An Alexion Pharmaceutical Story
Venk Dakshin of Alexion Pharmaceuticals recently joined Ashwin Nayak of Zaloni in a webinar on Alexion’s journey to data governance success using the Zaloni DataOps methodology and platform. Venk, who is Alexion’s Senior Director of Enterprise Applications and Architecture, began by illuminating the importance of data governance in the healthcare and pharmaceutical industries, with particular emphasis on treating rare diseases.
The statistics on rare diseases are staggering:
- 7,000+ known rare diseases in existence
- only 5% have an approved treatment
- over 400 million people affected by rare diseases
- 50% of those people are children
- 3 out of 10 of those children won’t live to see their 5th birthday
- that’s 60 million children who face an early death due to rare disease
Based on these numbers, rare diseases don’t seem so rare.
Venk continued on to talk about Alexion’s role in helping to get those people treated for their rare diseases. He discussed how critical data quality and analysis are to the operational excellence of a pharmaceutical company in solving these large-scale problems.
“Data governance is the key for us to get greater value and insight across multiple data domains and data sources… Enterprise data governance enables us to move from a siloed functional strategy and tools to aligned enterprise data strategy based on collaboration and consistent tools. It really helps us treat data as an enterprise asset.” – Venk Dakshin, Alexion
Venk mentions that an analyst or data scientist from a pharmaceutical company typically spends 70% of their time navigating the organization’s tribal knowledge and only 30% answering pressing business questions.
That means 70% of critical time understanding deadly rare diseases is potentially wasted on:
- Understanding where data is stored
- Understanding the definitions of the data
- Massaging the data to resolve conflict and definitions
How many more lives of those with rare diseases could be saved if analysts could answer the pressing questions 70% faster?
Slide 4 from the webinar: Data Governance Best Practices with Alexion Pharmaceuticals
- collaboration around data is enabled
- the data definitions are easily understood
- data can be easily accessed from a centralized catalog
- and data scientists have more time to work on answering pressing questions that may save the lives of those with rare diseases.
Journey to Data Governance Maturity
Slide 5 from the webinar: Data Governance Best Practices with Alexion Pharmaceuticals
The above image represents the key phases of a journey to data governance maturity, according to Venk Dakshin at Alexion.
- Have data in multiple warehouses
- Definitions that conflict with each other
- Very low data quality
- Extremely difficult to get good insights
- Siloed approach toward data projects
- Little or no cross-functional collaboration
- Build a data foundation
- Implement a data lake with multiple zones
- Serve the needs of the various business units from an analytics perspective
- Utilize descriptive analytics to identify what has happened – looking backward
- Limited collaboration with the business
- No consistent operating models
- Enable Customer Master Data Management
- Establish enterprise data governance
- Decide the operating model – centralized, distributed, or hybrid
- Enable key use cases for governance across business units
- Establish Employee data governance
- Enabling Finance Master Data Management
- Mature from descriptive to prescriptive and predictive analytics
- Improve collaboration and data literacy across the organization
- Start to embed data in the company culture
- Significantly improve data quality
- Data scientist team critical
- Being data-driven on a consistent basis
- Answering business questions
- Expand artificial intelligence and machine learning
- Prescriptive analytics and forecasting
- Embed data into the company culture
Data Governance an Enabling Force Across the Organization
Data governance offers continuous improvement to all functions of the business, from R&D to supply chain to sales and marketing.
Take these steps to deliver success:
- Catalog the data to make it easier to find and understand
- Establish roles and responsibilities, and manage access to the data on a regular basis.
- Streamline self-service consumption of trusted data to truly move up the maturity model
Create a “Google” for business data
Consider an end-to-end platform that allows you to catalog, control, and consume data in one place, like the Zaloni Arena DataOps platform.
“Maturity takes hard work, time, and consistent focus. It’s not easy, but you reap the rewards of being on top of your data game.” – Says Venk, and when that “game” is creating new drugs to save the lives of children with rare diseases, enterprise-wide data governance is of utmost importance.