Reflecting on 2022 with Brian Hills, CEO at The Data Lab

This month at The Data Lab ,?we're?looking back on the year that's been, as we take a bit of time to reflect on 2022. We've asked members of The Data Lab Community to share their?highs and lows, the challenges they've faced,?and what they've?learned along the way.?

The Data Lab Community? enables data and AI professionals, academics, students and other enthusiasts from around the world to connect, collaborate and learn from each other. It's free to join, and you'll gain access to events, job listings, mentoring opportunities, community discussions, news and more.

Our very own Brian Hills , CEO of The Data Lab - Innovation Centre reflects on 2022, shares some of his favourite resources, and development resolutions for 2023.

"Which of these do you like?" said the message on my phone, followed by pictures of five puppies.?

"The last one" I replied.?Little did I know that three days later I would be out voted by the family, despite protests like "I love dogs, its just not the right time" or "it will destroy your toys" and "we will need to share the dog walking in the winter".?

In the summer of 2021, we became the owners of Gigha.?At the start there was lots of enthusiasm for taking Gigha on walks but come winter, as predicted, this had dissipated as rapidly as the daylight and I spent a lot of time walking in the pitch black of the countryside with a frequent gale and driving rain for company.

Of the many aspects I could write about being a dog owner, there was one particular thing that I was grateful for and that was the gift of time - specifically thinking time.?Those dog walks, no matter the weather, created new opportunities to think about life, work or to try clear my mind from the day.

As I look back on the year I think about December 2021 and those walks becoming longer and longer.?There was a lot to think about: I had committed to stepping into Interim CEO role as?Gillian , our then CEO, had taken a great new opportunity and I was considering applying for the role.?My analytical mind kicked in and I spent many walks thinking about the positives and the negatives of applying for and doing the role.?The challenge was that for every positive there seemed to be a negative and vice versa, I was going round in circles.?I spoke to close friends in my network, but this added to the deadlock.

The daily walks became thinking about how to break the analysis paralysis and to try to do this I thought: "Am I asking the right question - can I reframe this by learning from the past?"?I then came up with two new questions.

The first was "What is the worst that could happen......and am I prepared to take the risk?"?

I remembered a previous line manager telling me, as I handed him my resignation, that I would not last long in the new role and would be "terminated" quickly (I wouldn't recommend this as a retention strategy).?My reply was that could well be the case, but I would regret for the rest of my career not giving it a shot - and if I crashed out in the probation period I would have learnt a lot about myself to take into finding the next opportunity.

The second was "Beyond the data and evidence, how do I feel about the opportunity?"?

Now this is a difficult and awkward question for someone whose career has been anchored in data analytics. The answers I discovered were: excited, nervous, supported and ready.

Reframing and answering these new questions gave me the confidence and motivation to move forward. Now in role, it is a privilege to lead an amazing team who are enabling pioneering collaborations that create opportunity and change people's lives.

Indeed, one of my top highlights of the year was from the graduates who wrote to The Data Lab Masters team to thank them for changing their lives. This fuels my excitement for the future: yes there are significant challenges nationally and across the world, but there are also opportunities to make a difference and scale that impact to completely new levels.

Reflecting back, there are three areas I'll be continuing to develop next year and I think they are useful for anyone:

1. Think about how to craft and ask better questions.??Crafting and asking better questions can help to break deadlock and open new opportunities: thinking and talking about this process with others is valuable to the collective team. One area I've found really useful this year is volunteering to be a mentor to other early career data students and professionals - it helps to develop the muscle of asking questions, rather than charging in with answers and I've learned so much from those I've mentored too.?
2. Develop decision making based on "informed intuition".??This is a concept I learned on a podcast with Marissa Mayer, former CEO of Yahoo, describing the ability to combine data with experience to make better decisions. That experience leads to instinct about situations, for me it is the "how do I feel?" question. I also believe it is a key part of digital transformation: many people feel threatened with the adoption of data and hard evidence fearing it will replace hard won experience; the value is to combine this experience with evidence, not to replace it.
3. ?Commit to thinking time.??Configuring routines to build in thinking and reflection time. Of course not everyone has a dog or lives in the country or has the luxury of no mobile phone signal - but we can architect and test models in our own routines. Try combining with mentoring or the accountability buddies concept to develop the habit.

Last week I spent 20 minutes chasing Gigha around the local park trying to rescue my son's glasses. In the end they were chewed to pieces and it was then suggested to me we should get a second dog as a calming influence (for Gigha, not me). There may well be more dog tales to share in 2023, in the meantime on behalf of everyone at The Data Lab , thank you for your support.

A few resources I'd recommend related to these themes:

1. Fear setting - TED Talk by Tim Ferris Tim Ferriss:?Why you should define your fears instead of your goals | TED Talk
2. Masters of Scale - Podcast interview with Marissa Mayer?How to make the star employees you need - Masters of Scale
3. Good to Great - Book by Jim Collins, particularly Chapter 2.?Good To Great: Why Some Companies Make the Leap... and Others Don't: Amazon.co.uk: Collins, Jim: 0201566620996: Books

Brian Hills : Twitter / LinkedIn / The Data Lab

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