2 items tagged "operational excellence"

  • Data, Analytics & Fuel Innovation at Celgene

    Williams-Richard-CelgeneCIO Richard Williams leads a global IT organization that’s harnessing digital, data, and analytics to support R&D innovation, drive operational excellence, and help Celgene achieve first-mover advantage in the shift to value-based, personalized health care intended to help patients live longer and healthier lives.
     
     
    An explosion of electronic health information is rocking the entire health care ecosystem, threatening to transform or disrupt every aspect of the industry. In the biopharmaceutical sector, that includes everything from the way breakthrough scientific innovations and insights occur to clinical development, regulatory approvals, and reimbursement for innovations. Celgene, the $11 billion integrated global biopharmaceutical company, is no exception.
     
    Indeed, Celgene, whose mission is to discover, develop, and commercialize innovative therapies for the treatment of cancer, immune-inflammatory, and other diseases, is aggressively working to leverage the information being generated across the health care system, applying advanced analytics to derive insights that power its core business and the functions that surround and support it. Long known for its commitment to external scientific collaboration as a source of innovation, Celgene is investing to harness not only the data it generates across the enterprise, but also the real-world health care data generated by its expanding network of partners. Combined, this network of networks is powering tremendous value.
     
    CIO Richard Williams sees his mission—and that of the IT organization he leads—as providing the platforms, data management, and analytics capabilities to support Celgene through the broader industry transition to value-based, personalized health care. At Celgene, this transformation is enabled by a focus on the seamless integration of information and technology. A cloud-first platform strategy, coupled with enterprise information management, serves as the foundation for leveraging the data generated and the corresponding insights from internal and external health care data.
     
    Williams recently shared his perspective on the changes wrought by enormous data volumes in health care, the role of IT at Celgene, and the ways IT supports life sciences innovation.
     
    Can you describe the environment in which Celgene is currently operating?
     
    Williams: We are living in an exciting era of scientific breakthroughs coupled with technology convergence. This creates both disruption and opportunity. The explosion and availability of data, the cloud, analytics, mobility, artificial intelligence, cognitive computing, and other technologies are accelerating data collection and insight generation, opening new pathways for collaboration and innovation. At Celgene, we’re able to apply technology as never before—in protein homeostasis, epigenetics, immuno-oncology, immuno-inflammation, informatics, and other fields of study—to better understand disease and develop targeted therapies and treatments for people who desperately need them.
     
    How does IT support scientific and business innovation at Celgene?
     
    At its core, Celgene IT is business aligned and value focused. Rather than looking at technology for technology’s sake, we view information and technology as essential to achieving our mission and business objectives. As an integrated function, we have end-to-end visibility across the value chain. This enables us to identify opportunities to leverage technology investments to connect processes and platforms across all functions. As a result, we’re able to support improvements in R&D productivity, product launch effectiveness, and overall operational excellence.
     
    This joint emphasis on business alignment and business value, which informs everything we do, is manifest in three important ways:
     
    First is our emphasis on a core set of enterprise platforms, which enable us to provide end-to-end visibility rather than a narrower functional view. We established a dual information- and cloud-first strategy to provide more comprehensive platforms of capabilities that can be shared across Celgene’s businesses. The cloud—especially with recent advances in security and analytics—provides tremendous scale, agility, and value because it allows us to standardize and create both consistency and agility across the entire organization regardless of device or access method. It’s our first choice for applications, compute power, and storage.
     
    Second is our focus on digital and the proliferation of patient, consumer, scientific, and it is creating. Health care data is growing exponentially—from something like 500 petabytes (PB) of data in 2013 to 25,000 PB by 2020, according to one study.
     
    To address this opportunity, we’ve initiated an enterprise information management (EIM) strategy through which we are targeting important data domains across our business and applying definitions, standards, taxonomies, and governance to data we capture internally and from our external partners. Establishing that consistency is critically important. It drives not only innovation, but also insight into our science, operations, and, ultimately, patient outcomes. Celgene is at the forefront in leveraging technologies that offer on-demand compute and analytic services. By establishing data consistency and influencing and setting standards, we will support our own objectives while also benefiting the broader industry.
     
    Third is our support for collaboration—the network of networks—and the appropriate sharing of information across organizational boundaries. We want to harness the capabilities and data assets of our partners to generate insights that improve our science and our ability to get better therapies to patients faster. Celgene is well-known in the industry for external innovation—how we partner scientifically—and we are now extending this approach to data and technology collaboration. One recent example is our alliance with Medidata Solutions, whose Clinical Cloud will serve as our enterprise technology and data platform for Celgene clinical trials worldwide. Celgene is also a founding commercial member of the Oncology Research Information Exchange Network, a collaboration of cancer centers spearheaded by M2Gen, a health informatics solution company. And we have teamed with ConvergeHEALTH by Deloitte and several other organizations for advanced analytics around real-world evidence and knowledge management, which will also be integrated into our data platform.
     
