The current hype with big data, analytics and artificial intelligence makes hiring and retaining top talents a very hard challenge. The main reasons are the complex blend of hard and soft skills required at a time when the sector is in full expansion.
Over the past few years, I have been setting up and enhancing teams in the digital domain and along the way, I have developed some some strategies that I believe can help organizations in hiring and retaining good data talent. Here are just a few:
Identify in-house talent pools
Many organisations do not easily recognize that data-savvy employees can also be found in unexpected talent pools. One needs to think outside the box and search for physicists, chemists, statisticians, mathematicians, possibly fromwithin your company. These profiles can be very good candidates for data-intensive jobs if you are willing to invest in up-skilling their domain-specific knowledge (e.g. Finance, Insurance, …).
Because of their natural affinity with data, they can become quickly productive once they have even a little knowledge in your sector.
Prepare ad-hoc training pipelines
Be ready to offer ad-hoc training to your new hires, specially tailored to the various “employee stages”: be they new to the organization, new to the industry, new to data and analytics, or ready for next level of analytical mastery. Simple, pragmatic, on the spot trainings can fast-track the productivity of your new recruits.
Care for data-driven decision makers
Data Executives or Project Managers which lead your company’s data initiatives deserve to be included in your talent development programs. Not everybody is aware of the tricks of big data and analytics. Make sure your decision makers grow their knowledge skills, so that they better understand the technology and help in resolving complex situations. Even a little additional knowledge can make a big difference. Failure in understanding what AI and big data really is jeopardize even the most thought through and carefully planned projects.
Use mainstream job titles
Don’t go for fancy job titles, or please do not invent new ones: it is already too difficult to juggle around the thousands of exotic qualifications and technical platform so that you almost need a data scientist to hire a data scientist. Try to avoid using SQL Ninja when you are looking for someone to build robust ETL flows. Use ETL developer. Conversely, don’t title your job description as a Database Analyst if you require Insurance business experience. Use Business Analyst, this makes the job search easier for you, for your applicants and for your HR team.
Do not forget the competition
The marketplace of data-intensive jobs is expanding exponentially. There are countless job opportunities in both start-ups and multinational organizations that are ready to pay over the top prices for mediochre talent. So make sure you understand the competition and can meet the expectations of your hires or be ready to lose them fast.
Give your team a purpose
Last but not least, motivation is key for retaining your top talents: a good salary, a fancy workstation, benefits, trainings, events and freebies will keep talented workforce just OK, but having a bigger purpose with them understanding the ‘why’ of what they are doing and the benefits the results of their work will have will make them feel like “data heroes” and reduce the risk of them looking for another job.
I hope my tips have been helpful, should you have any comments or questions, please do not hesitate to reach out to me, I might be busy but I am always open to learn something new.