text: SLB - Developing a Learning Plan to Upskill Employees and Pave the Way to AI Democratization
  Nikhil Choudhary, Learning & Competency Development Manager, Petro-Technical & Digital Experts
  Julie Neff, Digital & Integration - HR Director
  Boris Zolnikov, Digital & Integration - Learning & Competency Development Manager
  Sissel F. Wilson, Employee Development & Engagement Manager
  Country: United Kingdom
  SLB (SLB: NYSE) is a technology company that partners with customers to access energy. Our people, representing over 160 nationalities, are providing leading digital solutions and deploying innovative technologies to enable performance and sustainability for the global energy industry. With expertise in more than 120 countries, SLB collaborates to create technology that unlocks access to energy for the benefit of all. Find out more at www.slb.com.
  - Most Impactful Transformation Story
  - Partner Acceleration
  SLB is the market leader in digital solutions for the energy sector, and the competency of our domain experts helps us maintain leadership. The energy sector is now going through a digital transformation, powered mainly by artificial intelligence and machine learning. The transformation enables our domain experts to drive more value from the workflows for SLB and our customers. Automation and the Internet of Things enable digital transformation in the field, and as a result, we are now acquiring more and more data.
  Our business challenge was to ensure our domain expert improved their digital competency to keep pace with the transformation. Domain experts must draw insights from the data, make decisions with their digital workflows and take action in the field, which is impossible without automated data pipelines, feature engineering, and machine learning.
  We explored many options for our employees to start their data science journey, but all of these courses started with learning to code in Python. Learning to code is one of the most significant barriers for people to kick start their data science and machine learning journey.
  The EdTech platforms we looked at were also quite expensive, with no guarantees of measurable success. We also had to move fast as getting around 3000 of our domain experts to be data science practitioners in a short period of time was impossible in a classroom or virtual classroom format.
  In short, the main challenge we faced was figuring out how to upskill our people on application AI in an agile and open way while keeping employees motivated.
  As part of the Learning & Competency Management Team, we were responsible for upskilling our employees on data science and machine learning. Given that Dataiku is SLB's AI partner, with a philosophy of democratizing AI, Dataiku was a natural choice to help us accomplish this.
  To improve our data science literacy and understanding of Dataiku, the HR Team of the Digital & Integration division went through the Dataiku discovery training. A few team members completed the learning paths, and certifications offered online via the Dataiku Academy. The content was easy to digest with hands-on exercises, and the certifications, which are shareable externally, served as recognition and provided further motivation. We decided to use the Dataiku Academy as our domain experts' first step toward data science.
  We subsequently launched a custom Dataiku portal for SLB and a gamification campaign in November 2021 for our population, asking them to complete the certifications and post them on Yammer and LinkedIn. As an added incentive, we structured it so that the more certifications our employees acquired, the more their chances increased to win rewards as part of a raffle. We rewarded our employees with more learning, including internal courses of their choice and a limited number of virtual courses from top business schools.
  After successful phase 1 of the campaign, we initiated a second campaign in April 2022 with similar success, shown in the graph below.
  Many of our domain experts have completed multiple certifications, and adoption is increasing exponentially over time.
  Business Area: Analytics / Human Resources / Marketing/Sales/Customer Relationship Management / Product & Service Development
  Use Case Stage: In Production
  Since the launch of our learning plan, more than 500 employees have started their data science journey, acquiring over 1300 certifications with Dataiku.
  The conversation has now shifted from how to start learning data science to how one can use data science to solve a problem - true AI democratization within the company!
  Employees have become 2.0 versions of themselves, trying to use Dataiku for building automated data pipelines, data analytics, and simple machine learning solutions without code, which was the initial purpose of the campaign. Not only that, Dataiku is now used to resolve business challenges across different departments, including Human Resources, Compensation & Benefits, Risk Management, and Operations, among others.
  Previously identified as a barrier, motivated employees are now learning Python for code recipes, researching more machine learning concepts, and building connectors to internal software.
  AI is no longer a threat to our employees but an opportunity to drive more value from their work for SLB and our customers.
  Value Brought by Dataiku:
  Dataiku has an excellent Academy that provides the right mix of tutorials and hands-on exercises. You can complete your first machine learning workflow without using any code. What's more, the Dataiku Academy is entirely free to use.
  For SLB to start its data science journey, Dataiku was the ideal platform. With free learning content and no code workflows, the learning journey was low risk and high reward for the organization. Through the certification challenge, employees not only built their first machine learning workflow but also gained basic concepts of AI explainability and governance, ML Ops, and plugin development. A great offering to open people's minds!
  - Improve customer/employee satisfaction
  - Reduce cost
  Value Range: Hundreds of thousands of $