mckinsey big data report patient data, clinical data, revenues projection, and r&d data

Is the health-care industry ready for big data?

Although the health-care industry has lagged behind sectors like retail and banking in the use of big data—partly because of concerns about patient confidentiality—it could soon catch up. First movers in the data sphere are already achieving positive results, which is prompting other stakeholders to take action, lest they be left behind.

Who has access to health-care data?

Meanwhile, the US federal government and other public stakeholders have been opening their vast stores of health-care knowledge, including data from clinical trials and information on patients covered under public insurance programs.

What's new in health-data applications?

Since 2010, more than 200 new businesses have developed innovative health-care applications. About 40 percent of these were aimed at direct health interventions or predictive capabilities. That’s a powerful new frontier for health-data applications, which historically focused more on data management and retrospective data analysis (exhibit).

How can big data help the retail industry?

MGI studied big data in five domains—healthcare in the United States, the public sector in Europe, retail in the United States, and manufacturing and personal-location data globally. Big data can generate value in each. For example, a retailer using big data to the full could increase its operating margin by more than 60 percent.

The big-data prescription for pharmaceutical R&D

Our research suggests that by implementing eight technology-enabled measures, pharmaceutical companies can expand the data they collect and improve their approach to managing and analyzing these data.

The challenges of a big-data transformation

For a big-data transformation in pharmaceutical R&D to succeed, executives must overcome several challenges.

About the author (s)

Jamie Cattell is a principal in McKinsey’s London office, Sastry Chilukuri is an associate principal in the New Jersey office, and Michael Levy is an associate principal in the Washington, DC, office.

How will big data affect competition?

Big data will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus—as long as the right policies and enablers are in place.

What are the policies related to big data?

Policies related to privacy, security, intellectual property, and even liability will need to be addressed in a big data world. Organizations need not only to put the right talent and technology in place but also structure workflows and incentives to optimize the use of big data.

How does big data benefit consumers?

For instance, services enabled by personal-location data can allow consumers to capture $600 billion in economic surplus . 5. While the use of big data will matter across sectors, some sectors are set for greater gains.

Why are companies using data collection and analysis?

Leading companies are using data collection and analysis to conduct controlled experiments to make better management decisions; others are using data for basic low-frequency forecasting to high-frequency nowcasting to adjust their business levers just in time.

Why is big data important?

The use of big data will become a key basis of competition and growth for individual firms. From the standpoint of competitiveness and the potential capture of value, all companies need to take big data seriously. In most industries, established competitors and new entrants alike will leverage data-driven strategies to innovate, compete, ...

What is MGI research?

Research by MGI and McKinsey's Business Technology Office examines the state of digital data and documents the significant value that can potentially be unlocked. Open interactive popup. MGI studied big data in five domains—healthcare in the United States, the public sector in Europe, retail in the United States, ...

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To understand the potential of “big data,” look no further than the US healthcare sector. Information silos between payers and providers are crumbling, enabling the powerful integration of digitized public historical and real-time data.

Many innovative US health-care data applications move beyond retroactive reporting to interventions and predictive capabilities

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What are the tools used in pharmaceutical R&D?

Pharmaceutical R&D must continue to use cutting-edge tools. These include sophisticated modeling techniques such as systems biology and high-throughput data-production technologies—that is, technologies that produce a lot of data quickly, for example, next-generation sequencing, which, within 18 to 24 months, will make it possible to sequence an entire human genome at a cost of roughly $100.

How do organizational silos affect data?

Organizational silos result in data silos. Functions typically have responsibility for their systems and the data they contain. Adopting a data-centric view, with a clear owner for each data type across functional silos and through the data life cycle, will greatly facilitate the ability to use and share data. The expertise gained by the data owner will be invaluable when developing ways to use existing information or to integrate internal and external data. Furthermore, having a single owner will enhance accountability for data quality. These organizational changes will be possible only if a company’s leadership understands the potential long-term value that can be unlocked through better use of internal and external data.

Why are real world outcomes important?

Real-world outcomes are becoming more important to pharmaceutical companies as payors increasingly impose value-based pricing. These companies should respond to this cost-benefit pressure by pursuing drugs for which they can show differentiation through real-world outcomes, such as therapies targeted at specific patient populations. In addition, the FDA and other government organizations have created incentives for research on health economics and outcomes.

Why is it important to ensure the appropriate allocation of scarce R&D funds?

To ensure the appropriate allocation of scarce R&D funds, it is critical to enable expedited decision making for portfolio and pipeline progression. Pharmaceutical companies often find it challenging to make appropriate decisions about which assets to pursue or, sometimes more important, which assets to kill. The personnel or financial investments they have already made may influence decisions at the expense of merit, and they often lack appropriate decision-support tools to facilitate making tough calls.

Is R&D a secretive activity?

Pharmaceutical R&D has been a secretive activity conducted within the confines of the R&D department, with little internal and external collaboration. By breaking the silos that separate internal functions and enhancing collaboration with external partners, pharmaceutical companies can extend their knowledge and data networks.

A New Value Framework

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