Reimagining Law - The automated M&A deal?

Summary:

• Commoditised legal work has been unbundled, re-packaged and re-assigned between in-house, alternative legal service (new law) providers (ASLPs) and traditional law firms.  Commercial contracting is one example.
• M&A is ripe for the same process of commoditisation, unbundling and re-packaging but it is early days.
• Much of an M&A deal can be automated in some way and the technology is improving.  Alongside existing automation tools, AI and robotic process automation (RPA) offers much. This will reduce the need for manpower.  Manpower can also be flexibly sourced.  
• It will therefore become possible for some companies to design a process and technology framework that allows M&A to be executed wholly or mainly in-house with certain parts outsourced to new law and traditional law firms.
• The smart law providers will preempt this by providing winning and scalable solutions.
  

The problem

I was speaking to an old colleague recently who left our alumni firm to take an M&A role in a major software company.  We discussed the extent technology could automate an M&A deal and whether teams like his could execute M&A deals without outside counsel.  The benefits could include more control, a more standardised execution, better use of data and less cost.  Weighed against this is the cost and time involved in setting up the framework, processes and technology and the loss of specialised expertise.

Some companies do have M&A teams buy and sell businesses without outside advisors.  They are large, well resourced serial ‘deal doers’ and the exceptions to the rule.  

Of course the problem is not who does the work but how the work is being done.

The solution

We now have a real opportunity to strip down M&A, apply better processes overall and standardisation and automation where possible, capture data and completely redesign resourcing.

Take a case of a large technology company who is a serial buyer of small cloud native digital businesses.  What steps could it take to standardise and automate its M&A? 

Step 1 - unbundle the M&A deal and understand potential linkages 

The diagram below illustrates some of the key work packages and linkages.

Step 2 - Create modules and template processes

Each work package can be templated and then adapted to the needs of each deal.  For example, a template set of Management Q&A and workflow.  Initial Q&A - recorded zoom interview - follow-up questions.

Step 3 - Choose a technology platform to host the deal

In this step, we chose a technology platform that can host or access all of the information and data needed for the deal (seller’s due diligence documents, transaction structure and data, all reports and deal documents).  The platform has APIs into other platforms (such as some data in the Seller’s CRM such as Salesforce or contracts in the seller’s shared drive).  The platform has collaboration and permissioning capabilities so all parties can share data and negotiate the deal without email.  The APIs allow the ‘single source of truth about the deal’ to be analysed and transferred to the buyer’s systems.

Platforms like the Docyard (https://www.thedocyard.co), TR’s High Q (https://legal.thomsonreuters.com/en/products/highq), Littera’s Transact (https://www.litera.com/products/legal/transaction-management) and Legatics (https://www.legatics.com) already offer this or are moving that way.  

Step 4  - Introduce apps or ‘point solutions’ which could be integrated with the basic platform and which facilitate automation (see Step 4).

The customer has the choice of using features in the basic platform and integrating potentially superior point solutions.  With APIs and common data standards, this will become increasingly easy.

So for example, the customer might introduce StructureFlow (https://www.structureflow.co) which has great transaction structuring, visualisation and data capture capabilities.  

Or the customer might introduce AI guided contract review technology such as Lexical Labs (https://www.lexicallabs.com) for the diligence.

Or a contract creation tool to draft the SPA and other documents based on a questionnaire.  E-signature.  Its an already exciting and expanding list.

Step 5 - Accelerate automation over time

There are already a number of easy wins for automation. For example:

• Automated extraction of data from the target’s systems - sales, financial and legal data
  

• Automated document extraction and triaging for diligence.  Document data can be extracted, refined and filtered by basic NLP based technology.  You ask the question - show me all of the sales contracts valued annually above $100,000.  
  

• Cloud recording and automated transcripts for management interviews
  

• SPA and contract creation - Systems like Avokka allow the user to create contracts using a simple questionnaire.  
  

• Core deal terms - Office and Dragons have a really cool feature which allows all of the core deal terms to be centrally captured and automated deployed and updated across all documents.  
  

• Commenting, redlining and negotiation using ‘google docs’ style web-documents - Contract One is one example.  Avokka also. 
  

• Conditions precedent and signing and completion processes - Systems like Legatics automate the process of signing and completion.
  

• Who isn’t using e-signature today? 
  

Law firms are already using the technology above to some degree.  But knitted together into a common deal platform, common data standards and processes and when combined with the power of NLP, machine learning and RPA, the potential automation gains are vast.

Automation is a flexible process.  On introduction, it sometimes takes on a human task entirely (for example data sharing) whereas other times it speeds-up the user (for example the contract creation example).   The degree of automation can be accelerated over time, particularly by RPA.  

Predictions for the future

In the next 3 years we can expect to see:

• Improvements in AI guided document review for diligence - reviewers will get automated reports summarising key contract information and red flags.  Reviewers can ask intelligent questions of the portfolio - which contracts have ‘change in control’ restrictions?
  

• Automated extraction of sales data and revenue which is transferred to an online ‘expert system’ which analyses merger issues and produces a list of merger clearances.
  

• Similarly an automated extraction of all regulatory licenses of the target and online analysis of any gaps.
  

• Online assessment of the validity of key IP and identifying key gaps.
  

• Use of ISO type audits or online assessments of data and privacy compliance and governance
  

• Automatic detection of litigation and potential litigation from - sending data to the lawyer looking at litigation risks.
  

• A dynamic term sheet agreed in the system which automatically instructs the contract creation system to draft the SPA and other documents. Any changes to the deal terms are just applied to the dynamic term sheet and documents automatically updated.
  

• Introduction of AI guided contract review technology from the likes of Lexical Labs to help the parties compare contracts against digital playbooks  - for example understanding the other party’s redline and suggesting fallback positions.  
  

• RPA and machine learning will begin to accelerate automation and bridge the gaps between the work packages - for example checking a CP document and automatically releasing completion monies from escrow or transferring data from the deal platform into the buyer’s enterprise software.
  

• Basic analytics which help improve future M&A deals - time spent on certain tasks, refining fall-back positions and improving processes.
  

• Insurance products will begin to expand beyond the currently available ‘reps and warranty’ insurance as a way of filling risk gaps.
  

Longer term - the process and technology improvements will accelerate to the point that today’s M&A will look unrecognisable.  That won’t mean that M&A becomes easier; far from it.  The amount of data analysis, both in virtual data rooms and externally, will increase exponentially.  The fracturing and increasing complexity of global regulation, trade and antitrust will require more not less regulatory input.  

Conclusion

These process and technology improvements will empower companies to choose how to execute and resource their deals.  To maximise this potential, a serial M&A acquirer or seller would need some M&A ‘blueprints’, developed in collaboration with its service providers.  These would address 3 scenarios:

1. The company runs all or the vast majority of a deal internally;
2. The company largely runs the deal internally but bundles certain packages to service providers
3. The company outsources most of the deal.    
   

The blueprint would define all of the resourcing, process and technology internally in each scenario. It would also mandate specific processes and technology to external service providers but mainly it would set expectations.  For example, requiring automatic transfer of data into its systems from the deal. Law firms and ASLPs would innovate to meet these expectations.   

Using these blueprints, companies achieve common standards and outcomes whilst choosing the best approach for each deal.  For example, it may largely run the deal itself but have antitrust, regulatory, IP and litigation matters may be handled by an outsider using the technology.  Perhaps, they hire one experienced deal lawyer and a paralegal through an ASLP to run the document negotiation and closing.  Or a law firm still runs the process with a smaller team than traditionally the case under a fixed fee arrangement and enabled by technology.

It will be a better world for all.