Why it’s Getting Harder to Recruit Talent in Today’s Digital World

Digital Transformation isn’t exactly news: we now have an entire generation of working adults who don’t remember life before the internet.

Over the last few years the rise of the new digital economy has shattered norms, shaken established business models and empowered consumers. Businesses that want to thrive in the modern economy are embarking on a Digital Transformation journey and need to deliver the necessary people, processes and cultural changes to do so. This requires a new generation of talent with an entrepreneurial mindset who can harness technology, drive innovation and empower this change.

The trouble is, recruiting this new generation is easier said than done. One of the biggest challenges to delivering Digital Transformation is gaining access to the people with the new digital technology skills required to do so.  PwC’s 19th Annual Global CEO Survey revealed that 73% of CEOs identified a lack of new technology skills as a major threat to their business in 2016.

Organisations are struggling more than ever to find the right people with the right technology skills because a perfect storm is brewing; we are faced with an exploding skills gap combined with a fundamental shift in the way people are increasingly looking for work. The move to digital isn’t just disrupting the way in which we order taxis or book holidays, it is also creating new societal norms. The way in which we interact with each other, the very nature of how we communicate, is changing the entire employment industry.

This is hugely affecting your ability to recruit high quality tech professionals because your existing recruitment strategies are outdated, ineffective and not keeping pace with this change. Here’s why:

A change in mindset: proactive to reactive

Top talent now expect job opportunities to find them which means prospective hires now approach jobseeking as a reactive, rather than a proactive, process.

Tech candidates expect you to come to them, but only if you have something they care about, and only if you’ve done the necessary legwork. The digital ‘push model’ which was once highly effective, is now open to misuse – if you send candidates unwanted alerts, notifications, and emails, they’ll ignore you. If you want to learn how to recruit tech talent superstars, never forget: they can afford to be selective because the power base has shifted from you, to them. 

Move away from LinkedIn

LinkedIn was once a valuable tool for recruiting tech talent. It’s not anymore. The people you want to hire just don’t use the platform as much as they once did.

That’s because when they do they are faced with an almost-daily barrage of job offers (most of which are entirely untargeted and irrelevant), a constant stream of notifications and irrelevant messages and endless invitations to connect.

As a result, candidates are deactivating their accounts or leaving them dormant and migrating to other online communities and networking groups. A number of IT professionals, have moved to online communities such as SpiceWorks. They want to form connections and start conversations with sympathetic, technically-minded people, and anyone posting a vacancy has to know their stuff in order to be taken seriously.


The antisocial network

As people increase their digital footprints, so does the volume of job alerts and notifications. Whether on LinkedIn, Facebook, Stackoverflow or email, they are being subjected to a constant barrage of notifications about jobs.

This phenomenon is now breeding huge apathy and desensitisation towards these intrusive notifications. In fact, prospective candidates have become so disillusioned with the working practices of mainstream recruiters (both in-house and agency), they’re now considered like a new form of paparazzi.


The playing field is a level one

Yours is not the only company trying to hire these candidates to enable Digital Transformation. In the past, top companies were able to spend huge budgets to attract top talent. Today, however, the playing field is more of a level one.

Every company now has the same ability to market their vacancies to the same talent pool. It’s no longer about throwing money at the situation: anyone looking for tech skills has to be able to pay well for them, so a high salary will only get you so much engagement.


What does this mean for you?

Talent acquisition is no longer about identification, it’s about engagement. Engaging with the people your business needs the most, is becoming more difficult, and more competitive. Why? Because the way candidates are looking for work is changing, but you’re still adopting old fashioned and outdated recruitment strategies. So it’s time to move with the digital economy, adapt and change with them.

 

Struggling to source the digital talent necessary to drive your transformation?

Third Republic are specialists in their fields; using modern recruitment methods to access passive pools of talent, we act as a partner for our clients’ talent needs. Get in touch to learn more about how we can help.

More Insights

Benjamin Hanrieder

Q&A Benjamin Hanrieder (CTO, Engel & Volkers)

In this interview, Benjamin Hanrieder, CTO at Engel & Völkers Technology, discusses the company’s digital transformation, software development practices, and the role of the Cloud Platform Team in ensuring reliable and secure infrastructure. Mat Roche (MR): Can you give us an overview of your background?  Benjamin Hanrieder (BH):  Hi Mat,

Read more >

Get In Touch

Fill out the form below, and we will be in touch shortly.

Seniority

Software Developers
Senior Engineers
Software Architects
Senior Software Architects
Software Tech Leads
Senior Software Tech Leads
Software Tech Lead Managers
Senior Software Tech Lead Managers
Director of Engineering
VP of Engineering


Software Developers
Senior Engineers
Software Architects
Senior Software Architects
Software Tech Leads
Senior Software Tech Leads
Software Tech Lead Managers
Senior Software Tech Lead Managers
Director of Engineering
VP of Engineering

 

Software Developers
Senior Engineers
Software Architects
Senior Software Architects
Software Tech Leads
Senior Software Tech Leads
Software Tech Lead Managers
Senior Software Tech Lead Managers
Director of Engineering
VP of Engineering

 

Role

Full-stack Developers
Back-end Developers
Front-end Developers
DevOps Engineers
SRE Engineers
Cloud Engineers
Platform Engineer
Security Engineers
Mobile Developers
App Developers
No1 software engineers

Full-stack Developers
Back-end Developers
Front-end Developers
DevOps Engineers
SRE Engineers
Cloud Engineers
Platform Engineer
Security Engineers
Mobile Developers
App Developers
No1 software engineers

Full-stack Developers
Back-end Developers
Front-end Developers
DevOps Engineers
SRE Engineers
Cloud Engineers
Platform Engineer
Security Engineers
Mobile Developers
App Developers
No1 software engineers

