In Australia, a total of 436 merger and acquisition (M&A) deals, amounting in $85.3 billion, were announced in 2016.
This doesn’t, however, tell the full story of the deals that never get closed, nor of those that go on to fail in the first few years.
According to the Harvard Business Review, 70 to 90 percent of M&As fail.
Technology has the ability to help mitigate these potential failures by reducing the time, cost, emotions and risk associated with making complex M&A decisions with important implications.
Prescriptive analytics is one such emerging technology. It allows companies to understand the implications of a deal from all angles, before and during the decision-making process.
By merging fact and expert opinions, prescriptive analytics transforms every ‘input’ into a data point.
These data points can then be objectively analysed, used to predict outcomes, and suggest the course of action that is most likely to lead to success.
Prescriptive analytics gives organisations the ability to improve decision-making processes.
Bias
The current M&A process involves an exceptional amount of due diligence by executives and advisers.
Notwithstanding their hard work, people invariably miss things by approaching a large number of issues through their own biases.
Prescriptive analytics, using techniques such as analysis of competing hypotheses (ACH), safeguards against the unconscious fitting of evidence to support bias.
By mitigating the impact of this unavoidable bias and trust in ‘gut feels’, prescriptive analytics allows valuable insights to be analysed and transformed into potential value during the due diligence process.
Fitting evidence to one’s own views or those that align with the ‘groupthink’ is known as confirmation bias.
The person unknowingly ignores evidence that contradicts their own pre-conceived notions or takes into account only that which fits within their own frame of reference. It’s not that the numbers are wrong, it’s that decisions will only be based on numbers that back up a ‘gut feel’.
Company culture is a good example where confirmation bias can colour decision making.
Information gathered on two companies’ cultures before a deal is largely qualitative and subjective.
It can be hard to predict how different teams will react when thrown together, and individual biases are inevitably present. Recognising that this information is based on opinions, and acknowledging it as such, is half the battle.
A McKinsey study showed that when organisations worked at reducing bias in their decision-making processes, they achieved returns up to 7 percentage points higher than those businesses that didn’t consciously safeguard against biases.
According to cognitive psychologist Gary Klein, decision makers looking to achieve this need to instead take the ‘gut feeling’ as an important data point, and consciously and deliberately evaluate it.
This is what prescriptive analytics has the ability to.
Regulation
Making sure that all the i’s are dotted and the t’s are crossed from a regulation standpoint is a major part of any merger or acquisition.
This typically requires a lot of time from lawyers, accountants, auditors, and other professionals, and is heavily process and data-driven.
Technology has been used to disrupt other sectors that were previously dominated by time and process-driven tasks.
Regulation is the next frontier to be disrupted by technology. The potential applications and resultant benefits of ‘RegTech’ in the M&A space are numerous.
For example, businesses need to foresee potential regulatory issues when planning a takeover or merger, and analyse the risk these present.
These can include a target company’s compliance history, along with competition, tax and security regulations.
Significant time and money is lost in mergers and acquisitions due to regulatory risk analysis during due diligence.
For example, Treasurer Scott Morrison recently blocked the sale of AusGrid to the Chinese government-owned State Grid Corp citing national security risks that were overlooked due to poor regulatory due diligence.
Technology is able to store, manage and analyse considerably more issues than humans.
Prescriptive analytics predicts how many of these regulatory issues will affect each other, providing greater insight to enhance human oversight of crucial regulatory information during due diligence.
As well as improving accuracy levels, this will free-up more time for executives and advisers to focus on the other material aspects of the offer.
When the dust settles on a big deal, organisations are often left wondering why it failed or succeeded.
By turning both qualitative opinions and quantitative factors into data points, prescriptive analytics technology provides an audit trail that allows organisations to retrospectively assess why they made the decisions they made and clearly understand what factors led to the outcome.
The ability for prescriptive analytics to provide a more accurate evaluation of material available to inform an M&A decision improves the likelihood of success whilst reducing the investment of time needed to achieve this success.
Prescriptive analytics addresses uncertainty in the due diligence phase, whether that be around unconscious bias, culture or compliance.
It achieves this by providing predictions that allow organisations to make evidence-based decisions that are a balanced combination of opinion, data and external influencing factors – all of which is evidence after all.
Elizabeth Whitelock is the chief executive officer of Veriluma.
