At Computacenter, we are proud to offer a range of different career paths for people looking to start or progress their careers in IT, including our award-winning graduate programmes. These programmes are structured in a way to give candidates access to all parts of Computacenter, helping to accelerate the best fresh talent into the technology services industry and world of business as a whole.
This year, we are delighted to welcome Emily Gaskell, Sam Jones and Sharon Odozi as Graduate IT Consultants in the Platform and Hybrid Infrastructure Team (PHIT). The three talented young individuals have only been part of the team for a matter of days but are already settling in well.
In this blog, they share their insights and experiences over the last two weeks, exploring how their preconceptions of what a global, FTSE 250 organisation might have been like were changed:
Joining our new team
Two weeks ago, three of us started our new adventure at Computacenter as Graduate IT Consultants as a part of the Platform and Hybrid Infrastructure Team (PHIT). We each took a journey here through QA Consulting, a branch of QA where we all undertook a 12-week training program; Emily trained in Azure and Data Science while Sharon and Sam studied AWS and DevOps.
On our first day, we arrived feeling both nervous and excited. We expected that Computacenter, as a large organisation, would feel somewhat impersonal. The preconceived expectation was far from the truth.
Our team members Vicky and Neil gave us a very warm welcome and encouraged us to take part in icebreakers to get to know each other. We have, of course, discussed our background when talking to and networking with other members of the organisation, but this gave us the opportunity to discuss hobbies, interests and our families which has made it easy to quickly build relationships.
Meeting other graduates
On our second day, we met some of the project managers who had recently completed grad schemes at Computacenter. It was great to hear their thoughts about starting out at the company and how they had found the process.
Working with different areas of the organisation
As a large organisation, we had the expectation that there would be a rigid hierarchy at Computacenter which would determine who we could and couldn’t talk to and who we could and couldn’t work with. This absolutely wasn’t the case.
Since joining, we have had the amazing opportunity to meet lots of people from different areas of the company and with different levels of seniority. We were lucky enough to have the opportunity to meet Martin Provost, Head of Consultancy, who was easy to talk and relate to.
Everyone has been really excited to have us onboard. It’s made us feel inspired about the future and is so nice to know that we have a voice in the company.
This was especially apparent when we found out about Fresh Minds – an internal initiative which allows fresh talent to connect, network and have their opinions heard.
Another facet of the company that really stood out for us in the first two weeks was the overwhelmingly large warehouse in the Hatfield Ops building, that we only actually saw a very small part of. As we had no expectation, and little knowledge of the inner workings of the company as a whole, we were unsurprisingly blown away by the sheer scale of their physical technology production system.
The second we arrived into the warehouse we were inundated with rows and shelves full of a wide variance of technology all being prepared for prospective customers. It’s safe to say we could easily have wandered around the maze that were those laptops and servers for hours without finding an end or discovering everything there was to discover.
Strangely, this sense of awe and scale was shared when a week later we were exposed to the Cyber Defence Center. Despite being much smaller physically than the warehouse the CDC was truly impressive regarding the technology and systems they use to monitor the company as a whole. We were deeply impressed by the tools utilised by the defence centre.
We were so impressed with how lovely everyone has been when giving us these tours and inside looks into the company, it has truly made our first two weeks that much greater.
We would like to end this blog by saying a big thank you to Neil Walters and Vicky Mellor for the past two weeks, specifically for being so warm and accommodating, and for facilitating fantastic opportunities for us.
We are very much looking forward to developing our careers at Computacenter!
Interested in one of our award-winning grad schemes?
As a Sci-Fi fan, I watch many movies that showcase Artificial Intelligence (AI) in the future, and usually the narrative becomes one of humans battling machines in a race to survive. Granted this isn’t always the case, but it seems to happen more often than not. This causes many to question the ethics of AI and whether we should be pursuing our attempts to create something that has the potential to advance beyond what we are capable of. I think the point where AI will advance to that state is still some way off, but that is a topic I will cover in a later blog, especially around the ethics of AI.
We do however have interactions with AI and machine learning now that help to make our lives just a little bit easier. Let me give you an example; my wife turned to me after she’d finished her call somewhat puzzled, saying that the person that called her wasn’t a contact in her phone, but the phone suggested that the call might be from “John Appleseed”. She then asked how the phone could know who might be calling.
I explained to her that her phone will search through messages and emails and if that person‘s number and name appear together in any of these places a number of times, then through Machine Learning and AI, it can make reasonably accurate predictions.
My wife was quite taken about a back by this as she started talking about Big Brother, privacy and security but I do think that these capabilities and functions in our technology do help to make us more productive and improve our user experience. AI and machine learning also play an ever increasing role in the workplace.
The office I working in has multiple technologies that come together to form a modern workplace. As an example we have digital signage giving us messaging and updates on what’s going on in the business, we also have meeting rooms where we can either use monitors to project content from our devices or we can use video conferencing to enhance our remote meetings.
We have the ability to hot desk across multiple floors which can lead to the issue that if you don’t get into the office early enough, or if more people decide to work in the office than normal then it can be difficult to find a desk.
The biggest challenge these technologies and capabilities have is they are mostly disparate and disconnected thereby reducing the productivity and experience of users. One of the things I believe will happen in the medium to long-term is the consolidation of these technologies coupled with AI and Machine Learning will provide a more cohesive and coherent experience, let me give you an example.
If I get up at 6 o’clock in the morning my phone will tell me that the journey time to the office will take me an hour and 10 minutes. If I get up at 7 o’clock, the phone will tell me that the journey to the boys school will take 10 minutes, so clearly my patterns are being learnt and understood by my smart devices.
Now imagine this capability being connected to all of those ecosystems and technologies in the workplace. Imagine that when I get up at 6 o’clock in the morning and my phone tells me that the time to the office will take an hour and 10 minutes and I simply touch or confirm by voice that I am going into the office, it automatically books me a hot desk (or tells me there is no space to save a wasted journey) as well as booking a video capable meeting space as by looking at my calendar the AI determines that I have to do a video conference later on in the day.
Then as I walk into the office, either CCTV using facial recognition or proximity using the device I carry, the Digital Signage changes to tell me where my hot desk is and what meeting room has been booked for that day. As I approach my hot desk the chair automatically adjusts to my preferred settings along with that the monitors and keyboards altering height, brightness etc to my usual settings.
We can see how this kind of experience will change the way that we use our workspaces as AI, Machine Learning and connectivity between ecosystems adapt and evolve over time.
When we think about the technology and interconnections across systems that are required to realise this outcome, we see that architecting the systems or choosing the solutions that we deploy will become a much more holistic task, and require both our own organisations and those that we work with to have a broader skill set and capability than ever before.
AI = Smart?
I attended the ISE 2020 show last week in Amsterdam where we discussed topics such as 5G and Edge Computing, AI and Machine Learning, Smart Cities, Smart Buildings and the increasing role that human centric design will have in all of these solutions.
I’m planning to blog more about these topics over the coming weeks as they are each huge topics in their own right, but I think for the short term, we will see more and more capability being put into Buildings, Workplaces, Cities, Cars, etc. Machine Learning and AI will be integral to this. The danger sometimes is that we try to be too smart and over engineer or create solutions that are either too difficult to use, have no value to the people that use them most or are just not cost effective.
When designing solutions ask yourself what is the problem we are seeking to solve? Or What opportunities can we create? And think also about what behaviours will change or need to change. Using our intelligence coupled with Artificial Intelligence and Machine Learning will give us the best of both worlds and a future where we aren’t being hunted by robots.