January 2019 Issue
Mergers and acquisitions (M&A) are complex and time-consuming endeavours. Companies seeking synergies that improve balance sheets and deliver increased shareholder value must be conscious of the risks and rewards present in every transaction. Often, M&A fails to meet expectations. An acquirer may know what it wants to achieve, but lack the tools, experience or know-how to accomplish its goals. According to a 2018 Grant Thornton survey, only 14 percent of respondents feel that M&A deals exceed their initial expectations for income or rate of return. These failures are often due to a lack of strategy or poor implementation.
A successful deal requires a thorough risk assessment and appropriate due diligence of the target’s financial position, its personnel and its cultural compatibility. Furthermore, the potential gains that can be accrued through a deal can quickly be lost if they are not reaped in time.
Until recently and still for the vast majority of M&A transactions, risk assessment and due diligence have been performed by small armies of advisers. However, experts can be costly and time consuming and tech solutions are enabling faster results. As such, companies are increasingly turning to technology solutions. Artificial intelligence (AI), for example, is being applied across the span of the M&A process, from identifying targets, through due diligence and into post-deal integration.
Another impact is on the use of transitional service agreements (TSAs), which may be phased out or potentially enhanced by digital technology. A TSA typically allows a buyer to arrange for the seller to provide infrastructure support, such as accounting, IT and HR, after the transaction closes for a defined period of time. Buyers often utilise TSAs if they do not have the management or systems in place to absorb the target from day one or if they want to wind down some existing services over a short period. But a TSA can impede synergies and generate higher operational costs while limiting buyer flexibility and increasing the acquirer’s dependency on the seller, at least for a short term. Technology solutions, such as ‘as a service’ or on demand arrangements and even automated solutions, including potentially, smart contracts on a blockchain, for example, could reduce costs and plug gaps, simplifying and accelerating the process of transferring companies, or units, via divestments in the future, thereby reducing reliance on TSAs.
Digitalising M&A will be a game-changer as new technologies upend existing processes and give rise to new skill sets. It will also enable companies to cope with challenging business environments, faster transaction speeds and surging data volume. All of these issues can delay or jeopardise an M&A process and increase the financial strain on buyers and sellers.
Digitalising M&A means giving companies access to new tools which can alleviate some of the stress of a deal and contribute to its success. It can help M&A teams perform various tasks throughout the due diligence, drafting, negotiation, signing and closing phases. Law firms, for example, may use cloud-based and other software solutions to store files in electronic client folders for initial review, to analyse documents for key issues identification, and due diligence report generation, and to track the progress of negotiations and agreements.
AI – the way forward
One area where AI may have the biggest impact is M&A due diligence. Typical deals require analysis of huge amounts of data in a relatively short period of time. AI can streamline this process. Virtual data rooms (VDRs), for example, may contain many thousands of documents that need to be evaluated by interested parties on the buy side.
“There has been an influx of digital tools recently, with many more soon to enter the market,” says Tom Maasland, a partner at Minter Ellison Rudd Watts. “While AI is the poster child, and a focus of significant investment, digital tools such as VDRs, eSigning, document automation and transaction management have been in use for some time – improving efficiency, if used effectively and reducing deal times and costs or enabling more activities to be done for the same costs. Tools like VDRs and deal management transaction tools allow deals to be transacted more smoothly, with less friction and less email correspondence. They reduce the need for document sharing on a linear basis, instead allowing for multiparty collaboration, with robust security and action tracking,” he adds.
AI has the potential to offer more efficient and accurate analysis than any human counterpart. “The use of AI and machine learning-enabled applications is the most prominent and most recent development in M&A,” says Markus Nauheim, a partner at Gibson Dunn. “It is being used, for example, to review and analyse commercial contracts and other documentation in the course of the due diligence process. In our experience, as of today, the current machine learning tools are a more sophisticated and smarter version of a conventional text-finding tool. The new tools provide a safety net for attorneys by identifying, highlighting and structuring certain pre-programmed contract provisions more quickly – for example, party names, date, change of control and termination provisions.
“There are estimates by consulting firms saying that 22 percent of the work of lawyers can be replaced by AI,” he adds. “Irrespective of whether this figure is accurate, AI already has and will have an increased impact on the costs associated with a transaction and will help dealmakers to further improve their efficiency. At the same time, more time and resources can be freed up that can be used to strike the best deal possible and thereby create value ideally for both sides.”
AI and Big Data can integrate quantitative analysis and investment data. It can be challenging to collate relevant information about a target company stored in disparate and potentially unknown locations, and virtually impossible to do so manually. Not only is there too much data, but human error may taint that data. Financial and timing concerns may also suggest this work should be handled by AI. Data can be automatically gathered, filtered and analysed in a fraction of the time it would take a human, or a team of humans. AI can search thousands of uploaded contracts across hundreds of data points, for example, and identify issues which may derail a transaction.
