Despite the crazy world we find ourselves in today, life and business will go on. One key element of business is the ongoing activity in the Mergers & Acquisitions (M&A) space – the constant push and pull between shareholders and investors to find hidden value and commit to its long term extraction. Suddenly, the M&A space came to just about a complete stop in Q2 of 2020. With everyone in lockdown, deal teams have placed their activities on hold, if not cancelling them altogether. The definition of value and risk is facing a whole new reality in the world with Covid-19. This requires deep introspection for buyer and seller as we go forward.
Yet, as we get back to some form of a new normal, business M&A activity is picking-up. For some, the urgency of a transaction has become a much more critical factor than before. Deals are urgent as over-leveraged companies find themselves exposed by the pandemic and deal-seekers with cash are on the hunt for a bargain buy. But how should an organisation or savvy investor go about carrying out a due diligence assessment on a modern data-driven organisation? And how can this be done quickly and effectively?
- Business Dynamic
“You walk into a business and right away you can feel the dynamic” says Terence Nickolls, seasoned M&A specialist and CEO at Viatek group. “But times have changed. Although that dynamic is still very important, you cannot make ‘seat-of-the-pants’ decisions about a transaction. You need to delve deep into the data. You need to verify the bona fides of the company and delve deep into analytics to support the valuation”.
Today’s M&A transaction teams are required to check off various items on their due diligence (DD) checklist and information sources are becoming ever more distributed, complex, and intangible. This drives the need for experienced M&A practitioners to augment their expertise with technology that can assist with DD processes.
Collectively, the modern pre-deal team must be equipped with a disciplined approach following through on financial information, process analysis, field analysis and comprehensive data analysis.
“We’ll still see spot deals; the handshake over a table ‘all is done-and-dusted’ in a nick of time. We like those deals too. But there will be polarisation. We’ll see a shift to significant DD processes delving deep into company data. They need the technology to support their expertise”, says Nickolls.
- Manpower is No Luxury
Listed entities, banks, investment firms, pension funds, etc all have comprehensive processes for DD processes. Following the significant impact of the pandemic, deal teams no longer have access to large numbers of junior analysts to work through the bulk of seller/buyer data. Capacity is no longer available or the transaction simply cannot afford the time and cost required from such teams. Clients will no longer be paying for scores of junior analysts to build evaluation reports following cumbersome documentation reviews. Value drivers are necessary at every step of the process. The responsibility therefore shifts to those more experienced, supported by technology to discover and analyse the data critical to the business valuation.
“One has to appreciate the granularity of the information that is required for a DD process” says Steve Ackland, CEO of Aim Ltd. His company has developed dataBelt®, a specialised software system that supports data governance, cleansing and valuation for operational compliance and M&A activity. “We can expect that deals will take longer; there could even be a higher drop-out rate! Simply because smaller teams will need to work through much more information in pre-deal activity. We can already see the shift to using technology to support these processes”.
This carries through to post-deal integration. The better you understand what you are buying, the better your integration plans and better you can monitor subsequent progress and success.
- PP&E vs Data
Historically, business valuation was largely informed by the sales book and balance sheet. What captured one’s attention on the balance sheet, other than cash and receivables, was plant, property, and equipment. “This is no longer enough” says Matt Smith, M&A Technology and dataBelt specialist at AIM Ltd. “If we buy Facebook, there is not much in terms of brick-and-mortar. The value lies in the data. Customer information, digital processes and brand value now take centre stage”. These are intangibles and they require a different approach in valuations.
As an example, AIM demonstrated how their data crawler technology answered critical questions in a specific use case relating to customer sentiment. Using machine learning (ML) and optical character recognition (OCR), they informed the buyer’s M&A team about the true brand value, far beyond the feedback that annual feedback surveys can provide. In this use case customer surveys were in use, but the response rate was about 5%; more-or-less within the typical range for most companies. Yet the company had access to an extensive source of data in their CRM system, including customer engagements, customer letters, queries, voice calls, etc. “We could use the AI (artificial intelligence) to scan these records and look deep into the quality of their customer interactions. We could assess the true customer sentiment from these various data sources”. The analysis helped to create a net promotor score that proved to be a strong foundation for a revised brand valuation.
