There is no doubt about it, healthcare companies are big. It’s that way by design. Immense scale, high volume, and strict regulation are synonymous with their business models. There is no other way to meet regional and global needs, or to operate at a level of quality that demands life-changing and life-saving performance. This kind of big—billions big—often means complexity, teams operating in silos, disjointed experiences, lack of standardization, and decentralized functions.
But we already knew this. What we might not have known is how it became this way. The answer might surprise you: It happens slowly and without anyone realizing it.
Let’s illustrate how this can happen with a case study of a Medical Device Company. They started small and were regionally focused, but their product specialization was dominant, which allowed for steady growth. In that time, they organically made strategic acquisitions of competitors and complementary products to round out their service portfolio and increase their market share. As they became a global presence, they made bold investments in emerging markets and in approaches to optimize their opportunity funnel—working toward the goals of growth and relevance. Customer experience (CX) was an afterthought.
Why was customer experience an afterthought?
Scaling quickly outweighed the need to address the technical challenges that came with creating a seamless experience for their customers to transact with them. Why spend millions on technology if low-hourly rate operations staff can bridge the gap? But this Medical Device Company soon learned the speed of business is endless, and there was no “perfect time” to budget for CX. Eventually future programs were “taxed” by all the CX investments they never made.
And there they were—all at once, the technology landscape supporting people and processes was too complicated to maintain. This created a challenging experience for employees to do their jobs: working in silos, using multiple systems to do basic activities, not having reliable information to make decisions. Even worse, this created an unacceptable experience for customers: a lack of self-service capabilities, an inability to access their customer information (such as order status) reliably, and no consistent way to receive satisfactory customer service from “one team.”
The pain the Medical Device Company felt now impacted their bottom line. Unhappy customers were finding a better way of doing business, which meant going to competitors. Now, CX transformation was no longer optional—it became essential. But where to begin after putting it off for so long?
No, not by restructuring teams to better meet customer demands, although that’s a start.
No, not by redefining business processes to allow teams to work better together, although that’s also important.
No, not by consolidating platforms into a more streamlined technical architecture, although such an expensive endeavor would yield profound, long-term operational benefits.
The answer starts with customer data
If customer data is kept within silos with no holistic view of itself (meaning it’s separated by product family or regionally for all product data, all order data, all service data for a customer), then every new experience an organization attempts to create will be disjointed and fragmented. Any customer innovation or transformation will fail before it begins.
Remember, it shouldn’t be a surprise that these silos of customer data exist—in fact, it’s natural, especially after acquisitions. Legacy companies will inevitably have their own backend platforms that will need to be brought into one technology landscape. Problems arise —making future CX transformation investments difficult—when this data is kept in silos too long after the acquisition.
How did this now hyper-complex Medical Device Company begin their strategy of integrating disparate sources of customer data? They started by understanding which systems were hosting it, and who was responsible for the business processes stewarding it. With this understanding, the Medical Device Company assessed their customer data with three basic principles.
There’s no such thing as bad data, only bad practices
Perceived data quality is only as good as the stewarding practices and business processes that maintain it. To “fix” the perception, you need to be highly disciplined on how data is stewarded and ensure consistent practices are implemented so all data is treated the same.
Take order data as an example. Orders typically have a header with line items that map to one or multiple products that have estimated shipping and delivery dates. If orders are hosted across multiple backend systems, and inconsistent processes manage shipping information, customers might come to distrust their order data if delivery dates vary from order to order.
Connect the dots to unlock value
There is a “why” behind every bit-and-byte of customer information, either one of the following:
- Transactional value, which answers a critical question for a customer: “Where is my order?” or “What product can I substitute for the one I typically use?”
- Relationship value, which enables a company to do business with them: “Who will be billed for the purchase?” or “Where will this product be shipped?”
The accuracy and completeness of these elements will determine if customer data can be trusted. This should drive appropriate stewarding practices.
Bring it together with a uniformed model
Even if customer data is accurately and consistently maintained across disparate systems, it means nothing if it cannot be reliably accessed. Terminology, field level context, related objects, and dependent objects might vary from system to system. Or, perhaps, the integration doesn’t exist for one or more source systems, which prevents customers from getting to it.
Solve this challenge by creating a “new view” for each category of customer data (be it for accounts, orders, assets, etc.). This “new view” is not how customer data is represented in any one of its source systems, but a unified model that reconciles field mapping discrepancies, object hierarchy, and business process dependencies from all systems. Once this is defined, customer data can be transformed through integration architectures or possibly warehoused in a data lake that’s easily consumable for CRM platforms.
These principles allowed the Medical Device Company to create a customer data blueprint—essentially the DNA that defined a 360-degree view for all customer information. This “one view” of customer information was the foundational work of their CX transformation and drove all future people, process, and technology changes.
The path to delivering successful CX transformation programs begins with understanding your data. Implementing best practices for stewarding data, determining whether you can trust that data, and then making that data readily accessible can help you improve your customers’ experience and start you down that transformation path. Want to learn more? Contact us—we’d love to chat.
About the AuthorFollow on Linkedin More Content by Sebastian Barnes