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How advanced analytics can deliver value for life sciences

Life sciences companies are investing more and more in their compliance programs, upgrading the technology that collects data, maintaining robust IT departments and hiring independent reviewers to better identify, monitor, track and mitigate risks. To remain competitive in this highly regulated industry, it’s increasingly critical for top players to connect the dots between policy and efficient and effective internal processes.

Meeting compliance challenges is certainly top of mind, but what many life sciences companies may not realize is that the compliance data collection and reporting process generates an enormous amount of information that may be used in additional high-value ways. This data stockpile may be extremely useful for future risk planning purposes through using advanced analytics.

The role of data in the current regulatory environment

One of the most recent regulatory efforts driving data collection is the Open Payments website, launched by the Centers for Medicare and Medicaid Services (CMS). Mandated by the Physician Payments Sunshine Act provisions of the Affordable Care Act, the website came online in September 2014. Open Payments requires pharmaceutical or medical device manufacturers to publicly report payments made to physicians and teaching hospitals, using a database. The purpose of the regulation is to provide greater transparency around the financial relationships between these entities.

Another example is the Foreign Corrupt Practices Act,1 which requires any life sciences company operating internationally or engaging offshore third parties to ensure that it has implemented effective, consistent and enforceable anti-bribery programs. The Department of Justice and the SEC have issued A Resource Guide to the U.S. Foreign Corrupt Practices Act. The principles in the guidelines include implementing programs that provide a standard, consistent process to on-board third-party intermediaries (TPIs) and perform risk assessments and the necessary due diligence that will be used to determine if an organization should engage the TPI.

In both cases, a tremendous amount of data is being collected electronically for a fairly narrow purpose. But there is an opportunity for organizations to leverage these data assets to anticipate risks and make appropriate mitigation decisions.

Moving beyond compliance

On their own, bits of quantitative and qualitative data offer limited insight for use on a broader scale, as they are meant to satisfy specific regulatory requirements. There may also be challenges in understanding what data is available and then accessing the right information. Organizations typically house data in silos, which can make cross-referencing difficult — other parts of the organization may not know the data even exists. In addition, organizational resistance and other internal concerns over issues like data privacy and data quality may pose additional challenges. Overcoming these types of obstacles should be an important initial goal for leadership — taking a strong position on using data in new ways is integral to a sound business strategy.

Once project leaders have access to the data, they can use information discovery tools that incorporate advanced analytics. This kind of technology can help life sciences organizations sift through large sets of unstructured content, expose previously unprocessed data, determine the pertinent metrics and correlations, and define the right questions to ask. From this insight, enterprise data can be formalized and incorporated.

The data can then be used to make informed predictions about a range of possible future risks and outcomes. Sophisticated technology allows companies to view data to understand past performance, and also helps them utilize powerful, cutting edge solutions to analyze the data and uncover patterns, helping leadership predict future outcomes. This knowledge enables projection-based strategic decision-making, allowing a business to predict the best possible courses of action in the near and long terms.

A case in point: Leveraging data at a pharmaceutical company

We recently worked with a large global pharmaceutical company that was concerned about its lack of control over spending and ROI. The company was having difficulty leveraging the data gathered by its expense approval application and was looking for a way to analyze trends by activity and spending for potential compliance red flags. Ultimately, they were interested in delving deeper to examine the data at a country, entity, department, and individual requestor and health care professional level to help identify areas of high-risk or inappropriate spending. The team also was able to validate actual spending against marketing budgets. Going forward, we will be monitoring ROI.

Grant Thornton professionals worked with the organization to build an advanced analytics capability that provides insights into data about international health care professionals’ meals, entertainment and travel expenses for research, conference and marketing events. Using the information collected to satisfy transparency and monitoring reporting requirements, our team helped the company transform its once-idle dataset via an Oracle-based agile data discovery tool. The reports created by the tool enabled greater visibility through a search-based and search-guided navigation interface.

As a result, the pharmaceutical company gained the compliance awareness they required along with valuable business insight. The application allowed for dual analysis of structured data such as expense type, amount and associated individuals, and unstructured data such as event or expense justification comments. A watch list was developed, and expense thresholds were set for monitoring individuals with high expense totals of gifts and entertainment.

The application can be used going forward to proactively drive compliance and identify additional opportunities for optimizing spending and budgeting.

Conclusion

Advanced analytics are the key to flexibly and efficiently processing large amounts of existing data. Once analyzed, the data can be used to rationalize operations and also make predictions about future scenarios that may affect such things as revenue, operations and various risk options. Determining additional uses for data is the best way for companies to get the maximum return on their investment in new technology. And with advanced analytics, the process is cost-efficient, takes a relatively short time and provides useful predictive information that can give life sciences companies the insight they need to address critical issues both now and in the future.

1 The Foreign Corrupt Practices Act prohibits U.S. individuals or companies from making payments to foreign government officials and political figures. See http://www.justice.gov/criminal/fraud/fcpa for more information.