Originally published in American City Business Journals
By Joanne Baginski
When it comes to striking the right price for an M&A deal, a buyer and seller often paint very different pictures hoping to convince the other that their valuation is the right one. These days, however, both parties should know that data tells the true story.
Due diligence is an arduous, pain-staking task of poring over spreadsheets, financial statements, and industry benchmarks in search of that single grain of insight that might force a crucial change to a deal. It’s increasingly a big data exercise, and the right tools, such as data-mining software, makes all that much easier, bringing the power of cloud computing and analytics to what is admittedly a laborious process.
Make no mistake: Data-mining tools such as IDEA and Tableau require an expert analyst to create the right queries and interpret the information. But in the right hands, software can help uncover hidden issues that can lead to big problems later or to gems of opportunity along the way. The narrative the data tells will be more compelling than any story you spin.
Getting the most out of due diligence is critical. The shocking reality is that up to 60 percent of mergers are unsuccessful, destroying value and failing to produce the desired growth. According to a recent study in the Harvard Business Review, “too many executives bring insufficient discipline to the evaluation process that fuels these deals (and) as a result, they often get deals wrong.”
In other words, emotions and assumptions impede getting to an accurate valuation. Employing a modern data-mining approach will help determine the most complete and accurate understanding of a company’s value. The tools and the science itself can often reveal a view of a company that even its own executives were unaware of — including such things as profitability and volume by product or sales by individual staff or by region.
Inventory data, customer sales data and tax compliance figures, among others, when coupled with advanced analytics, can be used to reveal issues or opportunities.
Three areas can be especially important:
Inventory: High-level financials might suggest a company’s inventory is being turned over at a high pace and that gross margins are at or above expectations. However, a closer inspection can reveal any number of problems: Are some inventory items selling slower than others? Are there excessive levels of certain products on hand? Is the company overly reliant on items that are a fad or on a downward profitability or sales volume trend?
Smart companies will undertake such analysis regularly to better understand their business and where they may be incurring costs unnecessarily. Recently, my team worked on a home0building supplies company deal where the two parties reached a tentative agreement based on an $80 million valuation. However, an examination of the target company revealed that 20 percent of its thousands of products in inventory would take more than 150 years to sell based on recent sales trends. The discovery reduced the purchase price by $4 million, or 5 percent, for the purchasing company.
Customer trends: A company often paints a rosy picture of its financial situation, but a closer look can reveal all manner of problems. For example, does a company have a concentration with one customer or a small number of customers? Regardless of concentration, what is a customer’s contribution to gross margin? Are customer profitability or volumes declining? Or, are they being propped up by heavy marketing or customer discounts? Why? Is it due to customer service issues, product quality concerns, increased competition, or vulnerable relationships?
The data always tells a story. It’s up to us to find out what it is.
Taxes: Data can reveal a myriad of tax problems, particularly from ever-changing state and local tax regulations that companies often struggle to stay compliant with. Reviewing detailed sales data by delivery state can reveal potential nexus issues. For example, companies selling products fulfilled by Amazon are subject to income and sales tax nexus in any state where Amazon held its inventory throughout the year. In addition, some states have factor-based presence filing requirements (some may be based on certain thresholds of sales), which may be discovered through data analysis.
Finding such tax concerns won’t necessarily reduce the price of a deal, but, buyers may place a portion of the price in escrow pending a resolution.
Such analysis used to require analysts to input data from paper and PDF files into spreadsheets over a period of weeks. This information now can be scanned and ingested into data-mining software in a matter of hours.
Speeding up the data gathering makes time for deeper analysis. With due diligence more important than ever, data mined correctly will help tell a more complete story and will give any merger the best chance of success.
Joanne Baginski has almost 25 years of public and private accounting experience and leads the transaction advisory services area at EKS&H. She has been involved in more than 200 transactions, working on both the buy and sell sides of deals, and her expertise also includes business finance, financial planning and analysis, and capital financing.