What is the number one thing enterprises should consider when looking at big data?
The first step is to know what specific, measurable outcomes your organization is trying to achieve so your analysis will help drive those outcomes.
Understand the business case that the enterprise is trying to solve for.
Stop looking at Big Data unless you have “big focus.” An enterprise should have clear expectations aligned to its strategic objectives before investing in data analytics.
Big data in many cases these days is hard to distinguish from just a whole lot of data. Big data, small data, fuzzy data. Instead of starting with the data, we need to start with what job we are trying to accomplish—what value are we creating and why would someone want to hire us and our data to do that job? There's quite a bit of hype these days—however there are enormous gains we can make in healthcare if we can turn the information we have about how healthcare works – from supply chains, to claims data, to clinical records – into ways to improve our jobs to be done.
How do you move “big data” from an idea to a system?
Unlock the data from your IT systems and begin to analyze it, draw conclusions and implement changes based on those conclusions. Drive adoption. Set achievable goals and monitor performance. Join one or more benchmarking pand strive to be in the top percentile of your peers.
The move requires the right people resources with the relevant expertise.
Organizations must have flexibility to evolve. Your investment will be optimized by prioritizing data you need for visibility into particular events (e.g. customer behavior, operations and staff performance management, or whatever informs your strategy).
In order for it to be meaningful and of real value, it needs to be both insightful and actionable. In healthcare, you need to consider how the data can be used to optimize the system of which you are one part. As an example, how do you compare who is providing good care and who isn't? There are many factors that impact this—from the region, the provider's specialty, the type of patient's they treat, and even their patient's genetics. By pulling the right data together, you can generate insights into utilization patterns and you can gain insights into where variations exist, but for those insights to be actionable, you need to understand how this data will influence how a patient chooses his/her doctor. Otherwise, it's just nice data.
What does it take to make big data work?
Organizations must be prepared to use change management methodologies to help team members evolve.
To achieve meaningful impact from big data analytic insights requires the implementation of a sufficiently resourced program focused on meeting the objective. You don't get value from the data absent good analytics and an effective program to leverage the learned insights.
Culture cannot be over-emphasized in becoming a data-driven organization.
Making big data work requires engagement. Once you have insightful information, you need to choose how you present it to the people who need it in a way that they can consume and that impacts their decisions. As healthcare moves to a more consumer oriented model, this data can help patients be healthier and be smarter shoppers. To do so, they need insights regarding the best care at the best cost and a way to take action to make better healthcare choices. For this to be happen, the information needs to be available to patients at the time they need it in their own context—through their computer, their iPhone, their tablet. What makes this more complicated is many patients aren't consumers today, so this also requires incentives for behavior change.