Growing a business without the use of statistics is virtually impossible. In large organizations, statistics are used to make a wide range of decisions. In small businesses, statistics help banks make decisions on whether to offer loans based on key financial ratios contained in a company's financial statement, loans that can be used to grow a new firm. Interpretation of key statistics is essential to decision making.
Statistical analysis allows businesses to measure the performance of a business and identify trends. This allows managers to make sound judgments, knowing their decisions are based on data and not on assumptions. Statistics helps businesses to plan better and make predictions about the road ahead.
The use of statistics in the management of a business is so pervasive that it's nearly impossible to summarize. A business may buy hundreds of thousands of microchips, for example, so many that it would take years to inspect each one. The business might then pull random samples from the order and perform statistical analysis to decide whether to accept or reject the microchips. Statistics can be used for marketing and market analysis. For example, a business might use statistical techniques to estimate the size of a particular industry, and then use its own internal data to estimate its share of the market. Businesses might use their past experience to estimate future results through regression analysis, or they may use it to estimate the percentage of clients who'll fail to pay their bills. Credit card companies use statistical analysis to detect fraud, while drug companies use statistical analysis to determine whether new drugs work, and whether they work in large enough populations to be profitable. Suffice to say, if there's a statistical tool, a business has a use for it.
The advantage of statistics is that they're comparable. Statistics can usually be expressed as a percentage, a ratio, an average, a median and even a raw number. What's important is that the method used to calculate the statistic is uniform each time. A factory might want to simply count the number of widgets it makes. If employees work 10 hours per day one week, and eight hours the next, it would be difficult to say the numbers are necessarily comparable. It might be better to calculate the number of widgets made per hour. This basic principle extends to all manner of statistics, from the key financial ratios of a business to the productivity calculations of a factory or the number of page views a website gets.
The rise of the internet and its use in data gathering, along with a rapid decline in the price of computers and data storage systems has given rise to an explosion in statistics. Industries that have traditionally been firmly grounded in statistics, like actuarial science and insurance, have seen a rapid influx of new data and new variables to inform their decisions. This rise has also given rise to new fields in business, like computational learning, and new titles such as data scientist.