Jeremie originally started his career at Goldman Sachs and spent time in investment banking focused on equities, equity sales, and trading. He has experience on both sides of M&A, as an acquirer and “acquiree,” and says the deals he has seen in the past 10 years – some successful, others not – have changed his perspective on M&A.

0:00 – 2:12 Jeremie’s background in SaaS and investment banking

2:13 – 5:52 The value of focusing on giving in M&A transactions

5:53 – 11:40 Importance of pre-diligence diligence

11:41 - 14:12 Example of a deal not closed

14:13 – 15:50 Allocating resources and labor pool decisions

15:51 – 19:14 Advantages of quick integration

19:15 – 25:29 Painful lessons

25:30 – 30:57 How to use advisors

30:58 – 36: 11 How to pick a banker

36:12 – 41:33 Differences and clashes in culture

41:34 – 46:27 Setting up a deal framework

46:28 – 51:05 Facilitating good communication

51:06 – 52:22 Importance of prioritization

52:23 – 54:54 Lessons learned

M&A Science by Kison Patel (kison@dealroom.net)

DealRoom: Data Science and AI for M&A (www.dealroom.net)

In this interview, we touch on a range of topics from how Scott handles hurdles to post-closing surprises, deal disasters to integration management, and ultimately, the keys to running a successful process.

00:00 - 00:40 Intro

00:40 - 04:25 Scott’s corporate development background

04:25 - 06:36 Small vs large transactions

06:36 - 12:25 Diligence lessons learned

12:25 - 17:55 Walking away from deals

17:55 - 19:53 Post closing surprises

19:53 - 25:08 Bad deals

25:08 - 32:08 Post merger integration

32:08 - 36:26 Key lessons learned

M&A Science by Kison Patel (kison@dealroom.net)

DealRoom: Data Science and AI for M&A (www.dealroom.net)

Andrew Jordan is a Principal at Riveron Consulting where he provides transaction advisory services. He’s had his hand in mergers and acquisitions for the last 8 years and has incredible insight regarding quality of earnings (Q of E) and M&A deals.

Show Notes:

0:00 – 0:47 Summary of Andrew’s background

0:48 – 5:44 Advantages to sellers doing Quality of Earnings (Q of E) analysis

5:45 – 6:51 When to get buyers involved in process

6:52 – 9:51 Biggest challenge from financial accounting due diligence process

9:52 – 10:39 Particular strategies to overcome data challenges

10:40 – 19:19 Interesting and extreme expense item discoveries

19:20 – 25:38 Evaluating Q of E adjustments

25:39 – 26:30 How see diligence process evolving

26:31 – 27:27 Assuring proper controls, both in and outside of Q of E analysis

27:28 – 32:03 Key lessons learned

M&A Science by Kison Patel (kison@dealroom.net)

DealRoom: Data Science and AI for M&A (www.dealroom.net)