- Data Compliance
There are other considerations for M&A teams when it comes to digital analysis. With modern data privacy and protection laws such as General Data Protection Regulations (GDPR) in the European Union (EU) and Protection of Personal Information Act (POPIA) in South Africa, data governance and compliance are also DD checklist items of critical concern. Moreover, the strength of the digital infrastructure, data location and data quality management, as well as cybersecurity, all require critical analysis in the DD process. “It will probably not have a significant impact on the deal valuation,” says Rob Heaton, an M&A Expert from PMI Partners, “but it will determine if the deal goes ahead. No buyer wants to find out that a major cyber breach or penalty for non-compliance will be hitting them down the line. This is the sort of thing that you have covered in pre-deal analysis. You either have a plan or get out.”
Using dataBelt® for compliance assessment is one of the system’s core applications. dataBelt®’s Keras TensorFlow technology is used to discover images, audio and video files stored in any accessible location throughout a company’s data infrastructure. The software is employed to locate and classify files based on the analysis of textual information and image types. Non-compliant data can then be flagged for further attention. A number of models are used to train dataBelt® so that image, audio, and video identification can be done quickly and accurately. A dashboard provides management with constant oversight of how data compliance ebbs and flows throughout the organisation. Having this insight, pre-deal seller teams can proactively initiate clean-up activities to give momentum to buyer DD activities, thus smoothing the process. Such pre-deal de-risking will accelerate a transaction, perhaps even adding a cash value for the seller.
- M&A Skills
With this advance of technology, do we find a skills gap?
“Let’s rather see it as a ‘skills opportunity’”, says Rob Heaton. “We can expect that the classic analyst will be expected to shift capacity more towards strategic insights that are of value to the client”. Technology will deliver the information and analysis at speeds that even large deal teams could not replicate. “We can expect that the skills that will continue to be in demand are those who have a comprehensive understanding of the industry, i.e. how the business integrates into this ecosystem. There is probably a shortage here. It requires experience”, says Heaton.
It is clear that M&A team will have to augment their core skills with technology. These systems must be supported by experts that can attend to the data mining and analyses in pre- and post-deal activities. Expanding their ecosystem of skill sources will enable M&A experts to efficiently apply their capacity and capability where it matters most to the client.
- Mining Data
What can a seller do to support its M&A process? Well, a good point of focus would be to clarify the sources of data and how each will be relevant in the DD programme. Often, data is distributed across various disconnected sources. This is where dataBelt® can collate disparate data sets and display results/analyses to the user an a single accessible interface – the often sought after “single pane of glass”. For example: a company might have more than one legacy CRM system and requires consolidation and clean-up activities such as removing duplications, inactive customers, linking sales data, etc to be carried out. Such data sources can be cleansed and transformed very effectively with dataBelt®. This benefit will of course extend to the buyer who will later need to consolidate all systems in post-deal integration activities.
Next, a compliance status assessment of these data sources is essential. By using OCR and ML, dataBelt® will find personal information such as passport scans, sensitive company documentation such as intellectual property, contracts, etc. It will even find images and videos with sensitive content. So, you want to find the photos of that embarrassing office party 10 years ago? Yes, that’s possible too.
- Digital Valuation
The final step is the valuation of the data. dataBelt® does not only provide a static report, but can dynamically monitor the flow of data in an organisation. Combined with historical data analysis, the opportunity exists for deep analysis of data consumers, the quality of the data and how the data impacts and drives the value in the business.
We can see that modern businesses need to look deep into their digital assets. This becomes even more critical when divestment is planned. Although the intrinsic value of assets such as servers, computers, networks, and process control systems already amounts to significant numbers, the real opportunity to assess value (or downside risk) will be extracted from the intangibles.
So, if you are planning a sale or acquisition, make sure your DD team has access to the right skills and tools to make the processes efficient and derive value for the transaction stakeholders. Having dataBelt® on your side, this value can continue for the life of the business, even if that low-ball offer is not accepted.
Johan Louw is the founder of Aguru Business Solutions. We empower clients in industrial processing and manufacturing industries with differentiating strategies to plan and deliver automation and digitalisation solutions that drive efficiencies and improve asset value.
Aguru Business Solutions is the authorised representative in Southern Africa of dataBelt® – Aim’s Data Governance and GDPR Cloud Software Platform.
Aguru Business Solutions