Managerial & Business applications of Statistics
Statistics is one of the most primitive and primary fundamental domains applied in almost every aspect of analysis and decision making. Especially in the new domain of management, big data and analytics, statistics remain the most fundamental knowledge to be required to become a good researcher.
Statistics is widely used in Business and decision making in the following areas:
1. Planning
2. Production
3. Inventory management
4. Supply chain management
5. Marketing
6. Sales and demand forecasting
7. Services
8. Logistics
9. HRM
10. Data Analytics
Planning: Statistics is indispensable into planning in the modern age which is termed as “the age of planning”. Almost all over the world governments are re-storing planning for economic development by using electoral statistical databases.
Production: Statistics plays a vital role in production management. The statistical models like Linear programming etc., will ensure to attain the desired production objectives consistently, even though there is scarcity with the materials and human resources. And quality control charts etc., will help in attaining the desired quality too.
Inventory management: How many volumes of stock to be maintained and how many cycles of order is to be given and how many volumes of order to be given etc., is all analysed to reduce the inventory cost and to reduce the ordering cost etc., by using statistical tools.
Supply chain management: Statistics play a pivotal role in predicting future demand patterns based on historical data, market trends, and external factors. Accurate demand forecasting helps supply chain managers make informed decisions about production quantities, inventory levels, and resource allocation. And various statistical tools are used at various stages/channels in transforming the raw materials to finished goods.
Marketing: In marketing, statistics are used to identify market trends, measure and evaluate marketing strategies, and assess their effectiveness. To be successful in a campaign, it's important to identify the target market accurately as well as use effective marketing communication channels. A skill full analysis of data on various demographic factors like purchasing power, age group, habits and customs of consumer, logistics cost etc., will open the venues for the new markets/target markets.
Sales and demand forecasting: By using various statistical techniques like least squares method, moving averages method etc., sales and demand forecasting can be done. The future trend of sales patterns and demand patterns can be analysed/predicted.
Services: Now a days lot of companies are using statistics in analysing the huge data pertaining to buying patterns, reviews, customers behaviour patterns etc., Companies like Amazon, Flipkart, Uber, Zomato etc., use high end logistics in minimizing the delivery costs and in routing. With the advancement in the artificial intelligence and machine learning etc., the service industries can enhance and provide the best quality and service facilities.
Logistics: Logistics use high end transportation/transhipment models in minimizing the various transportation costs. These models are high end statistical models which use latest technology and statistical concepts to reduce the costs.
Human Resource Management: By using a statistical concept called as assignment problem, a HR manager can decide, which job is to be assigned to which person, to get the jobs done, with the minimal costs. Now-a-days most of the HR managers are using SPSS & SAS statistical software’s too in sorting out the big data pertaining to employees.
Data Analytics: Statistics is the preliminary knowledge, which is to be learned for gaining analytical skills. Currently, statistics and statistical methods play a key role in doing data analysis and to become a sound data analyst. Statistics stands as a prerequisite knowledge to be gained for learning big data analytics, machine learning, AI-based models, data visualization tools etc.,
Conclusion: In overall, without the proper knowledge of statistics and statistical methods, the business managers cannot make proper strategic decisions. The knowledge of statistics and statistical tools plays a vital role in Data Analytics, sales & demand forecasting etc., Even without the proper knowledge of Statistics researchers cannot yield the accurate results and they need to use the suitable statistical tools and methods to do correct inferences. Hence Statistics and Business strategic decision making and as well Statistics and Research are considered as inextricable.