After reading Big Data The Management Revolution from the Harvard Business Review 90 (10) 60-66 the authors Brynjolfsson & McAfee highlight how data has transformed the way businesses manage their customers and gain consistent cometitive advantage and acknowledge the fact that you cant manage what you dont measure. Data collection software has enabled executives to measure data that allows them to know more about their business and helps to improve deciosion making and performance.

McAfee  refers to retail businsses with special reference to book shops as they were impacted the most with consumers moving more towards online shopping due to the fact that online businesses are able to collect very important buying behaviour data. The data they collect looks at the way consumers navigate through the webpage, things they look at, how promotions, reviews and page-layouts influence their behaviour and simularities across groups and individuals. From this data the online businesses developed algorithims that performed better every time the customer responded to or ignored a recommendation. Companies like Amazon used this to their advantage and put many book stores out of business as they were unable to access this data or even act in a timely manner.

In the past alot of management decisions were based on gut and intuition, however now they can measure and manage more precisely enabling them to make better and more informed decions and smarter predictions. Big data is a management revolution, however there can be challenges faced with organisations becoming a big data  enabled organisation such as the way they lead the orgainsation they may need to outsource scientists who can translate the data into useful business information. Some Business executives refer to big data as analytics, which in some cases can be true, however Mcafee states that there are three key differences; firstly volume. Volume refers to the amount of data that is created in a day, and McAfee states that this volume is doubling in size every 40 months or so. McAfee refers to Walmart as an example and states that they collect more than 2.5 petabytes of data every hour from its customer transactions, one petabyte is the equivalent of about 20 million filing cabinets worth of text showing how data has a great impact on the success of a corporation especially in a fragmented market where customers needs are forever changing. Secondly velocity, McAfee states that more businesses believe this aspect of the Big data movement is the most important and far more important than the actual amount. Real-time information allows executives to make decisions that make them more responsive then there competitors creating competitve advantage. Lastly, variety as big data can take the form of messsages, up-dates, images posted to social networks, readings from sensors, GPS signals from cell phones and more. As technology is becoming more advanced it has enabled programmes to collect new sources of information as well as making it more economical to store and collect data.

McAfee has proven that data driven companies perform better by the research that was carried ou. McAfee found that the use of data driven decision making enabled businesses to become 5% more productive and 6% moe profitable on average copmpared to their competitors. McAfee makes it apparent that not all businesses will be successful if they transition to using big data due to the fact they may not manage the change effectively.

McAfee sets out 5 areas that have particular importance to management when big data is implemented into an organisation:

1. Leadership:

Leadership needs to have vision & human insight by setting out clear goals, be able to define what success looks like and ask the right questions. The ability to see opportunities and understand how a market is developing, think creatively, propose truly novel offerings, articulate a compelling vision, persuade people to embrace it, work hard to realise it and deal effectively with customers, employees, stockholders and the stakeholders. McAfee believes that successful companies of the next decade will be the ones whos leaders hold all these credentials as well as changing the way the organisation makes decsions.

2. Talent Management:

Key techniques for using big data are rarely taught, data scientists and other professionals skilled at working with large quantities of information are key and very hard to find so it is important to ensure you have someone with these expertise working within the organisation.

3. Technology:

This refers to the tools available to handle volume, velocity and variety of the big data and the software available to manage it. These technologies require a skill set that is new to most IT departments as they will need to integrate there internal and external sources of data.

4. Decision Making:

Knowing the people who understand the problems faced by the orgainsation is important as that will enable executives to put the right people together with the right data and ensure they have people who have problem solving techniques who are able to exploit them.

5. Company Culture

Moving to big data can create enormous cultural challenges within the organisation as well as privacy concerns and will involve breaking bad habits such as making decsions based on hunches and instinct. Alot of companies pretend to be more data driven then they actually are in order to supoort the decisions they have made, however it is is very easy to find misleading patterns in the data.

McAfee concludes that data-driven decision making is the way forward in order for companies to gain competitive advantage and insights into the markets they trade in.

McAfee, A., & Brynjolfsson, E. (2012). Big data: the management revolution. Harvard Business review, 90(10), 60-66

Ted Talks-BIG Data is Better by Kenneth Cukier

What is the future of BIG Data- driven technology and design? What is next for machine learning?

Kenneth starts off by making it apparent that having more data allows us to see new, better and different things.

BIG data as an extremely important new tool by which society is going to advance.

