The Mergers and Acquisition Puzzle and the Importance of Data Due Diligence

One of the persistent puzzles surrounding mergers and acquisitions (“M&A”) activity is its propensity for failure. In fact, hundreds of studies suggest that fifty to eighty percent ofmergers and acquisitions are failures. Thus, while the goal of an M&A deal is that the whole is worth more than the party, the converse is frequently true. An important determinant of any M&A transaction’s post integration success is data due diligence. In today’s M&A environment, where transaction experience substantial scrutiny and technology plays a crucial role, data due diligence is tantamount.

Nonetheless, merging or acquiring companies often fail to perform adequate data due diligence and fail to consider the electronically stored information (“ESI”) and data storage systems of the target company or merging counterpart. This oversight presents substantial risks and can cause substantial post-integration problem and, in turn, increase the likelihood of M&A failure.

Creating an E-Discovery Checklist

One of the crucial ways that in-house and outside counsel can fail to conduct proper data due diligence is by ignoring potential eDiscovery issues as part of the M&A deal.

Why is this important?

eDiscovery issues may well affect the value of the company being acquired, the cost and difficulty of merging the two companies, or heighten litigation risk going forward. Corporations and law firms have fine-tuned due diligence checklists to account for various traditional business risks such as legal, contractual, regulatory, securities, financial and undisclosed liabilities, yet eDiscovery is noticeably absent.

This failure of counsel to conduct data due diligence on a target company’s e-discovery issues, e.g. preservation and cost obligations regarding its ESI, can cause substantial losses for the acquiring company, impacting the expected return.

An e-discovery checklist could have many elements and would vary with respect to the industry and company, but regardless, it should account for:

1. The state of the target company’s ESI, ensuring that it has been thoroughly identified, categorized, and sourced;
2. Existing preservation and litigation holds;
3. The cost of preserving data for existing or anticipated legal holds;
4. and Both structured and unstructured data

I would like to hear your comments on this checklist, including additions. More thoughts on M&A coming in future posts.

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The Power of Similarity

Digital Reef provides technology that I call a similarity engine.  The similarity concept within search is a powerful one – the ability to determine both exact duplicates and near duplicate content.  And being able to set the level of similarity – whether it is 10% or 90% similar – provides a great deal of utility for the users.   Additionally, finding similarity between different types of content – for example, a Word document and a PDF can be critically important.  Or perhaps there is a table embedded in a presentation and that same table is in an Excel spreadsheet.  Someone could have cut and pasted text from a document and put it in an email. 

Finding exact duplicates can be useful but add to this near duplicates and there is potentially even greater implications.  Near duplicates allow you to find the same content in different types of files.  Perhaps you can find different revisions of the same document.  There may be information from a document that has been quoted, cut and pasted, and used within any number of other documents. 

The practical use of similarity is important – above and beyond the casual quest for content or information for which people often use general purpose and consumer search tools – there is real “utility”  that can have implications to your business.  One such utility is day-to-day work flow – getting better use and productivity out of the content already created within your company.  Similarity can help with performing research that has a wide range of applicability – medical, legal, science, consumer, business, technology, etc.  There is a concept that I call content mining (more on this in my next blog) that could be enabled by similarity technology.  And probably the greatest driver for using similarity technology in today’s environment  is for e-Discovery.  As my fellow blogger – Daniel Garrie astutely points out – “The onslaught that is sure to come–companies large and small are going to be under legal siege in 2009. Whether it is white collar crime, bankruptcy or wrongful termination, we’ll see surges maybe even a Tsunami of new lawsuits.”

Similarity technology is different from a search engine throwing anything and everything at you based on a keyword.  Rather, it is sophisticated technology with intelligent algorithms that scan content and analyzes similarity based on ratios that are user defined.  Additionally, it will present back to you the level of similarity – 100%, 95%, 70%, 60%, and so on.

I believe that Digital Reef’s similarity technology can elevate and accelerate the access of critical data within the enterprise.  It is extremely valuable and unique technology – in fact – I don’t know of anything similar.

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My Digital Reef Inaugural Blog

I’m a senior consultant and founder for the INI Group and am working very closely with Digital Reef as a consultant, advisor and blogger. I’ve been in the high tech industry for over 23 years with a focus on the data management and storage arena and you can find out more about me at www.contemplatingIT.com. I believe Digital Reef has brought to the table an extremely impressive solution at a critical time when our unstructured data content is growing to massive levels.

In addition to being and advisor and consultant for Digital Reef – I’m going to be blogging for them on a regular basis discussing a wide range of topic areas from business issues, compelling technology, market dynamics and visions going forward.

Who and what is Digital Reef? They are a startup – an emerging vendor – that came to right conclusion that Enterprise search is woefully inadequate on multiple levels – the mechanics of making it work efficiently and intelligently in environments with massive amounts of content; and the ability to get relevant data to the user rapidly and without drowning them with irrelevant results.

I describe the Digital Reef solution as a data and content management platform leveraging intelligent and scalable search and indexing technologies. Digital Reef provides appliances with a grid architecture that ingests and indexes massive amounts of content spread across heterogeneous storage throughout the Enterprise creating a global federated index. Some of the biggest challenges with indexing include scalability, transparency and true global federation – and Digital Reef solves all three.

Once you have all of your unstructured data indexed – what are you going to do with it? Another big challenge with management of unstructured data is making order out of chaos. If you just use keyword searches there will be a large number of irrelevant returns that obscure what you really need.

The problem with keywords is that there is very little useful context. Digital Reef’s magic ingredient is its similarity engine – the ability to analyze content including documents, email threads and terms and return to you results based on a user defined similarity ratio. Digital Reef’s similarity engine is sophisticated technology that not only uses keywords but the associations of terms and the context in which they are used within unstructured data – providing relevant results.

Companies are frustrated because information is really three dimensional but we are using two dimensional tools to access and manage them. The first step is to implement solutions that provide us rapid access to relevant data for reactive purposes such as a discovery process, audits, research, customer support, projects, etc. However, think of the potential of really using information to also build revenue generating products and services leveraging existing intellectual property. The potential is compelling and landscape changing.

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