By Simone Chavoor
Digital and Content Marketing Manager
The average car buyer spends 8 hours and 42 minutes online to research a new vehicle before ever stepping foot into a dealership. As a result, car buyers now visit 1.6 dealerships throughout their buying process, as opposed to ten years ago, when they visited 5. They arrive armed with knowledge and ready to take decisive action. In other words: the data now available to the consumer has transformed their decision-making process.
This hyper-connected world delivers data that anyone can use to make smart choices, and it’s no different for the Life Sciences industry. We already know that a big data strategy is essential to any organization looking to stay ahead of their competition, yet too many companies have sequestered this powerful resource within the realm of their IT and analytics departments. By siloing their data instead of opening it up to all departments, many organizations miss out on the opportunity to have every person make better, data-driven decisions. It’s now time to include data democratization in every big data strategy.
Breaking through the data science bottleneck
Massive data sets (a.k.a. big data) have the ability to help us make better decisions. More information equals more precise directions, right? In reality, trying to utilize such overwhelming amounts of data can be like trying to drink from a firehose. To torture this metaphor a bit more – this is why, until recently, we called on data scientists to handle that firehose for us. We civilians couldn’t make effective use of such powerful resources and tools, and so we turned to highly-trained specialists to do it for us.
Further complicating the matter is the relative shortage of the right kind of data scientists. According to Analytics Magazine, “a data scientist should have a deep understanding of mathematical concepts, proficiency in computational programming and sound domain knowledge. Unfortunately, relatively few data scientists possess all three skill sets, creating a scarcity of data science talent across the globe.” This creates a bottleneck that inhibits organizations from keeping up with the explosive growth of available data.
This choke point has been especially hard on the Life Sciences industry. Inc. cited Gaurav Tripathi, CTO of healthcare data company Innoplexus AG, as explaining: “Today’s volume, velocity, and veracity of data, render the manual collection and curation of intelligence impossible for small to midsize pharma and biotech companies” – resulting in many Life Sciences organizations outsourcing their data processes (if they have those processes at all), further separating data and its derived insights from the people who need it the most.
The democratization of data
Fortunately, as machine learning and artificial intelligence solutions become better at cleaning, connecting, and analyzing data, what was once too much for a small organization to handle is now quite manageable thanks to partnerships with technology vendors. The overwhelming firehose becomes an easy-to-handle drinking fountain that anyone can gain access to.
This is the democratization of data. According to The Innovation Enterprise, it’s “the idea of helping everybody access and understand data… [It] means breaking down silos and providing access to data when and where it is needed at any given moment.” This concept is quickly catching on: 77% of respondents in a study by MIT reported an increase in access to useful data since 2016.
Thanks to the emergence of these new technologies, everyone from the CIO to a sales field representative within a Life Sciences company now has the ability to make data-driven decisions. “The more people with diverse expertise who have the ability to access the data easily and quickly will enable your organization to identify and take action on critical business insights,” writes Bernard Marr of Forbes. “When you allow data access to any tier of your company, it empowers individuals at all levels of ownership and responsibility to use the data in their decision making.” The end result is an agile-but-accurate approach to commercial success.
Insights are in the eye of the beholder
Machine learning and artificial intelligence are powering this data revolution by structuring and linking massive data sets that would be impossible for a human being to process. But by presenting the data in a visual, graphic way, even the untrained eye can see gaps, trends, and next best courses of action. Rendering the raw information as graphically pleasing visualizations gives the end user actual value; they can understand and act upon what the data means, not just what it says. It’s the difference between looking at the glowing green code of the Matrix and actually stepping inside the world rendered from that code.
We’re already used to quickly assessing and absorbing data from visual media, so displaying data graphically is more natural than staring at a sheet of numbers. “[Data visualization] enables not only enterprises and organizations, but anyone, to use their spatial intelligence to spot patterns and make connections that break through the tangled clutter of big data… I picture the average Joe or Jane regularly making use of their spatial intelligence to slice and dice big data of any kind,” writes Amir Bozorgzadeh in Venture Beat.
This is where insights turn into actions. Empowered by an understanding of once impossibly complex data, users can now apply the gleaned insights to their business strategies. Per George Karapalidis at Business2Community , “Visualization helps distill complex processes into actionable steps. Looking at the numbers alone does not always help to determine the right course of action.”
Some technologies are even taking the next step by generating prescriptive recommendations. Zephyr Illuminate, a cloud-based data and insights platform from Zephyr Health, now offers users a feed comprised entirely of predictive insights. The moment users log in, they see their actionable insights about high priority customers, markets, and competitors – all on a single screen – so that they can expedite and improve decision-making. And, just like a news feed serving up the latest story, this Insights Feed changes based upon the latest modification or update from multiple data sources. Best of all, it’s so easy that anyone at any level can use it.
The only way to keep up with the fast pace of data and its related technologies is to open the gates that once walled off data and analytics, and allow everyone across an organization to participate. The days of keeping these essential resources locked away with data scientists are behind us – new technologies have made the benefits of insights and analytics available to anyone who wants to stay on the cutting edge of business strategy.