The 3 Biggest Pricing Complications in MedTech
Think about an MRI machine. Even just that instruction is more complicated than it initially appears. For one, you have to decide what kind of MRI machine you’re thinking of. If you want to diagnose arthritis or bone fractures, you’ll need to picture an extremity MRI. If your client is a neurology or cardiology practice and needs incredibly detailed imaging, they’ll most likely need you to picture a closed bore machine or an enhanced Tesla MRI. But if they’re a psychiatrist and their patients tend to suffer from heightened anxiety disorders, an open MRI might help ease diagnosis and treatment.
Considering the purpose of the medical device makes just picturing it complicated. Now try pricing it and you’ll see where the MedTech industry runs into trouble.
We’ve talked before about the importance of customer relationships in MedTech and the barriers that get in the way of managing those relationships. An integral part of maintaining customer relationships is accurate quoting and pricing on demand. Having the most up-to-date technology is vital to ensuring positive patient outcomes. Anything that slows down the pricing and quoting process could slow down the buying process and frustrate and alienate customers, maybe even pushing them to seek out alternative options.
A good pricing and quoting implementation can take stress off salespeople’s shoulders by ensuring they can trust the quotes they sent out—but the MedTech industry’s complexity can make that kind of implementation hard to achieve. Let’s explore some of the issues medical devices companies face when configuring pricing and quote generation.
Massive product catalogs cause lag and reduce scalability
Medical devices are some of the most varied products on the market and even just one kind of device, like an MRI machine, can have dozens of variants. MedTech catalogs don’t just include physical products either—hospitals, research centers, and medical practices have begun to expect MedTech companies to be able to provide maintenance and support for the machines they buy, making service yet another kind of product. These varied catalogs can include:
- Types of physical machines and devices (MRI machines, pacemakers, glucose monitoring systems, etc.)
- Various configurations of devices, sometimes based on the specific size of the location
- Maintenance and support services
- Digital technology and interface upgrades
- Individual components for larger machines and devices
- Personal protective equipment for medical staff
Add to this that many of these products can be configured to client and contract specifications and you can have multi-discipline, multi-customer, multi-contract-based product catalogs with tens of millions of rows of data, which can slow pricing calculations and quote generation. A good rule of thumb is that one price line should take a few seconds to calculate at most—some medical devices catalogs are so big that they can take over two minutes to generate individual quote lines.
This overload of data can prevent medical devices companies from fully digitizing their pricing and quoting models. If your pricing engine struggles to account for simple pricing updates, how can it possibly upgrade to more complex configurations?
Convoluted contract pricing risks quote errors and incorrect pricing
It’s tough to determine appropriate contract pricing in MedTech. Medical professionals need access to life-saving equipment, but without paying for the cost of manufacture and service, producing that equipment is unsustainable. TTI Research points out that price and cost can be very different, and understanding contracts is essential to achieving the best outcome for medical facilities, MedTech companies, and the patients they both serve.
That being said, contract pricing based on sales agreements is a complicated beast. Healthcare systems are known for their intricate bureaucracies and regulations and combining extensive product catalogs with contract-specific pricing can create complex calculations with dozens of steps—a perfect recipe for cracks to form. Salespeople work hard to make sure that the final quote is always accurate to the product and contract price, but when they need to manually double and triple check quotes to weed out any errors, it creates stress for them and their clients.
Sending out an incorrectly overpriced quote can damage customer trust and make it look like you’re trying to take advantage of how necessary medical devices are to public health. On the other hand, incorrectly underpricing quotes can lose a MedTech organization profit and make it more difficult to reliably manufacture and distribute those life-saving technologies. Either option is bad for both parties and the healthcare industry as a whole.
Region-specific pricing can be difficult to reliably digitize
The MedTech industry is complicated enough in individual regions. The United States’ healthcare system operates so differently from the rest of the world that trying to expand to even one other region can complicate pricing and contracting. The World Health Organization has worked to standardize countries’ regulation of medical devices, but many MedTech organizations still have to adhere to region-specific regulations on pricing, making it necessary to keep up with national, regional, and international standards.
Most of the systems built to manage pricing are manual and complex, consisting of Excel sheets, email databases, and external programs. These sprawling systems have a lot of functionality for individual cases but are extremely difficult to standardize—which is an important step in keeping up with standards. Converting these manual systems to digital implementations is vital to keep medical devices companies up to date with fluctuating prices and changing standards but can also seem like a monumental task.
A good pricing and quoting engine can make a huge difference in the day-to-day work of MedTech and medical devices salespeople and their clients, but it’s difficult to customize an implementation to the complexity of the medical devices industry. To learn more about how we’ve helped MedTech companies manage their pricing and quoting, read about how we helped Philips Healthcare cut their pricing calculation time by 85%.