Business intelligence blog

    Utilize financial analytics to ensure mergers & acquisitions success


     

    According to Reuters, merger and acquisition deals have seen a record boom this year due to low interest rates and high stock prices. Around 35,000 deals have been announce already, a jump of 24% over last year, and the total value of M&A deals has reached over $3.6 trillion dollars, already surpassing the total amount in 2020.

    Aided by the need to readjust business models in a post-pandemic world, organizations are more actively exploring M&A options. Whether you are on the buying or selling side, mergers and acquisitions can be extremely lucrative options. But successful mergers and acquisitions require lots of due diligence and your time and resources could be being wasted if you’re not taking the proper steps.

    Eliminate guesswork on important valuations

    Mergers and acquisitions are often valued on a multiple of the company’s EBITDA. To ensure the accuracy of these valuations, and that this number is not inflated, means you need access to lots of financial data to analyze the company’s financial performance. Since this data could be coming from multiple different sources it can be a daunting task if you’re lacking the right solution.

    Phocas makes it easy to bring in data from multiple sources and transform it from static data to data that is updated daily, so you always have a clear picture of performance. With an intuitive Phocas interface, you can access all the information you need at the click of a button.

    Achieve greater data visibility

    Phocas lets you go deeper into your data. Users can review not only a company’s financial records, but the data behind the records as well such things as customer and inventory concentration, and inventory turn, to salesperson performance, product pricing and vendors. This transactional data gives a better idea of business operations and revenue generation. Best of all, this visibility into the data means you’re not going back and forth with questions to the M&A company in question, avoiding any disruption to the business. 

    Having the ability to easily drill down deeper into this company data can lead to a more comprehensive overview of how the company is performing. It’s a unique feature that Phocas customers love since it helps to answer the “why” behind their questions and provide the clarity they need for better decisions.

    Trade Supply group relies on Phocas to evaluate acquisitions

    New York-based building supplier Trade Supply Group has grown the last several years through acquisition. Central to its acquisition strategy is Phocas Analytics software, which the company uses to evaluate acquisition candidates’ assets, and then streamline the integration of financial and operations data from candidates once they are acquired. 

    “Phocas helps us to complete the due diligence on prospective acquisitions and then clean their data for a smooth conversion to our ERP system,” said Nick Aversano, vice president of operations for Trade Supply. “[The] level of analysis shows important trends and can potentially lead to better product pricing for all of our businesses, as well as reveal details that didn’t necessarily show up in our financial analysis.” 

    Phocas offers a flexible user-friendly solution that makes it simple to import multiple data streams for quick analysis that can accelerate an acquisition. Phocas simplifies the conversion of the new acquisition’s data into the collective’s ERP system, and then empowers decision makers with the data access and analysis capabilities they need to better manage their areas of responsibility.  

    For more information, review this on-demand webinar, Streamlining the M&A process with Phocas.

    Written by Thomas Shoemaker
    Thomas merges his love of data and marketing at Phocas. He is keen to learn more about customers application of analysis to different data sets.
    Thomas merges his love of data and marketing at Phocas. He is keen to learn more about customers application of analysis to different data sets.
    Screen Shot 2021-09-22 at 10.03.48 AM
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