Skills

React.js
Node.js
AWS
JavaScript
React
Native
PostgreSQL
Ruby on Rails
Java
Angular
Golang
PHP

React.js
Node.js
AWS
JavaScript
React
Native
PostgreSQL
Ruby on Rails
Java
Angular
Golang
PHP

React.js
Node.js
AWS
JavaScript
React
Native
PostgreSQL
Ruby on Rails
Java
Angular
Golang
PHP

Sample By Job Family

Data Scientists
Data Engineers
Data Architects
Data Modelers
BI Developers
Data Analysts
Data Quality Engineers
Data Governance Experts MLOps Engineers
DataOps Engineers
Data Product Managers
Executive Data Leadership

Data Scientists
Data Engineers
Data Architects
Data Modelers
BI Developers
Data Analysts
Data Quality Engineers
Data Governance Experts MLOps Engineers
DataOps Engineers
Data Product Managers
Executive Data Leadership

Sample of Platforms & Tools

Cloud DW: Snowflake, BigQuery, Redshift ETL/ELT Tools: Airflow, dbt, Fivetran, Talend Big Data Frameworks: Spark, Hadoop, Kafka BI & Visualization: Tableau, Power BI, Looker ML Libraries: TensorFlow, PyTorch, Scikit MLOps Platforms: MLflow, Kubeflow, W&B Data Governance: Collibra, Alation Data Observability: Monte Carlo, Databand Data Lakes: Lake Formation, Delta Lake SQL/NoSQL DBs: PostgreSQL, MongoDB Real-time Analytics DBs: Apache Pinot, Druid Gen

Cloud DW: Snowflake, BigQuery, Redshift ETL/ELT Tools: Airflow, dbt, Fivetran, Talend Big Data Frameworks: Spark, Hadoop, Kafka BI & Visualization: Tableau, Power BI, Looker ML Libraries: TensorFlow, PyTorch, Scikit MLOps Platforms: MLflow, Kubeflow, W&B Data Governance: Collibra, Alation Data Observability: Monte Carlo, Databand Data Lakes: Lake Formation, Delta Lake SQL/NoSQL DBs: PostgreSQL, MongoDB Real-time Analytics DBs: Apache Pinot, Druid Gen

Sample of Skills Delivered

Programming in Python, R, and SQL
Python
Data Modeling Statistical
Analysis ETL/ELT
Pipeline Development
Database Design & Administration
Machine Learning Fundamentals
Cloud Data Warehousing
Data Ethics & Compliance
Data Security
Data Visualization & Storytelling
Real-Time Data Streaming

Programming in Python, R, and SQL
Python
Data Modeling Statistical
Analysis ETL/ELT
Pipeline Development
Database Design & Administration
Machine Learning Fundamentals
Cloud Data Warehousing
Data Ethics & Compliance
Data Security
Data Visualization & Storytelling
Real-Time Data Streaming

Sample By Job Family

AI Software Engineers
Gen AI Engineers
Machine Learning Engineers
Deep Learning Engineers
Prompt Engineers
AI Research Scientists
NLP Engineers
Computer Vision Engineers
MLOps Engineers
AI Product Managers
AI Governance Specialists
AI Ethics Office
AI Architects Executive

AI Software Engineers
Gen AI Engineers
Machine Learning Engineers
Deep Learning Engineers
Prompt Engineers
AI Research Scientists
NLP Engineers
Computer Vision Engineers
MLOps Engineers
AI Product Managers
AI Governance Specialists
AI Ethics Office
AI Architects Executive

Sample of Platforms & Tools

LLMs: Open AI, Anthropic, Llama, Gemini ML Platforms: SageMaker, Vertex AI, Azure ML ML Libraries: scikit-learn, XGBoost, LightGBM DL Frameworks: TensorFlow, PyTorch, Keras LLM Frameworks: LangChain, LlamaIndex Vector Databases: Pinecone, Weaviate, Milvus Data Science Notebooks: Jupyter, Colab, Kaggle Data Visualization Libraries: Matplotlib, Seaborn NLP Libraries: Hugging Face Transformers CV Libraries: OpenCV, Pillow, Albumentations MLOps Tools: MLflow, Kubeflow, W&B

LLMs: Open AI, Anthropic, Llama, Gemini ML Platforms: SageMaker, Vertex AI, Azure ML ML Libraries: scikit-learn, XGBoost, LightGBM DL Frameworks: TensorFlow, PyTorch, Keras LLM Frameworks: LangChain, LlamaIndex Vector Databases: Pinecone, Weaviate, Milvus Data Science Notebooks: Jupyter, Colab, Kaggle Data Visualization Libraries: Matplotlib, Seaborn NLP Libraries: Hugging Face Transformers CV Libraries: OpenCV, Pillow, Albumentations MLOps Tools: MLflow, Kubeflow, W&B

Sample of Skills Delivered

Generative AI Development
Machine Learning Algorithms
Deep Learning Architectures
NLP and NLG
Computer Vision
Data & Feature Engineering
MLOps & Model Deployment
Statistical Analysis & Hypothesis Testing
Python and R Programming Expertise
Model Evaluation & Performance Tuning
AI Governance & Compliance
Autonomous AI Agent Engineering
Building Agentic AI Applications

Generative AI Development
Machine Learning Algorithms
Deep Learning Architectures
NLP and NLG
Computer Vision
Data & Feature Engineering
MLOps & Model Deployment
Statistical Analysis & Hypothesis Testing
Python and R Programming Expertise
Model Evaluation & Performance Tuning
AI Governance & Compliance
Autonomous AI Agent Engineering
Building Agentic AI Applications