Advancements in data science will increasingly help health insurance companies to make decisions about issues such as reimbursement evolution, products usage, members knowledge and workforce management.
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 health insurance
We had the opportunity to work on projects across the whole health insurance value chain, for example:
Customer acquisition: profiling the type of customer per region to target prospects with the right arguments
Upselling: crossing online and offline data, propose the right product and services at the right time to the existing clients
Support: identify fragile clients that could be lost in complex processes and assist them while the situation is still under control
Retention: identify the main drivers leading members to leave and proactively retain them
Debt enforcement: segment bad payers (distracted, fraudulent behaviors, non-users…) and act on them adequately to recover the unpaid amounts
Workforce management: optimise the daily workload handled by the employees while respecting all the constraints imposed by the working environment
This broad expertise in the sector allows us to see beyond the “business as usual” and to suggest new perspectives while providing tangible results.
With a few examples, let’s see how Agilytic can help your Health Insurance project reach its ambitious objectives.
Customer Next Best Action
A recent project led us to evaluate all the dimensions of a member, from product detention to interactions history to proactively act on the different profiles.
The client was conducting a lot of activities towards its clients, namely related to marketing and client support. But these actions were targeted on very basic socio-demographic criteria.
Together with the client we have collected and consolidated members’ data to build a rich overview of each member. Based on the newly gathered indicators we have then defined recommended actions for various profiles.
The client is now able to precisely motivate its actions towards its members through an automated Next Best Action system : who should be contacted for a specific product or service, who seems to need assistance for faster and more efficient reimbursement, who are the clients at risk of leaving and what is the reason…
Workforce Management Automation
A big player in the Belgian healthcare industry was facing difficulties in handling an increasing number of clients’ requests within its back office. On top of being suboptimal, the manual process in place was taking a lot of time and was prone to a lot of human error.
Together we built an automated assignment tool to help address these questions, starting with a 2-week pilot project aiming at capturing the data sources, document the business logic and constraints to take into account, and finally develop a solver that would maximise the utility – the weighted number of assigned tasks - under the defined constraints.
After deploying the solution to 400 collaborators, we have developed additional functionalities providing the client with detailed information on missing skills in the teams, insufficient workforce, unassigned tasks, expected volume in the coming weeks based on historical data…
The resulting automated solution allowed the client to:
Obtain a daily optimal assignment of the open tasks to the Back-Office agents (400 people)
Gain the equivalent of 1,5FTE thanks to the extended automation of the assignment process: from +12 hours to less than 2 minutes
Prioritize recruitment and training activities based on unassigned tasks and inadequate/missing skills
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 business knowledge.
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.
Insights. Actions. Results.
Since 2015, Agilytic helps organisations reach their goals through the smarter use of data.
We have completed over 60 projects, in health insurance and beyond.