Roper Technologies has generally executed well over the past number of years. We offer three recommendations to Roper for driving superior operational performance and shareholder returns.
1.) Focus the Enterprise Software M&A strategy: This is Priority One. To date Roper has taken a buckshot approach to M&A with acquisitions scattered across the Software landscape. This is no accident. When Roper recently announced its new segment structure, CEO Neil Hunn stated that: “Our new segments reinforce Roper’s diversified, niche market strategy by emphasizing business models instead of end markets.” (Click HERE to view Roper’s Software portfolio).
Not focusing the M&A strategy around two or three end markets/industry verticals makes it unnecessarily difficult to scale in any one vertical – and “scale” is the name of the game in Software. This broad approach to Software M&A is a luxury afforded to the largest Platform Software companies including Adobe (ticker: ADBE), Microsoft (ticker: MSFT), Oracle (ticker: ORCL), Salesforce (ticker: CRM) and SAP (ticker: SAP).
2.) Link Executive Compensation to EBITDA AND the strategy: Roper’s CEO compensation plan ties comp to EBITDA growth. This incentive plan encourages the indiscriminate pursuit of acquisitions/ EBITDA without consideration of a larger strategy. A superior compensation plan would link variable compensation to EBITDA growth AND a focused strategy around two or three industry verticals.
3.) Consider all M&A targets within two or three strategic verticals: M&A targets ought to include public and private companies, large and small. 80-90% of the M&A operation ought to be focused around large acquisitions as large deals drive the most ROIC per unit of time invested across target identification, initial purchase negotiation, due diligence, purchase negotiation and post-close integration.
The occasional small, strategic acquisition makes sense when it means acquiring a disruptive product or service, particularly if it means acquiring the founding team. In terms of the latter, we predict that Technology companies will acquire teams fluent in Advanced Analytics/ AI, machine learning, deep learning, and Natural Language Processing (“NLP”), given the significant demand for qualified data scientists and the short supply.
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