There are advantages to be gained on both the buy- and sell-sides of a deal, pre- and post-close. AI tools can assist with day-to-day contract analysis, while document automation and generation and smart contracts – for example on a blockchain platform – can assist with streamlining post-deal matters. This would further reduce the need for manual processes. Blockchain technology may be used to create a bespoke transaction, or even to design a marketplace where businesses can communicate their metrics and asking price to potential purchasers, anonymously and privately. It may also speed up the negotiation and due diligence phases. Though blockchain could disrupt the M&A process, it is unlikely to completely overhaul it; human interaction will still be required for certain elements of a deal, such as negotiations.
However, there are issues with the practical application of AI. “Products currently available are relatively immature,” suggests Mr Maasland. “AI tools, particularly those using deep learning, are currently complex to use and require significant training of both the user and the AI-engine which, for adopters expecting instant results, can be frustrating. Anecdotal evidence suggests many firms have signed up to headline LegalTech tools only for those tools to languish and be underutilised.”
In addition, legal issues surround the use of AI in M&A, which companies must be aware of in an increasingly regulated economy. Furthermore, companies utilising AI and machine learning must respect the target company’s intellectual property rights.
While digitalising M&A transactions does not guarantee success or value creation, it does free up staff and resources, redirecting them away from repetitive, labour-intensive work, and minimises the potential for error in the process. It has the potential to offer greater accuracy and allows teams to focus on the areas where a human touch creates more value, such as cultural integration and strategic decision making.
Impact on knowledge
Digitalising dealmaking is set to change working habits and may even ‘democratise’ M&A, taking transaction management out of the hands of experienced, highly skilled and knowledgeable professionals, and allowing less skilled or experienced parties to assume a key role during a transaction. Many companies undertake M&A transactions without a standard process or template. Digitalisation can address this by creating a digital playbook based on best practices.
The unwritten habits and norms that an M&A professional relies upon during a transaction may be digitalised and encoded into playbooks that can be digested and applied by employees. Clear tasks, deliverables, key performance indicators and documented best practices for defined deal phases could be set out, amended and updated in real time. This could allow management to run several projects simultaneously and track their progress. It would also reduce reliance on middle management. By using technology to disrupt knowledge work processes, dealmakers can increase efficiency by making it easier to define, execute and improve those processes.
Human vs. machine
Technology already plays a vital role in pre- and post-close integration. As stakeholders continue to demand improved returns from dealmaking, technology and the digitalisation of M&A will be a growing area of focus.
Companies must not forget the human aspects of dealmaking, however. “Like in every part of our daily life, M&A transactions will be assisted by more and more digital technology,” says Dr Nauheim. “But a successful M&A transaction is based on a commercial agreement among human beings and is subject to a complex framework of commercial, legal, financial, tax, technological, cultural, political, environmental and other aspects and requirements. While, from the perspective of legal counsel, the efficiency in understanding a target and the hours spent drafting the transaction documents may be reduced, M&A transactions will fail if they are not based on trust and mutual understanding among the people running the show.
“While AI can help to facilitate making informed decisions more efficiently, the successful completion of a deal requires complex legal, financial and tax assessments by the advisers and commercial and strategic decisions by the principals,” he continues. “These assessments and decisions will, for the foreseeable future, continue to depend on a ‘human touch’. This is not a headwind for and will certainly not stop further digitalisation, but will remain the reality of modern dealmaking as long as the decision makers still want to be the ones who actually make the decisions.”
Driving organisational change
M&A offers the chance for companies to deliver real change to their organisation during the post-close integration period. Legacy systems can be updated, data centres and other assets consolidated and new roles and practice areas defined. AI, machine learning and other forms of technology can help with this process.
Chief information officers (CIOs) have an important role to play in this process. Already, they are assuming greater responsibility during dealmaking, as M&A digitalisation gathers momentum. No longer are CIOs simply responsible for delivering and building technology solutions; today, they are a core part of a company’s approach to innovation and dealmaking. They are becoming far more involved in formulating a company’s deal strategy.
There are drawbacks to using more technology in M&A, however. Fear of job losses is ever present when a company is digitalising or automating facets of its operations. That said, M&A, would still require human input. It is a hugely complex process, with tendrils that touch many different departments. AI algorithms are not yet sophisticated enough to operate independent of human interaction. People are still required to label the data that will be fed to the algorithms. The ‘human-in-the-loop’ (HITL) model means people also correct any incorrect predictions made by AI, to improve the accuracy of future results. The cross-functional nature of M&A requires thought processes which are beyond current technology.
Though leveraging digital tools is no guarantee of success or increased deal value, it will make the M&A process smoother and allow companies to identify synergies and close deals quicker. Digital technology is set to remain a key tool for M&A teams in the due diligence, drafting, negotiation and closing phase of transactions. In the coming years, as these innovations become more sophisticated, the deal process will continue to evolve.
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