Could Democratising Analytics Be The Solution To The UK’s Tech Skills Crisis?

Complexities around digital analytics threaten to hamper startup and SMB innovation amid UK tech talent shortages 

Digital analytics has become a critical tool for businesses, yet it remains frustratingly complex and inaccessible for many. While larger, well-resourced organisations can navigate the challenges of setting up and managing analytics, smaller companies and startups have traditionally suffered. The UK’s SMBs and startups are key to the economy, accounting for three-fifths of employment and around half of turnover in the UK private sector. And yet, these businesses often lack the resources to invest in a big data team, commonly relying on just one or two analysts – who, in turn, get overwhelmed by the myriad of data requests.

This is further exacerbated by the scarcity of technical skills in the UK, which recently ranked 45th globally for technology and business skills proficiency. The UK government launched Skills England to address nationwide skills gaps, but progress in this area – no matter how positive – will be slow. At the same time, the data and AI boom isn’t slowing down, threatening to outgrow the available skills in the UK. Against this backdrop of an increasingly digital world, companies simply need to be able to access, understand and use their data. 

Why is digital analytics so hard for SMBs?

Digital analytics can unlock huge gains for companies, but it’s been too hard – and too expensive – for too long. You have to start from a blank slate, and it takes a ton of engineering resources to set up data pipelines and instrument events. This takes weeks, especially if you run into data taxonomy issues and have to start over. 

Once you’re set up, using analytics to generate insights that are actually helpful requires asking the right questions, which oftentimes only a data expert will know. It’s perhaps no surprise then that, while 94% of IT leaders trust their data, more than half express frustration with accessing it. Organisations are heavily dependent on their small, stretched data teams. The climbing number of data requests creates a bottleneck, and other crucial departments – like sales and marketing – can’t get their hands on the insights needed to drive business growth. This issue is confounded within smaller organisations, whose teams usually have to wear multiple hats. This means the time they can spend on specific tasks – in this case, digital analytics – is heavily restricted.

One obvious answer here would be to simply train more analysts. However, this is a time-intensive, resource-heavy process – a generation of new data analysts won’t be born over night. Small companies need a quicker solution. 

How can we simplify digital analytics?

Digital analytics platforms need to be easy to use and accessible to technical and non-technical employees alike. The idea of democratising analytics has taken a firmer foothold in recent years, as a way to combat the ever-present technical skills shortages in the UK. 

It is with this in mind that Amplitude rebuilt its platform with the launch of Amplitude Made Easy, eliminating the digital analytics learning curve. Now, teams can set up analytics with a single line of code. The new platform allows teams to implement comprehensive analytics using minimal code – or even no-code – thereby significantly reducing setup time and resource requirements. The system includes AI-assisted tools that help generate insights, making data analysis more accessible to team members without specialised technical skills. By radically simplifying its platform, Amplitude has streamlined how companies get set up, get insights, and get value. 

“The value of data, and the importance of data analytics, is permeating every department of modern organisations – from sales, to marketing, to product,” said Lee Edwards, EMEA VP, Amplitude. “As platforms get easier to use, and the use of handy tech like low-code/no-code grows in prevalence, we’re moving towards a future where anyone, regardless of technical know-how, will be able to get valuable insights from data.”