Science Course. We used the above personas for our reference and set a couple of objectives for the course. Here’s a summary of the same:

Budgeting for your Course:

At this stage, your primary focus is getting approval on budgets for your course creation. Other cost elements such as advertising spending will follow. Here’s how you can create a costing plan for the above course module.?

• Define the persona of the instructor who will lead the module. You can choose to give them the mandate to create and teach the module. In case they don’t wish to do so, the content creation can be done by a freelancer as well.
• Negotiate a per-hour rate for every instructor and content creator.
• Define the man-hours needed to complete the module.

This will give you two important insights:

• The total cost of creating the course.
• The estimated monthly payouts (cash flow), since this will be dependent on the rate of course completion.

As illustrated above, the total expenditure of developing and teaching the course is approximately Rs. 25 lakhs, to be paid out over a period of 9 months. It is important to note that this estimation doesn't account for potential additional expenses, such as unplanned guest lectures or the costs associated with tools and infrastructure.

In the upcoming segment of this series, I will talk about other cost components, including course promotion and the necessary operational efforts for course management. Additionally, I will also discuss the revenue targets required to attain breakeven at a cohort level.