Innovation over the last 10 years

For nearly 10 years I have been sharing my technology & Innovation observations through my blog.  To offer a retrospective over this period is not only interesting but can shape where the industry will go in the future and to support this I have compiled a list of the annual 10 technology trends produced by Gartner over this timeline. It is good to keep in your mind that the observations and trends are cutting edge rather than adoptive and most companies will lag a few cycles behind so the immediate future can be gleaned from the last few years and the most up to date trends will not reach consideration for a few years to come.

At the beginning “back in 2007” it was evident that the trend was Infrastructural and encouraged the move from traditional Data Centre hosting models to ones which involved Cloud computing, automation and design that was web enabled with collaboration and mobile in mind.    We then entered a  period which was more transactional (which is where most companies will be now) which exploited the previous advances in technology and saw the evolution of Business Intelligence to Advanced Analytics and visualisation, the use of Big Data and where all development was device agnostic and ready for the web.

gartner-2007-2017

Even though Technology is moving at a tremendous pace I think the next 2 cycles will be extremely exciting.  I think initially we will have another infrastructural period where Cloud Technologies evolve into a hybrid state; we will understand more about how to exploit the data from connected devices and the internet of things including how to store it.  We will see advances in Artificial Intelligence and will start to hear about the first real time distributed ledger platforms being used.    Then comes the interesting stuff; the next period will show that we finally have the right technology in place to start exploiting all these new advances so Distributed Ledger applications will be common place, Augmented and Virtual Reality will come of age and start to become communication channels in their own right.  Machine Learning will also start to become intertwined in everything we do and appear everywhere from your home to your Car and even the workplace.

This last set of observations may seem a long way away however just look how far we have come in the last 10 years and remember Broadband is only just over 15 years old so in ten years anything could be possible.  We all just need to embrace the change and enjoy the ride.

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How valuable is your data?

data

Over the last decade social media and collaborative platforms have not only become popular for the masses they have also been seen as an easy win for corporates to extend market share and maintain relevance. It all started in 2006 when Google purchased You Tube and continued with further major purchases like Facebook buying Instagram and Whats App, Twitter buying Vine and Microsoft purchasing Skype, Yammer and this year LinkedIn for $26 Billion. From the consumer point of view it shows exactly how valuable our data is to corporate’s and indicates how important it is to ensure that our privacy settings are correct as no one can guess who will purchase the platforms in the future (especially as most people have dormant personal data littered across the internet). However from the corporate perspective there are 2 benefits for making a purchase. The first is to secure a pre-built user base to whom you can sell and the second is to hopefully obtain a platform that will continue to grow and innovate. The problem with most Social platforms is that it’s very hard to know if you are buying dormant users and what percentage of the data is correct. The interesting thing about the Microsoft purchase of LinkedIn (which apparently was also wanted by Sales force) is that this data source is one of the few which is believed to be accurate due to it being continuously updated with Career, Education, Training and content preferences.

Customer segmentation using Big Data

Customer

 

One of the benefits of data and big data is that it enables greater understanding of the customer and allows the enterprise to create multi dimensional segmentation models. Prior to this data being available the best way to segment the customer was to create generic personas and then create strategies based upon these. Personas although valuable are very generic and generally do not incorporate known life stage, aspirational and preferential desires of the customer. By collecting information based on known internet behaviour we are now able to create a multi dimensional models which should give greater customer understanding and enable future investment in products and technologies which will satisfy known desires rather than perceived.