Advancements in data science will increasingly help pharmaceutical companies to make decisions about issues such as drug discovery, patient access, production and marketing.
Since 2015, Agilytic has been a trusted partner of leaders in the healthcare ecosystem. In addition to mastering data methodologies and analytics tools, we built a comprehensive understanding of the business context. We have been actively recruiting and developing people with the requisite skills, partnering with universities and kept up to date with the latest advances of the leading cloud technology providers.
Broad experience in healthcare
Our expertise doesn’t stop at pharmaceuticals. We had the opportunity to work on projects across the whole health value chain, for example:
- R&D: structure the data analytics for an emerging player in proteomics research
- Health insurance: pricing, marketing and customer experience projects for a leading health insurer
- Pharmacy marketing: automated OTC reference classifier for a pharma marketing leader
- Hospitals: report automation at a leading hospital in Brussels
This broad expertise in the sector allows us to see beyond the “business as usual” and to suggest new perspectives.
With a few examples, let’s see how Agilytic can help your Pharma project reach its ambitious objectives.
Optimising the marketing mix at an international Pharma
A recent project led us to optimise the marketing mix of an international Pharma company.
Our client invested millions of Euros in a wide range of initiatives to support its sales efforts: sales representatives of course, but also trade publications or call centre outbound campaigns. The question was: how do we make sure this is all money well spent? Is there a way to make the most of our sales & marketing investments?
Although drug rep visits are far from obsolete, analytics can improve their return on investment. A key challenge was thus to save time and money by prioritising visits from pharmaceutical reps where it would count the most.
We analysed the sales rep visit patterns and matched them with doctors’ prescribing habits to maximise the impact of each visit, either by altering the visit plan or by recommending alternative products to discuss. We also built scenarios on budget reallocations between other promotional channels such as outbound calls or trade press to maximise the ROI further.
Pharmaceutical representatives were able to focus on specific physicians in a geographical area with patients most likely to need promoted medication based on predictive analysis.
The recommendations were fed to all international branches into the Pharma’s existing workflows so that no new software was required.
Ultimately, the marketing mix optimisation led to a better allocation of hundreds of thousands of Euros in marketing budget globally.
Hiring and retaining the best talents
Pharma is a highly competitive market. Without the right talent, technology is worthless. Agilytic helped organisations at every step of the HR process, such as
- Recruiting: automate the candidate classification with cutting edge Natural Language Processing technologies.
- Anticipating employee absenteeism in production lines and other critical activities
- Assess the risk of voluntary departure of key talent through advanced forecasting
Focus on rapid impact and knowledge transfer
While technological advances are generating great opportunities, they also pose resourcing and capability development challenges. One of the biggest is how to make the transition from legacy technology and analytical competence to more-powerful and sophisticated analytical tools and analysis methodologies.
That is why we work with an agile mindset. We aim at producing first results in a matter of weeks, not months. However, we are familiar with larger structures where organisational silos may result in data silos, where legacy systems don’t make it easy to rationalise and connect various sources and where not every stakeholder has the similar mindset when it comes to the transformational potential of analytics.
Data science is not an IT problem. We don’t solve complex issues by throwing more servers at them. A key barrier preventing Pharma from launching successfully into big data projects is its workforce. That’s why we
- assist business leaders in asking the right questions from the data and building a quantitative culture to complement medicine and biology
- make sure to plan our projects with knowledge transfer in mind, for example by pairing one of our data scientists with an internal colleague.
Playing nice with your technologies
We don’t sell software. Instead, we build the intelligence feeding your systems. We are familiar with most data sources and architectures and are able to push enriched data to your existing apps, be they CRM, ERP or HR.
To support our transformation, we needed to improve the way we master data and use it to achieve our strategic goals.
— D. Fraiture. Chief Transformation Officer, Partenamut
Historically, the pharmaceutical industry has recruited programmers who have executed well-defined analyses in a standardized, efficient manner. However, real-world data comes in a variety of different formats, is often highly unstructured (containing textual and other non-numeric data), and is rife with missing values. It is messy data, filled with inconsistencies, potential biases, and noise. These attributes force data scientists to find creative ways to answer critical questions to support drug R&D, but also supporting business functions such as Marketing and HR.
Consequently, there is an emerging need for data scientists who can take full advantage of tools and techniques developed in Silicon Valley that are capable of handling noisy data and presenting results to stakeholders in a simple, easy-to-interpret way. These analysts must be able to deal with ambiguity and be collaborative, entrepreneurial, and adaptive in their approaches. They must be able to apply “options thinking” to figure out what questions to ask, what data to examine, and what methodologies and technologies to use to address the aim. They must also have an in-depth knowledge of the health care system, including its standard practices, to understand how the data was initially collected, what biases may exist, and how it can be repurposed to answer questions.
It is never easy to learn how to tap the full potential of real-world data. However, it is possible. The potential to use that data to get the right treatments to the right patients at the right time is enormous.
Insights. Actions. Results.
Since 2015, Agilytic helps organisations reach their goals through the smarter use of data. We have completed over 80 projects, in healthcare and beyond.