Financial Analysis enables an organisation – regardless of its size or industry – to predict future outcomes against their current goals and strategies. Financial insights into efficiency measures, operational KPI’s, product, service or customer profitability, enable businesses to augment revenues and shareholder value. In Business Financial Management, a complement of tools, formulas and methods are used to derive these insights. As a result, it allows a business to be agile and competitive by making informed, mindful, calculative decisions that foster organisational growth.
Data-intensive corporations use a CRM, Data Science and Financial Analysis software, but business entities that have smaller data sets can still run this on Excel. This article lists 4 types of Financial Analysis commonly used in Business Financial Management.
Financial Management Analysis #1: Predictive Sales Analytics (PSA)
Sales revenue is the end objective of any organisation. Predictive Sales Analytics allows a business to implement strategies that identify and nurture high conversion probability leads. It is estimated by comparing historic sales trends and data patterns against the current sales pipeline, often using correlation analysis on the data. Predictive Sales Analytics allows a business to forecast expected sales revenue over a period of time, using this information for resource allocation, investment strategies and competitor behaviour.
Financial Management Analysis #2: Product Profitability Analytics (PPA)
Product profitability is one of the simplest Financial tools available to a business. It is calculated by dividing the total output with the total input and can be run on a company level, department level and even down to a service or product level. It allows a business to identify units that generate the highest and lowest return, allowing them to make decisions on what to invest, what to downsize and so forth. In recent years, Product Profitability Analytics have even been applied to employees, especially those in sales.
Financial Management Analysis #3 Customer Profitability Analytics (CPA)
An integral part of running a successful business is its ability to identify which customers generate the most profit. Customer Profitability Analytics does just that by using demographic, geographic, purchase frequency, lifestyle data and other factors to build clear customer segments, mapping revenue to them to identify the best performing segments. This allows an organisation to allocate additional money and resources to optimise the segments that are the most profitable.
Financial Management Analysis #4: Cash Flow Analytics (CFA)
Every business needs capital to operate and grow and predicting the inflow and outflow of cash is an important determinant in evaluating a company’s liquidity and fluidity. Data models using regression analysis uses historic data, debt-ratios, arrears etc. to forecast how much capital inflow a business entity can expect over a period of time. This prediction is used to determine future opportunities and threats for the organisation, giving them the time to act accordingly.
CEO’s, CFO’s and senior executives rely on Financial Management tools and analytics to make both tactical and long-term decisions. With data and technology playing an increasing role in business, regardless of its size, it has become apparent that anyone in a management function, especially those in Finance, learn how to analyse their existing and historic data to make informed business decision.
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