Throughout my career, I have been drawn to creating businesses which solve pressing Industry issues. This started back in 2000, when I joined forces with my current business partner Tim Smeaton. At the time, Tim was launching a search business which specialised in finding talent who possessed both technology skills and business literacy - a combination that was in dire need and incredibly short supply. We had a fantastic journey, we learnt an enormous amount and grew that business from a small niche operator to a listed company operating in 70-plus countries with 500 staff. Fast forward to today, it is clear that organisations are still facing the same challenges as they did almost 20 years ago, particularly within the data space. We knew we could go someway to solving this problem by disrupting the traditional consultancy model and creating a workforce which has the correct mindset and data skills to drive an organisation to success. This is exactly what attracted me to this industry, so we took the risk and created Kubrick.
It came very recently at the end of 2018, when our first consultant on site joined one of our early clients. This validated the key reason as to why Kubrick exists. From the outset we promised that we could create a highly-skilled data engineering workforce which could help organisations in their data journey. After two years of our consultants being employed by Kubrick, they were free to join our clients permanently at no cost. I am so proud to witness our very first group of data engineers become part of our clients.
The advice I would give to my younger self would be exactly the same as the advice I offer to the 1,400 applicants we have nearly every month: Have a demonstrable passion for data and the trends happening in the industry; ask high-quality questions which enable you to understand and define the problem you are trying to solve; become a strong critical thinker - spend time developing this skill.In some ways, yes. For example, the implementation of regulatory drivers such as GDPR combined with a more refined industry appreciation of keeping clean, accessible data resulted in the expected market shift towards people with skills in the data governance space. Conversely, taking diversity as one issue, in 2018, collectively as industry, did we do enough to attract under-represented groups into data careers? I anticipated more could have been achieved in driving diversity. At Kubrick, in 2018 we managed to achieve 40% females into our data engineering and data governance teams. I am really hoping that, in 2019, we can achieve more and as an industry we can build the momentum to make data more attractive to a diverse demographic.
Over the last three years since Kubrick’s inception, we have witnessed organisations mature in their approach to data. At the beginning of this period, many businesses perhaps rushed into trying to establish a data science function, without the correct platform and architecture in place. Some built data science teams and launched proof of concepts which ultimately failed as the data environment was not good enough to glean the insights they needed to get a return on their investment. This subsequently led to a growth of data engineers, which sought to build the data platform, subsequently supporting the data science teams in discovering the insights. 2019 will be the year that data governance grows in importance. As the potential power of data is beginning to be discovered, so is its true value. Organisations are beginning to realise how high the stakes are of not having a sound data governance strategy. Businesses and institutions now expect consistent quality, availability, integrity and usability of their data, while satisfying the demands of greater scrutiny and regulations.
We hire people with the right mindset. Hopefully, many of them will form the future DataIQ 100. For us, technical and analytical skills are the only foundation. What really separates people is being able to understand and appreciate how these skills can be applied truly to change a business. Our wins came from creating tests and challenges that accurately identified the skills we look for. We measure their effectiveness over time, by seeing if the scores correlate to our best performing people. Putting effort into being an open employer brand. The best people have a lot of choice, so we spend time on showing what we are like and what we stand for. We do this through multiple channels.
The data industry seems full of benevolent and caring folk who are always willing to lend their skills for a good cause. In this particular case, it’s been so impressive to see the amount of people prepared to lend their time to “Data 4 Duchennes” (Duchennes is a severe type of muscular dystrophy). It aims to use various sources of data collected from patients and then to discover insights which can improve the quality of their lives.Data and analytics technology/service provider