ZS Interview: Moneyball for Pharmaceutical Companies—How Dashboards Can Change the Market Access Game

Nitin Jain, Pratap Khedkar

The pharmaceutical industry pays $40 billion annually for formulary access, far more than any other single piece of its sales and marketing budget. And because these rebate contracts ensure access to managed-care formularies, it would make sense that companies place high priority on applying complex analytics and tracking to ensure they’re getting the most for their money.

But that would be wrong.

The pharmaceutical industry is extremely sophisticated in developing and using insights from analytics and dashboards for sales and marketing operations. But few companies are using this approach to find out which rebating deals are making sense or to track the effectiveness of their in­vestments. Instead, companies are like old-time baseball scouts, evaluating players based on observation and their gut rather than metrics.

Analytics and dashboards are to managed-care rebates what Moneyball-like statistical analysis is to evaluating baseball talent, helping identify truths that observation may miss. Pratap Khedkar, a ZS Principal based in Philadelphia, and Nitin Jain, a Principal based in Evanston, Ill., spoke about how analytics and dashboards have the potential to change the art of evaluating managed-care contracts into a science.

What is the rationale for applying analytics and dashboards for managed-care rebating contracts?

PRATAP KHEDKAR: There are several reasons. Pharma companies are spending more than ever on making sure access is still available, because they can’t take access for granted. Payers can cause a launch to fail.

Another element is that a lot of blockbusters will be going away because of the patent cliff, and pharmaceutical companies are trying to keep profits healthy with more specialty drugs. But payers are scrutinizing these products, and what was once a safe and high-growth area is not so safe anymore. Pharma companies will by no means be guaranteed access at a cost that makes sense.

Also, there are greater price controls in Medicare Part D. This points to the fact the government will have an increasing role in terms of prices.

NITIN JAIN: The pressure is on companies to determine if they’re spending in the right places or should be cutting back in others. They need to see where their investments will be most profitable, and where the price for access is too steep.

Also, there is an entire ecosystem of decision makers and influencers determining access. Analytics and dashboards can illuminate the importance of each of these parties and show the entire system.

How are managed-care rebating contracts usually analyzed?

NITIN: Traditionally, pharmaceutical companies have used managed-care information in the rear-view mirror—they’ve analyzed what has happened, but not necessarily to help them look ahead. For instance, a company might know it had “X” performance with a previous managed-care contract, as opposed to knowing where it needs more future access and why should it sign a different deal for the same product.

PRATAP: It’s like Moneyball. You take a well-understood thing like baseball-player scouting that’s existed for several years, using judgment and gut and experience to determine what to do—that’s how managed-care rebating operates like baseball. But if you look at numbers and step back, you can squeeze out inefficiencies, and do more with less.

Analytics will not radically change your strategy, but you’ll be able to pinpoint the right insight at the right time and the right place. It can enable you to get ahead when you don’t have an enormous payroll. And over time, things are going to get more difficult, because payers are going to squeeze you further.

How does Moneyball relate to contract performance?

PRATAP: Moneyball is about signing undervalued players based on statistics—hitters who had a high on-base percentage, for instance.

But Moneyball wasn’t just about collecting a lot of statistics, it was identifying which ones really mattered. Once you sign the players up, you still have to help them perform. It’s no good to get a baseball player and have him immediately go into a slump. How do you make sure that his performance is going to live up to its potential? It’s the same with managed-care rebates. You have to squeeze actual performance out of the contract.

The main thing is that there should be nothing that you must have. If you make a bad deal, you’re not necessarily stuck with it. Dashboards give you a high-level, accurate view of how good those deals should perform.

So what has been holding companies back?

NITIN: There needs to be the proper reporting and decision-making framework across the enterprise, not thinking in silos. A lot of times companies see metrics as a matter of simply having access to a therapeutic market, as opposed to having profitable access. But for analytics and dashboards to work, metrics have to be designed to measure profitability and the performance of sales and marketing investments, which requires breaking down departmental silos.

Large pharma companies are aware of the concept, and in some cases tried to create dashboards. Two things have been missing. Number one, they lack the metrics to help with profitability decisions and other future-looking decisions. The second thing they lack is the ability to drill down into a problem. You need to drill down to geographies, payers or even group practices. The ability to really analyze the problem is difficult, and that’s where the process breaks down.

PRATAP: Also, when we talk to managed-care stakeholders at pharmaceutical companies, they say they don’t get enough or as much attention from IT as other departments—I think that’s because managed care has a big investment in terms of dollars, but not people.

Managed-care spending is about twice as much as spending on the sales force, but the number of people facing managed-care customers is only 1% to 2% of the sales force. The number of people asking for managed-care information is much smaller. There are very few people managing managed care, and they’re asking IT for something extremely complicated. A lot of the attention goes to where the people are.

Why is it “extremely complicated” to build analytics and dashboards?

NITIN: The market is extraordinarily complex. The customer is no longer just a payer, but other things as well. You have payer orgs, IDNs, hospitals and GPOs getting involved in buying decisions as well.

The definition of “payer” is going to keep changing as well. The metrics for a payer is not going to be the same as for an IDN. And related to that, there are geographies like Boston in which there are payers and IDNs that are comingled and driving therapy decisions. How do companies think about those geographies, as opposed to places where it’s just about a payer they have to concern themselves with?

Like in baseball, you need to collect facts and control for situations—for instance, a hitter’s stats have to be in the context of the pitching he faced. Likewise, you have to take into account the nuances of payers, either singly or jointly. And combing multiple data streams is much more complex for IT.

What are the keys to analytics and dashboards in managed care?

NITIN: You need the ability to find the right metrics for each payer. Pharma-ceutical companies need to understand each payer—is it cost alone that drives their decisions or is it other factors like clinical benefits, choice or health economic benefits, such as if the patient would be hospitalized without medication? You shouldn’t use the same metric to measure everyone. Like in Moneyball, not only do you need to know the metrics, but which metrics you should be looking at.

About the Experts: Pratap Khedkar and Nitin Jain

Pratap has many years’ experience working with the pharmaceutical industry. Among other areas, he has worked extensively in managed-care strategy and decision support, customer segmentation, marketing mix modeling and sales force design.

Nitin is the Managing Principal of ZS’s Managed Care practice area. He has worked in analyzing and solving resource-optimization-related issues, including those for managed-care rebating, sales force design and marketing mix.