Smart machines are reinventing how work is done across industries. Companies across sectors and regions are seeing an initial boost in process speed and performance by implementing Artificial Intelligence (AI) technologies. However, there is significant untapped potential in reimagining business processes from the ground up as self-improving procedures that can sense, comprehend, act and learn—all in real time.
Until now, many business leaders have taken too narrow a view of AI. To maximize the potential of AI and be digital leaders, healthcare organizations must reimagine and reinvent their processes from scratch—and create self-adapting, self-optimizing “living processes” that use machine learning algorithms and real-time data to continuously improve. Machines themselves will become agents of process change, unlocking new roles and new ways for humans and machines to work together.
Among the 13 industries included in the Accenture 2017 Process Reimagined Survey, Healthcare is tied with Mining and Minerals for No. 1 overall (
see Figure 1
). Retail and Telecom follow close behind. Healthcare ranks No. 1 in Process and Data.
About 15 percent of healthcare companies (US payers, providers and pharmacy benefit managers) are applying machine learning across three dimensions: Process, people and data (
see Figure 2
). These healthcare respondents in the process reimagined phase are moving beyond automation to take full advantage of AI. The process reimagined average across all industries surveyed was 9 percent.
Among healthcare organizations surveyed, 42 percent are using machine learning to reimagine processes and process change. Furthermore, 42 percent of US healthcare firms surveyed say they are using machine learning in at least one business process and 42 percent are using it to transform the human-machine work relationship. More than half (52 percent) are harnessing data to create exponential improvements in speed and key performance indicators (KPIs).
Machine learning benefits
Many healthcare organizations report that machine learning-enabled processes are reducing costs/improving revenue and also improving KPIs.
More than half (51 percent) of healthcare organizations say that machine learning-enabled processes have helped to reduce costs to “service products after sales” by at least 50 percent. Many healthcare respondents (65 percent) say they have improved revenue by 10-20 percent by using machine learning-enabled processes to “understand markets, customers and capabilities.”
Almost all healthcare respondents (93 percent) “strongly agree” or “agree” that machine learning-enabled processes help achieve previously hidden or unobtainable value and 86 percent believe these processes are finding solutions to previously unsolved business problems (
see Figure 3
). A majority (91 percent) are seeing 200 percent improvement in KPIs in enterprise processes, and 77 percent are doubling KPIs for sales and marketing in the front office.
Process reimagined leaders are focusing on three overlapping areas: process, data and the workforce.
Process change: Reimagining processes from scratch
Forty-two percent of health organizations are reimagining processes by:
Applying AI to process change management
Rethinking standardized processes as continuously adaptive
Bringing AI-based change to multiple processes across the enterprise
Health respondents in significant numbers are using or piloting machine learning-enabled processes across several business process categories (
see Figure 4
Data and data models: Capturing the exponential power of data
Fifty-two percent of health organizations are harnessing data to create exponential improvements in speed and KPIs, help solve previously unsolved problems and see patterns that were previously hidden. They are:
Using data to train and sustain process change
Making processes self-adapting and self-optimizing
Discovering new patterns of opportunity
Healthcare respondents reported experiencing a variety of benefits from using machine learning-enabled processes, including cost savings across several processes (
see Figure 5
Workforce: Unlocking the full potential for human/machine interaction by inventing new jobs
Healthcare organizations are redesigning jobs to emphasize distinctive human skills and human-machine augmentation. Forty-two percent are transforming the human-machine relationship by focusing on:
Enlisting the C-Suite to remake the culture with AI
Helping employees keep pace
Emphasizing distinctively human capabilities when hiring
Making sure that algorithmic decisions are ethical, fair, safe and auditable
Many healthcare organizations are investing because they believe that machine learning-enabled processes will positively influence the future of work (
see Figure 6