In this article, Joanna Schloss, business intelligence and analytics evangelist at Dell Software, explains why healthcare organisation will benefit from taking advantage of 'big data'
Big data has generally been described as a set of data that is so large that it’s difficult to analyse and get useful information from, but when analysed can derive insights and information to make better business decisions.
As the perception of big data moves from futuristic hype to real-world opportunity, the promise of improved decision-making and increased operational efficiency has more healthcare organisations actively engaging in data analysis projects than ever before. That no longer just means more enterprise-sized organisations, either. Midmarket organisations are jumping on the big data bandwagon in a big way.
As the perception of big data moves from futuristic hype to real-world opportunity, the promise of improved decision-making and increased operational efficiency has more healthcare organisations actively engaging in data analysis projects than ever before
In fact a recent survey by Competitive Edge Research Reports indicates that an astounding 96% of midmarket organisations are either already in flight with a big data initiative, or plan to start one in the next year. In addition, Gartner also shared research with the market at the end of 2013, demonstrating that the healthcare sector would be a leading vertical to ‘tip their toe in the water’ of big data over the next two years.
One of the benefits to being a healthcare organisation that’s later to the game in the adoption curve of any technology cycle is the opportunity to learn from those who came before you, and in the case of midmarket healthcare organisations about to embark on a big data project, their forerunners have left a trail of lessons learned. Here we’ll look at the three most-important lessons mid-sized healthcare organisations should consider to be successful.
Lesson 1:
Lack of alignment with executive stakeholders will derail any project
Data analysis done right is not about technology. It’s about business. Before you start any big data analytics project, you first need to secure the support of the organisation’s executive stakeholders. If your key executives aren’t prepared to make tangible business decisions based on the findings of a big data project, the project itself will have served no purpose.
Lesson 2:
Don’t fixate on infrastructure savings
One of the benefits to being a healthcare organisation that’s later to the game in the adoption curve of any technology cycle is the opportunity to learn from those who came before you
Many big companies initially thought moving their archive data off legacy databases with expensive license requirements and onto the nearly-free clusters of databases would yield significant cost savings. While shifting data to these sources can in fact save your organisation on licensing costs, the labour required to architect, deploy and manage these systems can be significant. The takeaway for midmarket organisations is this: Factor labour costs into your ROI calculations, but, more importantly, don’t fixate on infrastructure savings to begin with. Focus instead on outlining and answering questions that are critical to your business. That’s where true cost savings are ultimately found.
Lesson 3:
Data scientists aren’t quite unicorns, but they’re close
Simply put, labour requirements in the big data realm are difficult to satisfy. Though new educational programs are now being created with increased regularity, healthcare organisations were not initially equipped to handle the tremendous demand for so-called data scientists. If deep-pocketed enterprise companies can’t go out and hire the talent they need, chances are you won’t be able to either. Instead of focusing on finding a single data scientist, you should instead focus on building data science teams from within your organisation that can manage your customised big data initiatives.
If your key executives aren’t prepared to make tangible business decisions based on the findings of a big data project, the project itself will have served no purpose
Organisations that wish to remain viable and avoid being outmoded by their competitors or outgrown by their customers need to embrace a data-driven approach to management and decision making. With the benefit of hindsight, midmarket companies can avoid the big data pitfalls by making collaboration between IT and lines of business a priority and building on the data science resources available in their IT team.
A data analytics project is of little value if you can’t trust the validity of its findings. However, today the vast majority of these big data pitfalls have been exposed and the path to success is clear. For midmarket companies, it’s now just a matter of following it.