    You’re building this network-enabled, data-rich environment. But are your users prepared to take advantage of it?
     
    That’s an important aspect of the transformation and disruption taking place across multiple industries. Sure, IT can make information, technology, and insights available for improved decision-making, but the growing complexity of the data—whether it’s molecular structures, genomics, electronic medical records, or payment information—demands different skill sets.
     
    Data scientists are in high demand. We need to embed individuals with those specialized skills in functions from R&D to supply chain and commercial. At the same time, many more roles will require analytics acumen as part of the basic job description.
     
    As you build out your platform and data strategies, are you likely to extend those to your external alliances and partners?
     
    External collaboration enabled by shared data and analytics platforms is absolutely part of our collaboration strategy. If our informatics platforms can help our academic or commercial biotech collaborators advance the pace of their scientific evaluations, clinical studies, and commercialization, or they can help us with ours, that’s a win-win situation—and a differentiator for Celgene. We are already collaborating with Sage Bionetworks, leveraging Apple ResearchKit to develop an app that engages patients directly in innovation aimed at improving treatments for their diseases. We’re also working with IBM Watson to increase patient safety using cognitive computing to improve drug monitoring. As the power of collaborative innovation continues, collaboration will become more commonplace and lead to some amazing results.
     
    As you look out 12 to 18 months, what technologies might you want to bolt onto this platform or embed in your EIM strategy?
     
    The importance of cognitive computing, including machine learning and artificial intelligence, will continue to grow, helping us to make sense of the increasing volumes of data. The continued convergence of these technologies with the internet of things and analytics is another area to watch. It will result in operational insights as well as new, more intelligent ways to improve treatments for disease.
     
    What advice do you have for CIOs in health care or other industries who may not be as far along in their cloud, data, and analytics journeys?
    A digital enterprise is a knowledge- and information-driven enterprise, so CIOs should first focus on providing technologies and platforms that support seamless information sharing. In the process, CIOs should constantly be looking at information flows through an enterprise lens—real value is created when information is connected across all functions. Next, it’s increasingly important for CIOs to help build a technology ecosystem that allows the seamless exchange of information internally and externally because transformation and insight will occur in both places. Last, CIOs need to recognize that every job description will include data and information skills. This is an especially exciting time to be in IT because the digital capabilities we provide increasingly affect every function and role. We need to help people develop the skills they need to take advantage ofwhat we can offer now and in the future.
    Source: deloitte.wsj.com, November 14, 2016
  • Leveraging operational intelligence to proactive insights

    operational intelligenceEarlier i discussed the way technology and its adoption are shifting within organizations. Now, business intelligence (BI) and analytics are much more flexible and can adapt to a variety of business needs beyond simple reporting, dashboards, advanced analytics, etc. Storage options, the Internet of Things (IoT), operational insights, artificial intelligence (AI), and predictive analytics are being adopted by organizations to complement their traditional BI implementations.

    Taking advantage of what the market has to offer can make the difference between being able to align analytics to quantifiable business value and simply delivering traditional reporting and dashboards to a series of end users. The potential to drive operations and create competitive advantage remains limited with the more traditional approach.

    The Shift in BI Infrastructures and Data Access

    Before organizations consider changing the way they address BI and analytics, they need to educate themselves about where technology is headed within the market. For instance, the role of traditional data warehouses is no longer essential to BI and analytics deployments within certain use cases. Some companies have adopted big data infrastructures as a centralized data store while others look to real-time data streaming to support operational visibility. A good example is the use of sensors for quality control or worker safety.

    Taking advantage of the right technology for the right use case requires an understanding of the following:

    1. Technology: Understanding innovation and how current and emerging technologies will affect a particular industry is important when evaluating solutions. Some organizations focus on deploying a set of dashboards or a self-service portal to access their analytics, but overlook the data management requirements that will actually support the types of analytics required.

    Technology adoption should be directly tied to the desired outcomes. With all of the messaging in the market, identifying the right set of software or the right infrastructure to support advanced analytics can be a challenge. Although traditional reporting and analytics will always provide value due to visibility into trends, BI infrastructures moving forward need to take into account both traditional and operational analytics. This means ensuring right-time access to data and leveraging technologies that can be flexible enough to shift with the changing needs of an organization.

    The ability to leverage IoT data or create predictive models are only two areas that are becoming more important. Making sure that business and technology considerations take into account both current and potential future requirements will make it easier for organizations to mature and broaden their analytics use as their needs expand.
       
    2. Industry and competitive factors: It is not always easy to anticipate future challenges or industry direction. At the same time, it is possible to research what competitors are doing, understand market trends, and make sure that the technologies selected take into account these trends and can meet these needs. Understanding the competition and what competitive and environmental factors may affect the business can help organizations hone in on what type of solutions they require and the type of analytics that will best meet their needs.

    Author: Linday Wise (Information Builders)

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