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Vision, investment, refinement and engineering are all needed to transform an industry. In the early 20th century, business magnate Henry Ford introduced the moving assembly line method of manufacturing, resulting in faster and cheaper production. This type of transformation was a wholesale reengineering of the factory floor.
When we talk real-time customer experience (CX) at Forrester's FeedbackNow, it's more than just a buzz phrase -- it's a visionary idea that requires the same grand-scale transformation that auto manufacturing underwent with the assembly line.
Actual real-time customer experience is a future where organizations constantly and fluidly redeploy resources, continuously flex policies and procedures and deliberately and effortlessly change and improve apps and kiosks.
Getting there, though, requires a colossal effort. Yet when it comes to the healthcare sector, the payoff is ultimately there because the tie between CX improvement and revenue is clear.
The sector will have to clear hurdles as cost, highly regulated and protected data and disparate channels and businesses all stand as major barriers. Nonetheless, the industry has always led in customer experience innovation. While the COVID-19 pandemic introduced innumerable and historic stresses, it's also been the impetus for even more advancement such as telemedicine and new innovative online services.
Imagine a few examples of real-time customer experience in healthcare, some of which are already available: confusing or broken web and app touchpoints changed on the fly; waiting times reduced dramatically as resources are redirected and redeployed in real time; cleaning resources deployed proactively based on real-time weather and foot traffic data.
Steps to real-time customer experience
Ultimately, the revolution of real-time customer experience in healthcare is defined by three major steps:
- Real-time sensing. This means measuring customer experience at every single physical or digital touchpoint possible in the customer journey, such as making appointments, waiting areas and working with insurance. It requires pulling in data from every area that impacts customer experience, whether intuitive or not. Other elements like weather, road traffic, foot traffic and transaction times are sensed in real time as well. This is not easy, as much of this data isn't accessed and protected in real time.
- Real-time analysis. This means discovering correlations, making predictions, suggesting next best actions and augmenting decisions. Machine learning is critical here, as correlations and predictions made to serve customers are seldom intuitive. This requires massive architectural gymnastics to assemble.
- Real-time action. This means acting to help the individual customer in their moment of experience while also recognizing in real time when to flex an overarching policy, process, staffing issue or other issue that exists to benefit the next immediate customer. This step requires revolutionary transformation. Instead of one policy or operation, you might develop a playbook of them to suit real-time changes and be ready to flex from one to another at a moment's notice.
Reengineering your healthcare enterprise to provide dynamic, real-time customer experience requires further buy-in from the board, CEO and the entire enterprise. For most companies, real-time customer experience is too big and visionary to achieve that kind of buy-in, especially without immediate and obvious revenue benefits.
Achieving real-time customer experience
Small, concentrated pilots with eager participants can prepare you for this kind of overhaul to demonstrate benefits and possibilities and create rapid impact on today's customer experience as well as revenue.
Consider the following, starting in one area of a hospital or clinic, on one section of an app or website or with one application process:
Collect real-time data, not surveys. This includes feedback from customers -- not after-the-fact surveys but immediate, short-pulse questions with simple answers -- and related data such as transaction times, traffic and response times.
Use the data to manually augment decisions. Look at what the data denotes and determine changes or actions to make as a result, followed by hypothesizing and experimenting to test it.
Learn and iterate in three dimensions. Define success as learning what works and what doesn't work for a company. From there, expand further in each dimension with each success:
- Imagine a hospital that places a kiosk at the entrance that asks, "How was your experience with our information desk today?" The next step could be to go wider -- perhaps collecting data at more discrete touchpoints in the customer journey in that same location. Or maybe go further, sticking with the original single question but trying it at three areas of the same clinic for real-time comparison. It's more complex, but the next step could introduce a second source of real-time data like transaction time or weather.
- While examining the data, experiment with decisions. Redeploy personnel when a data threshold is reached and see if it affects the outcome. Tweak a process or policy at one location and see what results. See what happens if the decisions get bolder.
- Once it's determined how a specific real-time operational change can affect customer experience, shorten the time it takes to sense the data to realize true real-time customer experience.
Customer experience is about a customers' perceptions and emotions, not the company's brand intentions or marketing messages. Those experiences and emotions happen in real time and need to be addressed in real time. Customers are fickle and switching costs get lower all the time. As a result, every impression is now a first impression and not relying on yesterday's surveys. Today's "factory floor" cannot hope to manufacture true customer experience without being overhauled.
About the author: As Forrester's first "chief business technology officer," Steve Peltzman was responsible for guiding the transformation of Forrester's own internal technology efforts from the traditional information technology approach to what Forrester advocates companies should adopt: business technology. Now, he leads Forrester's FeedbackNow business and is a member of Forrester's executive team.
Prior to joining Forrester, Steve spent a decade as the chief information officer at The Museum of Modern Art (MoMA) in New York City. He led the technology design and implementation for MoMA's $858 million new building project from 2001 to 2004. In addition, Steve spent seven years as a United States Air Force officer, where he developed and assessed stealth technology and tactics for the B-2 Stealth Bomber Program Office and served as a program director for the Joint Mission Planning Program Office. Steve holds a B.S. in Aeronautical Engineering from MIT and an M.B.A. from Columbia Business School.