Araminta is a Data Management Consultant for Ortecha in London (working alongside EDM Council stalwarts Mark McQueen and Pete Youngs) in a new phase of her twenty-year data career. Happiest when combining contrasting disciplines, she’s an Oxford-educated physicist with an interest in castles, a systems engineer with a preference for people over machines, and a DCAM champion with an enthusiasm for information design. She has never baked banana bread.

Interview Questions

Can you describe your current role?

I enjoy variety in my work so am fortunate to wear three ‘hats’ at Ortecha, the specialist Data Management consultancy. I spend most of my time as a Principal Consultant, running DCAM Assessments and helping organisations improve their Data Management capabilities. I have a particular interest in making Data Management more engaging and easier to understand, so I’m delighted to be leading our Data Culture practice. And I have an internal role as Head of People, Comms & Culture, fostering a supportive, efficient, inspiring environment for our fabulous consultants.

How long have you been in your current role?

I’ve been in my triple-role for 9 months, although I’ve worked with some of the Ortecha crew before, so it already feels like home.

What do you like best about your job?

One of the advantages of working at a small company is being able to draw on the collective wisdom of colleagues in different areas of expertise. Each client’s Data Management journey is unique, and it’s a satisfying intellectual puzzle to develop an approach that works well for them - and enormously rewarding to see it become reality.

What do you think is the most significant challenge to female leadership? Why?

The main challenge seems to be defining what female leadership really means, because male leadership has traditionally provided the template for what qualities are required. Studies show that women who try to emulate men (for example, by being assertive or direct) are perceived to be less likeable; those who take a more typically feminine approach (by, say, being more collaborative and asking for input before making a decision) are seen as weak. In reality there is plenty that male and female leaders can learn from each other, and the process should get easier as the numbers start to balance out. I hope that ultimately, women in data will become the norm, not the exception.

What was your first paying job and what did you learn from it?

In university holidays I worked as a kitchen assistant at a local high school: helping to prepare lunch, dish it out to hundreds of pupils, and wash all the crockery and cooking pans afterwards. It was exhausting! I learnt to work quickly under pressure and appreciated the camaraderie of my fellow-dinner ladies - we really did operate as a team to get all the food ready on time, and shared the different clean-up roles so no-one was stuck with the worst jobs for long.

Who inspires you and why?

My earliest inspiration was the maths & science television presenter Johnny Ball – he was incredibly enthusiastic about the facts he was imparting, and so energetic in his little skits and demonstrations that I still remember them forty years later. Nowadays I am most impressed by people who can make complicated subjects understandable: the blend of empathy for the audience and mental discipline to avoid technical jargon is rare.

If you weren’t working in your current role, what would you want to do?

I would love to apply my data experience from the corporate world to other subjects like archaeology and history. In academia, cutting-edge projects using Artificial Intelligence and Machine Learning are already deciphering spidery old handwriting, categorising Roman pottery sherds and digitising old maps. Like all Analytics, it needs to be based on a solid foundation of high-quality, well-managed data – but that’s not so easy when some of your data was lost in the Great Fire of London in 1666! It’ll be fascinating to see the techniques and insights that emerge.