Robotic process automation and cognitive intelligence in M&A
November 2018 | TALKINGPOINT | MERGERS & ACQUISITIONS
Financier Worldwide Magazine
November 2018 Issue
FW moderates a discussion on robotic process automation and cognitive intelligence in M&A between Mark Steele, Paul Leather and Mo Habbas at Deloitte.
FW: Could you provide an overview of the increasing role played by cognitive intelligence (CI) and robotic process automation (RPA) in M&A processes? To what extent are you seeing increased utilisation of these tools?
Leather: The main use cases of CI or robotics are to analyse a lot of disparate data quickly and try to decide on what is important and might warrant further investigation. This is clearly relevant to M&A, where clarity of insight and presentation in short timescales is key to a successful outcome. The use of process automation also opens external datasets that might have been unwieldy or inaccessible without these tools, and that opens up an arena to use technology to do things like market sensing, and identify investment opportunities.
Steele: CI and analytics are now increasingly used in the M&A arena for sensing market opportunities, undertaking due diligence and in rapidly realising deal benefits. Scraping tools and fuzzy matching are being used by organisations to better identify deal indicators from potential sellers while enhancements in benchmarking, analytics and more dynamic and interactive reporting are used throughout the diligence process.
Habbas: We have seen an increase in the use of these tools in creating value post-deal. In particular, RPA is being used by some private equity backed parties, particularly in the business outsourcing sector, to increase productivity and to save costs. A key challenge for these businesses has been to drive change in underlying processes and to organise people in a way that allows them to implement RPA automation. This has led to significant organisational changes being driven by management. Given the expected improvements in profitability as a result of automation and RPA, they have been identified as strategic value drivers for these businesses.
FW: What are the main advantages that CI and RPA, when utilised properly, bring to the M&A arena?
Habbas: In our experience, the successful use of CI and RPA helps free up time across critical functions in the business, whether it is finance or operations. This time can either be used to focus on more value-adding tasks or it can provide the business with the opportunity to downsize the headcount in some areas, ultimately reducing its cost base.
Leather: M&A analytics capabilities have evolved naturally from the use of increasing CI. As well as better quality analysis, speed of information and better communication, analytical tools can tell you what is statistically important and remove bias, and challenge the practitioner as to whether their personal intuition and experience is giving them the right answers.
Steele: CI and RPA have helped improve the quality and comprehensiveness of deal analysis, with both RPA and the wider application of CI helping to analyse far greater amounts of information and provide far richer advice and insight for businesses than has been possible previously, through the use of benchmarking and Big Data analysis. It is also clear that sellers are promoting CI and RPA as a key competitive advantage in the businesses they are taking to market, with organisations highlighting the efficiency delivered through these technologies.
FW: In your experience, are there any potential pitfalls associated with using – or misusing – CI and RPA? What mistakes do acquirers need to avoid in their application?
Steele: The key challenges are that for all the use of technology in this area, it only provides you with information and not certainty. The risk is that CI and RPA may be disconnected from the process by experienced practitioners who understand their industry and the environment over which the CI is being applied. Understanding the data captured and analysed, and the context to which the analysis is applied, minimises the impact of statistical or analytics anomalies.
Leather: The main challenge is that M&A processes have some common themes, but are still bespoke. Therefore, any application of analytics has to be focused on giving the right outputs, and connecting analytics, insight and experience becomes very important. Analytics and having technical capability will never give you the answer on its own; it supports decision making by giving you a greater ability to analyse more data when trying to inform certain decisions and a greater ability to present the answer more clearly to help with that decision making. Therefore the main risk becomes false positives and over-promising where data cannot tell you the answer. That also applies to constructing the right team. Buying in data analytics capability is a small piece of the puzzle – blending that with the right experience and domain knowledge is the critical success factor.
FW: What considerations should acquirers make when evaluating potential CI and RPA solutions to meet their particular needs?
Habbas: Consideration should be given to the suitability and likely adoption rate of these solutions. People often find it challenging to adapt to new technologies and ways of working, which may mean that the business does not realise the full benefit potential of those solutions. Having a good understanding of the underlying processes and workflows that will be impacted by the technology is therefore a critical prerequisite.
Leather: Consider how you are enhancing your IP through implementing these solutions. This should help you focus on the difference between the application of knowledge and pure technology solutions, and how you retain and enhance your own enterprise’s IP and the value you can bring to a customer as an organisation. There is a wealth of models and algorithms available as open source code on the internet, along with many paid-for third-party providers, but all of this is rather inert until you have locked down what you plan to use it for.
