From making faster, smarter decisions to predicting customer preferences and improving user journeys, data skills are opening up a world of possibilities for small and medium-sized enterprises (SMEs). So it’s no surprise that data has become one of the top priorities for the UK’s smaller businesses, with 37% planning to increase their use of data and insights throughout 2022.
To enjoy the widespread benefits that data offers, SMEs need to have access to the necessary skill sets. But this is proving difficult, as companies of all sizes find themselves competing for a limited talent pool.
Fortunately, help is at hand. We’re Tech Intellect, an IT Delivery and Technical Talent specialist, and we believe in empowering SMEs to diagnose and solve their business challenges. We’ve produced this in-depth guide, which offers a roadmap for smaller businesses looking to build or expand their data teams. In it, we cover:
- Where to find the best talent
- Key data skills to hire for in 2022
- Factors in assessing candidate suitability
- Salary expectations
- Team size and structure
1. Where to Find the Best Talent
Data may be digitised, but when it comes to finding talent with key data skills, traditional tactics still work best.
There is a huge amount of noise on LinkedIn and other online platforms about data. That makes it extremely challenging to cut through and find the right people – not just in terms of skills, but also cultural fit. Networks and contacts are therefore the most effective way to reach data talent.
If you’re looking to expand your data network, check out our regularly updated list of data networking events. And if you don’t have the time to organically build a network of data talent, Tech Intellect are here to help. We connect SMEs with the tech talent they need to diagnose and solve their business challenges. Get in touch today to find out more.
2. Key Data Skills to Hire for in 2020
While every business and every data project is different, some skills are particularly valuable within the current business landscape. Indeed, five of LinkedIn’s 10 most in-demand hard skills for 2020 are either directly related to data, or data-adjacent:
Cloud Computing
What is it?
- The on-demand delivery of computing services – such as servers, data storage and software – via the internet.
Why is it so important?
- Holds the key to effective data storage and accessibility through technical architecture, design and delivery.
Analytical Reasoning
What is it?
- The ability to look at information – whether qualitative or quantitative in nature – and discern patterns from it.
Why is it so important?
- Enables businesses to better understand their data and use it to generate insights needed to inform stronger, smarter strategic decisions.
Artificial Intelligence
What is it?
- A field within computer science dedicated to creating intelligent machines with the ability to work and react like humans.
Why is it so important?
- Greatly enhances the capabilities of the human workforce, supporting businesses to deliver products and services that are more personalised, relevant and innovative.
Business Analysis
What is it?
- The practice of defining requirements and recommending solutions to deliver organisational change.
Why is it so important?
- Supports better decision-making across all areas of business, allowing SMEs to identify new opportunities, avoid unnecessary costs and realise potential benefits.
Scientific Computing
What is it?
- A fast-growing field focused on understanding and solving complex problems through the use of advanced computing capabilities.
Why is it so important?
- Allows businesses to develop machine learning models, and use programs like MATLAB and Python to apply analytical and statistical approaches to big data sets.
3. How to Assess Candidate Suitability
Technical skills are hugely important when building an SME data team – but they are only one piece of the puzzle. Just as significant are the personality traits, softer skills and other factors that dictate whether or not a candidate will fit in well at your organisation. Consider the following:
- Do they identify with your culture and values? If a candidate shares your vision, they will naturally feel more empowered to help make it happen. Likewise, if they are a good cultural match, they are more likely to work productively and efficiently on collaborative projects.
- Do they have a rounded skill set, or a niche specialism? All-rounders will be able to take on a wider range of responsibilities, but will naturally lack the deep expertise of someone with a specialism. Most SMEs will lean toward more rounded candidates, although the right decision for your business will depend on your specific requirements.
- Are they well-suited to the SME environment? Inevitably, some candidates will shine within a small business setting – where they will likely play a bigger role in delivering change and achieving goals – whereas others are better suited to the structure of the corporate world.
- Can you afford them? Realistically, smaller businesses will often find themselves unable to compete with salary and benefits packages offered by their larger rivals for more experienced talent. For this reason, SMEs may prefer to look within the graduate market, finding candidates with potential and supporting them to develop in the role.
4. Structuring Your Data Team & Understanding Salary Expectations
There is no one-size-fits-all solution to building a data team. Instead, the structure should be dependent on the scope of work, as what is to be delivered can often dictate the ideal team makeup.
However, it’s possible to provide a typical team structure for a common data use case. In this scenario, we’re going to consider the sort of team that would be built to deliver a small to medium-sized data migration from on-premises to the cloud, with two or three data extraction tools on top of the data. We’re also going to assume the team is using agile methodology within the SCRUM framework.
An ideal team makeup could look like this:
- Business Analyst
- 2x Data Engineers
- Data Architect
- SCRUM Master
This team would be able to deliver the scope of work detailed above, but can also be easily scaled into multiple squads in the case of a large migration. For more information on this, check out our guide: “Chaos to Order: Building a Data Team for 2020 (& Beyond).”
As time passes, there may also be a need to add “fringe” – or supplementary – roles to this team, such as a Machine Learning Specialist and/or Data Scientist. Again, this will be wholly dependent on the project scope.
It is just as important to understand the salaries your team would require as it is to know the structure. Any company building or expanding a team needs to go into the process with their eyes open around salary expectations. This is even more important for SMEs, where staffing budgets are inevitably tighter than at large corporates. With that in mind, we’ve used data from IT Jobs Watch to provide current median annual salaries for key data roles in London:
- Data Architect – £85k
- Data Scientist – £75k
- Data Engineer – £72.5k
- Business Analyst – £70k
- Data Modeller – £62.5k
- Machine Learning Engineer – £75k
- Product Manager – £70k
How Tech Intellect Can Support SMEs In Landing the Best Data Talent
Finding the right people for your organisation – both from a technical and cultural standpoint – isn’t easy in the current data marketplace. Competition for top talent in the UK is already high, without factoring in the potential ramifications of Brexit.
That’s where Tech Intellect can help. We build meaningful partnerships with our clients, allowing us to diagnose your business problems and solve them through talent. We have extensive experience of working with SMEs, taking the time to understand not just your company culture, but the culture-within-a-culture that so often exists within technical teams. That helps us to understand how we can work best together, and to support you in making positive change where needed.
Want to find out more about how we work, and how we can support you to build the ideal data team for your business? Email us at [email protected] and we’ll get right back to you.
