Data Solutions to Power Decision-Making
After a corporate separation, a major acquisition and development of a modern IT ecosystem, Elanco IT is looking at opportunities for data solutions at Elanco to deliver a foundation that can be used to power decision-making.
Common Design Pattern & Technologies: The first opportunity that the separation from our former parent company introduced was the fact that we had to migrate or rebuild almost all our data solutions in a two-year period. Many of them could not be migrated because they leveraged technologies and designs that were no longer part of Elanco’s IT desired footprint – mostly because they required heavy deployment of virtual machines and aging packaged software rather than modern PaaS / SaaS approaches. Under our established enterprise cloud strategy, we were able create patterns based off published approaches and offer them to all development teams to build consistent solutions.
Data Products: Traditionally, data-focused solutions have been given labels like “data warehouse” or “operational data store.” The boundaries of these solutions tend to be quite broad – either functional or enterprise – and over time, they can become large repositories of code. This level of complexity impacts our ability to maintain, evolve and secure these solutions and can also limit our ability to react with appropriate flexibility to changing business needs. Borrowing from the micro-services architecture that exists for the application world, data products represent specific data domains and business outcomes that can then be combined to form even more powerful business outcomes and results. This approach is being recognised in the industry as a key part of creating a “data mesh” and we already have products at Elanco leveraging our common foundation.
Decentralization: Another common challenge with developing data-focused solutions is that the work tends to be developed by a single team. This can generate issues if multiple, competing priorities exist and the most common result is that a separate development team is spun up and they build a new solution on separate infrastructure. This regularly results in duplication of work and additional movement of data between systems – for example if both solutions want customer data. Building on the data product concept and through a combination of processes, tools, and technology, we can create an environment where multiple teams can work in parallel within one main platform – each working on different priorities for Elanco across various functional areas, from R & D to Manufacturing to Finance.
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Frameworks (Accelerators): After a few data products had been delivered, we identified opportunities to improve on our design pattern. This resulted in the creation of a framework that contained all the key requirements for data ingestion and data quality measurement. Using a combination of PaaS offerings, we have been able to deliver an approach that can make data from source systems available in our enterprise platforms with only a few days of technical development required – mostly spent figuring out how to connect to the source system and retrieve its data.
Accessibility: Ingesting data into a data platform is only valuable if the right people know it is there, know how to access it and have appropriate access methods to meet their needs. Therefore, in addition to the more traditional approaches of exposing data through business intelligence tools, data catalog and API management technologies provide further transparency and visibility to the breadth of data and become core parts of the landscape.
What Next? Of course, our data journey is far from complete. While everything described above establishes a great foundation, challenges and opportunities always lie ahead. data governance processes/capabilities/platforms, delivering machine learning consistently, improving the measurement of data flowing through solutions and progressing from frameworks to reusable components are all exciting opportunities to allow for better customer support, which for Elanco means improving the health of animals around the world.
? AI & Cloud Technology Account Director @ Oracle ? | Transforming Data into AI-Driven Insights | Life Sciences Industry Leader | Polyglot | Social Sales Strategist & Coach | ?? Master AI Before It Masters You
2 年Great story and data journey creating a solid & modern foundation. Congrats Matthew Bull and team. Very curious to learn more. Currently on similar journeys with many top global Pharma entities to leverage data governance processes, capabilities, platforms, and taking advantage of trends with machine learning predictions, intelligent automation, and other technologies to stay ahead of problems and see data in new ways, discover insights, extract the maximum value from data and unlock endless possibilities... Oracle & I are very much eager to exchange insights about your next step. - Can we?