Leveraging social media data analytics to improve M&A – Lexology Reply

Social media part 3: leveraging social media data analytics to improve M&A – Lexology.

Data Analytics for M&AThere is no question that social media has a role to play in M&A activity.  In a recent survey by Toronto based international law firm Fasken Martineau; respondents reported that they were not only using social media to communicate deals but also for research and due diligence .

  • 36%  for research.
  • 48% for investigation.
  • 72% like LinkedIn to research personalities.  Only 50% said the same of Facebook.
  • 78% disclose transactions through Facebook and 44% use LinkedIn.

More importantly

  • 77% said they have no social media strategy, and
  • 65% said they have no intention of developing one.


There are 2 benefits of social media: (i) expert opinion, and (ii) trending sentiment.  Much of the hype behind the trends in Big Data are about connecting these 2 powerful elements with the hard numbers around corporate valuations.  For instance, an acquirer may wish balance valuations with the trending market sentiment and the opinions of experts.  An extreme example of this is the Facebook IPO where market hype vastly outweighed traditional valuations.  So much so that Warren Buffet said that he had no idea how the valuation was so high and that he just couldn’t value companies like this.  Social media is often seen as an echo chamber; a small community talking to itself.  Posts range from  self-aggrandisement to advertising puffery with very few hard facts and figures in between.  What few figures are there may be real, may be fictional or may be somewhere in between.  The value is in aggregating these figures but the algorithms needed to ensure that the right weighting is placed against the right number based on author, time etc (let alone how they account for hearsay).  the maths behind this is hard enough let alone the semantic interpretation by computers.  Needless to say, when this sort of calculating can be done it will be worthwhile for many and will be, initially, a very, very expensive service.

The moral of the story is  – BEWARE!

Social media remains useful for advertising and developing an extended network of sector contacts in order to deepen one’s contextual market knowledge.  However, as an analytical tool, to my mind, it is still out there with witchcraft.

Information Outsourcing Reply

Although the Gartner article deals with the monetisation of information assets, the sentiments may lead many businesses to outsource their entire information management responsibility.

The volume of data that most businesses can – or think they should be able to – manage is reaching an inflection point.  Businesses which grasp how analytics supports their revenue model will be able grapple with the continuing demands of information management (IM).  Businesses which cannot cope with the perceived threat of information overload may seek to outsource this responsibility.  The former will survive, the latter will fail. The research is clear:

  • IM is critical business:  derogating from one’s IM responsibility leads to an overall loss of revenue as businesses are unable to respond to market trends, develop appropriate differentiators, design suitable new products and services as well as leverage their information and knowledge for wider benefit.  Information is a firm’s core business, whether they like it or not.  Outsourcing the responsibility to understand the intricacies of a company’s business model and dependencies into the extended value net is a recipe for disaster.  Businesses should use all available software and technical expertise to do this but must do so with internal resources.
  • Outsourcing accounts for cost differentiators not key value drivers:  Firms which seek to cut costs by outsourcing their IT function do not recoup their losses.  The lessons of Ford, GM and Levi Strauss still remain.  Businesses which outsource their entire IT function continue to lose economic-value-added (EVA).  Although it is a good idea to outsource platforms and infrastructure it is rarely beneficial to outsource applications and services which are deeply intertwined with the more social aspects of a company’s business processes, i.e. if your process isn’t rigidly vanilla and perfectly understood then don’t outsource it.  Banks have well documented electronic processes which allow customers to manage their money and transactions remotely.  Even so, they manage these processes internally because it’s core business.

Businesses which purport to leverage economies of scale in order to be able to make sense of a firm’s information are not telling the whole story. It is virtually impossible to crunch structured and unstructured data to squeeze out additional value unless the vendor has also programmed the client’s value chain and key differentiator’s into their big-data algorithm.

“IM is not a software problem it is a business problem.  Regardless of the promises by vendors they will never be able to support management in their daily needs to navigate the subtleties and complexities of corporate information.”

It is highly likely that by 2016 the next fad, after Big Data, will be the monetisation of a firm’s information assets.  No doubt that in the low-end of the market there will be some level of commoditisation of information which will support more targeted marketing and the procurement of specialist advertising services.  However, businesses which outsource critical IM functions (largely through cost pressures)  in their business will turn unprofitable (if not already) as they become unable to respond to the market.

Big Data is Big Nonsense 3


Big Data is the next big solution looking for a problem.  Faced with falling revenues from lower ICT spends and clients with reduced consulting budgets Big ICT looks to Big Data for Big Revenue.  Customers will be left as Big losers if they fall for this parlour trick.


The central premise of Big Data is thisCompanies, organisations and government can spend a lot of money cleaning and storing data through traditional means.  This takes a long time and costs a lot of money.  On the other hand, the same bodies can buy a supercomputer and software to crawl over their data and run sophisticated algorithms and come up with the same answer.  The answer will be about 80% correct and based on statistical analysis rather than absolute truths but it’s still a good answer.  Therefore, don’t worry about information management.  Just buy really expensive hardware and get a bunch of clever people to use it and voilà! instant brilliance.


There are 2 problems with the aforementioned premise, namely: (a) Most businesses cannot do small data well, let alone big data.  Secondly, (b) there is no proven link between ICT spend and business productivity.


IT companies would have you believe that businesses are drowning in data.  Well, to continue their analogy, a person can drown in 6 inches of water.  To go even further, an infant can drown in 2.  The point is clear.  If management do not know what they wish to do with the data then no amount of computing power will save them.  In the absence of clear action companies should structure their important information so that it can be stored and found easily.  ERP systems do a good job of this and there are plenty of EDRM systems which are convergent.  More sophisticated users need more sophisticated solutions and this is where Big Data can assist.  More importantly, with the capital costs of Big Data solutions it will not be feasible (at least in the short term) to use it on standard management information.  Big Data solutions will only be cost effective for advanced business intelligence-type analyses.  If a business is looking for mainstream solutions to support business intelligence it will need to look for the more mundane.


Secondly, the link between ICT spend and business productivity is not made out for any other sector other than Financial Services & Insurance (FS&I).  This sector is now so heavily automated in its business processes that there is a clear dependency between IT and profitability.


For the rest of industry and government nothing much has changed since Strassmann’s work in the mid-90’s (see below).  This is to say that there is no point buying ICT to automate a bad process.  Expensive IT will not help poor management.  This is why banks, Tier-1 consultancies and advanced process oriented firms (such as GE) will likely be the only beneficiaries from Big Data.


Big Data is somewhat of a misnomer because it is not like standard ICT spend.  The Big Data will almost inevitably be run in conjunction with technical services because part of the benefit is determining veracity through market sentiment.  For instance, if an investment bank is trying to determine the initial share price for an IPO they would like to run trend analysis on similar companies but also see how this fares against potential investor sentiment.  Big Data used in this way is certainly a unique offering if not a competitive advantage for smaller companies.


Big Data is not a game-changer.  As computing power and processing speed increase (according to Moore’s Law), along with ubiquity, then the benefits and services of Big Data will become mainstream.  In the meantime, however, Big Data will be a competitive advantage for many of the smaller and 2nd Tier businesses.