15th October 2018•Uncategorized

Technology is an accelerant for humanity and we are now entering a new phase, referred to by the world economic forum, entitled “The Fourth Industrial revolution”.

1^st Industrial Revolution = Steam

2^nd Industrial Revolution = Electricity

3^rd Industrial Revolution = Computer and Communication technology

4^th Industrial Revolution = Digital, Physical & Biological systems.

Technologists predict that by the end of the century 70% of the jobs we are currently doing now will be obsolete. Although this sounds a scary thought, revolution creates evolution and new types of jobs will be created e.g. web developers did not exist 100 years ago.

Big data facts

• *2.5 quintillion bytes of data is created every day (equates to 4 trillion books that if stacked would reach the moon and back)
• 90% of the worlds data has been collated in the last 2 years.
• Every minute 300 hours of video is uploaded to You Tube
• There will be 6 billion smartphones by 2020

*Source: IBM (slightly outdated but you get the picture)

Where does it come from?

First of all, data is generated from us via smartphones, laptops and computers:

• Text messages
• Emails,
• Whatapp
• Social media posts (Facebook, Instagram , Twitter etc)
• Videos
• Photos

Secondly, large amounts of data is collected via the Internet of Things (IOT) i.e:

• Sensors
• Machines
• Vehicles
• Trackers / Wearables (Watches, Fitbit etc.)

The term “Big” Data refers to the huge data sets we are all building although the term “Big” is now left out.

Benefits

What Benefits can we gain from these huge data sets?

• We can make better informed decisions
• We can solve problems
• We can Improve life
• We can Improve performance

As an example; I am a bit of an amateur cyclist, albeit a bad one, although I still have 4 sensors when out cycling:

Speed Sensor – To tell me how fast I am going

Cadence Sensor – Calculates the amount of times the pedals go around (Revolutions Per Minute (RPM))

Heart Rate Monitor – Records beats per minute (BPM) to record how hard I am (actually) working.

Power Meter – How much power I am generating (watts) (how hard am I pushing the pedals)

All the above sensors work together in line with GPS to log data throughout the entire ride. Once the ride is complete all this data is uploaded to a web based system so I can review the statistics. By reviewing the statistics allows me to know where my weak spots are allowing me to train them effectively (of which there are loads). It sounds complex but by using the data I can make far better decisions than just guessing. I also know how fit (or unfit) I am at all times.

Data uses by industry

Healthcare

Big data in healthcare is changing the way we identify and treat illness along with improving life and avoiding preventable deaths. Some of the cool things currently happening:

• Smart nappies – Nappies that send data (from samples collected in the nappy) of special needs babies to a doctor which in turn can predict an infection 24 hours before it materialises.
• Medical Diagnosis – Using IMB Watson to help diagnose illness efficiently.
• Genomics – Predictive analysis to determine the most appropriate treatment on an individual basis.
• Pace makers – Connected to the internet and remotely monitored and analysed.

Retail

The way in which we buy and sell things is changing rapidly and retailers are adopting a data first approach whether they are on or offline:  Some of the cool things currently happening:

• Tesco Club card – Using data to encourage shoppers by sending coupons based on shopping habits (nothing new but a highly effective strategy)
• Walmart’s Data Café – Walmart has a dedicated data team called the “Data Cafe” whereby any member of the team can go to them with issues i.e. why aren’t certain product’s selling etc. It is up to the team to provide answers and a solution based on the data.
• Pizza Shops – Using mobile and real-time coupons based on bad weather and power outages (when people are preventing from cooking)
• Social Listening – Monitoring social media to identify trends and reacting accordingly.

Financial services, banking and insurance

Large data sets and algorithms have been used to trade stocks and shares however data is now being used more widely.

Some of the cool things currently happening:

• RBS – Strategy called “Personology” to reconnect with customers and offer a more personal service (just like the good old days)
• Mortgage – A number of players using data to speed up mortgage applications / house buying transactions.
• Fraud detection – Using advanced predictive analysis to prevent credit card fraud
• Individual Insurance – Several players using activity trackers / wearables to monitor and create bespoke insurance products on an individual basis. (WeSavvy)

TV

The way in which we watch TV has changed. Gone are the days of going to the video / DVD shops (they have all but disappeared). We now consume TV on demand with services like Apple TV, Amazon Prime, Netflix. These players have now have also started to make their own programs. How do they know what to make? Data… Everything we do within these services i.e. Search for, play, pause, rewind, stop, skip etc.is analysed and is used to analyse what we like and how we consume. This is how House of Cards was made.

 

Smart data

One of my favourite data stories crosses the pond to a family butchers located in North West London. The butchers were established in 1996 and had a good customer base however after a supermarket moved in opposite they noticed a big drop in footfall and subsequently a big drop in revenue. They knew they had quality on their side but found it impossible to compete with the multinational supermarket therefore they had to think smarter. They sought advice which prompted them to put inexpensive sensors in the shop window to measure the amount of people walking past the shop, how many people stopped to look at the window display and how many people came into the shop as a result.

Armed with this information, they were able to refine their messaging and shop displays based on what interested customers the most. That’s not the best part. One thing that the sensors also picked up was that there was a real increase in footfall at night, due to a couple of pubs located at the top of the road, which pointed to a potentially new revenue stream for the business between the hours of 21:00 to midnight. The butchers therefore decided to trial evening opening hours, serving premium hot dogs and burgers to folk heading home from the pub. The butchers also used Google Trends to see which food items were particularly popular. This led to the creation of their pulled pork burger with chorizo. Now that is a good example of thinking outside the box and a great example of a small company using data.

 

Conclusion

The above sectors are just a few examples of how data is changing the ways in which organisations are adopting a data first approach.

Our world has sped up and the rate of technology is changing 10 x faster than the industrial revolution. No business or sector will be untouched by the Fourth Industrial Revolution and it is happening as you are reading this article! One thing for sure is that data is a key business asset, central to the success of any organisation large or small.
Contact Origin today if you would like our agency help to unlock your data potential.

Jerry Staple
Technology and Innovation Director of Origin