In an age when mergers, acquisitions, and spin-offs are increasingly common in business, you need a new skill in your kit bag: the ability to analyze and value potential partners, deals, investments—even your own company.
The Business Analysis and Valuation Model (BAV) tool uses historical financial data to perform accounting analysis, ratio analysis, forecasted financials, and valuation. It also provides benchmarking for comparable firms. It was created by Harvard Business School faculty Krishna Palepu and Paul Healy, in collaboration with former HBS research associate Jonathan Barnett.
Originally designed for HBS classroom use, the BAV software was recently made available to the public for purchase for $69 through Harvard Business School Publishing.
We asked Healy to discuss the BAV in an e-mail interview.
Sean Silverthorne: What's the history of the Business Analysis and Valuation tool?
Paul Healy: The tool was first developed to show students who were taking BAV how discounted cash flow (DCF) and earnings-based valuations work and can be reconciled. Over time, based on feedback from students about the value of the tool, and the opportunities for making it more powerful, we have extended its generality and output to really help a broader user to take advantage of the insights that it provides.
Q: How does the tool work?
A: The tool requires users to input financial statements for a company, enables the user to standardize those statements, and if needed modify key elements of the firm's accounting if they believe that reported data do not capture the economic performance of the company. The model then provides standardized financial statements and financial ratios for the firm to allow users to assess the firm's performance.
Users can then input forecasts for the key performance variables (sales growth, profit margins, working capital turnover and long-term asset turnover) as well as financial leverage and cost of capital. Users can judge whether their forecasts are reasonable by comparing them with performance for comparable firms, based on historical data.
From these inputs, the model estimates the value of the firm's assets or equity, using a variety of approaches (DCF, abnormal earnings, or abnormal ROE). Finally, the model provides users with the opportunity to create different scenarios to judge how these affect firm valuation.
Q: Who are the likely users of the product? Could you provide a scenario or two of how it would be used?
A: The model is valuable for professional investors (money managers, financial analysts, hedge fund managers), for individuals that are interested in investing, and for general managers who wish to have an understanding of how the market is judging their firm's stock.
Typical decisions could include: (1) Should I buy or sell this stock? (2) As a private company, what would my stock be worth as a public company or if I had an IPO? (3) As a CEO of an acquirer, what is a potential target worth to my firm given the synergies and performance improvements I anticipate being able to generate?
Q: There are other analysis/valuation tools and books on the market. How does yours differ?
A: Our tool has several features. First, it allows users to adjust a firm's accounting if they want to. For example, if they want to see how off-balance sheet debt affects the company's performance, they can easily adjust the financials for that affect. If they want to see how expensing stock options would affect the company's performance, they can add that adjustment.
Second, the model provides benchmarks for long-term performance based on historical data that should help users to avoid a common mistake of overestimating the sustainability of strong (or poor) current performance.
Finally, the model shows the direct linkage between variables that are used to evaluate a firm's performance (margins, turnover, and financial policies) and economic value.
Q: The tool was first used for an MBA course at HBS. Have you made many modifications to move it out to the commercial world?
A: This year we have added an interaction with online data sources, to enable users to quickly download data for public companies into the model. We are continuing to enhance this feature.