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    January 05, 2018 by Actando Consulting Team LEARNING SOLUTIONS > Blended learning

    Database Dashboards & Dilemmas


    For whatever reason, your data sources are simply not producing relevant and compelling insights. So what next? There seems to be data at every turn, but it is impossible to manage and make sense of it to yield new insights.

    We seem to have too much data available and it is growing.

    To our traditional industry data such as IMS (Quintiles), in-house CRM data on the activities of the sales force, and manufacturing and distribution data we have now added even more with the introduction of digital activities.  Our entrenched evidence-based mindset drives our need for lots of data to draw valid conclusions and make informed action-driven strategic decisions. However, we are often paralysed by the amount of data, feeling like we need more and more, so we can be sure we know everything we need to know and our decisions are sound.

    Analytics has always been important, but now they are a critical business requirement to meet not only internal demands but also the market and regulatory demands that prove our value. The challenge today is that we have so much data to consolidate into one database, then clean, manipulate and filter in order to create usable analytics for each functional role.

    Making Sense Of It All

    Finding meaning in data always begins with the patient in mind. Apart from clinical trial data, most of the usable marketing and sales data comes from the billing and processing of healthcare interactions during patient care, with perhaps the most relevant being the prescription and distribution of our products. In some cases, manufacturing and distribution data along with account pricing and contracts are relevant data in the management of customer relationships, driving targeted marketing and sales activities, and ensuring patient access.

    Once prescription and sales data is captured, cleansed and integrated, it is bucketed into broad distribution channels: pharmacy/retail (Point of Sale or POS) with HCP, Payer and patient tags, hospital/institutional channels (distribution and company sales), each sorted by geography.  The data is then used by various departments within the organisation for resource allocation decisions, performance evaluation and goal setting, targeting and forecasting, call planning, incentive management, demand management, and pricing and contract compliance, to list a few.

    In certain markets, rebates, contracts and benefit dollars pass through many channels throughout a managed care process. Government mandates and restrictions add further complexities and are additional sources of data. It’s no longer about the growth or maintenance of market share through HCP targets or the management of contracts, but more broadly includes balancing patient and payer dynamics as well.

    Add to this, new sources of data from customer interactions, primary market research and data in the format of voice recordings, video, paper-based assets and PowerPoint agency summaries.

    So where does this leave us?  

    Finding Solutions

    At the core of any solution, you will need skilled individuals and teams who understand our data to handle more and more complex data collection, storage, management and analytics. Centralisation is critical to being able to scale up and use one source of truth for across applications. To have the right tools in place, IT and Business Intelligence must forge a strong partnership, with a shared understanding of the back-end requirements and the front-end functional deliverables, and be able to divide and conquer.

    While we tend to want to keep it all in-house, the intensity and scarcity of in-house resources can lead to engaging third parties to expedite the consolidation of various data sources and the speedy production of frequent analytics in usable dashboards.  

    Application of pharma and life sciences analytics ranges from basic reporting and internal dashboard creation to high-end predictive and prescriptive analytics. The key applications of analytics in Pharma and life sciences include regulatory compliance reporting, marketing/sales support, and product/service enablement. The third-party analytics services market for healthcare is expected to increase by over five times its current size by 2020. [ Genpact 2014]

    The role of the Business Intelligence team is no longer to manipulate various data sources and build dashboards, but rather to focus on interpreting the data, aligning it to the business needs, and continuously facilitate insight discovery in partnership with the other functions.

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    Digitally Charged Pharma

    The digital transformation of healthcare is well underway and provides new opportunities to get to know our customers and patients. With this brings Big Data – lots and lots of real-world data, streaming in every minute of every day. This is fantastic if harnessed. “The concept of the connected human being given personalised care and improved diagnostics is one long foreseen by science fiction. “ [March 2017 by Ben Davis @ Econsultancy ]

    If you have not already started to transform your Business Intelligence area to meet the growing demands of managing more and more data and delivering new insights, consider shifting to an outsourced option and start building the business case before you get too far behind. The alternative, a large operational in-house solution, is potentially unaffordable, and likely not agile and responsive enough for the majority of us, leaving our business without up to date data to make good decisions.



    If you are interested in our mobile learning solutions on digital channels, contact Actando.

    The Actando Consulting Team


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