Big data has been around for years but it’s only recently that small businesses have been able to use it at the rate of the larger players. 

In healthcare, SMEs are using big data to solve many problems. Thriva is a UK-based preventative healthcare SME that offers finger-prick blood tests, GP analysis and a data-led dashboard to improve health. People using Thriva can proactively track things like cholesterol, liver function and diabetes risk. 

Big data analysis is absolutely core to its success, and the company has processed more than 100,000 results. One of its first tech hires was a computer science and artificial intelligence graduate who leads on all data. 

But SMEs are also using big data to solve productivity problems. For example, digital clinic company MedicSpot is using big data to improve its growth strategy, identifying new geographical areas to move into by analysing thousands of different data points. 

“Analysing big data is becoming cheaper and cheaper,” says founder Dr Zubair Ahmed, “and this does give smaller companies the scope to combine big data with their own insights to compete with established players. Big data is not needed by all SMEs, but data collection and analysis can be a very powerful way to help stand out from competitors.” 

But there are caveats: “Compliance is quite strict in how you can collect and analyse personal data,” Ahmed warns, “especially with the new General Data Protection Regulation [GDPR]. The potential fines for messing up here run into the millions. The data also has to be analysed and acted on correctly, as failure to do so could end up hindering business growth.” 

Jake Freivald is VP product marketing at US-based international data analytics company, Information Builders. The company has worked with a US health network to develop a patient-centric data repository to include clinical and administrative data. 

“The way to get the most value from data is to develop visualisation tools, or dashboards, that allow people with different roles to use the same combination of data sources to identify key performance indicators, make decisions and take actions,” Freivald says. 

The important thing, says Freivald, whether they are a clinical director, impact and quality manager, chief operating officer or an evidence officer, is that they “should be able to reconcile the data that they are seeing with what everyone else sees. This unified view of the same data sources allows everyone in the healthcare system to pull together.”

Data drives everything diabetes-support company diabetes.co.uk does. The company, which employs a small team of data specialists, offers digital health interventions, or digital therapies, based on the information generated.

“The application of big data is truly life-changing. It’s enabling people to live longer, happier and, ultimately, healthier lives,” says founder and CEO Arjun Panesar. But the company is also using big data to streamline its own processes: “As we’re constantly analysing huge amounts of data, we have had to optimise our printing services,” Panesar says. “We’ve started to mine our internal data to determine spikes in printed paperwork, which has helped us figure out how our campaigns are affected by printing volumes, devices that aren’t being utilised to their maximum capacity, and internal processes that have a business case for becoming digitalised.”

Panesar believes healthcare SMEs have been slow on the big data uptake. “The finance, energy and transport industries have been quick to learn from big data,” he says. “However, the health industry has only seen a surge in the generation and application of big data over the past five years. This makes sense. Lives are at risk in healthcare, so you can understand why innovation has been slow to propagate.”

Ensuring data validity and consistency in healthcare is paramount, says Panesar, but the rewards can be enormous. “Quite simply – it allows us to become more intelligent – and in this case, more efficient. It can help identify how to redistribute resources in order to support those who truly require more help.” 

However, Thriva CEO Hamish Grierson adds a word of caution. “Data is great but don’t get too saturated in it. We utilise data with medical rigour from our medical director, to make sure that we set out with the right questions. Data for data’s sake is never good. Make sure you clearly set out what you want to use it for, first,” she says. 

“Always add a human element. Data is there to be interpreted. Speaking to your customers regularly allows you to put a human voice to the data. Data will only show so much.”
Freivald says that the biggest pitfall to avoid in big data is “stovepiping” information, where raw data is presented without any context or analysis. This, he says, results in people in different parts of the healthcare system seeing different versions of the truth: “Data viewed in isolation from other sources might lead a CEO to conclude that an NHS trust needs to make redundancies to reduce the staff bill – whereas a quality and impact manager would view a different data set and decide that the trust is delivering an effective service but needs to recruit more nurses to reduce reliance on agency staff.”