How Life Sciences and Pharmaceutical Companies Can Reap More RPA Benefits with Content Intelligence
Between COVID-19 and the rush to digitally transform, companies across the globe are facing a "new normal.” And, the secret to navigating and thriving in today’s economy is agility. Yet, when it comes to making decisions faster and taking on greater risk to compete at a higher level, the stakes are especially high for the pharmaceutical and life sciences industry. To help them bring to market life-saving drugs as efficiently and safely as possible, pharmaceutical and life science leaders are turning to Robotic Process Automation (RPA) Software.
For RPA projects to succeed in our new normal, life sciences and pharmaceutical enterprises must commit to an RPA strategy and be willing to take on a level of uncertainty.
Planning amid uncertainty is an unavoidable part of implementing intelligent process automation successfully. Organizations willing to experience fast failure and adjust their RPA strategy accordingly will gain more from the technology than companies that proceed with caution.
There is another vital component to getting the most out of RPA: fueling it with intelligent data. The primary issue is that 80% of enterprise data is unstructured, locked away in disparate systems in hundreds of formats, and largely inaccessible and unusable. Bots can’t perform well with incomplete or inaccurate data. Companies need an AI-driven Content Intelligence platform for RPA to transform unstructured data into easily searchable, structured data for RPA software solutions.
Read on to learn how intelligent RPA solutions can help pharma enterprises overcome these challenges to develop new medicines faster, accelerate time to market, and meet stringent compliance regulations faster than ever.
Pharmaceutical & Life Sciences Priorities
Bringing potentially life-saving drugs to market as safely and quickly as possible is in our collective best interest. It makes sense that this industry leverages automation to replace the many manual processes that bog it down. For instance, data entry for clinical trials, customer feedback, side effects reporting can be done with bots, which reduces costs and enables these companies to focus on strategic initiatives that deliver new medicines and devices to patients worldwide.
Pharmaceutical and life sciences companies that turn to RPA solutions for help can expect to:
- Gather and analyze real-time information quickly to develop therapies and bring them to market faster.
- Facilitate the management of increasingly complex regulatory compliance requirements.
- Automate repetitive, tedious tasks.
Rules-based tasks dominate clinical drug trials and sales force operations, making automation the perfect solution for improved productivity and cost reductions.
Commit to Better Planning for RPA
A critical step in planning for RPA is to invite key stakeholders to participate in bot development, the employees that will use the technology.
Daniel Goodstein, President of the Institute for Robotics Process Automation (IRPA) and AI, shared with Adlib that among the most practical approaches to ensure automation buy-in is for companies to start with realistic expectations, provide employees with (re)skilling opportunities, and support developers’ communication with users.
“If employees can customize bots to make their jobs better and more productive, they will always be a fan versus the alternative, where the concept is forced on them, and the natural human fear of "a bot will take my job" sets in.” —Daniel Goodstein
Goodstein added that users are often more familiar with the details of a process than executive leadership, which makes it more likely that these employees can create usable bots that will lead to more significant ROI.
According to Automation Anywhere, RPA can deliver up to 628% ROI to life sciences companies within six months.
Life Sciences Use Cases
- Pharmaceutical and life sciences companies use chatbots to provide patients with real-time information. Developers program scripts based on input from employees that result in a personalized customer experience with shorter response times. Employees no longer have to process every mundane request. When bots are unable to facilitate an inquiry, customer specialists can take over and provide resolution.
- Life sciences and pharmaceutical companies utilize software bots to perform data entry to facilitate faster drug development and approval.
- Pharmaceutical and life science enterprises leverage RPA to prepare accurate reports based on comprehensive data gathered from multiple sources to meet greater accuracy and confidence compliance requirements.
Don’t Shy Away From Fast Failure
Gone are the days of taking 6-18 months for a proof of concept. Today’s new normal requires companies to make quick decisions, even at the risk of uncertainty. Tentative leadership will impair an enterprise’s transformation journey.
Mr. Goodman added, “Failing fast and adjusting are always a good idea. The most successful organizations we see have a cross-organization strategy, with various “low-hanging fruit” RPA programs that will produce near-term ROI but will also take them down a path of holistic transformation.”
Course-correcting from fast failure requires an agile corporate mindset from the C-suite down and helps to usher in long-term RPA ROI. For instance, a bot sifting through large amounts of clinical trial information to determine applicability to move forward with a new device or drug aligns to a fail-fast approach. Pharma companies can pull the plug on a new treatment plan or change direction depending upon information gleaned from the bot.
Start With the Right Inputs
Simply put, RPA automation solutions require clean, structured data. Unstructured content that has not been transformed into intelligent data leads to garbage in, garbage out. Life sciences and pharmaceutical companies can avoid this misfortune with Adlib's Content Intelligence Cloud, built upon five essential steps to find, transform, and apply unstructured data to get as much out of RPA as possible.
- Automation makes it possible to Discover Unstructured Data across an enterprise regardless of location or format.
- Utilize OCR or create PDFs to generate content that can be searched for, read, and analyzed by RPA systems. Converting unstructured data enables companies to extract more significant ROI from these systems.
- Build trainable AI models that categorize and meta-tag documents faster and more scalable than humans can perform with fewer errors.
- Classified, metadata-rich content can be analyzed, sorted, and filtered to surface data-driven insights that fuel innovation and intelligent decisions.
- Clean, structured data is automatically delivered to the people, processes, and technology that rely on it to improve customer experiences, meet compliance, and increase profits.
Too many disparate systems with data in multiple places and in various formats truly limit the full potential of automation.2
The Final Verdict
The latest new normal is an exciting time for pharmaceutical and life sciences companies because it presents an opportunity to reflect, pivot, and compete at a higher level. However, success is dependent upon collaboration and agility. As long as employees across life sciences companies have been made a part of the immediate and long-term plan, RPA has the potential to boost customer and employee satisfaction, increase profits, and help bring medicines to market faster than ever. Resolving unstructured data with Adlib's AI-driven Content Intelligence Cloud for RPA will enable pharmaceutical and life science companies to layer insight on top of automation and achieve true digital transformation leading to hyperautomation.