Bill Schmarzo

I’m struck by what’s happening in the healthcare industry – between healthcare providers such as hospitals, and healthcare payers such as insurance companies – and how that industry is ripe for a metamorphosis into something much more efficient, effective and customer (patient)-centric. And within this metamorphosis, new power brokers are likely to emerge; those players who are able to leverage new sources of patient, physician, clinical, medication and care data to optimize key operational processes and dramatically reduce inefficient and unnecessary processes and procedures.

We are seeing from industry to industry the transformational power of organizations leveraging data – in the form of new customer, product and operational insights. We only need to look at the revolution started by Billy Beane and “Moneyball” – who set into motion a data and analytics revolution in how professional sports teams and players are evaluated, drafted, developed and managed.

But let’s review a history lesson from another industry that has already gone through this metamorphosis process – the Retail and Consumer Packaged Goods (CPG) industry – and what the ramifications for that metamorphosis might mean to the healthcare industry.

History Lesson: Metamorphosis of Retail – CPG Industries

In the 1970s and early 1980s, Consumer Package Goods (CPG) manufacturers based much of their marketing decisions on bimonthly store audit data. Companies such as A.C. Nielsen would send auditors into a sample of stores in 13 markets to conduct physical audits—to count how much product was on the shelf, price of the product, shelf space, and other data. The results of the audits were then packaged and delivered bimonthly to CPG manufacturers, who painstakingly integrated this data with their own sources of primary research and household panel data, in the hopes of improving inventory management, production, product mix and other basic CPG disciplines.

Then in the late 1980s, Information Resources Inc. (IRI) introduced their Infoscan product, which combined retail Point of Sale (POS) scanner systems with barcodes (universal product codes or UPCs) to revolutionize the Retail-CPG value chain.  Companies like Procter & Gamble, Frito Lay, Tesco, and Walmart leveraged this new POS scanner data to create new business applications such as demand forecasting, supply chain optimization, trade promotion effectiveness, category management, and customer loyalty programs.  But more importantly, the POS scanner data eventually upset the balance of power in the Retail-CPG industries by redistributing where the actionable insights lay.  Let me explain.

Up until this POS scanner data revolution, CPG manufacturers called the shots. CPG manufacturers had the financial resources to buy third-party market research data and integrate that data with their own primary research and household panel data to understand how consumers were using their products. CPG manufacturers hired some of the early data scientists to build analytic models around key value drivers of the business including pricing, product forecasting, promotional and advertising effectiveness and new product introductions. CPG manufacturers dictated terms to the retailers including how much product they were going to be “allocated,” and where and how to price, promote and place their products within the retailers’ establishments.

However, leading retailers realized that the POS scanner data yielded more insights about their customers’ behaviors, tendencies and usage patterns than CPG manufacturers knew.  And when combined with loyalty programs, the retailers could leverage this POS scanner data to uncover insights about individual customers such as:

• What products does Bill Schmarzo buy in what product combinations?
• At what stores does Bill Schmarzo primarily shop?
• What times of day and days of the week does Bill Schmarzo primarily shop?
• For what products did Bill Schmarzo use coupons and rebates?
• Which products does Bill Schmarzo always buy on discount?
• To which promotions is Bill Schmarzo most responsive?
• What is the impact of in-store merchandising on Bill Schmarzo’s market basket?
• How price sensitive is Bill Schmarzo to the different products?
• What products did Bill Schmarzo tend to buy based upon factors such as seasonality, holidays and special events?

And finally, with the inclusion of some external data sources, the retailers knew:

• What products did Bill Schmarzo buy under what weather conditions (rain, snow, extreme cold, extreme heat)?
• What products did Bill Schmarzo buy under what economic conditions (stock market changes, GNP changes, how the Chicago Cubs faired)?

Walmart was one of the first to realize that POS scanner data was a game-changer.  As highlighted in a Fortune article titled “The 12 Greatest Entrepreneurs of Our Time”:

 “He [Sam Walton] shared the real-time data with suppliers to create partnerships that allowed Wal-Mart to exert significant pressure on manufacturers to improve their productivity and become ever more efficient. As Wal-Mart’s influence grew, so did its power to nearly dictate the price, volume, delivery, packaging, and quality of many of its suppliers’ products. The upshot: Walton flipped the supplier-retailer relationship upside down.”

The balance of power in the Retail-CPG industry had shifted to the retailers because the retailers knew more about their customers’ shopping patterns, behaviors and tendencies than the CPG manufacturers.

Ramifications for the Healthcare Industry

There is definitely friction between healthcare providers (doctors, hospitals, clinics) and the healthcare payers (insurance companies, government agencies).  Today, the healthcare payers seem to control the cost of medical services by dictating how much they are willing to reimburse for particular types of care under, under particular conditions.

However, the healthcare providers are capturing more of their patient data; such as structured data from operational systems such as Epic and Cerner, to unstructured data sources including nurses notes and patient comments, and external data sources like WebMD, Fitbit, MyFitnessPal, Yelp, Lumosity and a wide variety of other website and mobile apps.  Leading healthcare providers are integrating and analyzing these data sources to create predictive scores about their patents’ overall wellness and stress, as well as calculate scores about the patient’s likelihood for strokes, heart attacks, diabetes and other maladies (see Figure 1).

Figure 1:  Patient Analytic Profile

If we apply the Retail-CPG historical lesson to the healthcare industry, then it’s likely that healthcare providers will be able to leverage their superior insights into patients, physicians, drugs and procedures in order to exert significant pressure on the insurance companies with respect to what procedures should be reimbursed and for how much because the healthcare providers will know which procedures and medications work best for which patients in what situations.

Let’s drill into this potential metamorphosis in more details, and outline how the healthcare providers can leverage new sources of patient data to uncover actionable insights

First, healthcare providers are going to have a wide range of patient, physician, quality of care, cost procedures and medication data including:

Second, healthcare providers can leverage this growing wealth of data to uncover new patient, care and operational insights including:

• Which medical procedures and medications work best with what types of patients in what situations?
• What is the optimal level of in-hospital care versus in-home care to deliver the best medical quality of care and the optimal prices given the type of care and the patient situation?
• What patterns of diet, sleep, stress and exercise reduce the risk of maladies such as diabetes, strokes and heart attacks?
• What doctor, nurse and technical combinations are most cost effective in different surgical situations?
• Which medications are most effective in treating different health conditions regardless of the price?
• What are the optimal combinations of rehab, medication and diet that deliver the most cost effective patient recovery?

With this patient, medication, quality of care and cost insights in hand, the healthcare providers will be able to tell the healthcare payers:

• What are the optimal treatments given a patient’s conditions and history and how much the payer should reimburse?
• What is the value of preventive care (diet, exercise, sleep, medication) and how much should healthcare payers cover to incentive more healthy and more profitable behaviors?

Summary

Industries as diverse as professional sports, consumer package goods, retail, and healthcare are going through business model metamorphosis by leveraging the wealth of rich data sources about their customers, products and operations.  And leading organizations are learning to leverage the resulting analytic insights to change the balance of power within their industry.

In the healthcare industry, healthcare providers that know the most about their patients’ and physicians’ behaviors, tendencies, and usage patterns are in the best position to “correct the fuzzy math that healthcare payers have been using to set their reimbursement rates”.

Bottom-line across all industries: the companies that know the most about their customers’ behaviors, tendencies, and usage patterns are in the best position to monetize those insights and exert control over those organizations within their value chains that lack those customer, product and operational insights.

Healthcare Industry and Big Data: Impending Business Metamorphosis?
Bill Schmarzo