Steele: While many technologies provide similar functionality and capabilities, it is important to also consider the infrastructure and architecture implications, with user access, cyber security and data protection becoming increasingly critical if regulatory and reputational risks are to be minimised. Data leakage can have commercial and legal implications which should not be ignored.
FW: How important is to have the right people involved, to get the most out of these technologies? What knowledge and skills are required?
Leather: What innovation through analytics is really about is investing in the future IP of a business. The challenge is that the technical platform has to be reusable. If you have to recreate it every time you work on a deal, it becomes unwieldy and does not help transfer knowledge and capability from one deal to the next. If success is a blend of analytics capability, technical architecture and domain knowledge, then investing in people and then improving how they share knowledge becomes crucial.
Steele: To get the best out of these technologies, it is important to be able to bring together the skills of data scientists, subject matter experts and practitioners, technology architects and the end users, in order to deliver the most effective and user-friendly solution. Having clarity around the use case for CI and RPA is critical, along with ensuring the technologies deliver, rather than ‘delivering a near miss’ for what people need.
Habbas: In order to operationalise and benefit from RPA and CI solutions, it is critical to have team members who understand how these solutions work, including their limitations, and are able to articulate that to the business in a simple way. If these solutions are implemented in a silo through an IT or technology department, without sufficient buy-in from the business’ operations, they are unlikely to result in the expected benefits.
FW: Looking ahead, do you believe these technologies are set to have an increasing impact on future M&A transactions? What long-term trends and developments do you expect to see in this area?
Steele: In all areas of the end-to-end M&A lifecycle, technology is increasingly being seen and used to support M&A activity, from identifying the assets that may be appropriate to acquire, to doing the deal. Long-term diligence will increasingly become digitalised with less use of MS Word and PowerPoint and more use of analytics and cloud technologies. In addition, technology will increasingly see inter-organisation teams using and working on the same data and using the same technologies at the same time, creating a faster and more real-time interactive discussion as part of the deal-making process.
Leather: These technologies will undoubtedly have an increasing impact on future transactions, more because of customer expectations than anything else. Dealmakers want to see process efficiency, increased benchmarking versus the market and risk analysis that helps them plan and execute transactions. Early, large-scale analytics is required to identify issues and helps to focus due diligence in the right areas, and web-scraping and interpretation of unstructured data through RPA and CI is required to harness the information assets needed to place a business in its external context.
FW: Considering the investment in analytics that most businesses are making in the current climate, how do they get to the future vision, embracing CI and RPA, from where they are now? What is the medium-term outlook and roadmap for analytics through to CI and RPA?
Leather: Medium-term success is driven by what you decide to buy and what you decide to build yourself. Leaders will shape the market and others will follow and challenge based on evaluating the leaders’ success.
Habbas: Embracing these technologies requires a business to get the quality of its data and processes to a level where the full benefits of automation can be experienced. Therefore, in the medium term, businesses should focus on streamlining their operations, processes and data in a way that makes them fit in order to benefit from RPA and CI in the long term.
Steele: The medium-term will see a continued development of the CI and RPA tools and technologies, but it will also see an increase in the use of proprietary tools and a greater reliance on point solution tools. It will also see a significant increase in intellectual property and patents for some technologies being developed, resulting in licensing and an increase in organisations buying data insights as well as buying advisers’ time.
Mark Steele is head of technology for Deloitte’s deals practice, leading clients and Deloitte’s own approach to technology in the deals arena. He works in the digital, data and analytics arena supporting parties in acquiring and optimising the use of technology commercially. He can be contacted on +44 (0)20 7303 5393 or by email: email@example.com.
With a background in retail operations, data analytics and financial due diligence, Paul Leather leads Deloitte’s Transaction Services Analytics team, a team of data scientists who deliver a wide range of visualisation, automation and analytics insights that transform the M&A experience. He is also the Global Product Owner for iDeal – Deloitte’s global analytics and automation platform. He can be contacted on +44 (0)161 455 6738 or by email: firstname.lastname@example.org.
Mo Habbas heads Deloitte’s Value Creation Services team in the UK. His focus is value creation planning and implementation for private equity acquisition targets and portfolio companies. His experience in value creation covers rapid diagnostics, large and complex transformations and cost reduction programmes. He can be contacted on +44 (0)20 7007 1515 or by email: email@example.com.
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