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Big Data. New realities and implications for Boards and Directors

In recent times, a decent number of articles about Big Data have been published, basically suggesting its great capacity to add value to our organizations. Some even say it is part of the 21st Century fingerprint for progress (jointly with social media, mobile and cloud computing). (4) What`s behind that name? Let`s try to clarify the concept and usefulness of Big Data.

What is it? How can it be defined? and its effects relevant?

The fact is more and more data are collected everyday; everything we do is data producing or data driven.

Big Data is partly made of the different databases stored in data centers, but in order to build Big Data (BD), firms must add:

–         Dark data, which are collected informally while doing business, in most cases in non electronic formats,

–         Internal unstructured data,

–         Machine data, (provided by sensors such as security cameras, etc),

–         Databases external to the company, (universities, and so on), structured or not

Businesses should be able to gather information in every point a customer acts in the revenue chain, and the same can be said of the supply chain.

The main characteristics of Big Data are shown below:

–         Velocity: it is live, and it is coming all the time, (twitter, for instance).

–         Variety: image, (youtube), text, (blogs), numbers, (transactions, automated logs), etc.

–         Veracity: it is uncertain, we don`t really know what is inside.

–         Volume: there is a huge continuous flow of data. This is what makes a difference between BD and analytics, (volume and advanced technology).

Speed is perhaps more relevant than volume: real-time data is so relevant.

Individuals, firms and governments need to turn to data in order to answer their questions and machine learning and pattern detecting data mining will help disentangle the jungle of data they will be facing. As a result, decision-making processes will be more scientific and objective.

BD helps describe what a person or all people “actually do”, (for instance in twitter), but it is not yet a predictive tool, and it is not a policy designing tool either. Social systems are dynamic and need reflexive minds for prediction and policy. It can tell where to aim to, not how to get there.

Certain Social Sciences, (Sociology for instance), unlike Maths or Economics are badly equipped to deal with big data, their scientific methodology will suffer and will need to change. But in order to keep clinical eye some usual data methodologies in well prepared sciences will have to be tackled, for instance: a) shrinking data takes out extreme cases, so relevant in social science; b) data mining, machine learning and pattern recognition need to have “facts” classified, to determine what is similar or different, to execute counting.

Can Big Data boost Productivity?

General Electric uses data from its 19.000 windmills installed around the world to improve the efficiency of each of them and help solve problems; intelligent machines interact among them and with humans. But, productivity gains take time to be obtained after innovation and capital investment are deployed, so it is not for sure that large benefits are going to be reached during the implementation process.

Stanford University and Conference Board research suggest that only 7% of firms use Big Data today. MIT and other institutions consider those firms get a higher profitability, (up to 6 % more). How do those firms succeed in improving their productivity?

They probably develop processes to identify, mine and exploit the most relevant information for that purpose. Digital modes and codes have reduced the cost of obtaining information in an analogic world, (just think of a survey made face-to-face and compare with today`s online forms). So, what is really differentiating is the higher capacity to exploit data.

Another change refers to what is relevant today: in the past, data were analysed to understand “why” things happened, but today things are looked into to discover “what” happens, in order to react, avoid negative effects or take advantage of the opportunities.

Moreover, Big Data could eventually change the business equilibrium between experience and instinct in decision-making processes, thus affecting recruiting needs by firms, and the value of human capital.

How can Big Data be used to add value?

According to Gartner, value usually comes from:

–         Better informed decisions,(for instance when deciding product segmentation with better information on demand needs),

–         Hidden insights being discovered, (for instance as for the patterns of fraudulent cases, or other regularities into years of forgotten reports),and

–         Digital processes,

but above all, firms need to adopt a predictive view of business, so as to make things happen differently.

How to adopt a predictive and prescriptive attitude?

Perhaps the kind of question is a good start, that is changing the “what were the profits last year?” for a very different “How can we improve customer satisfaction by 30%?”

Secondly, a culture of change needs to be deployed throughout the organization; and the board should oversee the way Big Data gives results in time, with milestones and objectives.

Thirdly, until now we have taken as a given that data were correct; but when dealing with Big Data, very often contradictory data appear, inconsistent or erroneous data need to be deleted or clarified, etc.

Fourth, IT departments need to have resources, talent and will for change, and proactivity to propose the needed changes for the new landscape.

Is Big Data to change the ways Boards behave?

This is in fact what many argue, as Barry Libert in (4). Governance 2.0 should imply a more data-centric decision-making model; BD created by social, mobile and cloud -among other sources- generate information flows and communications between firms and communities that could not be imagined only years ago. So, how could a director not know about these forces?

In today`s business environment, strongly dominated by intangible assets, BD can also play a major role when boards determine when and where they invest the firm`s resources. Could we talk about Strategy 2.0?

Financial activities can also benefit from BD, in that predictive mode we advanced above; moreover, most of past inputs to financial activities were internal, but these strong connections with external communities need to be included, as they provide value and opportunities. Mining the relevant metrics and KPI`s out of BD would help jump to a new Finance 2.0

Operations 2.0? Yes, indeed. Re-engineering operations not only internally but across the firm`s boundaries and until these communities, thus eliminating intermediaries for example, (see crowdfunding of direct sale of consumer products) can eventually engender big opportunities.

Barry Libert suggests that boards need to require not only financial and operational but big data reporting in the usual pack; that they need to recruit technology savvy directors; directors would also need to create a digital-centric strategy to unveil this new environment`s opportunities for long-term growth.

Based on several articles on the subject, listed below, (and probably others):

(1)    http://www.directorship.com/mining-big-data-2/

(2)    http://economia.elpais.com/economia/2013/09/27/actualidad/1380283725_938376.html

(3)    http://smartdatacollective.com/bernardmarr/150126/revealed-top-5-big-data-use-cases-your-ceo-will-love

(4)    http://www.corporatesecretary.com/articles/technology-social-media/12562/governance-20-future-boards-age-big-data/

(5)    http://www.directorship.com/why-boards-must-embrace-big-data-2/

(6)    http://www.huffingtonpost.com/chad-pollitt/big-data-fuels-spying_b_3940432.html

(7)    http://www.businessweek.com/articles/2013-09-19/innovation-and-productivity-are-not-dead-thanks-to-big-data

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