The Evidence on Acquisitions

I was looking at a potential acquisition recently and wanted to look at the research on factors for success. I searched for meta-analyses and systematic reviews to get an aggregated evaluation of the evidence. I found a good 2021 study on the topic by King, D., Wang, G., Samimi, M., & Cortes, F.

In short, while research claims plenty of drivers - the most important factors were the financial performance of the acquired firm and the acquiring firm prior to the transaction. Those that were performing well, continued to perform well post acquisition. This shouldn't be news to anyone in the search fund space.

While there are plenty of statistically significant drivers of success, most of them have effect sizes that are too small to be useful. Buy smart!

Original Article

TL:DR: In the end, there were 4 predictors that had effect sizes on performance measures that are worth considering:

The acquirer firm size is positively correlated with long-term market based performance (BHAR, beta = 0.40).

The prior performance of the target is positively correlated with post-acquisition accounting-based performance (beta = 0.34).

Acquisition experience is negatively correlated with long-term market based performance (BHAR, beta = -0.25).

The prior performance of the acquirer is positively correlated with post-acquisition accounting-based performance (beta = 0.23).

Plenty of owners and managers have opinions about what drives acquisition success. Some read the abstracts of studies relevant to the topic to understand what the researchers think. Few analyze the research to understand what the strength of these predictors really are - what I'm talking about is effect sizes.

As an anecdote, a medical doctor / research specialist I was speaking with shared this story:

"Imagine I could sell you a pill that was statistically proven to make you taller. Tens of thousands of subjects to create a statistically significant research result that indeed would make you taller. How much would you pay for the pill?

Now, if I told you that though it's statistically proven to make you taller, the effect was on average two millimeters of growth and 95% of patients experienced between one and three millimeters of growth. How much is it worth now?"

This anecdote sheds light on the often forgot about effect size. For any measurable effect, if we can collect enough data we may be able to find statistically significant correlations between variables. But that doesn't mean they're useful.

In M&A research - a lot of work has gone into determining what factors in an acquisition predict success. What even the best research tends to ignore is that the effect sizes of these predictors are small or non-existent, many to the point of complete uselessness.

Yet, there are some worth noting!

The Research

In a recent Meta-Analysis (King et. al, 2021), researchers examined 220 studies and found 16 significant predictors of different measures of acquisition success. Some of the measures where they found predictors were short-term stock market performance (CAR), long-term stock-market performance (BHAR), accounting measures (ROA, ROE, ROS), management self-assessment and innovativeness (# of new patents).

Yet, when looking at the predictors - most only predicted one or a few measures of success, and only at very low effect levels. After aggregating the measures of performance by category, only 12 predictors were left that had significant predictive ability. But even then, the effect sizes were small with few exceptions.

In the end, there were 4 predictors that had effect sizes on performance measures that are worth considering:

The acquirer firm size is positively correlated with long-term market based performance (BHAR, beta = 0.40).

The prior performance of the target is positively correlated with post-acquisition accounting-based performance (beta = 0.34).

Acquisition experience is negatively correlated with long-term market based performance (BHAR, beta = -0.25).

The prior performance of the acquirer is positively correlated with post-acquisition accounting-based performance (beta = 0.23).

Those effect sizes are still in the small-to-medium range, they're not huge but they're worth noting. While the research does associate some theories for each, we don't have causal explanations - but here are a few thoughts:

Market-based performance could be more about signaling than success. Large firms that are acquiring may be sending lots of positive signals to the market (item #1). But if the acquirer is making too many acquisitions it might be sending the message that it's core business is not succeeding (item #3).

Accounting based performance, the one I'm more biased towards, tends to be fairly consistent; we shouldn't be surprised by #2 and #4. Companies that are performing well before an acquisition tend to perform better after an acquisition. This could speak to countless structural, human, economic, and industry-specific factors that make some businesses better than others.

So the next time you hear someone say "X factor drives acquisition success", take it with a grain of salt. If you're interested in fundamental financial performance (accounting measures), pick targets that are successful and acquire from a solid performance footing.

King, D., Wang, G., Samimi, M., & Cortes, F###-###-#### A meta-analytic integration of acquisition performance prediction. Journal of Management Studies, 58(5): ###-###-####

If you want to reference my article, you can find it here: https://www.linkedin.com/pulse/predictors-ma-success-performance-scott-beaton