We are entering a truly exciting time in IT. The industry is really starting to focus on driving clear outcomes. This is true whether you work in a FTSE 100 company, a healthcare trust, a charity or a motorsport team. We must all ask the question 'why?'. Why are we buying this infrastructure? Why are we investing in more software? Why 'cloud-first'? If we don't ask these questions, our technology investments are unlikely to provide the outcomes we desire.
The focus on technology outcomes was front-and-centre at this year's HPE Discover in Madrid. Vendors and suppliers were all focussed on tangible use cases. For example, using drones to improve farming, processing data faster in motor racing and using data to improve the customer experience at major sporting events.
It is no longer a case of "you need to buy this new technology because it's bigger, better, faster". It’s now critical to ask “how is this technology going to help my organisation."
Tech Trends 2019: HPE's Future Focus
In this year’s general session, Antonio Neri - President and Chief Executive Officer of HPE - walked us through some key focus areas and tech trends for 2019:
Like many, HPE believe the world is going to be Edge-Centric, Cloud-Enabled and Data-Driven. Working closely with key partners, such as HPE and Microsoft, we are certainly aligning our own focus for 2019 in a similar way.
Cloud and Data are areas most of you will be familiar with (and you have probably formed your own opinions by now). But 'Edge' is relatively new, so let's dig a little deeper into this key area.
What exactly is the Edge?
When you boil it down it's simple to understand. The Edge is really everything outside of the data centre.
It's the place where IT is generally consumed, and its value realised. We are all creating and consuming data across a myriad of devices. So, in the home, hospitals, schools, offices, shops, on farms and even at the race track.
When we talk about being Edge-Centric, we're really talking about the mass consumerisation of IT.
How do you store, manage and process the data at the Edge? How can data then be delivered as something tangible to the customer? These are two of the biggest challenges for most enterprises today.
Data at the Edge: Use Case Examples
Probably in one of the most extreme examples of data at the Edge is HPE's partnership with the Mercedes AMG Petronas F1 Team.
Source: HPE Discover
At this year’s HPE Discover, Antonio discussed data at the Edge with Toto Wolff (Team Principal and CEO) and Lewis Hamilton (five times F1 World Champion).
During their conversation, they regularly touched on the ever-present need to analyse data as thoroughly and as quickly as possible.
At the trackside, data needs to be analysed at lightning speed. With the sheer volume of data being produced, it is simply not feasible to send this type of data to remote data centres. It needs to be analysed, and a dashboard of results surfaced to team analysts in real-time from the track side (aka the Edge). This way, they can make near-instant decisions during practice, qualifying and the race itself.
This is an extreme example of Edge plus Data and Cloud technologies working together to provide instant insights. It’s not too difficult to see how similar Edge capabilities could be used more broadly across the general motor industry. Especially as cars become increasingly connected and “smarter.” And, of course, across other sectors.
"Technology's greatest promise lies in the good we can do and the challenges we can overcome together".
Antonio Neri, President and Chief Executive Officer of HPE.
One of the most poignant sessions at HPE Discover was Emily Kennedy’s, the President and Co-Founder of Marinus Analytics. She talked passionately about how combined AI and Edge technologies had helped find a young girl of 16, a victim of human trafficking.
Source: HPE Discover
Using facial recognition technology she was located by comparing distinguishing features from two sets of photos. One from when she went missing aged 14 and one from multiple recent images, where she was now aged 16, but her hair colour and style had changed.
The combined technology was able to identify the girl where a human police officer had previously decided there wasn't a match.
Arguably, there is be no better technology outcome than saving a human life.
It's vital to understand your data so you can classify it and standardise it - then create value from it. We are currently helping different organisations set up processes to systematically create greater value from their data.