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  • Service: Audit, Audit Related Services, Audit Committee Institute, Advisory, Management Consulting, IT Advisory, Business Intelligence & Analytics, Risk Consulting, Board Advisory Services
  • Type: Business and industry issue
  • Date: 13/12/2013

ACI Roundtable Discussion Summaries

ACI Roundtable Discussion Summaries
Key issues discussed at KPMG's Audit Committee Institute (ACI) Roundtable series.

ACI Discussion Summary: Series 2, 2013

Issues discussed include cyber security, data sovereignty, big data and data analytics.

The current state of Big Data: and why it matters 

We are now in the age of ‘Big Data’.

An age where, as noted in a 7 November 2013 European Commission Fact Sheet, What is big data? "Every minute the world generates 1.7 million billion bytes of data, equivalent to 360,000 standard DVDs. More digitised data was created in the last 2 years than in the rest of human history. This trend and the mountains of data it produces is what we call ‘Big data’. The big data sector is growing at a rate of 40 percent a year."

 

 

Think about that number.

 

360,000 DVDs (4.7Gb per disc) worth of data per minute. And for some organisations that’s the tip of the iceberg.


Two years ago Facebook alone was storing 100 petabytes of data1. That’s all of the data from their near 1 billion plus ‘active users’.


Then consider the estimated 154.6 billion emails sent globally every day (89 billion of which are corporate emails – a figure expected to grow at an average annual rate of 13 percent over the next 4 years2).

 

Now add in every Twitter tweet (over 30,000 per second), every SMS, every data transfer, returned survey, indirect tax statement, bank transfer, Frequent Flyer and supermarket rewards card transaction, scanned data from supermarket checkouts, etc... the list goes on.

 

All of which combines to become what we now call ‘Big Data’, a term that can be broken down into the three V’s:

 

 

1

Volume

The amount of data

2

Volocity

How fast it is processed/analysed

3

Variety

The different types of data
– structured (databases, spreadsheets, etc.)
– unstructured (emails, social media, SMS, etc.)



And to make that even more complex, a fourth and a fifth are also key:

 

 

 

4

Veracity

The accuracy of that data and how it may relate to business value (remember that ‘bad data in means bad data out’).

5

Value

Making sure the findings are insightful and can be 'used' as opposed to just 'interesting'.

 


Needless to say, the potential value of all of that data cannot be underestimated.


So the question is – how many organisations are making the best of what they’ve got? Are they using data analytics to identify and extract any valuable information and insights?


And the answer matters.


A recent Bain & Company study3 showed that those who were early adopters of Big Data analytics not only gained a substantial lead in the corporate world but those with advanced analytics capabilities outperformed their competition by a wide margin. Additionally, another European Commission study4 showed that ‘data-driven decision making leads to 5–6 percent efficiency gains in the different sectors observed’.


It’s no surprise then that data analytics is a quickly evolving area within businesses – with different organisations and industries at different stages or maturity.


Naturally, data analytics can be used by many different areas of the business for a variety of reasons. By being able to look deeper into the their data, directors and senior management can, for example, better tailor services and products to specific customers, minimise risk, boost innovative product and service development, make better management decisions, and improve decision-making.


The difficulty is in ensuring it is utilised in all departments, not just a select few. How can you recognise all potential benefits if you don’t share ideas, projects and insights that cover more than one or two key areas? How can you identify data of real value so you can adequately use it and protect it from risk (and being a risk)?


An entity-wide perspective is essential for optimal use of data analytics. As is being able to identify ‘why’ you want the information and ‘how’ it can add value and align to your business strategy.


This can mean utilising in-house capabilities – while ensuring those people have the right amount of expertise to analyse and interpret results – rather than outsourcing to external consultants.

 

Like big data itself, its potential is growing exponentially.

 

Google Flu Trends uses big data to predict the spread of the flu virus. Police departments use it to predict crime before it happens. Retailers use it to optimise their stock based on weather forecasts, social media and online search trends.

 

And your employees, clients and suppliers are increasingly becoming aware of how their information is being used bringing broader public scrutiny (for example ABC Four Corners’ story on external data usage and privacy in September 2013).

 

It’s a clear indicator that for any company wanting to stay competitive, they have to start thinking seriously about data.

 
That means getting serious about privacy and data security, up-skilling those needed to analyse the data, investing in appropriate technology to make use of these large datasets and looking at ways and areas to broaden the ability to analyse and provide actionable insights.

 

Because in a world of data, knowledge is king.

 

 


 

1 Facebook IPO filing to the US Security and Exchange Commission on 1 February 2012.

2 Email Statistics Report, 2012–2016. The Radicati Group, Inc.

3 Big Data: The organizational challenge. 11 September 2013 by Travis Pearson and Rasmus Wegener, Bain & Company.

4 Big Data for All: Privacy and User Control in the Age of Analytics. Omer Tene and Jules Polonetsky, 20 September 2012 (revised 1 November 2013).

 

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