Analyzing Digital Transformation in Life Sciences
Digital transformation cannot be completed by simply checking a box. As technology, people and processes continue to evolve, so too will the means in which Life Sciences organizations accelerate their product and service development, enhance the customer journey and address compliance requirements. Even though the benefits of digital initiatives are vast, the truth is only 20 percent of Life Sciences companies are currently digitally maturing.*
In a recent sit-down with Tamara McCleary, CEO of Thulium, and Scott Mackey, SVP of Market Strategy for Adlib Software, we took a look at some of the pain points that are preventing Life Sciences organizations from implementing digital initiatives, and how data quality is proving to be an essential lifeline.
What’s Driving Digital Transformation in Life Sciences?
With a clinical background in science and medicine, McCleary has been closely involved in digital transformation projects aimed at digitizing legacy processes in various organizations. Whether a business’ digital tactics involve artificial intelligence (AI), robotic process automation (RPA) or other technologies, she says the ultimate goal typically centers on maintaining a competitive heartbeat in the increasingly demanding industry.
“When you look at how Life Sciences organizations plan to benefit from digital transformation initiatives like the implementation of AI and RPA, it’s always about efficiency and their bottom line – it’s about how they can stay relevant and stay in business,” she said.
Staying in business for many Life Sciences organizations means being agile enough to compete with new market competitors, adapting to tighter regulatory requirements, providing an enhanced customer experience and simply keeping pace of the rise of technology itself. Decades-old, legacy businesses are finding themselves in a digital arms race to keep up their more nimble competitors on all fronts.
“Everybody is scrambling to make sure they are able to stay competitive with smaller, more agile companies that have already begun using AI and machine learning to their advantage,” McCleary said.
Digitization is Data-Dependent
But in order to achieve any of the noted advantages, Life Sciences organizations must first overcome the challenges of unstructured data, making up about 80 percent of enterprise data in the industry, according to Scott Mackey whose career background centers on enterprise content management.
“With AI, for example, making the machines smart enough to generate the same kinds of insights that a human can require copious amounts of data to feed their intelligence,” he said. “For AI or any digital initiative to deliver on its promise, it needs high-quality data.”
While structured data housed in the rows and columns of a Life Sciences organization’s database is primed for ingestion by insight and intelligence engines, the unstructured data locked in documents, lab notebooks, emails, contracts or clinical Power Point presentations, is creating a hiccup. Without immediate access to the vast amount of data contained within these documents, Life Sciences organizations are limited in their ability to fuel any data-driven digital initiatives.
“When we look at being able to garner the insights that are going to keep Life Sciences businesses on pace with healthcare changes and growth, they have to be able to understand what their data is telling them by harnessing their unstructured data,” McCleary said. “Not everything is contained within structured datasets.”
A Three-Step Approach to Better Data
Honing in on unstructured data and enriching it to a point where it’s usable for machine intelligence, analytics or other digital initiatives requires adherence to three pillars:
1. Access to Data
According to Mackey, Life Sciences businesses can begin by broadening access to their fileshares, repositories and legacy storage systems since digital transformation initiatives are reliant on computers to find and read documents before utilizing the data they contain.
This is contingent upon having content that’s machine-searchable, meaning it’s standardized into universal formats so that an automated data extraction process can be employed to unlock the information within each fie.
2. Quality of Data
“Intelligence systems are only as smart as the fuel they’re given,” Mackey said. “Quality is key because if you feed a digital system a lot of garbage, you’re going to get inaccurate outputs.”
To weed out redundant, obsolete or trivial (ROT) information that could be impacting not only the quality of data but also its output when fed into analytics or automation engines, AI-based document classification is essential. By using machine learning, Life Sciences businesses can analyze their documents and classify the content to rid themselves of any ROT in order to fuel their digital initiatives with better data.
3. Data Efficiency
“Based on the sheer volume and growth of content in the industry, being able to execute the above steps with automated tools and technologies can improve the speed with which businesses leverage their content,” Mackey said.
The impacts of digital transformation in Life Sciences are far-reaching, impacting not only a business’ bottom line, but improvements to the quality of healthcare services and solutions that we all enjoy as well. By implementing governance strategies that address data access, quality and efficiency, both McCleary and Mackey agree that Life Sciences enterprises will be better positioned to leverage the latest digital technologies to not only keep pace with their competitors and meet compliance measures, but also to predict trends and garner insights that will aid in developing the live-saving solutions that we all depend on.
To undergo a Health Check and determine if your data is primed to deliver insight and intelligence as part of digital transformation, download our datasheet.
About Tamara McCleary
Tamara McCleary is CEO of Thulium, a social media analytics and consulting agency, driving Smart Social through proprietary data analytics and award-winning storytelling. Tamara ranks in the top 1% in influence globally. Named the #1 most influential woman in MarTech by B2B Marketing, recognized by Entrepreneur Magazine as one of 10 Online Marketers to watch, and named Top Digital Marketer by Brand 24 in 2019. Featured multiple times in Forbes for her pioneering influencer marketing strategies on social media for B2B and Enterprise, Tamara serves as a unique advisor to leading global technology companies such as SAP, Mercer, Marsh & McLennan Companies, Cisco, Dell, AWS, RSA Security, IBM and Verizon.
About Scott Mackey
As SVP of Market Strategy at Adlib, Scott has built his career in content management by driving industry initiatives related to data capture, archival, knowledge management, Enterprise Content Management and File Analytics. Scott regularly engages Adlib's customers and partners to analyze and assess latest trends in the ECM space, and stays up to speed on industry best practices by attending global engagements and industry events. He is also a member of several boards and speaks at several industry events each year.
Scott has an Honours BA from the University of Toronto. Outside of the office, Scott shifts gears to enjoy time with family and friends, traveling the world and -- of course -- pursue his love of all things automobiles.
*Digital Maturity in Life Sciences