Michelin: Democratizing AI for Improved Industrial Performance
Michelin uses Dataiku to democratize AI, improving quality, maintenance, machine availability, supply chain, energy consumption, and more.
Learn Morereduction in data ingestion time
In the fast-paced world of pharmaceuticals, where every decision can impact real lives, Novartis faced a critical business challenge that demanded a revolutionary solution.
Tasked with weekly updates of data in Excel to generate crucial metrics, the team found themselves entangled in a web of manual calculations and decisions with far-reaching consequences. The need to modify parameters, coupled with a lack of real-time data refresh and ineffective tracking, led to discrepancies and hindered the identification of risks in budget forecasts and field-force allocation.
Enter the dynamic duo – Novartis’s data engineer and data science teams. Faced with these challenges, they embarked on a mission to streamline analytics and machine learning across the organization.
The journey began with the development of an automated solution utilizing SARIMAX in Python for time series modeling and forecasting future values based on historical data. The result was a transformative shift from repetitive manual calculations to informed decision-making grounded in accurate and real-time data.
To attain its goals, Novartis harnessed the power of Dataiku, a robust platform offering modular components for project design, batch process automation, real-time API scoring, and AI governance. The team created a customized simulation dashboard, empowering decision-makers with automated analyses of budget allocation and field-force allotments, unlocking the potential for better decisions and seizing demand-growth opportunities.
Dataiku not only facilitates the development of tailored, machine learning-based forecast models, but also presents the results of these models in a user-friendly environment. The platform’s informative wikis for data sources and processes, coupled with support for global variables and parameterization, ensured not just efficiency but also an organized approach to problem-solving.
At Novartis, the day-to-day change was palpable. Adopting Dataiku was a natural evolution for the data teams, exposing them to new functionalities that quickly found their way into other teams’ workflows. The self-explanatory workflows and parallel execution of scenarios reduced implementation time, transforming the once endless rabbit hole of user queries into a streamlined, one-stop shop for all questions.
In the areas of marketing, sales, and customer relationship management, in particular, Novartis witnessed the tangible impact of Dataiku’s value generation. The platform’s pushdown design ensured optimum performance and efficiency, even when handling massive workloads. Metrics, checks, and testing capabilities provided by Dataiku brought a new level of quality assurance to the models, elevating the team’s confidence in decision making.
The true value of Dataiku became evident in the efficiency gains. The platform’s automation features, including real-time data refresh and analysis, automatic periodic reports, and pre-built visualizations, became the cornerstone of Novartis’s success. The ability to track actual versus forecast variance through intuitive dashboards and sliders brought clarity and precision to decision-making.
For a more tangible example, let’s look at a specific challenge that surfaced in the commercial analytics at Novartis space for a newly launched product in the United States. The team needed to summarize large data volumes (on the order of 7 billion records), copy that data to Excel, and then create visualizations consisting of 50+ different charts with millions of data points.
Dataiku proved to be a game changer for this business challenge, delivering immense value across multiple dimensions:
With Dataiku at the helm for this use case, Novartis experienced significant reduction in the data ingestion time by 600% from a week to a matter of five hours and effort required to maintain up-to-date visualizations reduced from creating 35+ manual slides to the click of a button.
Novartis Pharmaceuticals found in Dataiku not just a solution implementation tool but a game-changer that aligned seamlessly with its vision to reimagine medicine. The platform’s features empowered the team to automate machine learning model solutions, create customized forecasts, and ultimately reach their business goals. In its quest to enter the AI- and data-driven future, Novartis Pharmaceuticals has not only reduced costs and saved time, but has moreover increased its teams’ trust in data-based decisions, fostering a culture of innovation and excellence.
Debbie Reynolds, VP Enterprise Data Solutions and Engineering at Pfizer, discusses how the company has been able to put data at the core of everyday business decisions.
Read moreMichelin uses Dataiku to democratize AI, improving quality, maintenance, machine availability, supply chain, energy consumption, and more.
Learn MoreLG Chem noticed that their employees were spending a lot of time searching for safety regulations and guidelines so, with the help of Generative AI and Dataiku, they provided an AI service that helps them find that information quickly and accurately.
Learn MoreBy moving to Dataiku and working with Dataiku partners, Snowflake and Snow Fox Data, Thrive Skilled Pediatric Care (Thrive SPC) has been able to advance from complicated spreadsheets to a central platform that provides clear insights and metrics to fuel their data-driven healthcare solutions.
Learn MoreMount Sinai has pivoted its processes to create more holistic methods which enable lasting results and life-long, positive impacts in patients’ lives. At the core of this transformation? Dataiku.
Learn More