A new survey by Reveal has indicated that more than half (53%) of IT professionals say that recruiting developers with the right skills will be the biggest business challenge for 2022.
This is also besides the fact that the demand for developers is outpacing the supply.
With skills mostly including cloud computing, AI and machine learning, as well as analytics and big data, there are a few ways to deal with this challenge.
From developing the necessary skills internally, to outsourcing the right company to get the job done, here are three ways to help you get the talent necessary for digitisation.
#3) Develop The Talent Internally
An obvious route to take is to focus on developing your own in-house talent.
This can be through training and mentorship programs, as well as by offering competitive salaries and benefits.
It also allows you to groom future leaders for your company. Which helps to ensure continuity and also to retain valuable knowledge and expertise within your organisation.
In addition, developing in-house talent can help you stay agile and responsive to changes in the market. Your teams will be familiar with your company’s culture and systems, and will be able to hit the ground running when new projects come up.
However, it can be expensive to train and develop employees in-house. Which is especially true if you’re not able to find candidates with the right skill sets and experience.
On top of that, it can take time to train employees and get them up to speed. Which can end up delaying project timelines and disrupting your workflows. Which also take effort and resources away from other projects.
#2) Try A Recruitment Agency
Another option is to partner with a recruitment agency that specialises in finding qualified developers.
This can be a cost-effective way to find the right candidates,while taking the burden off of your HR department. And these recruitment agencies typically have a large pool of candidates to draw from, helping you find the best fit for your company.
They also have expertise in assessing candidates’ skills and matching them with the right job.
But, there are a number of disadvantages.
First, it can be expensive to work with agencies. Which is especially true if you need to hire a lot of employees.Then, it can be difficult to find the right agency. There are plenty of agencies out there, which make it hard to determine which one is right for your company.
Finally, it can be difficult to retain employees once they are recruits. This is because they may be tempted by offers from other companies.
#1) Outsource The Talent
Finally, you can outsource the talent and target specific cases within your organisation.
Perhaps you need to migrate your existing infrastructure to the cloud. Or need your big data cleaned, sorted and made accessible. Maybe you require healthier, cost-effective machine learning models that don’t constantly break.
Depending on your needs, it might be easier to outsource the talent and target specific use cases. Which can be especially helpful if you don’t have the resources or expertise to develop your own team.
Outsourcing also allows you to focus on your core business and leave the development work to experts. Third-party development firms can help you scale your development operations quickly and efficiently.
They also have expertise in specific areas, such as UX design, mobile app development or web development.
It essentially means that you can get the help you need without having to hire a full-time developer.
And if you already have a data scientist, there are a few reasons why it might be better to outsource data and machine learning engineers:
- Complexity – Data engineering and machine learning are complex disciplines. It’s often difficult to find someone with the right skillset who is also a good fit for your organisation.
- Adaptability – These disciplines are also rapidly evolving fields. The skills required today may be different from what is required in the future. By outsourcing these functions, you can ensure that you are getting the latest and most up-to-date technology and expertise
- Affordability – Data engineering and machine learning can be time-consuming and resource-intensive. If you already have a data scientist, you may not have the time or resources to also invest in data engineering and machine learning
By outsourcing these functions, you can free up your data scientist to focus on more strategic tasks, such as optimising machine learning models and improving your business’s understanding of its data.
Get The Job Done With Us
If you’re looking for a solution to your IT challenges, look no further than Teraflow.ai.
We provide cutting-edge solutions with our data engineering and machine learning experts. Not on the cloud, yet? We can migrate you to GCP or AWS safely and securely.
With us, you get access to all of the developers with the right skills without having to worry about recruitment or retention yourself!
