The Role of Business Analyst in Small Business Growth

By Marketing Advisory, 3EA
The Role of Business Analyst in Small Business Growth

Business Analysis is one of the core business practices. The role of a business analyst is very crucial. He acts as a link between the organization’s technological capabilities and its business objectives. Business Analyst utilizes every form of data towards the profitability of the business. Data is a vital resource for any firm, in other words it is a strategic asset. In present scenario, there is large volume of data in market but small firms are reluctant to get into data analytics because of the cost involved in doing it. Data analytics has now become imperative for any business to survive in long run. Improving hundreds of thousands of small decisions may add large annual value for any business. One has to dive into the data and draw appropriate inferences and present it in a way which is easy to comprehend.

Business Analyst analyzes the business data and provides a company with decision-making insight into the following fields -
1. Increasing business productivity
2. Helps in decision making
3. Product Quality Management
4. Analyzing the requirements of the organization
5. Helps in exploring new opportunities
6. Increase the market value
7. Predict the customer behavior


Business analytics can help businesses of any scale to grow in different ways, it can help in:-

1) Planning the Future Actions to be taken

Planning is the primary key for any business. Business Analytics helps to optimize actions by pointing out the areas where the strategies are going wrong. Proper planning and execution of strategic plans helps in increasing operational efficiency of the business hence increasing the business potential. As a result, one can take well informed decisions for future course of action by weighing the risks and consequences.

Predictive analysis plays a crucial role in planning future course of action. It has proven its worth in critical business cases especially in MSMEs - sales forecasting, manage customers, customer retention, production forecasting, capacity planning and much more.

Predictive analysis techniques used are -
1. Correlation & Regression
2. Cluster Analysis
3. Association Analysis
4. Time Series Analysis

Suppose there is an e-commerce company that has a plan for the forth coming festive season. Before executing the plans, the decision makers want to evaluate the results of their strategy. Here comes the role of Business Analyst. A good analyst employs predictive analysis techniques such as - churn prevention, identify sales activity on basis of present trends, demand forecasting etc. This would help the company to achieve the business growth expectations in the upcoming festive season. The pinpoints to be considered by the analyst should be -

1. Predicting the behavior of the customers on the basis of historical data such as customer's personal information, how they respond to promotional offers and campaigns, how frequently they visit sites and apps etc. Analyst will predict the impact of new promotional activities on the customer engagement using above historical data.

2. He will also monitor the fraudulent activities while doing the payment transactions using historical customer transaction data and their geographical area.

Business Analyst will first work with the marketing team to gather all the useful data - promotional history, transactional data, purchase history, customer past behavior data. Data is then cleaned and structured for further analytical operations such as regression, correlation, associations whatever suits the best. Patterns in the results help in determining the impact and effect of all the marketing campaigns and thus the business can further modify their operational activities accordingly.

2) Continual Performance Improvement
Is market trending upwards or downwards? Is it growing or shrinking? Is there is any demand of your product? There are some terms like Market Trend Analytics and Time Series Analysis which answer the above questions. Everything is based upon data in today's world. The only concern is how to play with data to draw out the accurate inferences. There is no business that could run without strategizing your market plans.

One needs to evaluate his performance at every step for continual improvements. Analytics helps businesses to identify new opportunities that are still unexplored, identify areas that need improvement, identify the competitor actions and how to make the market better than the competitors, evaluating the performance of the employees and analyze how their potential can benefit the organization, improve products and services on the basis of customer feedbacks, improve business strategies that would bring better results, improve customer and dealer/supplier relation that would bring better value to business, depending more on technology than on manual work. For the performance improvement one uses the descriptive and diagnostic analysis to analyze the actions performed and optimize them to achieve expected results in future.

3) Product Quality Management
Customers have a very high expectation for quality. If the product does not meet the quality requirements, this would result in customer dissatisfaction, customer churn and will damage the brand name. Data Science can help to identify the quality issues at very early stages by quality control technique and fix it before it causes any type of damage to the business. A quality control analysis is run and if the process is going beyond upper control line or lower control line then that indicates that there is some problem in production that would hinder the quality. It's imperative to identify the issue and resolve it as soon as possible. This would reduce liability costs and warranty cost and enhance your brand name.

4) Innovative and Effective Marketing Strategies
Today's research suggests that social media marketing has become the key marketing technique for any businesses to grow. Branding sounds a big term nowadays. How the brand is advertised and how customers perceive it are two different things. A business may think that the current marketing strategy is good but it may not have any idea that how customers will perceive its product or how the product would survive against those of competitor's if it is unaware of the competitor's marketing strategy.

If there is a local firm that manufactures kitchen utensils and they have planned to launch some new type of pressure cookers. Before the execution of the plan, the owner has to answer himself some questions like -
1. Is there any market demand for such type of product now?
2. Why the customers should buy our product instead of those major market players such as Prestige, LG or Hawkins?
3. Is there anything very peculiar with our product that customer should pay for it?
4. How to advertise the product to create brand awareness?

Big data analytics answers all these questions whether the new business plan is suitable for business growth or not. The historical data about the marketing patterns must be used actively, to trace the successful marketing techniques. All the statistical data related to approaches and actions can be used to evaluate the fruitful and failed marketing tactics.

The business analyst's primary objective is helping businesses achieve their goals in a strategic and cost-effective way by determining the requirements of a project or program, and communicating them clearly.

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Article by: Marketing Advisory, 3EA