He states that in the past we as humans used to look at small data to try and understand the world, BUT now we have more data than ever before. Having a large body of data enables us to do things that we could not do when we only had access to the small data such as addressing global challenges like feeding people, providing medical care, supplying energy/electricity and dealing with the effects of Global Warming.

Kenneth then went onto talk about our ancestors and the way they recorded data in history, and makes it apparent that how we used to record data in the past has not changed all that much. He uses the example of an ancient heavy clay disc (2000bc) that was found with inscriptions en-carved into the clay that were unchangeable. He states that data is a fluid dynamic and can be seen as the liquidity of information, and today a huge amount of data can be stored onto something so small like the size of a fingernail and can be shared at the speed of light. Searching for data has become much easier as well as sharing, copying and processing it, which allows us to re-use the information for uses that we could never of even imagined from when we first collected the data. Databases record and store information which can create ‘fingerprints’ creating aggregate data in which predictions can be made. BIG data is valuable because its allowing us to have access to information to do things we could not do before.

The term Machine Learning is when data is thrown at a computer and is left for it to make sense of it by itself this is also know as Artificial  Intelligence. In the 1950’s Arthur Samuel who worked for IBM was very fond of the game checkers and decided to write  a program which enabled him to play against the computer. Every time he played against the computer he won and kept winning, due to the fact the computer only knew what a legal move was but Arthur Samuel knew the strategy behind the game. He then went on to write a small sub program that would  operate in the background of the existing program he initially created. The sub Program was used to score the probability of who would win, and Arthur Samuel continued to play, but he was still winning every time he played the program. He then decided to stop playing and allowed the program to play itself, which then enabled it to collect more data which resulted in an increased accuracy of its predictions. Arthur Samuel goes back to play with the program and he lost the game, he played again and again and the same result happened in the fact he kept loosing to the program. Arthur Samuel created a machine that surpasses his ability in a task that he taught it.

The machine learning idea is everywhere and is at the basis of what we do online, for example voice recognition, computer translation, location services, search engines and Amazon’s personalisation algorithms. Kenneth Cukier gives another example of machine learning within cancerous biopsies for breast cancer. The computer was given data and survival rate statistics to identify and to determine if the cells was cancerous or not. The machine identified 12 top signs that could be seen to know if the cells were cancerous or not. However a problem surfaced in the fact that the medical literature they had only spoke about 9 top signs, resulting in the fact the computer spotted 3 more signs that the scientists were not aware of.

Kenneth Cukier then went onto saying that BIG Data is good but there is a bad side to it. He says that we should be aware that people may be punished for prediction, for example the police may use BIG data for their own purposes a lot like the film Minority Report. This term is called prediction policing also know as algorithmic criminology. This is the idea of taking a large amount of data like places of where past crimes have been committed so they know where to send patrols, however this data will not just involve location data but also data about the individual such as education, credit scores, web surfing behavior, employment history, sleeping patterns.  Biochemistry uses data to study chemical processes through algorithms that affect us as humans such as aggressive thoughts. We could have algorithms  that predict what we are about to do and we may be held accountable before we actually do anything.

Cukier states that in the small data era, privacy was the essential challenge, but now in the BIG data age we are faced with a new challenge, according to K.Cukier and that is safeguarding free will, world choice, human volition, human agency. He also suggests another problem with BIG data is the fact it can steal our jobs. BIG data and Algorithms are going to challenge white collar professional work in the 21st century in the same way that factory automation and assembly line challenged blue collar labor in the 20th century resulting in peoples jobs changing and the elimination of jobs. It is assumed that technology creates jobs over a period of time after a short temporary period of dislocation just like the industrial revolution, however there are some jobs that never returned.

Cukier advises us that we must be careful with the use of BIG data by adjusting it to fit our human needs, we have to be the master of this technology and not a servant, we are just an outset of the big data era. Cukier also states that we as individuals are not that good at handling all the data that we now can collect, which is not just a problem for National Security agents. Businesses also collect lots of data & misuse it too, he believes that we need to get better but this takes time, BIG data is a tool, however if we are not intelligent enough to use in the correct way it can burn us!

BIG data transforms how we live , work and think, it can help to manage careers, lead lives of satisfaction, hope, happiness and health. Cukier goes onto say that in the past we often looked at information technology as just the physical aspect of the technology, we now need to look at the information which is less apparent but in some ways a lot more important.

Lastly, Cukier believes humanity can finally learn from this information that it can collect as part of the timeless quest to understand the world and our place in it.

BIG data is a big deal!!!