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- W2896410968 abstract "Ever since the dawn of internet, a new wave of fast-growing software companies hasemerged. The M&A scholars have struggled to find appropriate valuation mechanismsfor unprofitable companies with ultra-high revenue growth. To overcome the uncertainfuture, a contractual provision called earnout is often used. An earnout is a contractualprovision in a M&A-deal that states the seller of the business is to obtain additionalcompensation in the future if the business achieves certain metrics.The purpose of this study is to contribute to practice and nascent literature by exploringand evaluating metrics for SaaS-companies that can be used in earnouts. The study appliesLean Anaslytics to suggest a framework for choosing what metrics to use, and discusseshow to avoid sub-optimisation and metric manipulation.In order to answer the research questions, a qualitative, exploratory and abductive methodologywas used. The study combines a literature and thought leader review and interviewsto explore certain areas, with a case study that applies the findings.The study suggests that the process for determining metrics should start with the buyer’sacquisitions strategy. For acquisitions where the objective is to access talent, technologyor accelerate product road-map, the study has shown that earnouts in most cases not beused at all. If the acquisition is made based on financial objectives, Lean Analytics canbe used to determine what stage the seller’s company is in. Understanding what stagethe company is in is crucial as the type of metrics that matter differ depending on stage.The study suggests that the most suitable earnout metric for M&A based on financialobjectives is monthly recurring revenue (MRR). The metric must be clearly defined so itcannot be manipulated. The reason why many other metrics from Lean Analytics cannotbe used is that they are vulnerable to manipulation and can restrict the operating freedomfor the entrepreneur." @default.
- W2896410968 created "2018-10-26" @default.
- W2896410968 creator A5088807117 @default.
- W2896410968 date "2018-01-01" @default.
- W2896410968 modified "2023-09-27" @default.
- W2896410968 title "Applying Lean Analytics to Performance Metrics in M&A Earnouts" @default.
- W2896410968 hasPublicationYear "2018" @default.
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