FINANCIAL ANALYSIS IN A DATA-DRIVEN WORLD

FINANCIAL ANALYSIS IN A DATA-DRIVEN WORLD

December 24, 2018

Today, all eyes are on a business’s finance department as it is asked to cut costs, reassess risks, and cope with the deep uncertainty generated by ongoing economic conditions. New questions arise everyday: what new challenges these departments are facing; which activities are taking up more, and less, of their time; whether their centralization or outsourcing plans are being modified; and how the CFO’s focus has shifted. In this era of ever-changing business, it is imperative that the financial analysis play a significant role in how businesses deal with such changes.

In Layman’s terms, Financial Analysis is defined as being the process of identifying financial strength and weakness of a business by establishing relationship between the elements of its financial statements – the balance sheet income statement. The information pertaining to the financial statements is of great importance through which interpretation and analysis can be made.

Through the process of financial analysis, businesses get to identify key performance indicators, such as, liquidity solvency, profitability as well as the efficiency of operations of a business entity, while short term and long term prospects of a business may also be evaluated. By using such analysis and identifying the potential weaknesses of a business, the intent is to arrive at recommendations as well as forecasts for the future of a business entity.

PUSH TOWARDS FINANCIAL ANALYTICS

In today’s data-filled world, traditional financial analysis is no longer sufficient, rather data-based analytics is an essential part of staying competitive. Financial analytics can help businesses understand current and past performance, predict future performance and make smarter decisions. Let’s look at some of the key financial analytics that any business, regardless of size, should be using in the modern world.

PREDICTIVE SALES ANALYTICS

Sales revenue is the lifeblood of any business. So knowing how much you can expect to receive has important tactical and strategic implications. Predictive sales analytics involves figuring out how successful your sales forecast is and improving your sales predictions in the future. There are many ways to predict sales, such as looking for trends in past data or using predictive techniques like correlation analysis. Predictive sales analytics is an extremely useful tool for planning and helping businesses manage the peaks and troughs of their life cycles.

Tip: Predicting future sales is always helped by detailed and thorough sales data from the past so it is crucial to keep accurate records.

CUSTOMER PROFITABILITY ANALYTICS

It is important to differentiate between the customers that help a business make money and the customers that make a business lose its money. Customer profitability usually falls within the 80/20 rule, whereby 20% of the customer base accounts for 80% of profits; and looking at it from the other side, 20% of customer base accounts for 80% of customer-related costs. Therefore, knowing the significance of these circumstances is particularly important.

By understanding the profitability of certain groups of customers, businesses can also analyze each group and extract useful insights. For example, one may discover which customer made the first purchase being influenced by a particular advertisement in a particular magazine. That knowledge can help direct future marketing efforts.

Tip: The biggest danger with customer profitability analytics is when businesses do not analyze a customer’s full lifetime value. It is important to focus on a customer’s cumulative value to the business.

PRODUCT PROFITABILITY ANALYTICS

In order to stay competitive, businesses need to know where money is being made and lost. Product profitability analytics is the way of discovering profitability by individual product, rather than looking at the business as a whole. To do this, managers need to assess each product and its costs individually. Admittedly, this can be tricky because the products may well share production processes or cost bases. Therefore, one needs to find a reliable and fair way to apportion costs to various products. Product profitability analytics helps businesses uncover profitability insights across the product range so better decisions are made and profit is protected and grown over time.

Tip: Watch out for loss leaders. Some products may lose business money but their purchase leads on to more profitable purchases, such as a razor and the expensive replacement blades.

CASH FLOW ANALYTICS

The day-to-day running of a business requires a certain amount of cash to keep the lights on, wages paid, etc. Knowing how money is moving in and out of the business is essential for gauging the health of one’s business. Cash flow analytics involves using retrospective or real-time indicators such as the Cash Conversion Cycle and Working Capital Ratio. Managers can also use tools like regression analysis to predict future cash flow.

On top of managing cash flow and making sure the business has enough cash to keep the cogs turning, cash flow analytics can also support a variety of corporate functions. For example, analytic software can help accounts receivable personnel to increase cash flow by prioritizing which customers are contacted by collection staffs and when.

Tip: When trying to predict future cash flow based on past data, it is important to ensure that right assumptions are being made. Scenario analysis can help with this.

VALUE DRIVER ANALYTICS

Most businesses have a sense of where they are heading and what they are trying to achieve. Often these goals are formalized on a strategy map that identifies the value drivers in the business. These value drivers are the key levers that the business needs to pull in order to meet its strategic objectives. Value driver analytics is the assessment of these levers to ensure they actually deliver the expected outcome.

Value drivers are often based on assumptions which need to be tested to check they are correct. For example, a business may use price as one of their value drivers and assume that price influences sales and revenue, but it needs to test that hypothesis so it can establish if the hypothesis is right or not.

Tip: Managers must properly identify their value drivers and be really clear about what it is you are trying to achieve strategically.

SHAREHOLDER VALUE ANALYTICS

The results and interpretation of the results by investors, analysts and the media will determine how successful a business is on the stock market. Shareholder value analytics is a calculation of the value of a company made by looking at the returns the business provides to its shareholders. It effectively measures the financial consequences of strategy and assesses how much value the business’s strategy is actually delivering to the shareholders.

Shareholder value analytics should be used frequently alongside profit and revenue analytics. To measure shareholder value analytics, one can use a metric called Economic Value Added (EVA). This calculates the profit of a business when the cost of equity finance has been removed.

Tip: This metric needs to be tempered with additional customer-based analysis to ensure that the shareholder value is not occurring at the expense of customer value.

DATA FOR THE CONTINUOUS PROGRESS

It must be noted that Financial Analysis is a continuous process being applicable to every business to evaluate its past performance and current financial position. It is useful in various situations to provide managers the information that is needed for critical decisions. The process of financial analysis, paired with big data is bound to provide businesses with information about the ability of a business entity to earn income while sustaining both short term and long term growth, and provide the competitive edge necessary for an ever-changing, ever-challenging financial landscape.

By Taposh Ghosh

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