With a background in mechanical engineering and software engineering, my career has spanned many disciplines and global roles, starting in the Gulf region in the Middle East and India. This was followed with management studies in the UK and the completion of my chartered accountancy qualification. At the same time, my career took me to one of the large consultancies in operations, technology consultancy and programme delivery, working for many large global and UK organisations.
All this led to pursuing a leadership role at Dufrain (a data management, data engineering and analytics services company), to define and execute a strategy to build capability, run the consulting arm and deliver new offerings to clients. This year, I am involved in running all aspects of our business, from hiring and growing talent to delivering successful outcomes for clients on data initiatives. I am also working on developing our data business further through new internal capability and propositions, as well as effective sales and marketing.
There have been various moments throughout my career where I have been immensely proud of what was achieved. From my first decent looking Powerpoint slide and a promotion or a personal or work milestone to a collective team achievement and project outcome, I will struggle to pinpoint one. However, one of the most recent ones was being made managing director of our business in 2019.
One person who has recently stood out is someone who I was fortunate to grow up with in my childhood years. His achievements prove that, no matter what your background is or where you come from, you can achieve great things in life with the right dedication and commitment. His first venture gave him numerous global awards including from The Economist and Time, he was also World Economic Forum social entrepreneur of the year and named in the MIT Tech Top 35 under 35.
With many of the advancements in algorithms/applications and computing power to fuel AI and data science, as well as the vast improvements in the general maturity of tech landscape, you would have expected many organisations to fully harness the benefits at scale from this by 2019.
However, the majority still struggle to do so at enterprise level and many achievements are still in silos or at a local level. So, a lot of the larger organisations took a pause to catch a breath and prioritise budgets for this year on getting the fundamentals right (access to the right data at the right time for the right people with the tools to do basic analytics efficiently) ahead of all the “sexy” stuff alone.
In parallel to getting the data foundations in place, the democratisation of AI will begin to accelerate, with developments in open source and cloud platforms. Currently, most organisations are at the prototype/proof of concept stage to see what works best. The more mature organisations have some successful deployments as well as multi-year roadmaps in place (albeit not necessarily always covering the whole enterprise) and it’s now into the difficult delivery phases with constrained budgets.
For everyone else, this is the year to ensure data is high up on the agenda, as it’s no longer about a competitive market advantage but about survival. Also, there are armies of data scientists coming on to the job market who don’t fully realise that a huge part of their jobs won’t be creating cutting edge models but will be cleansing, preparing, integrating data and deploying models into production. So, we will begin to see a slight deflation of the data science expectations bubble.
Nothing around us will be immune from the advances in data and technology as can already be observed for many sectors. If anything, there will be positive disruption across all sectors. AI (in some way or other) will eventually be at every firm’s core as a weapon to gain competitive advantage.
The biggest opportunity will be for us humans to move away from repetitive, non-value adding and mundane tasks to a step further up from where we are individually on the value and skills ladder to better use what is unique to us – our brain power, augmented with technology advancements, to solve some of the biggest problems in every sector and therefore the world.
The real challenge in making the best use of data to achieve successful transformation is not just about the tech solution. It’s about getting the basics right and ensuring all the key ingredients are in place - senior buy-in; transformation led by the business; right operating model; a culture that promotes data literacy and understands the importance of data-driven decisioning; investing in data management foundations; collaboration across silos; and disciplined project delivery management to get from A to B. Most programmes fail - or don’t achieve the necessary outcomes - due to that last point alone (incomplete scope, every good and bad practice badged as agile, delivered late and over-budget) and yet hardly anyone talks about this.