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The Two Biggest Obstacles Facing Clinical Trials Pricing System Implementations

August 4, 2022

man working in lab

It's no secret that Contract Research Organizations struggle with adopting Configure-Price-Quote systems. An industry as complex as clinical trials has a lot of road bumps on the way to automation, and while the end of the trip might be worth it, you don't want to start a journey without understanding what you're getting into. So, let's talk about two of the biggest obstacles to adopting CPQ systems for clinical trials: complicated pricing and entrenched legacy systems.

How complicated pricing models get in the way of quoting proposals

Any salesperson in health and life sciences knows how complicated pricing can get in this industry. I mean, consider all the costs associated with just one clinical trial participant providing one tissue sample: First, the participant has to travel to a trial site, be seen by a nurse or physician, have the tissue sample extracted, record that sample data, and then have that sample tested in various lab conditions. Then, after all that, that data must be analyzed and prepared for presentation.

For just this one participant, CROs and clinical trials companies have to price at least:

Travel expenses

Site leasing and maintenance

Nurse and physician payments

Medical preparations, such as anesthesia

Equipment for extraction and collection

Administrative expenses

Laboratory usage

Data analysis

And all the while making absolutely sure to comply with state, federal, or international regulations.

Clinical trials involve complex, meticulous research with hundreds, or even thousands, of participants. This becomes even more complicated when CROs go international and have to manage different countries' regulatory standards for equipment, drug testing, staffing, and more. Some governments even regulate pricing itself.

All of this amounts to incredibly detailed quotes, sometimes with thousands of lines of quote items. This complexity can be almost impossible to manage in an out-of-the-box vendor CPQ or pricing implementation, and even customized solutions struggle to account for the hyper-specificity of a clinical trials quote.

Why it's hard to move on from Excel

CROs already worked with a huge amount of data long before Roger Magoulas popularized the term “big data” in 2009. Before the digital era, this data was recorded manually. The digital revolution fueled a drive to record this information digitally, but the data's complexity and companies' entrenched business processes made transitioning away from these analog filing systems tough. Some companies and organizations took years to go fully digital, and some still rely on paper filing systems to this day.

With the advent of contract pricing engines and process automation, we're experiencing a new tough transition. Many—if not most—clinical trial companies rely on the manual systems that they've used for decades. CenterWatch reports that 78 percent of study startup processes are conducted in Excel, including pricing, budgeting, and quoting. Excel can't accommodate all the functions a startup process needs, though, which has led to companies incorporating external programs like cloud storage systems and electronic signature applications. These fulfill business needs but also create intricate, disconnected networks of programs that make it incredibly difficult to keep track of price lists, quote drafts, and even client communications.

78 percent is a lot of the industry to fall behind the curve. Occasionally CROs rely on these systems because that's what they're used to. More often, though, it's because the systems they've created in Excel are so complicated and vast that a basic pricing implementation doesn't seem to live up to a company's very real business needs. A clinical trial company's CPQ implementation can't just pop out of a box and be ready to go; it must be customized to the needs of an industry subject to intense regulation, scrutiny, and complexity. That customization has growing pains, and sometimes, it seems like a better option to just stick with the devil you know.

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