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The Active Ingredient features expert insights and commentary from leaders of ZS Associates' global pharmaceuticals practice.

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Making the Case for a New Analytics Consumption Model

Posted by ZS Editors on Thu, Nov 29, 2018

Industries like retail and technology are transitioning to an AI-driven, personalized approach to surfacing insights to end users, and they’re reaping the benefits. Life sciences companies have the same opportunity to capitalize on the runaway growth in data and rethink the way that analytics are consumed.  

ZS recently partnered with IDC to study how commercial life sciences teams are currently consuming data, and to determine their data and analytics pain points. The study revealed that sales and marketing professionals in life sciences want

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Topics: Analytics, artificial intelligence, AI, data and analytics, analytics disruption, commercial analytics, artificial intelligence & pharma, cutting-edge analytics, advanced analytics, personalized analytics, analytics maturity, pharma commercial model

New ZS Research on Forecasting in an Evolving Landscape

Posted by Ram Ramakrishnan on Mon, Jul 09, 2018

This post is the second in a four-part series on how pharmaceutical companies can elevate their forecasting operations.

The pharmaceutical industry is facing an increasingly challenging environment with looming biosimilar launches, tighter access and pricing controls, and saturation within primary care markets. Forecasting as a functional area is affected by these changes, given the range of decisions that forecasts inform.

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Topics: forecasting, Pharma, insights, artificial intelligence, AI, machine learning, artificial intelligence & pharma, pharma landscape, ZS research, forecasting in pharma

Having Customer-Centric Capabilities Doesn’t Mean That You’re a Customer-Centric Organization

Posted by Pete Mehr on Mon, Jul 02, 2018

This post is the second in a three-part series on how pharma companies can achieve customer centricity.

In my previous blog post, we spoke about pharmaceutical companies moving from a tactic-based marketing process to an orchestrated marketing process. The motivation for making this change is to optimize the customer experience. To achieve this goal, pharmaceutical companies have started to leverage cloud-based computing capabilities, purchase marketing automation platforms, enhance their analytic capabilities using data science and machine learning, use social media platforms, and hire digital experts from other industries, just to name a few of the changes. Yet companies still struggle to realize the value from these investments. 

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Topics: customer centricity, Pharma, Pharmaceutical Companies, integration, change management, AI, customer-centric, automation, point change, customer-centric capabilities, customer-centric pharma organizations, system change

AI Across the Pond: Implementing Next Best Actions in Europe

Posted by Zainul Jafferji on Wed, Jun 27, 2018

There’s no shortage of news about how artificial intelligence techniques are helping us engage customers better in healthcare. Many pharmaceutical companies have visions of Amazon-like targeting serving up Netflix-esque recommendations on how to engage customers better with the right channels, content and cadence.

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Topics: customer experience, Pharma, pharmaceuticals, personalization, Europe, artificial intelligence, EU, AI, machine learning, next-best actions, european market, artificial intelligence & pharma, personalized analytics

Collaboration in Clinical Operations: Three Takeaways From SCOPE 2018

Posted by Qin Ye on Fri, Mar 02, 2018

Abhay Jha and Venkat Sethuraman co-wrote this blog post with Qin Ye.

More people than ever before attended the ninth-annual Summit for Clinical Ops Executives (SCOPE)—a testament to the growing importance of innovation within clinical development. Attendees from across life sciences gathered in Orlando Feb. 12-15 to discuss clinical development challenges and solutions, and to network with peers and partners.

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Topics: Innovation, Pharma, pharmaceuticals, artificial intelligence, AI, SCOPE, clinical trial design, clinical trials, machine learning, SCOPE 2018, clinical operations, clinical development, blockchain, clinical trial recruitment

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