BAV : From Classroom to Marketplace
HBS professors Krishna Palepu and Paul Healy have developed a business analysis and valuation software program, which is being sold to the public.
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.
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.
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.
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.