Organizations looking for justification to move beyond legacy reporting, should review this little ditty from the healthcare industry:
The report identified six major areas of waste: unnecessary services ($210 billion annually); inefficient delivery of care ($130 billion); excess administrative costs ($190 billion); inflated prices ($105 billion); prevention failures ($55 billion), and fraud ($75 billion). Adjusting for some overlap among the categories, the panel settled on an estimate of $750 billion (see Figure 1).
Figure 1: Preventable Healthcare Costs
“Best way to reduce operating and business costs and risks is to prevent them!”
“Preventive Analytics” typically refers to solutions that monitor systems to identify and prevent unplanned failures and downtime, and the associated costs. Yet, that narrow definition misses the larger opportunity to apply preventive analytics across a broad range of industry problems. Companies across numerous verticals, besieged by fraud, waste, abuse, foodborne illnesses or food poisoning, excessive and obsolete inventory, and product returns, would benefit from a greater commitment to preventive analytics:
“A billion here and a billion there, and pretty soon we’re talking about real money!”
To date, technologists have heavily focused on three core functions of analytics — Descriptive, Predictive, and Prescriptive. Surprisingly, little has been written about Preventive Analytics and how it complements the other three. As a refresher, these analytics grouping are defined as:
Now we need to add the category for Preventive Analytics.
Figure 2 lays out the Analytics Value Chain progression from Predictive to Prescriptive to Preventive analytics.
Figure 2: Predict to Prescribe to Prevent Analytics Value Cycle
See the blog “Artificial Intelligence is not ‘Fake’ Intelligence” for deeper definitions on these analytics classifications.
Let’s make preventive analytics come to life through some examples. Imagine a local government searching for opportunities to 1) reduce costs while 2) improving resident quality of life. Tackling fraud, waste, and abuse while simultaneously increasing citizen satisfaction and quality of life is a compelling win-win combination!
Another example is occurring within “Smart City” initiatives. Traffic data helps local agencies better predict traffic flows and patterns in order to decrease the number rate of traffic jams and traffic accidents (see Figure 3).
Figure 3: From Predicting to Preventing Traffic Accidents
Below are more opportunities for city, state, and local governments to apply preventive analytics to decrease costs while improving citizen quality of life:
Opportunities are only limited by the organization’s creative thinking. For the average business, the most significant preventive analytics opportunities will have bottom line impacts – preventing customer and employee attrition.
It is estimated that new customer acquisition is 5 to 25 times more expensive than retaining an existing one. Consider the research done by Frederick Reichheld of Bain & Company (inventor of net promoter score) that observed customer acquisition in the banking industry. Reichheld’s data reveals that increasing customer retention rates by 5 percent boosts profits by 25 percent to 95 percent.
Furthermore, reducing defections by just 5 percent generated 85 percent% more profits in one bank’s branch system, 50 percent more in an insurance brokerage, and 30 percent more in an auto-service chain. MBNA America found that a 5 percent improvement in defection rates increases its average customer value by more than 125 percent(see Figure 4).
Figure 4: “Customer Experience Management for Startups”
The financial impact of preventing customer attrition is staggering! See my blog “Optimizing the Customer Lifecycle With Customer Insights” for more details on leveraging Big Data to rewire your customer lifecycle management processes.
It isn’t just customer attrition that carries significant costs. Analysis by the Center for American Progressreviewed 30 case studies published between 1992 and 2007 that provided cost estimates from employee turnover. The analysis found that businesses spend approximately 20 percent of an employee’s annual salary to replace that worker. That cost is even higher for high skilled and senior management (see Figure 5).
Figure 5: Hidden Costs associated with Employee Attrition
Yes, it is financially smart for organizations to use Preventive Analytics to identify, understand, and act on at-risk employees that can both decrease employee acquisition costs while improving employee workplace satisfaction.
Preventive Analytics – like Descriptive, Predictive and Prescriptive Analytics – plays an important role in exploiting the power of data and analytics to drive digital transformation and create an intelligent enterprise (see Figure 6).
Figure 6: Creating the “Intelligent Enterprise”
The "has potential to dramatically reduce or eliminate costs associated with fraud, waste, and abuse while simultaneously increasing customer, employee, and citizen satisfaction and quality of life. Hard to beat those benefits!
Source: “How the U.S. Health-Care System Wastes $750 Billion Annually” https://www.theatlantic.com/health/archive/2012/09/how-the-us-healt...
Harvard Business Review “Zero Defections: Quality Comes to Services”
“How to Calculate (And Lower!) Your Customer Churn Rate” https://www.wordstream.com/blog/ws/2014/05/12/customer-churn
“There Are Significant Business Costs to Replacing Employees” https://www.americanprogress.org/issues/economy/reports/2012/11/16/...